bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Adding Y Elements on Microstructure Refinement and Mechanical Properties of Mg-9Al-1Zn Alloy
Authors: Cao Jinhua , Wei Shuaihu , Wang Xiaoming , Li Xuejian , Li Muyuan , Shi Hailong , Hu Xiaoshi , Wang Xiaojun
Published: January 2025

Grain refinement is of very important significance for improving the microstructure and mechanical properties of Mg alloys. This work investigated how the addition of various amounts of Y element affected the microstructure and mechanical properties of Mg-9Al-1Zn alloy. It was found that the grain size of Mg-9Al-1Zn alloy decreases as Y element content increases. When 1.2 wt.% Y element content was added, the grain size of Mg-9Al-1Zn alloy could be reduced from 334.2 μm to 134.6 μm, and grain refinement efficiency of 60% was achieved. HRTEM analysis demonstrated a good orientation relationship between the Al2Y phase and the Mg interface, and therefore, it was determined that the Al2Y phase can be used as a heterogeneous nucleation site for α-Mg grains, which promotes the grain refinement of α-Mg grain. Furthermore, the addition of Y element can also significantly refine the eutectic Mg17Al12 phase of the Mg-9Al-1Zn alloy. In this way, the mechanical properties of the Mg-9Al-1Zn alloy are significantly enhanced. It was found that the YS and UTS of the Mg-9Al-1Zn alloy reached 87 MPa and 154 MPa with the addition of 0.9 wt.% of Y element—24% and 43% higher than the Mg-9Al-1Zn alloy.
Design of Iron-Based Multifunctional Alloys Electrodeposited from Complexing Electrolytes
Authors: Tsyntsaru Natalia , Cesiulis Henrikas , Bersirova Oksana
Published: January 2025

There is a growing focus on sustainability, characterized by making changes that anticipate future needs and adapting them to present requirements. Sustainability is reflected in various areas of materials science as well. Thus, more research is focused on the fabrication of advanced materials based on earth-abundant metals. The role of iron and its alloys is particularly significant as iron is the second most abundant metal on our planet. Additionally, the electrochemical method offers an environmentally friendly approach for synthesizing multifunctional alloys. Thus, iron can be successfully codeposited with a targeted metal from complexing electrolytes, opening a large horizon for a smart tuning of properties and enabling various applications. In this review, we discuss the practical aspects of the electrodeposition of iron-based alloys from complexing electrolytes, with a focus on refractory metals as multifunctional materials having magnetic, catalytic, mechanical, and antimicrobial/antibacterial properties with advanced thermal, wear, and corrosion resistance. Peculiarities of electrodeposition from complexing electrolytes are practically significant as they can greatly influence the final structure, composition, and designed properties by adjusting the electroactive complexes in the solution. Moreover, these alloys can be further upgraded into composites, multi-layered, hybrid/recovered materials, or high-entropy alloys.
A Teacher-Learning-Based Optimization Approach for Blur Detection in Defocused Images
Authors: Khan Sana Munir , Mahmood Muhammad Tariq
Published: January 2025

Defocus blur is often encountered in images taken with optical imaging equipment. It might be unwanted, but it might also be a deliberate artistic effect, which means it might help how we see the scenario in an image. In specific applications like image restoration or object detection, there may be a need to divide a partially blurred image into its blurred and sharp regions. The effectiveness of blur detection is influenced by how features are combined. In this paper, we propose a parameter-free metaheuristic optimization strategy known as teacher-learning-based optimization (TLBO) to find an optimal weight vector for the combination of blur maps. First, we compute multi-scale blur maps, i.e., features using an LBP-based blur metric. Then, we apply a regularization scheme to refine the initial blur maps. This results in a smooth, edge-preserving blur map that leverages structural information for improved segmentation. Lastly, TLBO is used to find the optimal weight vectors of each refined blur map for the linear feature combination. The proposed model is validated through extensive experiments on two benchmark datasets, and its performance is comparable against five state-of-the-art methods.
The Comorbidity of Depression and Diabetes Is Involved in the Decidual Protein Induced by Progesterone 1 (Depp1) Dysfunction in the Medial Prefrontal Cortex
Authors: Xu Chen , Liao Mengxing , Zhang Shize , Chen Yuang , Shulai Xinyue , Wang Guangji , Aa Jiye
Published: January 2025

Background: There is a high rate of depressive symptoms such as irritability, anhedonia, fatigue, and hypersomnia in patients with type 2 diabetes mellitus (T2DM). However, the causes and underlying mechanisms of the comorbidity of depression and diabetes remain unknown. Methods: For the first time, we identified Decidual protein induced by progesterone 1 (Depp1), also known as DEPP autophagy regulator 1, as a hub gene in both depression and T2DM models. Depp1 levels were increased in the mPFC but not in other brain regions, such as the hippocampus or nucleus accumbens, according to Western blot and PCR assays. Results: Glucose dysregulation and synaptic loss occur in both depression and T2DM. The typical hyperglycemia in T2DM was observed in two models of depression, namely, chronic social defeat stress (CSDS) and chronic restraint stress (CRS). Hyperglycemia, which occurred in T2DM, was observed, and metabolomics data clearly showed the perturbation of glucose levels and glucose metabolism in the medial prefrontal cortex (mPFC). Decreased protein levels of BDNF and PSD95 suggested significant synaptic loss in depressed and diabetic mice. Conclusion: These findings suggest that the comorbidity of depression and diabetes is involved in the dysfunction of Depp1 in the mPFC.
Nipah Virus: A Zoonotic Threat Re-Emerging in the Wake of Global Public Health Challenges
Authors: Branda Francesco , Ceccarelli Giancarlo , Giovanetti Marta , Albanese Mattia , Binetti Erica , Ciccozzi Massimo , Scarpa Fabio
Published: January 2025

The re-emergence of the Nipah virus (NiV) in Kerala, India, following the tragic death of a 14-year-old boy, underscores the persistent threat posed by zoonotic pathogens and highlights the growing global public health challenge. With no vaccine or curative treatment available, and fatality rates as high as 94% in past outbreaks, the Nipah virus is a critical concern for health authorities worldwide. Transmitted primarily through contact with fruit bats or consumption of contaminated food, as well as direct human-to-human transmission, NiV remains a highly lethal and unpredictable pathogen. The World Health Organization has classified Nipah as a priority pathogen due to its alarming potential to cause widespread outbreaks and even trigger the next pandemic. Recent outbreaks in India and Bangladesh, occurring with seasonal regularity, have once again exposed the vulnerability of public health systems in containing this virus. This study explores the epidemiology, ecological factors driving transmission, and the public health response to NiV, emphasizing the role of zoonotic spillovers in pandemic preparedness. As the global community grapples with an increasing number of emerging infectious diseases, the Nipah virus stands as a stark reminder of the importance of coordinated surveillance, rapid containment measures, and the urgent development of novel strategies to mitigate the impact of this re-emerging threat.
A Bis-Glycosylamine Strategy for the Synthesis of Dimeric Iminosugars Based on a DAB-1 Scaffold
Authors: Lamara Kamilia Ould , Noël Nathan , Massicot Fabien , Vasse Jean-Luc , Vincent Stéphane P. , Behr Jean-Bernard
Published: January 2025

A straightforward synthetic route towards DAB-1 scaffolded dimeric iminosugars is described here, starting from readily available bis-glycosylamines. The method allows the integration of a variety of linkages (aryl, alkyl, polyethyleneglycol chains) between both iminosugars through the choice of the bis-amine used in the first step. Moreover, an additional substituent (allyl, ethynyl) may be inserted into the structure via nucleophilic addition of an organometallic reagent to the starting bis-glycosylamine. A symmetrical ethynyl-iminosugar proved susceptible to intramolecular Glaser coupling, affording the corresponding macrocyclic structure. Dimeric iminosugars were tested towards a series of commercial glycosidases to uncover potencies and selectivities when compared to DAB-1, their monomeric counterpart. Whereas a significant drop in inhibition potencies was observed towards glucosidases, some compounds displayed unexpected potent inhibition of β-galactosidase.
Malnutrition and Frailty Are Associated with a Higher Risk of Prolonged Hospitalization and Mortality in Hospitalized Older Adults
Authors: Tseng Hsiang-Kuang , Cheng Yun-Ju , Yu Hui-Kung , Chou Kuan-Ting , Pang Chin-Yen , Hu Gwo-Chi
Published: January 2025

Background/Objectives: Malnutrition and frailty are independent risk factors of prolonged hospitalization and mortality, respectively. However, the combined association of these conditions with the risk of prolonged hospitalization and mortality in hospitalized elderly patients remains unclear. Our object was to investigate the combined association of malnutrition and frailty on the risk of prolonged hospitalization and mortality in hospitalized elderly patients. Methods: The current study was a retrospective analysis of 470 patients admitted to the geriatric care unit of a tertiary hospital in Taiwan between 01 August 2019 and 31 March 2023. The Mini Nutritional Assessment-short form and Clinical Frailty Scale were used as evaluation tools for nutritional and frailty status, respectively. Patients were divided into four groups based on nutritional and frailty status. The association between these conditions and the risk of prolonged hospitalization and mortality was investigated using multivariate logistic and Cox proportional hazard models and adjusting for potential confounders. Results: Among 470 patients, 144 (31%) exhibited no malnutrition risk or frailty, 146 (31%) exhibited malnutrition risk but no frailty, 46 (10%) exhibited frailty but no malnutrition risk, and 134 (28%) exhibited both malnutrition risk and frailty. Compared to patients with neither condition, those with both conditions had higher risks of prolonged hospitalization (odds ratio 3.23, 95% confidence interval [CI] 1.68–6.12) and mortality (hazard ratio 4.33; 95% CI 2.01–9.34). Conclusion:: The co-occurrence of malnutrition and frailty has significant detrimental impacts on the risk of prolonged hospitalization and mortality in hospitalized older adults. The findings of this study emphasize the importance of early screening and intervention for malnutrition and frailty among hospitalized elderly patients.
Detection and Whole-Genome Characteristics of Bordetella trematum Isolated from Captive Snakes
Authors: Zając Magdalena , Bona Inga , Skarżyńska Magdalena , Kwit Renata , Lalak Anna , Skrzypiec Ewelina , Mikos-Wojewoda Emilia , Pasim Paulina , Wojdat Dominika , Koza Weronika , Wasyl Dariusz
Published: January 2025

Bordetella trematum is a rare member of the genus Bordetella, primarily associated with human wound infections rather than respiratory diseases. The bacterium has been isolated from various clinical specimens, including ear inflammatory discharge, diabetic ulcers, and chronic wounds. The study aimed to characterize the genomes and antimicrobial resistance (AMR) profiles of B. trematum obtained from the fecal samples of asymptomatic highland eyelash pit vipers (Bothriechis schlegelii). The identification was conducted using MALDI-TOF mass spectrometry and biochemical tests. AMR was assessed using the microbroth dilution method, while whole-genome sequencing was performed on the Illumina NextSeq platform. The isolates displayed characteristic B. trematum biochemical features and demonstrated a resistance to cefotaxime, ciprofloxacin, and trimethoprim, while one also exhibited a resistance to ceftazidime. The whole-genome sequencing and comparison with limited public data revealed a high diversity within B. trematum, reaching >48,000 single nucleotide polymorphisms (SNPs), with 64 SNP differentiating tested snake isolates and thus, being considered epidemiologically unrelated. This is the first report of B. trematum isolated from an animal source in Europe. The findings provide valuable insights into this rare bacterium’s phenotypic and genomic characteristics, addressing an important knowledge gap in its ecology and AMR profile.
A Systematic Review of Potential Opioid Prescribing Safety Indicators
Authors: Khawagi Wael Y. , Bansal Neetu , Shang Nan , Chen Li-Chia
Published: January 2025

Background/Objectives: This systematic review aimed to identify a comprehensive list of potential opioid-related indicators from the published literature to assess prescribing safety in any setting. Methods: Studies that reported prescribing indicators from 1990 to 2019 were retrieved from a previously published systematic review. A subsequent search was conducted from seven electronic databases to identify additional studies from 2019 to June 2024. Potential opioid safety prescribing indicators were extracted from studies that reported prescribing indicators of non-injectable opioids prescribed to adults with concerns about the potential risk of harm. The retrieved indicators were split by each opioid, and duplicates were removed. The identified indicators were categorized by the type of problem, medication, patient condition/disease, and the risk of the indicators. Results: A total of 99 unique opioid-specific prescribing indicators were identified from 53 included articles. Overall, 42 (42%) opioid prescribing indicators focused on a specific class of opioids. Pethidine, tramadol, and fentanyl were the most frequently reported drugs (n = 22, 22%). The indicators account for six types of problems: medication inappropriate for the population (n = 20), omission (n = 8), inappropriate duration (n = 10), inadequate monitoring (n = 2), drug–disease interaction (n = 26), and drug–drug interaction (n = 33). Of all the indicators, older age (over 65) is the most common risk factor (n = 38, 39%). Central nervous system-related adverse effects are the risk of concern for the 28 (29%) indicators associated with drug–drug interactions. Furthermore, five of the six ’omission’ indicators are related to ’without using laxatives’. Conclusions: This review identified a comprehensive set of indicators for flagging patients at high risk of opioid-related harm, thereby supporting informed decision-making in optimizing opioid utilization. However, further research is essential to validate these indicators and evaluate their feasibility across diverse healthcare settings.
Epistemic Goals of Scientific Inquiry: An Explanation Through Virtue Epistemology
Authors: Khort Mikhail
Published: January 2025

The paper examines the integration of virtue epistemology into the philosophy of science, emphasizing its potential to deepen our understanding of scientific inquiry. The article begins by considering the limitations of traditional epistemological frameworks that focus on beliefs. The discussion is set in the context of the “value turn” in contemporary epistemology. Arguments are made to move towards recognizing the significance of intellectual virtues and the nature of epistemic agents. The current gaps in definitions of intellectual virtues about reliabilist and responsibilist approaches are examined and conceptual steps are proposed to bridge these gaps. It is suggested that the local and general epistemic goals of science should be clearly distinguished and then different ways of knowing should be attributed to these goals. These ways of knowing are proposed to be seen as exemplifying the realization of reliable skills and intellectual character traits. In sum, the article argues that adopting a virtue epistemology not only enriches the discourse on scientific knowledge but also promotes a culture of responsibility and integrity in the scientific community.
Tunable Ultraviolet Pulse Generation from a High-Power Self-Similar-Amplification Yb-Fiber Laser
Authors: Wang Zefeng , Luo Daping , Xie Gehui , Deng Zejiang , Gu Chenglin , Li Wenxue
Published: January 2025

A tunable high-power 60 MHz ultraviolet pulse laser directly produced by the extra-cavity fourth-order harmonic generation of a self-similar amplification infrared pulse laser is reported in this study. Utilizing the self-similar pulse evolution and the self-phase modulation in a self-similar amplifier, the system generates a 58.9 W pulse train with a spectral half-width of 85.4 nm, corresponding to a pulse duration of 36 fs. To obtain the ultraviolet pulses from the infrared pulses, a single-pass frequency quadrupling system comprising two cascaded β-BBOs was used. The ultraviolet spectra can be tuned within a spectral range of 253.6 to 275 nm owing to the broadband infrared seed spectra. The maximum ultraviolet average power of 1.44 W was achieved at 275 nm with spectral half-width and an infrared-to-ultraviolet efficiency of 1.1 nm and 2.44%, respectively. To the best of our knowledge, this is the first demonstration of tunable high-power ultraviolet pulse generation from a self-similar amplification Yb-fiber laser.
Temperature Monitoring in PIC Surface
Authors: Pandey Sushma , Teixeira Antonio , Lima Mario
Published: January 2025

In this work we present the extended work of the previously proposed scheme for in-PIC temperature monitoring. This can be used in any photonic integrated circuitry platform, allowing simplified temperature monitoring and improved independence of the interrogating laser wavelength. Theoretically, power sensitivity was observed to be 0.77 dB/°C and 0.98 dB/°C for common mode and differential mode, respectively. The experimentally noted sensitivity of common mode and differential mode are 1.45 dB/°C and 0.8 dB/°C, respectively, at 1524 nm. The scheme allows the monitoring of the average temperature on the surface of the chip, which results from the global effect that affects both gratings (common mode) and the monitoring of the difference in temperature between gratings (differential mode).
Enhancing Thermal Insulation Property and Flexibility of Starch/Poly(butylene adipate terephthalate) (PBAT) Blend Foam by Improving Rheological Properties
Authors: Hong JunGi , Lee Junhyuk , Kim Sung Kyu , Son Dasom , Kang DongHo , Shim Jin Kie
Published: January 2025

Starch foam has attracted significant attention as an alternative to expanded styrene (EPS) foam owing to its abundance and biodegradability. Despite these merits, its limited thermal insulation and flexibility compared to EPS have hindered its utilization in packaging. Herein, we report the effect of blending with starch/PBAT on foaming behavior and physical properties during foaming processing. We fabricated a starch/PBAT blend with systematically controlled blending ratios (0, 10, 15, 20, and 25 wt%) to analyze their effect on the interaction and characteristics of blended foam. The blending of starch and PBAT significantly reduced complex viscosity, enhancing resin flow during the foaming process. This improvement in resin flow led to increases in expansion ratio while reducing density and cell wall thickness. The thermo-insulation performance improved to 0.043 W/mK with 20 wt% of PBAT due to the enhanced expansion ratio and cell morphology. Additionally, the flexural strain at break improved significantly from 2.8 ± 0.6% to 9.6 ± 1.0% with increasing PBAT content. Enhanced water resistance was also observed, demonstrated by a reduction in water absorption and an extension of dissolution time. Overall, these findings underscore the potential of starch/PBAT foam to improve the thermal-insulating property, flexibility, and water resistance while maintaining their biodegradability and sustainability.
Effects of Printing Orientation on the Tensile, Thermophysical, Smoke Density, and Toxicity Properties of Ultem® 9085
Authors: Vīndedze Elīna , Glaskova-Kuzmina Tatjana , Dejus Didzis , Jātnieks Jānis , Sevcik Scott , Bute Irina , Sevcenko Jevgenijs , Stankevich Stanislav , Gaidukovs Sergejs
Published: January 2025

Despite the impressive properties of additively manufactured products, their inherent anisotropy is a crucial challenge for polymeric parts made via fused filament fabrication (FFF). This study compared the tensile, thermophysical, smoke density, and toxicity characteristics of Ultem 9085 (a blend of polyetherimide and polycarbonate) for samples printed in various orientations (X, Y, and Z). The results revealed that mechanical properties, such as elastic modulus and tensile strength, significantly differed from the Z printing orientation, particularly in the X and Y printing layer orientations. Thermomechanical analysis revealed that Ultem 9085 had high anisotropic effects in the coefficient of thermal expansion, indicating superior thermal properties along the printing orientation. The smoke density and toxicity test results proved that Ultem 9085 complies with aviation safety standards. Smoke density tests showed that all samples, regardless of print orientation or thickness, stayed well below the regulatory limit, making them suitable for aircraft interiors.
The Influence of Iron Particles and Polyethylene Glycol on Selected Properties of Polylactide-Based Composites
Authors: Oksiuta Zbigniew , Nowińska Dominika , Joka Yildiz Magdalena , Jałbrzykowski Marek
Published: January 2025

This article presents the characteristics of composites comprising polylactide combined with iron powder, from 1 to 10 wt.%, and nanoiron powders with a mass fraction from 0.1 to 1.0 wt.%, along with polyethylene glycol. A total of nine composites were prepared, with three variations each: polylactide with iron powder, polylactide with nanoiron powder, and polylactide with micro- and nanoiron powder combined with polyethylene glycol. The samples underwent mixing, extrusion, and pressing processes. To assess the properties of the resultant composite samples, ultimate tensile tests, Shore hardness tests, fracture surface observations, degradation tests in 0.9% saline solution, and DSC analyses were conducted. The findings revealed that nanoiron powder incorporated into the polylactide matrix demonstrates better tensile properties, both strength and elongation, compared to those incorporating micrometric-iron powder only. However, both iron powder additions led to a decrease in the total elongation of neat polylactide acid except for the composite with 1% nanoiron. Furthermore, all samples with polyethylene glycol addition show a lower Young’s modulus compared to neat PLA. In general, the microiron powder decreases the Young’s modulus of PLA composites, whereas the nanoiron powder slightly increases the Young’s modulus of these samples. Polyethylene glycol, a biocompatible substance, emerged as a suitable candidate for enhancing the adhesion of iron particles and improving the strength and elongation properties of the tested composites. Also, fracture surface analysis of the tensile samples suggests using fine nanoiron particles instead of coarse ones to improve the mechanical properties due to the stronger bonding of nanoiron particles to the PLA matrix.
Mechanical Properties and Decomposition Behavior of Compression Moldable Poly(Malic Acid)/α-Tricalcium Phosphate Hybrid Materials
Authors: Hara Shuta , Kojima Akiko , Furukawa Atsushi , Toyama Takeshi , Ikake Hiroki , Shimizu Shigeru , Kurita Kimio
Published: January 2025

Calcified tissues in living organisms, such as bone, dentin, and enamel, often require surgical intervention for treatment. However, advances in regenerative medicine have increased the demand for materials to assist in regenerating these tissues. Among the various forms of calcium phosphate (CaP), tricalcium phosphate (TCP)—particularly its α-TCP form—stands out due to its high solubility and efficient calcium release, making it a promising candidate for bone regeneration applications. Nevertheless, its rapid dissolution rate presents challenges when used as a reinforcing agent. In this study, we developed a hybrid material composed of poly(malic acid) (PMA) and α-TCP to achieve controlled calcium release while maintaining mechanical strength. The hybrid materials were prepared using a compression molding method optimized to suppress the hydrolysis of PMA. The bond between the carboxyl group of PMA and α-TCP was confirmed through infrared (IR) spectroscopy. A calcium release test demonstrated that the interaction between PMA and α-TCP extends the dissolution period of both components. These findings indicate that PMA/α-TCP hybrid materials have significant potential for applications in bone tissue engineering.
The Use of Non-Conventional Sensors to Monitor and Evaluate the Quality of Coal During the Cleaning Process
Authors: Estrada-Ruiz Rosa Hilda , Flores-Campos Rubén , Ramos-Escobedo Gema Trinidad , Rodríguez-Reyes Mario , Martínez-Luevanos Antonia , Matamoros-Veloza Zully
Published: January 2025

Coal is one of the most important sources for energy generation. In order to reach buyer or legislation requirements, and prevent environmental pollution, coal must be washed by processes such as froth flotation to remove mineral matter and to increase the coal quality. Different techniques such as X-ray diffraction and artificial vision are employed to monitor coal flows during the washing process; nevertheless, these techniques require high-cost equipment and qualified personnel to perform the analysis; also, data interpretation is a time-consuming task. The use of non-conventional sensors, such as a solid–liquid electrical conductivity sensor, to forecast the quality of coal offers an easy to employ method to monitor the process in real time, take corrective actions and improve the resulting coal grade, reduce the loss of valuable material and reduce pollution, increasing the sustainability of the process. For this research, coal samples from Región Carbonífera in Coahuila, Mexico were analyzed to obtain their intrinsic characteristics and their electrical conductivity. It was found that the electrical conductivity value is directly proportional to the calorific value and inversely proportional to the ash content. A conductivity value increase from 25 to 30 µS/cm was obtained when using a surfactant modified coal pulp.
SFDA-MEF: An Unsupervised Spacecraft Feature Deformable Alignment Network for Multi-Exposure Image Fusion
Authors: Xiong Qianwen , Ren Xiaoyuan , Yin Huanyu , Jiang Libing , Wang Canyu , Wang Zhuang
Published: January 2025

Optical image sequences of spacecraft acquired by space-based monocular cameras are typically imaged through exposure bracketing. The spacecraft feature deformable alignment network for multi-exposure image fusion (SFDA-MEF) aims to synthesize a High Dynamic Range (HDR) spacecraft image from a set of Low Dynamic Range (LDR) images with varying exposures. The HDR image contains details of the observed target in LDR images captured within a specific luminance range. The relative attitude of the spacecraft in the camera coordinate system undergoes continuous changes during the orbital rendezvous, which leads to a large proportion of moving pixels between adjacent frames. Concurrently, subsequent tasks of the In-Orbit Servicing (IOS) system, such as attitude estimation, are highly sensitive to variations in multi-view geometric relationships, which means that the fusion result should preserve the shape of the spacecraft with minimal distortion. However, traditional methods and unsupervised deep-learning methods always exhibit inherent limitations in dealing with complex overlapping regions. In addition, supervised methods are not suitable when ground truth data are scarce. Therefore, we propose an unsupervised learning framework for the multi-exposure fusion of optical spacecraft image sequences. We introduce a deformable convolution in the feature deformable alignment module and construct an alignment loss function to preserve its shape with minimal distortion. We also design a feature point extraction loss function to render our output more conducive to subsequent IOS tasks. Finally, we present a multi-exposure spacecraft image dataset. Subjective and objective experimental results validate the effectiveness of SFDA-MEF, especially in retaining the shape of the spacecraft.
FAMHE-Net: Multi-Scale Feature Augmentation and Mixture of Heterogeneous Experts for Oriented Object Detection
Authors: Chen Yixin , Jiang Weilai , Wang Yaonan
Published: January 2025

Object detection in remote sensing images is essential for applications like unmanned aerial vehicle (UAV)-assisted agricultural surveys and aerial traffic analysis, facing unique challenges such as low resolution, complex backgrounds, and the variability of object scales. Current detectors struggle with integrating spatial and semantic information effectively across scales and often omit necessary refinement modules to focus on salient features. Furthermore, a detector head that lacks a meticulous design may face limitations in fully understanding and accurately predicting based on the enriched feature representations. These deficiencies can lead to insufficient feature representation and reduced detection accuracy. To address these challenges, this paper introduces a novel deep-learning framework, FAMHE-Net, for enhancing object detection in remote sensing images. Our framework features a consolidated multi-scale feature enhancement module (CMFEM) with integrated Path Aggregation Feature Pyramid Network (PAFPN), utilizing our efficient atrous channel attention (EACA) within CMFEM for enhanced contextual and semantic information refinement. Additionally, we introduce a sparsely gated mixture of heterogeneous expert heads (MOHEH) to adaptively aggregate detector head outputs. Compared to the baseline model, FAMEH-Net demonstrates significant improvements, achieving a 0.90% increase in mean Average Precision (mAP) of the DOTA dataset and a 1.30% increase in mAP12 of HRSC2016 datasets. These results highlight the effectiveness of FAMEH-Net in object detection within complex remote sensing images.
Maximum Mixture Correntropy Criterion-Based Variational Bayesian Adaptive Kalman Filter for INS/UWB/GNSS-RTK Integrated Positioning
Authors: Wang Sen , Dai Peipei , Xu Tianhe , Nie Wenfeng , Cong Yangzi , Xing Jianping , Gao Fan
Published: January 2025

The safe operation of unmanned ground vehicles (UGVs) demands fundamental and essential requirements for continuous and reliable positioning performance. Traditional coupled navigation systems, combining the global navigation satellite system (GNSS) with an inertial navigation system (INS), provide continuous, drift-free position estimation. However, challenges like GNSS signal interference and blockage in complex scenarios can significantly degrade system performance. Moreover, ultra-wideband (UWB) technology, known for its high precision, is increasingly used as a complementary system to the GNSS. To tackle these challenges, this paper proposes a novel tightly coupled INS/UWB/GNSS-RTK integrated positioning system framework, leveraging a variational Bayesian adaptive Kalman filter based on the maximum mixture correntropy criterion. This framework is introduced to provide a high-precision and robust navigation solution. By incorporating the maximum mixture correntropy criterion, the system effectively mitigates interference from anomalous measurements. Simultaneously, variational Bayesian estimation is employed to adaptively adjust noise statistical characteristics, thereby enhancing the robustness and accuracy of the integrated system’s state estimation. Furthermore, sensor measurements are tightly integrated with the inertial measurement unit (IMU), facilitating precise positioning even in the presence of interference from multiple signal sources. A series of real-world and simulation experiments were carried out on a UGV to assess the proposed approach’s performance. Experimental results demonstrate that the approach provides superior accuracy and stability in integrated system state estimation, significantly mitigating position drift error caused by uncertainty-induced disturbances. In the presence of non-Gaussian noise disturbances introduced by anomalous measurements, the proposed approach effectively implements error control, demonstrating substantial advantages in positioning accuracy and robustness.
MambaShadowDet: A High-Speed and High-Accuracy Moving Target Shadow Detection Network for Video SAR
Authors: Xu Xiaowo , Zhang Tianwen , Zhang Xiaoling , Zhang Wensi , Ke Xiao , Zeng Tianjiao
Published: January 2025

Existing convolution neural network (CNN)-based video synthetic aperture radar (SAR) moving target shadow detectors are difficult to model long-range dependencies, while transformer-based ones often suffer from greater complexity. To handle these issues, this paper proposes MambaShadowDet, a novel lightweight deep learning (DL) detector based on a state space model (SSM), dedicated to high-speed and high-accuracy moving target shadow detection in video SAR images. By introducing SSM with the linear complexity into YOLOv8, MambaShadowDet effectively captures the global feature dependencies while relieving computational load. Specifically, it designs Mamba-Backbone, combining SSM and CNN to effectively extract both global contextual and local spatial information, as well as a slim path aggregation feature pyramid network (Slim-PAFPN) to enhance multi-level feature extraction and further reduce complexity. Abundant experiments on the Sandia National Laboratories (SNL) video SAR data show that MambaShadowDet achieves superior moving target shadow detection performance with a detection accuracy of 80.32% F1 score and an inference speed of 44.44 frames per second (FPS), outperforming existing models in both accuracy and speed.
Laboratory Tests Using Distributed Fiber Optical Sensors for Strain Monitoring
Authors: Silveira Rodrigo Moraes da , Buras Marcelo , Pereira Filho André Luiz Delmondes , Fernandes Juliana Ferreira , Futai Marcos Massao
Published: January 2025

Using fiber optics as a tool for different kinds of geotechnical monitoring can be highly attractive and cost-effective when compared to conventional instruments, such as piezometers and inclinometers, among others. A single fiber optic cable may cover a larger monitoring area compared to conventional instrumentation and allows for monitoring more than one physical quantity with the same fiber optic cable. The literature provides several different examples of distributed fiber optic systems usage. For using any sensor, a calibration curve and parameters are required. In the case of strain sensors, calibration is required to derive strain values from the frequency measurement quantity. However, fiber optic sensor cable manufacturers do not often provide cable calibration parameters, and researchers should consult the specialized literature. This article thus presents a bench adjusted for tests with single-mode fiber optic cables, as well as results of tensile tests for defining the function of strain variations in two different optical fiber cables manufactured by different companies using two different distributed interrogators. This paper also proposes a methodology for calibrating fiber optic cable deformation. A few manufacturers of fiber optic cables aim at civil engineering applications. Therefore, we propose a calibration methodology to show the possibility of obtaining calibration parameters of any fiber optic cable, even those manufactured for telecommunications purposes and not only for cables manufactured for civil engineering use. Thus, researchers will not be restricted to the acquisition of special cables for their applications. The results allowed us to conclude that the application of calibrated fiber optic sensors to experimental pile foundations permits the evaluation of the load–displacement behavior of these elements under different loading conditions.
Partial Discharge Detection from Large Motor Stator Slots Using EFPI Sensors
Authors: Wang Jinlong , Sun Weizhong , Zhou Jun , Wang Lei , Chen Lianfei , Chen Pengcheng , Chen Qichao , Zhang Weichao
Published: January 2025

This study addresses the challenges of electromagnetic interference and unstable signal transmission encountered by traditional sensors in detecting partial discharge (PD) within stator slots of large motors. A novel Extrinsic Fabry–Perot Interferometer (EFPI) sensor with a vibration-coupling air gap was designed to enhance the narrowband resonant detection sensitivity for PD ultrasonic signals by optimizing the diaphragm structure and coupling interface. The sensor features a quartz diaphragm with a thickness of 20 μM, an effective constrained radius of 0.9 mm, a vibration-coupling air gap depth of 100 μM, and a first-order natural resonant frequency of 66 kHz. Simulation and experimental analyses revealed the distribution characteristics and propagation paths of ultrasonic signals within stator slots. The results demonstrate that the EFPI sensor effectively detects PD ultrasonic signals at its resonant frequency of 66 kHz with a localization error of less than 5 mm, meeting engineering requirements. This study provides theoretical and practical insights into the efficient detection and precise localization of insulation faults in large motor stators.
Reusable Biosensor for Easy RNA Detection from Unfiltered Saliva
Authors: Wityk Paweł , Terebieniec Agata , Nowak Robert , Łubiński Jacek , Mroczyńska-Szeląg Martyna , Wityk Tomasz , Kostrzewa-Nowak Dorota
Published: January 2025

Biosensors are transforming point-of-care diagnostics by simplifying the detection process and enabling rapid, accurate testing. This study introduces a novel, reusable biosensor designed for direct viral RNA detection from unfiltered saliva, targeting SARS-CoV-2. Unlike conventional methods requiring filtration, our biosensor leverages a unique electrode design that prevents interference from saliva debris, allowing precise measurements. The biosensor is based on electrochemical principles, employing oligonucleotide probes immobilized on a hydrophobic-coated electrode, which prevents air bubbles and salt crystal formation. During validation, the biosensor demonstrated a sensitivity and specificity of 100%, accurately identifying SARS-CoV-2 in saliva samples without false positives or negatives. Cross-validation with RT-qPCR, the gold standard for COVID-19 diagnostics, confirmed the reliability of our device. The biosensor’s performance was tested on 60 participants, yielding 12 true positive results and 48 true negatives, aligning perfectly with RT-qPCR outcomes. This reusable, easy-to-use biosensor offers significant potential for point-of-care applications in various healthcare settings, providing a fast, efficient, and cost-effective method for detecting viral infections such as COVID-19. Its robust design, minimal sample preparation requirements, and multiple-use capability mark a significant advancement in biosensing technology.
Self-Reduction of Nitric Oxide on Alumina-Supported Ultra-Small Nickel Particles
Authors: Magkoev Ramazan T. , Men Yong , Behjatmanesh-Ardakani Reza , Elahifard Mohammadreza , Pukhaeva Nelli E. , Takaev Aleksandr A. , Khekilaev Ramazan A. , Magkoev Tamerlan T. , Ashkhotov Oleg. G.
Published: January 2025

The adsorption and reaction of nitric oxide (NO) molecules on the surface of the model-supported metal/oxide system, consisting of Ni nanoparticles deposited on α-Al2O3 (0001) in ultra-high vacuum, have been studied using in situ surface-sensitive techniques and density functional theory (DFT) calculations. As a combination of X-ray and Auger electron spectroscopy (XPS, AES), Fourier-transform infrared (FTIR) spectroscopy, and temperature-programmed desorption (TPD) techniques reveals, there is a threshold of Ni particle mean size () of c.a. 2 nm, differentiating the electron state of adsorbed NO molecules and their reaction. The main feature of Ni particles normally not exceeding 2 nm is that the NO adsorbs in the form of (NO)2 dimers, whereas, for larger particles, the NO molecules adsorb in the form of monomers, usually characteristic for the bulk Ni substrate. This difference is demonstrated to be the main reason for the different reaction of NO molecules on the surface of Ni/alumina. The striking feature is that, in the case of ultra-small Ni particles ( ≤ 2 nm), the nitrous oxide (N2O) molecules are formed upon heating as a result of the NO self-reduction mechanism, which are otherwise not formed in the case of larger Ni particles. According to DFT results, this is due to the significant synergistic impact of NO co-adsorption on the neighboring NO dissociation reaction over ultra-small Ni particles, mediated by the metal/oxide perimeter interface. The observed molecular conversion effects offer an opportunity to tune the catalytic selectivity of this and related metal/oxide systems via varying the supported metal particle size.
Electrospinning for Biomedical Applications: An Overview of Material Fabrication Techniques
Authors: Tsareva Anastasiia D. , Shtol Valeriia S. , Klinov Dmitriy V. , Ivanov Dimitri A.
Published: January 2025

This review examines recent methodologies for fabricating nonwoven polymer materials through electrospinning, focusing on the underlying physical principles, including the effects of external parameters, experimental conditions, material selection, and primary operational mechanisms. Potential applications of electrospun polymer matrices in tissue engineering are analyzed, with particular emphasis on their utility in biomedical contexts. Key challenges in incorporating new materials into biomedical devices are discussed, along with recent advances in electrospinning techniques driving innovation in this field.
Optimization of Multi-Vehicle Cold Chain Logistics Distribution Paths Considering Traffic Congestion
Authors: Lu Zhijiang , Wu Kai , Bai E , Li Zhengning
Published: January 2025

Urban road traffic congestion has become a serious issue for cold chain logistics in terms of delivery time, distribution cost, product freshness, and even organization revenue and reputation. This study focuses on the cold chain distribution path by considering road traffic congestion with transportation, real-time vehicle delivery speeds, and multiple-vehicle conditions. Therefore, a vehicle routing optimization model has been established with the objectives of minimizing costs, reducing carbon emissions, and maintaining cargo freshness, and a multi-objective hybrid genetic algorithm has been developed in combination with large neighborhood search (LNSNSGA-III) for leveraging strong local search capabilities, optimizing delivery routes, and enhancing delivery efficiency. Moreover, by reasonably adjusting departure times, product freshness can be effectively enhanced. The vehicle combination strategy performs well across multiple indicators, particularly the three-type vehicle strategy. The results show that costs and carbon emissions are influenced by environmental and refrigeration temperature factors, providing a theoretical basis for cold chain management. This study highlights the harmonious optimization of cold chain coordination, balancing multiple constraints, ensuring efficient logistic system operation, and maintaining equilibrium across all dimensions, all of which reflect the concept of symmetry. In practice, these research findings can be applied to urban traffic management, delivery optimization, and cold chain logistics control to improve delivery efficiency, minimize operational costs, reduce carbon emissions, and enhance corporate competitiveness and customer satisfaction. Future research should focus on integrating complex traffic and real-time data to enhance algorithm adaptability and explore customized delivery strategies, thereby achieving more efficient and environmentally friendly logistics solutions.
Study on the Identification of Terminal Area Traffic Congestion Situation Based on Symmetrical Random Forest
Authors: Ji Yuren , Yu Fuping , Shen Di , Peng Yating
Published: January 2025

As the demand for air transport continues to increase, air traffic congestion in the terminal area is becoming more and more serious. In order to assist the controller in efficiently handling the symmetrical activities of aircraft take-off or landing and alleviate traffic congestion, this paper proposes a method for identifying traffic congestion situations based on complex networks and a multiclass random forest algorithm with symmetrical characteristics. First, the approach points, departure points, waypoints, and navigation stations are used as nodes, the flight paths as edges, and the busyness of the paths as edge weights to construct a traffic network model for the terminal area. On this basis, five congestion situation recognition indicators are selected from the perspective of network topology, and a symmetric multiclass random forest algorithm is proposed to recognize the congestion situation. Finally, this method is compared with the situation recognition method based on the traditional random forest algorithm. The results of the simulation experiment show that compared with the traditional random forest algorithm, the proposed recognition model improves the recognition accuracy by 17.5%, can better handle symmetry information, and can accurately determine the traffic congestion situation in the terminal area.
Performance Analysis of NR-DCSK Based Copper Cable Model for G.fast Communication
Authors: Al-Askery Ali Jaber , Al-Ali Ahmed Kamil Hasan , Hasan Fadhil Sahib
Published: January 2025

This article studies the performance of the copper wire communication channel in the existence of the Middleton impulsive noise model. Differential chaos shift keying (DCSK) scheme is implemented with a noise reduction (NR) technique to mitigate the impulsive noise effect and improve system performance. The proposed communication system is simulated using Monte Carlo simulation using MATLAB 2023 and the result is compared with the derived theoretical performance. The use of NR technique in accordance with the proposed model has improved the performance and promoted its use with G.fast Communication.
Unraveling the Invisible: Topological Data Analysis as the New Frontier in Radiology’s Diagnostic Arsenal
Authors: Singh Yashbir , Quaia Emilio
Published: January 2025

This commentary examines Topological Data Analysis (TDA) in radiology imaging, highlighting its revolutionary potential in medical image interpretation. TDA, which is grounded in mathematical topology, provides novel insights into complex, high-dimensional radiological data through persistent homology and topological features. We explore TDA’s applications across medical imaging domains, including tumor characterization, cardiovascular imaging, and COVID-19 detection, where it demonstrates 15–20% improvements over traditional methods. The synergy between TDA and artificial intelligence presents promising opportunities for enhanced diagnostic accuracy. While implementation challenges exist, TDA’s ability to uncover hidden patterns positions it as a transformative tool in modern radiology.