bluuebunny/crossref_metadata_2025 huggingface dataset:
Adjuvant Immunotherapy After Resected Melanoma: Survival Outcomes, Prognostic Factors and Patterns of Relapse
Authors: Martinez-Recio Sergio , Molina-Pérez Maria Alejandra , Muñoz-Couselo Eva , Sevillano-Tripero Alberto R. , Aya Francisco , Arance Ana , Orrillo Mayra , Martin-Liberal Juan , Fernandez-Morales Luis , Lesta Rocio , Quindós-Varela María , Nieva Maria , Vidal Joana , Martinez-Perez Daniel , Barba Andrés , Majem Margarita
Published: January 2025

Background: Anti-PD-1-based immunotherapy has improved outcomes in stage IIB to IV resected melanoma patients in clinical trials. However, little is known about real-world outcomes, prognostic factors and patterns of relapse. Methods: This is a retrospective multicenter observational study including patients with resected melanoma treated with subsequent anti-PD-1-based adjuvant immunotherapy. Data on clinical and demographic characteristics, delivered treatment, prognostic factors, time and pattern of relapse were collected. Results: We included 245 patients from eight centers; 4% of patients were at stage IIB-C, 80% at stage IIIA-D and 16% at stage IV. Recurrence-free survival (RFS) rates at 18 and 36 months were 60% and 48%, respectively, with a median RFS of 33.7 months. Prognostic factors associated with recurrence were melanoma primary site (HR 2.64, 95% CI 1.15–6.01) and starting adjuvant therapy more than 12 weeks after the last resection (HR 1.68, 95% CI 1.13–2.5); presence of serious immune-related adverse events was associated with better RFS (HR 0.4, 95% CI 0.19–0.87). Early relapses accounted for 63% of the total recurrences, with a higher number of metastatic sites (18%); in contrast, late relapses presented more frequently with brain metastases (20%). Conclusions: In our patients with resected melanoma who underwent anti-PD-1-based adjuvant immunotherapy, survival outcomes were worse than those reported in clinical trials. Primary melanoma site and time interval between the last resection and the start of adjuvant therapy were associated with survival.
The Influence of Cell Isolation and Culturing on Natriuretic Peptide Receptors in Aortic Vascular Smooth Muscle Cells
Authors: Rager Christine , Klöpper Tobias , Tasch Sabine , Whittaker Michael Raymond , Exintaris Betty , Mietens Andrea , Middendorff Ralf
Published: January 2025

Vascular smooth muscle cell (SMC) relaxation by guanylyl cyclases (GCs) and cGMP is mediated by NO and its receptor soluble GC (sGC) or natriuretic peptides (NPs) ANP/BNP and CNP with the receptors GC-A and GC-B, respectively. It is commonly accepted that cultured SMCs differ from those in intact vessels. Nevertheless, cell culture often remains the first step for signaling investigations and drug testing. Previously, we showed that even popular reference genes changed dramatically after SMC isolation from aorta. Regarding NP receptors, a substantial amount of data relies on cell culture. We hypothesize that the NP/cGMP system in intact aortic tunica media differs from isolated and cultured aortic SMCs. Therefore, we studied isolation and culturing effects on the expression of NP receptors GC-A, GC-B, and NP clearance receptor (NPRC) compared to sGC. We investigated intact tunica media and primary SMCs from the longitudinal halves of the same rat aorta. GC activity was monitored by cyclic guanosine monophosphate (cGMP). In addition, we hypothesize that there are sex-dependent differences in the NP/cGMP cascade in both intact tissue and cultured cells. We, therefore, analyzed a male and female cohort. Expression was quantified by RT-qPCR comparing aortic media and SMCs with our recently validated reference gene (RG) small nuclear ribonucleoprotein 2 (U2). Only GC-A was stably expressed. In intact media, GC-A exceeded GC-B and NPRC. However, GC-B, NPRC, and sGC were dramatically upregulated in cultured SMCs of the same aortae different from the stable GC-A. The expression was mirrored by NP-induced GC activity. In cultured cells, changes in GC activity were delayed compared to receptor expression. Minor differences between both sexes could also be revealed. Thus, isolation and culture fundamentally alter the cGMP system in vascular SMCs with potential impact on drug testing and scRNAseq. Especially, the dramatic increase in the clearance receptor NPRC in culture might distort all physiological ANP, BNP, and CNP effects.
Prognostic Value of PSMB5 and Correlations with LC3II and Reactive Oxygen Species Levels in the Bone Marrow Mononuclear Cells of Bortezomib-Resistant Multiple Myeloma Patients
Authors: Plakoula Eva , Kalampounias Georgios , Alexis Spyridon , Verigou Evgenia , Kourakli Alexandra , Zafeiropoulou Kalliopi , Symeonidis Argiris
Published: January 2025

Proteasome inhibitors (PIs) constitute the most common type of induction treatment for multiple myeloma. Interactions between the proteasome, autophagy, and reactive oxygen species (ROS) have been shown in the past, thus emphasizing the need for a better understanding of the underlying pathophysiology. For this study, bone marrow mononuclear cells from 110 myeloma patients were collected at different disease stages. PSMB5 and LC3I/II protein levels were determined using Western blot, proteasome proteolytic activity (PPA) with spectrofluorometry, and ROS with flow cytometry. PSMB5 accumulation was found to diminish after PI treatment (p-value = 0.014), and the same pattern was observed in PPA (p-value < 0.001). Conversely, LC3II protein levels were elevated at both remission and relapse compared to baseline levels (p-value = 0.041). Patients with a baseline PSMB5 accumulation lower than 1.06 units had longer disease-free survival compared to those with values above 1.06 units (12.0 ± 6.7 vs. 36 ± 12.1 months; p-value < 0.001). Median ROS levels in plasma cells were significantly higher at relapse compared to both baseline and remission levels (p-value < 0.001), implying poor prognosis. Overall, post-treatment PSMB5 reduction could indicate a shift from proteasomal to autophagic degradation as a main proteostatic mechanism, thus explaining resistance. The elevated oxidative stress in PI-treated patients could possibly serve as an additional compensatory mechanism.
Antiedemic Effect of the Myosin Light Chain Kinase Inhibitor PIK7 in the Rat Model of Myocardial Ischemia Reperfusion Injury
Authors: Sonin Dmitry L. , Medved Mikhail S. , Khapchaev Asker Y. , Sidorova Maria V. , Palkeeva Marina E. , Kazakova Olga A. , Papayan Garry V. , Mochalov Daniil A. , Minasyan Sarkis M. , Anufriev Ilya E. , Mukhametdinova Daria V. , Paramonova Natalia M. , Balabanova Ksenia M. , Lopatina Anastasia S. , Aleksandrov Ilia V. , Semenova Natalya Yu. , Kordyukova Anna A. , Zaichenko Kirill V. , Shirinsky Vladimir P. , Galagudza Michael M.
Published: January 2025

Myocardial ischemia-reperfusion injury increases myocardial microvascular permeability, leading to enhanced microvascular filtration and interstitial fluid accumulation that is associated with greater microvascular obstruction and inadequate myocardial perfusion. A burst of reactive oxygen species and inflammatory mediators during reperfusion causes myosin light chain kinase (MLCK)-dependent endothelial hyperpermeability, which is considered a preventable cause of reperfusion injury. In the present study, a single intravenous injection of MLCK peptide inhibitor PIK7 (2.5 mg/kg or 40 mg/kg) was found to suppress the vascular hyperpermeability caused by ischemia/reperfusion injury in an in vivo rat model. The antiedemic effect of PIK7 is transient and ceases within 90 min of reperfusion. The early no-reflow detected for the first time after 30 min ischemia in this model of myocardial infarction reduces the area accessible for PIK7. Electron microscopy has shown membrane-bound blebs of endotheliocytes, which partially or completely obturate the capillary lumen, and few capillaries with signs of intercellular gap formation in samples obtained from the center of the early no-reflow zone in control and PIK7-injected rats. Co-injection of PIK7 with NO donor sodium nitroprusside (SNP) increases blood flow in the zone of early no-reflow, while reducing the increased vascular permeability caused by SNP.
Identifying the Areas at Risk of Huaico Occurrences in the Department of Lima, Peru
Authors: Santos Geise Macedo dos , Schneider Vania Elisabete , Cemin Gisele , Poletto Matheus
Published: January 2025

Because of local climate, a phenomenon called huaico occurs in the coastal regions of Peru, configured by an alluvial flow of surface runoff caused by precipitation and accompanied by the transport of solid particles. A total of 24% of the huaicos recorded in Peru from 2003 to 2019 were concentrated in the Department of Lima alone and affected 38,000 people. Thus, the aim of this study was to use Maxent to identify the areas at risk of huaicos in this department. To this end, a georeferenced database was created that included the locations of these events for modeling. We used variables suggested by Peru’s Geological, Mining, and Metallurgical Institute (INGEMMET)—geology, geomorphology, DEM, slope, and precipitation—which returned extremely high kappa coefficients. Approximately 42% of Lima’s area is likely to have a huaico occurrence. The most crucial variable for the models was the geomorphological classification characterized by the accumulation of mobilized material, as was the case in previous huaico models. In addition, the monthly approach should have been more effective at determining the differences in the precipitation levels. Thus, new models for the coastal departments of Peru using Maxent algorithms should take a new approach related to precipitation, although the use of Maxent proved satisfactory.
Effects of Annealing Time on the Structure Characteristics and Magnetic Properties of FeSiBPCCuNb Amorphous Ribbons
Authors: Huang Xi , Wang Lianbo , Ding Song , Li Jiajun , Wang Zemin , Liu Min , Wang Zhanyong , Zhu Wenlong
Published: January 2025

In this paper, the structure characteristics and magnetic properties of Fe83Si6B6P1.5C1.5Cu1Nb1 amorphous alloy ribbons annealed at 550 °C for different times were systematically investigated using X-ray diffraction, vibrating sample magnetometer, and atom probe chromatography. The results show that high-density Cu atomic clusters of appropriate sizes help to stabilize the α-Fe(Si) phase and improve the uniformity of the grains to enhance the soft magnetic properties. The solubility difference between the α-Fe(Si) phase and the B-rich phase, the formation of a localized amorphous structure in the transition region, and the inhibition of nanograin growth. However, when the annealing time is extended, the size of the α-Fe(Si) grains decreases, the grain boundary density increases and secondary phases such as Cu clusters become pinning sites for magnetic domain walls. This leads to a decrease in soft magnetic properties, an increase in hard magnetic properties, and a rapid increase in coercivity. When annealed at 550 °C for 20 min, the number density of Cu atomic clusters was 9.18 × 1022 m−3, the spherical equivalent radius was 1.13 ± 0.29 nm, and the ribbons had good soft magnetic properties with a coercivity of 4.59 Oe. The saturation magnetic induction reached a peak value of 185.11 emu/g.
Development Status of Textured Piezoelectric Ceramics and Preparation Processes
Authors: Shen Nianyi , Liao Qingwei , Liao Yaoyao , Li Ruifeng , Zhang Yushan , Song Shiliang , Song Ying , Zhu Chengzhi , Qin Lei
Published: January 2025

There are many factors that determine the performance parameters of piezoelectric ceramics, but the process of preparing ceramics plays a decisive role in their properties. By improving the preparation process, significant improvements in ceramic properties can be achieved. In order to meet the growing demand for improvement in the performance of piezoelectric ceramics, various crystal preparation methods such as Template Crystal Growth (TGG), Reflected Template Growth (RTGG), and Oriented Curding (OCAP) techniques have been used for the preparation of piezoelectric ceramics. This article first introduces the performance parameters of piezoelectric ceramics, then summarizes the influence of various preparation processes on the performance of piezoelectric ceramics, and finally summarizes the parameters of high-tech ceramics reported this year, and predicts the future of the preparation of high-tech ceramic materials.
Topological Superconductivity of the Unconventional Type, S = 1, Sz = 0, in a Layer of Adatoms
Authors: Silva Edine , Continentino Mucio A.
Published: January 2025

In this paper, we study the appearance of topological p-wave superconductivity of the type S=1, Sz=0 in a layer of adatoms. This unconventional superconductivity arises due to an anti-symmetric hybridization between the orbitals of the adatoms and those of the atoms in the superconducting BCS substrate. This two-dimensional system is topologically non-trivial only in the absence of a magnetic field and belongs to class DIII of the Altland–Zirnbauer classification. We obtain the Pfaffian that characterizes the topological phases of the system and its phase diagram. We discuss the differences between the two-dimensional case and a chain with the same type of superconductivity.
Hair Growth-Promoting Effects of Astragalus sinicus Extracts in Human Follicle Dermal Papilla Cells
Authors: Jeon Chae Young , Go Min Young , Kim In-Kyung , Park Myung-Rye , Lee Hyean Woo , Kim Youn-Kyu , Shin Dong Wook
Published: January 2025

Hair loss is influenced by various stresses and disruptions in the hair growth cycle within hair follicles. The activation of these follicles is primarily driven by dermal papilla cells, which play a central role in the progression of the hair growth cycle and formation. Many studies are being carried out on various natural plants to improve hair loss. In this study, we assessed the potential of Astragalus sinicus, known as a pharmacological herb, in mitigating damage to human follicle dermal papilla cells (HFDPCs) caused by dihydrotestosterone (DHT). We found that Astragalus sinicus extracts (ASEs) facilitated wound healing and elevated alkaline phosphatase expression in DHT-damaged HFDPCs. ASEs also significantly reduced reactive oxygen species (ROS) generated by DHT and increased ATP levels by restoring mitochondrial membrane potential in damaged cells. Furthermore, we demonstrated that ASEs substantially enhanced the phosphorylation levels of the AKT/ERK pathway and activated the Wnt signaling pathway in DHT-damaged HFDPCs. Taken together, we suggest that ASEs may be a potential ingredient for enhancing hair loss treatment.
Forest Attribute Dynamics in Secondary Forests: Insights for Advancing Ecological Restoration and Transformative Territorial Management in the Amazon
Authors: Rodríguez-León Carlos H. , Sterling Armando , Trujillo-Briñez Amelia , Suárez-Córdoba Yerson D. , Roa-Fuentes Lilia L.
Published: January 2025

The Amazon ecosystem plays a vital role in global climate regulation and biodiversity conservation but faces escalating threats from deforestation and degradation. The resulting secondary forests (SFs) provide a promising opportunity for Transformative Territorial Management, fostering restoration and enhancing conservation values. This study evaluated aboveground biomass (AGB), species diversity, forest structure, and soil properties in SFs of the Colombian Amazon along a chronosequence, from early to mature successional stages, in landscapes of mountains and of hills to identify key indicators for effective restoration management. The results show a consistent increase in AGB, species diversity, forest structure, and soil quality with forest age, though recovery patterns varied between both landscapes evaluated. Topographic differences influenced successional dynamics, with mountainous landscapes showing faster early recovery compared to the steadier, linear growth observed in hill areas. In hills, AGB at 10 years reached 12.65% of the biomass expected in a mature forest, increasing to nearly 42% by 40 years of abandonment, at a rate of 0.708 Mg C ha−1 year−1. In contrast, in the mountain landscape, AGB at 10 years reached approximately 8.35% of the carbon in a mature forest and increased to nearly 63.55% at 40 years. Forest age and soil properties emerged as primary drivers of AGB recovery, while diversity and forest structure played indirect but significant roles. In hill areas, soil conservation practices are critical for maintaining steady growth, whereas mountain regions benefit from assisted natural regeneration (ANR) to accelerate recovery. These findings highlight the importance of prioritizing the management of SFs as a central strategy for achieving restoration goals. Such practices are essential to enhance the ecological resilience of SFs and ensure their long-term sustainability, fostering their role as key contributors to restoration efforts and the provision of ecosystem services.
A Numerical Modeling Study of a New Type of Hydraulic Mechanical Continuously Variable Transmission (HMCVT) with Optimized Transmission Efficiency
Authors: Ma Zexin , Li Zhengyu , Sun Deming , Cai Yanbin , Zhang Jiwei , Liu Hongyu , Wang Qingxin , Li He , Zhou Long , Yu Wenbin , Zhao Feiyang
Published: January 2025

Hydraulic mechanical continuously variable transmission (HMCVT) is widely used in powerful tractors due to its excellent performance. This paper aims to find universal methods for analyzing and optimizing the transmission efficiency of HMCVT. The energy efficiency improvement of HMCVT is important for the economy of powerful tractors. Firstly, by correctly analyzing the transmission efficiency of HMCVT, the transmission efficiency during the operation of HMCVT can be accurately calculated. Secondly, an improved NSGA-II genetic algorithm was adopted to achieve dynamic optimization of shifting points through transmission parameter combination optimization, ensuring smooth shifting while improving overall transmission efficiency. According to the transmission efficiency simulation platform, the accuracy of the transmission efficiency calculation was verified. Adopting an improved NSGA-II genetic algorithm to continuously optimize the design of HMCVT configurations achieves dynamic optimization of HMCVT parameters without being limited by shifting speed. The specific HMCVT structure proposed in this study can meet the requirements of a three-speed continuously variable transmission at speeds of 0–50 km/h. Meanwhile, the improved NSGA-II genetic algorithm can effectively provide support for the design of various HMCVT powertrain systems.
Combining Postural Sway Parameters and Machine Learning to Assess Biomechanical Risk Associated with Load-Lifting Activities
Authors: Prisco Giuseppe , Pirozzi Maria Agnese , Santone Antonella , Cesarelli Mario , Esposito Fabrizio , Gargiulo Paolo , Amato Francesco , Donisi Leandro
Published: January 2025

Background/Objectives: Long-term work-related musculoskeletal disorders are predominantly influenced by factors such as the duration, intensity, and repetitive nature of load lifting. Although traditional ergonomic assessment tools can be effective, they are often challenging and complex to apply due to the absence of a streamlined, standardized framework. Recently, integrating wearable sensors with artificial intelligence has emerged as a promising approach to effectively monitor and mitigate biomechanical risks. This study aimed to evaluate the potential of machine learning models, trained on postural sway metrics derived from an inertial measurement unit (IMU) placed at the lumbar region, to classify risk levels associated with load lifting based on the Revised NIOSH Lifting Equation. Methods: To compute postural sway parameters, the IMU captured acceleration data in both anteroposterior and mediolateral directions, aligning closely with the body’s center of mass. Eight participants undertook two scenarios, each involving twenty consecutive lifting tasks. Eight machine learning classifiers were tested utilizing two validation strategies, with the Gradient Boost Tree algorithm achieving the highest accuracy and an Area under the ROC Curve of 91.2% and 94.5%, respectively. Additionally, feature importance analysis was conducted to identify the most influential sway parameters and directions. Results: The results indicate that the combination of sway metrics and the Gradient Boost model offers a feasible approach for predicting biomechanical risks in load lifting. Conclusions: Further studies with a broader participant pool and varied lifting conditions could enhance the applicability of this method in occupational ergonomics.
Combining UAS LiDAR, Sonar, and Radar Altimetry for River Hydraulic Characterization
Authors: Coppo Frias Monica , Vesterhauge Alexander Rietz , Olesen Daniel Haugård , Bandini Filippo , Grosen Henrik , Nielsen Sune Yde , Bauer-Gottwein Peter
Published: January 2025

Accurate river hydraulic characterization is fundamental to assess flood risk, parametrize flood forecasting models, and develop river maintenance workflows. River hydraulic roughness and riverbed/floodplain geometry are the main factors controlling inundation extent and water levels. However, gauging stations providing hydrometric observations are declining worldwide, and they provide point measurements only. To describe hydraulic processes, spatially distributed data are required. In situ surveys are costly and time-consuming, and they are sometimes limited by local accessibility conditions. Satellite earth observation (EO) techniques can be used to measure spatially distributed hydrometric variables, reducing the time and cost of traditional surveys. Satellite EO provides high temporal and spatial frequency, but it can only measure large rivers (wider than ca. 50 m) and only provides water surface elevation (WSE), water surface slope (WSS), and surface water width data. UAS hydrometry can provide WSE, WSS, water surface velocity and riverbed geometry at a high spatial resolution, making it suitable for rivers of all sizes. The use of UAS hydrometry can enhance river management, with cost-effective surveys offering large coverage and high-resolution data, which are fundamental in flood risk assessment, especially in areas that difficult to access. In this study, we proposed a combination of UAS hydrometry techniques to fully characterize the hydraulic parameters of a river. The land elevation adjacent to the river channel was measured with LiDAR, the riverbed elevation was measured with a sonar payload, and the WSE was measured with a UAS radar altimetry payload. The survey provided 57 river cross-sections with riverbed elevation, and 8 km of WSE and land elevation and took around 2 days of survey work in the field. Simulated WSE values were compared to radar altimetry observations to fit hydraulic roughness, which cannot be directly observed. The riverbed elevation cross-sections have an average error of 32 cm relative to RTK GNSS ground-truth measurements. This error was a consequence of the dense vegetation on land that prevents the LiDAR signal from reaching the ground and underwater vegetation, which has an impact on the quality of the sonar measurements and could be mitigated by performing surveys during winter, when submerged vegetation is less prevalent. Despite the error of the riverbed elevation cross-sections, the hydraulic model gave good estimates of the WSE, with an RMSE below 3 cm. The estimated roughness is also in good agreement with the values measured at a gauging station, with a Gauckler–Manning–Strickler coefficient of M = 16–17 m1/3/s. Hydraulic modeling results demonstrate that both bathymetry and roughness measurements are necessary to obtain a unique and robust hydraulic characterization of the river.
Outlining the Psychological Profile of Persistent Depression in Fibromyalgia Patients Through Personality Assessment Inventory (PAI)
Authors: Doreste Andrea , Pujol Jesus , Penelo Eva , Pérez Víctor , Blanco-Hinojo Laura , Martínez-Vilavella Gerard , Pardina-Torner Helena , Ojeda Fabiola , Monfort Jordi , Deus Joan
Published: January 2025

Background: Fibromyalgia (FM) is a complex condition marked by increased pain sensitivity and central sensitization. Studies often explore the link between FM and depressive anxiety disorders, but few focus on dysthymia or persistent depressive disorder (PDD), which can be more disabling than major depression (MD). Objective: To identify clinical scales and subscales of the Personality Assessment Inventory (PAI) that effectively describe and differentiate the psychological profile of PDD, with or without comorbid MD, in FM patients with PDD previously dimensionally classified by the Millon Clinical Multiaxial Inventory III (MCMI-III). Method: An observational, cross-sectional study was conducted with 66 women (mean age 49.18, SD = 8.09) from Hospital del Mar. The PAI, the MCMI-III, and the Fibromyalgia Impact Questionnaire (FIQ) were used to assess the sample. Results: The PAI showed strong discriminative ability in detecting PDD, characterized by high scores in cognitive and emotional depression and low scores in identity alteration, dominance, and grandeur. High scores in cognitive, emotional, and physiological depression, identity alteration, cognitive anxiety, and suicidal ideation, along with low scores in dominance and grandeur, were needed to detect MD with PDD. Discriminant analysis could differentiate 69.6–73.9% of the PDD group and 84.6% of the PDD+MD group. Group comparisons showed that 72.2% of patients with an affective disorder by PAI were correctly classified in the MCMI-III affective disorder group, and 70% without affective disorder were correctly classified. Conclusions: The PAI effectively identifies PDD in FM patients and detects concurrent MD episodes, aiding in better prognostic and therapeutic guidance.
NI-LIO: A Hybrid Approach Combining ICP and NDT for Improving Simultaneous Localization and Mapping Performance
Authors: Yu Jie , Yu Ting-Hai , Zhang Qing-Yong , Nguyen Trong-The
Published: January 2025

The accuracy and stability of front-end point cloud registration algorithms are crucial for the mapping and localization precision in laser SLAM (simultaneous localization and mapping) systems. Traditional point-to-line and point-to-plane iterative closest point (ICP) registration algorithms, widely used in SLAM front ends, often suffer from low efficiency, significant data dependency during the matching process, and a propensity for local optima. This registration method exhibits a more pronounced local optimum issue in large-scale SLAM mapping, thereby diminishing matching accuracy and increasing reliance on initial values. To address these limitations, this paper introduces NI-LIO, a novel SLAM algorithm that integrates ICP with normal distributions transform (NDT) to enhance localization accuracy, computational efficiency and robustness. By combining the precision of ICP with the robustness of NDT, the proposed algorithm significantly improves system stability and localization accuracy. The analysis of mapping and localization experiments indicates a significant reduction in errors compared to traditional SLAM algorithms, with experiments showing a REMS value decrease of over 20%. Compared to ALOAM, FAST_LIO2 and Lego-LOAM algorithms, the new NI-LIO algorithm shows improvements in both accuracy and stability, enabling the construction of a more precise and consistent global map. This algorithm exhibits excellent adaptability to various environments.
Investigating Intelligent Call Technology for Dispatching Telephones Towards System Integration
Authors: Tai Chunliang , Sun Yibo , Sun Shiming , Sun Zhixin , Chen Xing , Shi Yue , Liu Chao
Published: January 2025

The dispatching telephone functionality acts as a pivotal interconnection between the power grid dispatch business and telecommunications business, playing a vital role in ensuring the efficient conduct of grid dispatch activities. Nonetheless, the current power grid dispatch system and communication program-controlled exchange system are disjointed, leading to a cumbersome process for the dispatching telephone functionality that severely impacts grid dispatch efficiency. To better tackle the above challenges, in this paper, we introduce an innovative intelligent call technology designed to facilitate data interchange and information integration between the power grid dispatch system and the communication program-controlled exchange system. By leveraging the K-Nearest Neighbors (KNN) algorithm, the technology enables automated querying of operational information with heightened efficiency and precision, thereby optimizing the operations of the dispatching telephone functionality. Subsequently, a prototype software application is developed to conduct experimental testing of intelligent call technology. The findings demonstrate that the method proposed in this paper successfully reduces the time expenditure associated with the dispatching telephone functionality, enhancing the productivity of dispatchers in routine operations and emergency response, thus ensuring the secure and stable operation of the power grid.
Path Planning for Autonomous Balloon Navigation with Reinforcement Learning
Authors: He Yingzhe , Guo Kai , Wang Chisheng , Fu Keyi , Zheng Jiehao
Published: January 2025

In the stratosphere, the use of winds to navigate balloons has emerged as a practical approach for Earth observation, collecting meteorological data, and other applications. However, controlling such balloons is challenging due to imperfect wind data and the need for real-time decisions. Research in this field predominantly concentrates on station-keeping missions, but there is an absence of studies on stratospheric balloon path planning. In this work, we employ deep reinforcement learning to train a controller that guides the balloon from a random starting point to a target range within a simulated wind field that changes over time and space. The results prove the feasibility of using reinforcement learning for superpressure balloon path planning in complex, dynamic wind fields, and the RL controller outperforms the hand-crafted baseline controller, achieving faster navigation with a higher success rate.
PDS-YOLO: A Real-Time Detection Algorithm for Pipeline Defect Detection
Authors: Zhang Ke , Qin Longxiao , Zhu Liming
Published: January 2025

Regular inspection of urban drainage pipes can effectively maintain the reliable operation of the drainage system and the production safety of residents. Aiming at the shortcomings of the CCTV inspection method used in the drainage pipe defect detection task, a PDS-YOLO algorithm that can be deployed in the pipe defect detection system is proposed to overcome the problems of inefficiency of manual inspection and the possibility of errors and omissions. First, the C2f-PCN module was introduced to decrease the model sophistication and decrease the model weight file size. Second, to enhance the model’s capability in detecting pipe defect edges, we incorporate the SPDSC structure within the neck network. Introducing a hybrid local channel MLCA attention mechanism and Wise-IoU loss function based on a dynamic focusing mechanism, the model improves the precision of segmentation without adding extra computational cost, and enhances the extraction and expression of pipeline defect features in the model. The experimental outcomes indicate that the mAP, F1-score, precision, and recall of the PDS-YOLO algorithm are improved by 3.4%, 4%, 4.8%, and 4.0%, respectively, compared to the original algorithm. Additionally, the model achieves a reduction in both the model’s parameter and GFLOPs by 8.6% and 12.3%, respectively. It saves computational resources while improving the detection accuracy, and provides a more lightweight model for the defect detection system with tight computing power. Finally, the PDS-YOLOv8n model is deployed to the NVIDIA Jetson Nano, the central console of the mobile embedded system, and the weight files are optimized using TensorRT. The test results show that the velocity of the model’s inference capabilities in the embedded device is improved from 5.4 FPS to 19.3 FPS, which can basically satisfy the requirements of real-time pipeline defect detection assignments in mobile scenarios.
Feature-Level Image Fusion Scheme for X-Ray Multi-Contrast Imaging
Authors: Zuo Zhuo , Luo Jinglei , Liu Haoran , Zheng Xiang , Zan Guibin
Published: January 2025

Since the mid-1990s, X-ray phase contrast imaging (XPCI) has attracted increasing interest in the industrial and bioimaging fields due to its high sensitivity to weakly absorbing materials and has gained widespread acceptance. XPCI can simultaneously provide three imaging modalities with complementary information, offering enriched details and data. This study proposes an image fusion method that simultaneously retrieves the three complementary channels of XPCI. It integrates block features, non-subsampled contourlet transform (NSCT), and a spiking cortical model (SCM), comprising three steps: (I) Image denoising, (II) Block-based feature-level NSCT-SCM fusion, and (III) Image quality enhancement. Compared with other methods in the XPCI image fusion field, the fusion results of the proposed algorithm demonstrated significant advantages, particularly with an impressive increase in the standard deviation by over 50% compared to traditional NSCT-SCM. The results revealed that the proposed algorithm exhibits high contrast, clear contours, and a short operation time. Experimental outcomes also demonstrated that the block-based feature extraction procedure performs better in retaining edge strength and texture information, with released computational resource consumption, thus, offering new possibilities for the industrial application of XPCI technology.
A Fine-Grained Car Recognition Method Based on a Lightweight Attention Network and Regularized Fine-Tuning
Authors: Zhang Cheng , Li Qiaochu , Liu Chang , Zhang Yi , Zhao Ding , Ji Chao , Wang Jin
Published: January 2025

Car fine recognition is a typical scenario for fine-grained image classification, which has great research and application value in both civilian and military fields. However, current research on fine-grained classification is often limited to improving the accuracy of classification models, ignoring the need for lightweight and efficient applications in practical applications, resulting in a disconnect from reality. In this paper, a fine-grained car recognition method based on a lightweight attention network and regularized fine-tuning is proposed. Based on the high-performance, lightweight convolutional neural network (CNN) architecture MobileNet V3, an improved CNN architecture HAM-MobileNet that includes a hybrid attention module is designed. A regularized fine-tuning strategy that includes correlation constraints is adopted. By fine-tuning the HAM-MobileNet, accurate classification of car images can be achieved. The experimental results on the Stanford cars dataset show that the proposed method achieves an accuracy rate of 84.6%, which is the highest level among all lightweight CNN architectures and is comparable to non-lightweight CNN architectures. The visualization results show that the proposed hybrid attention module can make the network model focus more on the target objects with consistent classes, suppress task-irrelevant backgrounds and other noise, and improve the learning ability and generalization of the network model.
Experimental Testing Results on Critical Components for Molten Salt-Based CSP Systems
Authors: Russo Valeria , Petroni Giuseppe , Rovense Francesco , Giorgetti Mauro , Napoli Giuseppe , Giorgi Gianremo , Gaggioli Walter
Published: January 2025

Concentrated Solar Power (CSP) plants integrated with Thermal Energy Storage (TES) represent a promising renewable energy source for generating heat and power. Binary molten salt mixtures, commonly referred to as Solar Salts, are utilized as effective heat transfer fluids and storage media due to their thermal stability and favorable thermophysical properties. However, these mixtures pose significant challenges due to their high solidification temperatures, around 240 °C, which can compromise the longevity and reliability of critical system components such as pressure sensors and bellows seal globe valves. Thus, it is essential to characterize their performance, assess their reliability under various conditions, and understand their failure mechanisms, particularly in relation to temperature fluctuations affecting the fluid’s viscosity. This article discusses experimental tests conducted on a pressure sensor and a bellows seal globe valve, both designed for direct contact with molten salts in CSP environments, at the ENEA Casaccia Research Center laboratory in Rome. The methodology for conducting these experimental tests is detailed, and guidelines are outlined to optimize plant operation. The findings provide essential insights for improving component design and maintenance to minimize unplanned plant downtime. They also offer methodologies for installing measurement instruments and electrical heating systems on the components.
Natural Bioactive Compounds from Orchard Biomass Waste and Cosmetic Applications
Authors: Bruno Maria Roberta , Ponticelli Maria , Sinisgalli Chiara , Milella Luigi , Todaro Luigi , Faraone Immacolata
Published: January 2025

Antioxidants are crucial in counteracting the impact of free radicals, thereby preventing cell damage. Extracts from orange, apricot, and olive tree pruning, classified as by-products according to environmental laws, underwent examination of their antioxidant properties. In the present investigation, data on the antioxidant activity of extracts of these tree by-products were used to calculate the relative antioxidant capacity index (RACI). The latter made it possible to identify Apricot bark maceration extract as having the highest antioxidant index. Further analysis through UHPLC-MS enabled the identification of compounds known for their antioxidant activity, including catechin, epicatechin, and others. Cytotoxicity assays conducted on human hepatocellular carcinoma cell lines (HepG2) confirmed the safety of the chosen extract for cosmetic applications. The extract was then used to formulate a cosmetic cream, which subsequently underwent quality control and proved to be stable, of good consistency, and free of pathogens. The results show that developing a sustainable cosmetic cream prototype is a promising step toward realizing an environmentally friendly product in the circular economy context.
Modeling Tree Mortality Induced by Climate Change-Driven Drought: A Case Study of Korean Fir in the Subalpine Forests of Jirisan National Park, South Korea
Authors: Lim Wontaek , Park Hong-Chul , Park Sinyoung , Seo Jeong-Wook , Kim Jinwon , Ko Dongwook W.
Published: January 2025

Increased drought frequency due to climate change is intensifying tree mortality, a critical issue in forest ecosystem management, especially in vulnerable subalpine ecosystems. Korean fir (Abies koreana E.H. Wilson), an endemic species of South Korea that grows in subalpine areas, is threatened by climate change-induced drought. However, our understanding of drought’s impact on tree mortality, particularly its seasonal and legacy effects, remains limited. To better understand drought-related mortality of Korean fir, we conducted annual mortality surveys, starting in 2012, at 10 fixed transects in Jirisan National Park, identified seasonal and legacy effects using redundancy analysis, and modeled Korean fir mortality, incorporating biotic and abiotic factors, using random forests. We found that early growing season drought had the greatest impact on Korean fir mortality, with legacy effects extending up to three years, while late growing season drought affected mortality only in the previous year. The mortality model achieved high predictive accuracy (94%) and revealed significant site- and size-dependent mortality patterns. These findings provide critical insights into the complex interactions between biotic and abiotic factors affecting tree mortality and offer valuable guidance for conservation strategies aimed at preserving climate-sensitive species in the face of ongoing climate change.
A Hierarchical Cache Architecture-Oriented Cache Management Scheme for Information-Centric Networking
Authors: Chao Yichao , Han Rui
Published: January 2025

Information-Centric Networking (ICN) typically utilizes DRAM (Dynamic Random Access Memory) to build in-network cache components due to its high data transfer rate and low latency. However, DRAM faces significant limitations in terms of cost and capacity, making it challenging to meet the growing demands for cache scalability required by increasing Internet traffic. Combining high-speed but expensive memory (e.g., DRAM) with large-capacity, low-cost storage (e.g., SSD) to construct a hierarchical cache architecture has emerged as an effective solution to this problem. However, how to perform efficient cache management in such architectures to realize the expected cache performance remains challenging. This paper proposes a cache management scheme for hierarchical cache architectures in ICN, which introduces a differentiated replica replacement policy to accommodate the varying request access patterns at different cache layers, thereby enhancing overall cache performance. Additionally, a probabilistic insertion-based SSD cache admission filtering mechanism is designed to control the SSD write load, addressing the issue of balancing SSD lifespan and space utilization. Extensive simulation results demonstrate that the proposed scheme exhibits superior cache performance and lower SSD write load under various workloads and replica placement strategies, highlighting its broad applicability to different application scenarios. Additionally, it maintains stable performance improvements across different cache capacity settings, further reflecting its good scalability.
IoT Firmware Emulation and Its Security Application in Fuzzing: A Critical Revisit
Authors: Zhou Wei , Shen Shandian , Liu Peng
Published: January 2025

As IoT devices with microcontroller (MCU)-based firmware become more common in our lives, memory corruption vulnerabilities in their firmware are increasingly targeted by adversaries. Fuzzing is a powerful method for detecting these vulnerabilities, but it poses unique challenges when applied to IoT devices. Direct fuzzing on these devices is inefficient, and recent efforts have shifted towards creating emulation environments for dynamic firmware testing. However, unlike traditional software, firmware interactions with peripherals that are significantly more diverse presents new challenges for achieving scalable full-system emulation and effective fuzzing. This paper reviews 27 state-of-the-art works in MCU-based firmware emulation and its applications in fuzzing. Instead of classifying existing techniques based on their capabilities and features, we first identify the fundamental challenges faced by firmware emulation and fuzzing. We then revisit recent studies, organizing them according to the specific challenges they address, and discussing how each specific challenge is addressed. We compare the emulation fidelity and bug detection capabilities of various techniques to clearly demonstrate their strengths and weaknesses, aiding users in selecting or combining tools to meet their needs. Finally, we highlight the remaining technical gaps and point out important future research directions in firmware emulation and fuzzing.
Conservative Interference Injection to Minimize Wi-Fi Sensing Privacy Risks and Bandwidth Loss
Authors: Sharma Aryan , Wang Haoming , Mishra Deepak , Seneviratne Aruna
Published: January 2025

With the impending integration of sensing capabilities into new wireless standards such as 6G and 802.11 bf, there is a growing threat to public privacy. Recent studies have revealed that even small-scale activities, like keyboard typing, can be sensed by attackers using Wi-Fi Channel State Information (CSI) as these devices become more common in commercial spaces. This paper aims to model the minimum CSI data rate required to sense activities in the channel and quantifies the detection accuracy of WiFi-based keystroke recognition in relation to the CSI sensing data rate. Our experimental findings using commercial-off-the-shelf hardware suggest that interference can be used as a defence strategy to degrade the CSI data rate and prevent undesirable Wi-Fi sensing attacks. To achieve a reduced data rate, we propose an extension to Bianchi’s model of CSMA/CA systems and establish a new mathematical relationship between channel contention and the available CSI. This proposed relationship was empirically verified, and our contention-based defence strategy was experimentally validated. Experiments show that our contention-based defence strategy increases the chances of evading undesired WiFi-based keystroke recognition by around 70%. By leveraging prior work that shows a degradation in CSI quality with lower transmission rates, we show that conservative interference injection can sufficiently reduce sensing accuracy whilst maintaining channel bandwidth.
Fluids and Surfaces
Authors: Guilizzoni Manfredo
Published: January 2025

Fluids is pleased to present a Special Issue named “Fluids and Surfaces”, a curated collection of ten research articles focused on capillary phenomena and the interaction between fluids and surfaces [...]
Unlocking Consumer Preferences: Sensory Descriptors Driving Greek Yogurt Acceptance and Innovation
Authors: Bolini Helena Maria Andre , Cardello Flavio , de Medeiros Alessandra Cazellatto , Moskowitz Howard
Published: January 2025

Greek yogurt, a traditional food with roots in Ancient Greece, Mesopotamia, and Central Asia, has become a dietary staple worldwide due to its creamy texture, distinct flavor, and rich nutritional profile. The contemporary emphasis on health and wellness has elevated Greek yogurt as a functional food, recognized for its high protein content and bioavailable probiotics that support overall health. This study investigates the sensory attributes evaluated by a panel of 22 trained assessors and the consumer preferences driving the acceptance of Greek yogurt formulations. Samples with higher consumer acceptance were characterized by sensory attributes such as “high texture in the mouth, surface uniformity, creaminess, apparent homogeneity, mouth-filling, grip in the mouth, ease of pick-up with a spoon, milk cream flavor, sweetness, and dairy flavor” (Tukey’s test, p < 0.05). These attributes strongly correlated with consumer preferences, underscoring their importance in product optimization. The findings provide a framework for refining Greek yogurt formulations to address diverse market demands, achieving a balance between sensory excellence and practical formulation strategies. This research reinforces the significance of Greek yogurt as a culturally adaptable, health-promoting dietary component and a promising market segment for ongoing innovation.