bluuebunny/crossref_metadata_2025 huggingface dataset:
In Vitro Interactions Between Bacteriophages and Antibacterial Agents of Various Classes Against Multidrug-Resistant Metallo-β-Lactamase-Producing Pseudomonas aeruginosa Clinical Isolates
Authors: Paranos Paschalis , Vourli Sophia , Pournaras Spyros , Meletiadis Joseph
Published: February 2025

Background: Combination therapy with antibiotics and phages has been suggested to increase the antibacterial activity of both antibiotics and phages. We tested the in vitro activity of five antibiotics belonging to different classes in combination with lytic bacteriophages against multidrug-resistant metallo-β-lactamase (MBL)-producing Pseudomonas aeruginosa isolates. Material/Methods: A total of 10 non-repetitive well-characterized MBL-producing P. aeruginosa isolates (5 NDM, 5 VIM) co-resistant to aminoglycosides and quinolones were used. Phage–antibiotic interactions were assessed using an ISO-20776-based broth microdilution checkerboard assay in 96-well microtitration plates. Two-fold dilutions of colistin (8–0.125 mg/L), ciprofloxacin, meropenem, aztreonam, and amikacin (256–4 mg/L) were combined with ten-fold dilutions of five different phages (5 × 109–5 × 100 PFU/mL) belonging to Pakpunavirus, Phikzvirus, Pbunavirus, and Phikmvvirus genus. Plates were incubated at 35 ± 2 °C for 24 h, and the minimum inhibitory concentration of antibiotics (MICA) and phages (MICP) were determined as the lowest drug and phage concentration, resulting in <10% growth based on photometric reading at 550 nm. Interactions were assessed based on the fractional inhibitory concentration index (FICi) of three independent replicates and clinical relevance based on the reversal of phenotypic resistance. The statistical significance of each drug alone and in combination with phages was assessed using GraphPad Prism 8.0. Results: Synergistic and additive interactions were found for 60–80% of isolates for all drugs. FICis were statistically significantly lower than 0.5 for colistin (p = 0.005), ciprofloxacin (p = 0.02), meropenem (p = 0.003), and amikacin (p = 0.002). Interactions were found at clinically achievable concentrations for colistin, meropenem, and amikacin, and a reversal of phenotypic resistance was observed for most strains (63–64%) for amikacin and meropenem. Antagonism was found for few isolates with all antibiotics tested. Phage vB_PaerM_AttikonH10 and vB_PaerP_AttikonH4 belonging to Phikzvirus and Phikmvvirus genus, respectively, showed either synergistic (FICi ≤ 0.35) or additive effects with most antibiotics tested. Conclusions: Synergy was observed for most drugs and phages with amikacin, showing strong synergy and reversal of phenotypic resistance against most isolates. Taking into account the wide utility of jumbo phages obtained, the findings of vB_PaerM_AttikonH10 in combination with different classes of antibiotics can enhance the activity of currently ineffective antibiotics against MBL-producing P. aeruginosa isolates.
Correction: Bakr et al. Efficacy of Quercetin and Quercetin Loaded Chitosan Nanoparticles Against Cisplatin-Induced Renal and Testicular Toxicity via Attenuation of Oxidative Stress, Inflammation, and Apoptosis. Pharmaceuticals 2024, 17, 1384
Authors: Bakr Alaa F. , El-Shiekh Riham A. , Mahmoud Mohamed Y. , Khalil Heba M. A. , Alyami Mohammad H. , Alyami Hamad S. , Galal Omneya , Mansour Dina F.
Published: February 2025

Error in Figure [...]
Compact Spectrometer: A Dedicated Compact Wide Band Spectrometer for Free-Electron Laser Monitoring
Authors: Zeni Gabriele , Frassetto Fabio , Di Fraia Michele , Coreno Marcello , Sansone Giuseppe , Contillo Adriano , Callegari Carlo , Poletto Luca
Published: February 2025

The calibration activities of the COmpact SPectrometer—COSP for the FERMI Free-Electron Laser (FEL) facility at the Elettra Synchrotron (Italy) are presented. COSP is an in-house built grating spectrometer designed to be used during the optimization of the FERMI parameters and to control the relative stability between different FEL harmonics in the multi-harmonic emission mode. The spectrometer is designed to work in single-shot mode at a repetition rate of 50 Hz providing medium resolution in a wide spectral range in order to either measure the separate intensities of the harmonics being mixed in a multi-color experiment or to quantify the amount of possible spurious harmonics. These activities are of key importance in the new class of experiments based on the wave mixing paradigm tested at the seeded FEL FERMI.
Optimizing Semiconductor Saturable Absorption Mirrors Using Subwavelength Dielectric Gratings for Fiber Lasers
Authors: Wei Chaoqun , Jia Xiansheng , Chen Hongmei , Liu Boyuan , Zhang Ziyang , Jiang Cheng
Published: February 2025

Ultrafast fiber lasers have shown exceptional performance across various domains, including material processing, medical applications, and optoelectronic communication. The semiconductor saturable absorber mirror (SESAM) is a key enabler of ultrafast laser operation. However, the narrow wavelength range and limited modulation depth of conventional SESAMs pose challenges to further advancing ultrafast fiber laser technology. To address these limitations, we explored the integration of guided mode resonance (GMR) effects to enhance light–matter interaction within the absorption layer. By incorporating subwavelength dielectric film gratings onto the cap layer of SESAMs, we excited GMR and formed a microcavity structure in conjunction with the distributed Bragg mirror (DBR). This design significantly improved the absorption efficiency of InAs quantum dots. The experimental results demonstrate that the modulation depth of the SESAM increased from 6.7% to 17.3%, while the pulse width was reduced by 2.41 times. These improvements facilitated the realization of a high-quality, stable ultrafast fiber laser. This study not only broadens the application potential of ultrafast lasers in diverse fields but also offers a practical pathway for advancing SESAM technology toward industrial-scale deployment.
Analytical Investigation of DNA Hybridization Sensing Using Integrated Photonic Micro-Ring Resonators
Authors: Vardhan Shalini , Singh Ritu Raj
Published: February 2025

The study of infected biological cells is crucial in modern biomedical research. This work presents a passive sensing approach using optical resonators, designed to detect malignant diseases within a refractive index (RI) range of 1 to 1.5. A comprehensive theoretical analysis is conducted, yielding an expected limit of detection (LoD) ranging from 0.03 nm/RIU to 0.92 nm/RIU. Furthermore, an in-depth investigation of DNA hybridization is performed, incorporating a 1.8 nm linker layer at the analyte boundary. The refractive indices of single-stranded DNA (ssDNA) and double-stranded DNA (dsDNA) are 1.456 and 1.529, respectively. The novelty of this work lies in the renaturation process of ssDNA to dsDNA, demonstrated through a labeled sensing modality with a measurable shift in the resonance wavelength spectrum. The proposed surface-functionalized resonators, designed using Silicon-on-Insulator (SOI) technology, include (a) a Rectangular Waveguide-based Ring Resonator (RWRiR), (b) a Rectangular Waveguide-based Racetrack Resonator (RWRaR), (c) a Slot Waveguide-based Ring Resonator (SWRiR), and (d) a Slot Waveguide-based Racetrack Resonator (SWRaR). Among these, the SWRiR exhibits the best performance for DNA sensing, achieving a quality factor (Q-factor) of 2216.714, a sensitivity (S) of 54.282 nm/RIU, and a normalized sensitivity (S’) of 0.0349.
Discrimination of the Skin Cells from Cellular-Resolution Optical Coherence Tomography by Deep Learning
Authors: Yi Jui-Yun , Huang Sheng-Lung , Li Shiun , Yen Yu-You , Chen Chun-Yeh
Published: February 2025

Optical coherence tomography (OCT) is a cellular-resolution imaging technique that can be used as non-invasive and real-time imaging and is useful for detecting early stages of diseases. Five in vitro skin cells were measured by the Mirau-based full-field OCT, including keratinocyte (HaCaT cell line), melanocyte, squamous cell carcinoma cell line (A431), and two melanoma cell lines, i.e., A375 and A2058. Deep learning algorithms (particularly convolutional neural networks, CNN) that extract features from images efficiently process the OCT’s complex images. We used four models to classify the images of five types of 2D-OCT skin cells. Based on the ResNet-15 model, the mean accuracy (average accuracy of 10-fold cross-validation) reaches 98.47%, and the standard deviation is only 0.28% with the data augmentation method. Interestingly, while two normal skin cell images mix and the other three cancer skin cell images mix, the model still works to identify normal and cancer cell features. The mean accuracy reaches 96.77%. Furthermore, we used k-fold analysis to detect the model reliability and adopt the Gradient-weighted Class Activation Mapping (GRAD-CAM) to explain the discrimination results. The deep learning algorithm is successfully and efficiently applied to discriminate the OCT skin cell images.
Genetic Variation of Growth Traits and Seed Production in a Patagonian Native Pasture in Semiarid Rangelands Under Different Environmental Settings
Authors: López Aldana Soledad , Nagahama Nicolás , Aparicio Alejandro , Azpilicueta María Marta , Guidalevich Verónica , Angeli Juan Pablo , Marchelli Paula
Published: February 2025

Rangelands play a crucial socioeconomic and environmental role worldwide. In South America, desertification and overgrazing has led to their deterioration and declining productivity. Breeding programs that use native forage species of economic and ecological importance, such as Festuca pallescens (St. Yves) Parodi, may provide locally adapted germplasm that enhances productivity without threatening local biodiversity. These programs may even promote the conservation of native species. To this end, we characterized the phenotypic variation of nondestructive variables (growth and reproductive traits) related to forage and seed production during spring and early summer (growth and reproductive periods). Plants from ten populations were grown under common garden conditions in two environmental settings (sites) over two years. By early summer of the second year, most populations maintained a consistent relative performance with higher values for basal diameter, height and synflorescence production at site 2. This suggests more favorable environmental conditions for the species and highlights their potential for enhancing both seed and forage production. The growth and reproductive traits were probably largely influenced by micro-environmental cues (i.e., soil type and moisture), showing predominantly plastic patterns. The populations displaying phenotypic plasticity and above-average values for both traits were selected for further evaluation in breeding programs.
Foliar Application of Amino Acids Increases Sweet Basil (Ocimum basilicum L.) Resistance to High-Temperature Stress
Authors: Deveikytė Justina , Blinstrubienė Aušra , Burbulis Natalija , Baltušnikienė Aldona
Published: February 2025

Climate change poses a significant threat to food security, with projections indicating a decline in crop yield due to reduced crop growth in the face of rising temperatures. This study evaluated the effects of L-Isoleucine, L-Methionine, L-Glutamine, L-Tryptophan, and L-Phenylalanine on the morphophysiological parameters, total phenolic content, and antioxidant activity of Sweet Basil (Ocimum basilicum L.) under high-temperature stress. Ten cultivar varieties of the sweet basil, “Rosie”, “Red Opal”, “Bordeaux”, “Dark Opal”, “Red Rubin”, “Genovese”, “Cinamon”, “Italiano Classico”, “Marseillais”, and “Thai”, were grown in a controlled-environment growth chamber. The seedlings with 5–6 true leaves were divided into seven groups: the first group of seedlings had no treatment and was grown under 25/22 °C (day/night) temperature, the second group of seedlings had no treatment and was grown under 35/30 °C (day/night) temperature, and the remaining five groups were sprayed with 100 mg L−1 of L-Isoleucine, L-Methionine, L-Glutamine, L-Tryptophan, or L-Phenylalanine. As our results show, L-Tryptophan increased fresh and dry biomass in green sweet basil, while L-Methionine had the greatest effect on biomass in purple varieties. L-Phenylalanine increased chlorophyll a and b in heat-stressed “Bordeaux” (purple variety) and “Marseillais” (green variety). L-Isoleucine and L-Glutamine increased total phenolic compounds (TPCs) in purple cultivars (“Rosie”, “Red Opal”, “Dark Opal”, and “Red Rubin”), while L-Tryptophan (“Cinamon” and “Italiano Classico”) and L-Phenylalanine increased TPCs in “Cinamon”, “Marseillais”, and “Thai” green cultivars. Antioxidant activity (ABTS) was highest in “Dark Opal” and “Bordeaux” treated with L-Tryptophan or L-Phenylalanine under heat stress, while “Thai” benefited most from L-Isoleucine. The exogenous application of amino acids could serve as a viable solution to alleviate the negative effects of temperature stress on sweet basil and serve as an environmentally friendly agricultural strategy.
Unveiling the Potential Role of Dhurrin in Sorghum During Infection by the Head Smut Pathogen Sporisorium reilianum f. sp. reilianum
Authors: Fall Coumba , Lim Seunghyun , Ahn Ezekiel , Park Sunchung , Prom Louis K. , Magill Clint W.
Published: February 2025

The cyanogenic glucoside dhurrin is found in sorghum and has been reported for its role in defense against biotic and abiotic stresses, both involving hydrogen cyanide (HCN) release. The fungus Sporisorium reilianum f. sp. reilianum (SRS) causes sorghum head smut and the infection occurs at the seedling stage, later resulting in panicle loss. Here, the focus was to determine the role of dhurrin in sorghum’s reaction against SRS infection. We investigated the genomic basis of HCN potential (HCNp) variation and its relationship with seedlings’ response to SRS inoculation, along with other sorghum traits, and the expression of dhurrin biosynthetic genes in SRS-inoculated young sorghum. Genome-wide association studies (GWAS) using HCNp scores showed significant single nucleotide polymorphisms (SNPs) on chromosomes harboring the dhurrin biosynthetic and catabolic genes but not in proximity. Significant hits were also detected in or near genes encoding proteins involved in plant defense/resistance against biotic stresses. Correlation analyses showed a strong positive relationship between average HCNp scores and latent period in SRS-inoculated sorghum seedlings. RT-qPCR revealed that the dhurrin biosynthetic genes were upregulated in the leaves of the head smut resistant line BTx635 up to two days after SRS inoculation. Our results suggest the involvement of dhurrin in sorghum’s protection against SRS.
Heterogeneity of Pore and Fracture Structure in Tight Sandstone Using Different Fractal Models and Its Influence on Porosity–Permeability Variation
Authors: Kang Qinrong , Jiang Yongdong , Li Jiahui , Qin Zhengyuan , Zhang Weizhong , Guo Yuqiang , Zhang Junjian
Published: February 2025

The study of pore structure in low-permeability sandstone uranium deposits has become a key factor in the profitability of uranium mining. In this paper, pore and fracture distribution in the target sandstone were determined by using mercury injection parameters. Single and multi-fractal models are used to calculate the heterogeneity of pore and fracture volume distribution. Moreover, the correlation between compressibility and the heterogeneity of pore distribution has been studied. The results are as follows. (1) All the samples can be divided into three types by using maximum mercury injection volume and mercury withdrawal efficiency. Type A is represented by a lower maximum mercury injection volume (less than 0.5 cm3·g−1) and a higher mercury withdrawal efficiency (larger than 25%). The volume percentage of pores whose diameter is less than 100 nm and 100~1000 nm in type A samples is larger than that of type B and C samples since in this type of sample, micropores are developed. (2) The fractal dimension value assessed using the Menger model has a good linear relationship with the thermodynamic model, which indicates that the abovementioned models have good consistency in characterizing the pore distribution of tight sandstone. Multi-fractal results show that the lower pore volume in the selected samples controls the heterogeneity of pore distribution in the overall sample. (3) As the effective stress increases, the permeability damage rate gradually increases in a power exponential equation. The correlation between porosity and compressibility is weaker, indicating that only a portion of the pore volume in the sample provides compression space. As the pore volume of 100~1000 nm increases, the compressibility decreases linearly, indicating that pore volumes larger than 1000 nm provide compression space for all the selected samples.
Optimizing Oil Recovery: A Sector Model Study of CO₂-Water-Alternating-Gas and Continuous Injection Technologies
Authors: Hussain Majid , Boukadi Fathi , Hu Zeming , Adjei Derrick
Published: February 2025

Optimizing oil recovery from mature reservoirs remains a key challenge in the petroleum industry. This study evaluates the efficiency of CO2-WAG injection compared to continuous CO2 and water flooding using a sector model of the X Oil Field. A compositional reservoir simulator was employed to analyze oil recovery under water-wet and mixed-wet conditions, incorporating three-phase relative permeability and wettability effects. The results show that continuous CO2 flooding yields the highest oil recovery, with water-wet systems outperforming mixed-wet reservoirs. CO2-WAG injection provides a balanced approach, enhancing recovery while enabling CO2 sequestration, but remains less effective than continuous CO2 flooding. Water flooding, though the least efficient in terms of oil recovery, demonstrates long-term production stability. The gas–oil ratio (GOR) is notably higher in CO2-WAG, indicating gas breakthrough challenges. These findings emphasize the significant role of wettability in enhanced oil recovery (EOR) and suggest that continuous CO2 flooding is the most effective technique for maximizing production in heterogeneous reservoirs. This study contributes valuable insights for optimizing injection strategies, improving hydrocarbon recovery, and supporting sustainable reservoir management.
Research on the Mechanism and Prevention Countermeasures of Stuck Coiled Tubing During Coiled Tubing Fracturing in the Junggar Basin
Authors: Yin Hongcheng , Ren Lan , Guo Changyong , Chen Xianjiang , Ren Qianqiu , Lin Ran , Deng Qinyue
Published: February 2025

The coiled tubing (CT) fracturing technology offers advantages such as pressurized dragging operation and maintaining a large borehole diameter after fracturing. However, during fracturing in the conglomerate and volcanic rock reservoirs of the Junggar Basin, CT stuck during retrieval occurs frequently. In this study, a model simulating the variation in the in situ stress field during CT hydraulic fracturing is established based on elastic mechanics and the displacement discontinuity method (DDM). Based on the geological characteristics of conglomerate and volcanic rock reservoirs in the Junggar Basin, and considering engineering parameters such as fracture length and fracture count in CT hydraulic fracturing, this study investigates the variation in the in situ stress during CT hydraulic fracturing and explores the stuck mechanism of CT. An index for fracturing completion is constructed to evaluate the stuck of CT during the fracturing process. With the goal of full stimulation of the horizontal section, a quantitative optimization design is conducted for the fracturing stage spacing and number of stages under different geological conditions, resulting in corresponding charts. The results indicate that the stuck mechanism during CT fracturing is caused by the continuous accumulation of stress induced by hydraulic fractures, leading to stress inversion. The fracturing completion increases with the stage spacing and the original horizontal stress difference. The length of the fractured section first increases and then decreases with the increase in stage spacing, while it increases with the original horizontal stress difference. The research findings can be applied to the optimization design of stage spacing and number of stages for CT hydraulic fracturing in conglomerate and volcanic rock reservoirs of the Junggar Basin, effectively preventing and controlling stuck coiled tubing in CT fracturing.
Practitioners’ Rule of Thumb for Quantum Volume
Authors: Dalla Torre Emanuele G.
Published: February 2025

Quantum volume (QV) is a widely recognized metric for assessing the practical capabilities of quantum computers, as it provides an estimate of the largest quantum circuit that can be reliably executed. However, measuring QV on a real device requires comparing experimental outcomes with ideal theoretical results—a process that rapidly becomes computationally expensive. By examining the cumulative impact of errors in two-qubit gates, we present a simple, accessible `rule of thumb’ that relates the quantum volume directly to the average error rate of native gates. Our formula shows a strong agreement with experimental data from leading quantum computing platforms, including both superconducting and trapped-ion systems. This straightforward model offers a clear, intuitive guideline for predicting quantum hardware performance, enabling more informed decisions regarding circuit design and resource allocation.
Superstition, Faith, and Scripture: Sakaino Kōyō and the Politics of Buddhism in Meiji Japan
Authors: Wu Peiyao
Published: February 2025

As described in several recent studies, the appropriation of the concept “religion 宗教” in modern Japan made “Buddhism 仏教” enter a transformation process that led, ultimately, to the reimagining of its very content; according to historian of religions Isomae Junichi, one of these elements was, for instance, an emphasis on “belief” to the detriment of “practice”. However, in terms of Buddhism’s reframing into the category of “religion”, we should also pay attention to the construction of the idea of “superstition 迷信”, which appears during this time as a concept relative to “belief” or “faith”. Often considered the epitome of this belief-centered version of the dharma, the so-called New Buddhism movement (shinbukkyō undō 新仏教運動) that occurred in the turn of the 20th century played a fundamental role in establishing the concept of “superstition”. This paper focuses on Sakaino Kōyō (境野黄洋 1871–1933), a pioneer of Chinese Buddhist studies in modern Japan and one of the main leaders of the movement. In order to explore the intellectual context that gave birth to such reformist efforts, I explore his ideas during the later 1890s, a period in which he was dedicated to differentiating “belief” from “superstition”. During this time, he emphasized the eradication of “superstition”, arguing that it constituted an unsound element both socially and intellectually. Sakaino offered the idea of “poetical Buddhism” (shiteki bukkyō 詩的仏教), a method for interpreting scripture in general, and segments thereof contemporarily regarded as “superstitious” specifically. This paper situates Sakaino’s contributions to Buddhist reform—analyzed through historical and hermeneutical methods and influenced by liberal Christian theology—within the global discourse on religion and science, while critically examining how his reinterpretations navigated tensions between modern rationality and the preservation of Buddhist truth in Meiji Japan.
The Design and Manufacturing of Mithra: A Humanoid Robot with Anthropomorphic Attributes and High-Performance Actuators
Authors: Semasinghe Chathura , Taylor Drake , Rezazadeh Siavash
Published: February 2025

While the concept of humanoid robots stems from the goal of replicating human movement, these systems have yet to match the elegance and efficiency of human locomotion. A key reason for this gap is that current humanoid robots differ from humans in their kinematics, dynamics, and actuator properties. This work seeks to close that gap by designing an optimized humanoid robot with characteristics closely resembling those of an average human. For this purpose, we built a detailed framework for the in-depth electromechanical modeling of actuator components. This model was used in the comprehensive optimization of the robot’s actuator system, which was designed as a multi-objective scheme based on the objectives introduced in our previous work. This process helped both in achieving efficient and high-performance actuators and in streamlining the design of the structural parts to have mass and inertia distributions similar to those of humans. The proposed design process was utilized in the design of our humanoid robot, Mithra. Initial test showed that Mithra achieved its design goals in terms of human-like kinematics and dynamics characteristics, together with sufficient actuator strength for tasks such as stair navigation, squatting, and running.
Comparative Analysis of Despeckling Filters Based on Generative Artificial Intelligence Trained with Actual Synthetic Aperture Radar Imagery
Authors: Cardona-Mesa Ahmed Alejandro , Vásquez-Salazar Rubén Darío , Travieso-González Carlos M. , Gómez Luis
Published: February 2025

The speckle is a granular undesired pattern present in Synthetic-Aperture Radar (SAR) imagery. Despeckling has been an active field of research during the last decades, with approaches from local filters to non-local filters that calculate the new value of a pixel according to characteristics of other pixels that are not close, the more advanced paradigms based on deep learning, and the newer based on generative artificial intelligence. For the latter, it is necessary to have a large enough labeled dataset for training and validation. In this study, we propose using a dataset designed entirely from actual SAR imagery, calculated by multitemporal fusion operations to generate a ground truth reference, which will yield the models to be trained with the actual speckle patterns in the noisy images. Then, a comparative analysis of the impacts of including the generative capacity in the models is performed through visual and quantitative assessment. From the findings, it is concluded that the use of generative artificial intelligence with actual speckle exhibits notable efficiency compared to other approaches, which makes this a promising path for research in the context of SAR imagery.
Enhancing Slip, Trip, and Fall Prevention: Real-World Near-Fall Detection with Advanced Machine Learning Technique
Authors: Schneider Moritz , Seeser-Reich Kevin , Fiedler Armin , Frese Udo
Published: February 2025

Slips, trips, and falls (STFs) are a major occupational hazard that contributes significantly to workplace injuries and the associated financial costs. The application of traditional fall detection techniques in the real world is limited because they are usually based on simulated falls. By using kinematic data from real near-fall incidents that occurred in physically demanding work environments, this study overcomes this limitation and improves the ecological validity of fall detection algorithms. This study systematically tests several machine-learning architectures for near-fall detection using the Prev-Fall dataset, which consists of high-resolution inertial measurement unit (IMU) data from 110 workers. Convolutional neural networks (CNNs), residual networks (ResNets), convolutional long short-term memory networks (convLSTMs), and InceptionTime models were trained and evaluated over a range of temporal window lengths using a neural architecture search. High-validation F1 scores were achieved by the best-performing models, particularly CNNs and InceptionTime, indicating their effectiveness in near-fall classification. The need for more contextual variables to increase robustness was highlighted by recurrent false positives found in subsequent tests on previously unobserved occupational data, especially during biomechanically demanding activities such as bending and squatting. Nevertheless, our findings suggest the applicability of machine-learning-based STF prevention systems for workplace safety monitoring and, more generally, applications in fall mitigation. To further improve the accuracy and generalizability of the system, future research should investigate multimodal data integration and improved classification techniques.
Dual-Encoder UNet-Based Narrowband Uncooled Infrared Imaging Denoising Network
Authors: Wang Minghe , Yuan Pan , Qiu Su , Jin Weiqi , Li Li , Wang Xia
Published: February 2025

Uncooled infrared imaging systems have significant potential in industrial hazardous gas leak detection. However, the use of narrowband filters to match gas spectral absorption peaks leads to a low level of incident energy captured by uncooled infrared cameras. This results in a mixture of fixed pattern noise and Gaussian noise, while existing denoising methods for uncooled infrared images struggle to effectively address this mixed noise, severely hindering the extraction and identification of actual gas leak plumes. This paper presents a UNet-structured dual-encoder denoising network specifically designed for narrowband uncooled infrared images. Based on the distinct characteristics of Gaussian random noise and row–column stripe noise, we developed a basic scale residual attention (BSRA) encoder and an enlarged scale residual attention (ESRA) encoder. These two encoder branches perform noise perception and encoding across different receptive fields, allowing for the fusion of noise features from both scales. The combined features are then input into the decoder for reconstruction, resulting in high-quality infrared images. Experimental results demonstrate that our method effectively denoises composite noise, achieving the best results according to both objective metrics and subjective evaluations. This research method significantly enhances the signal-to-noise ratio of narrowband uncooled infrared images, demonstrating substantial application potential in fields such as industrial hazardous gas detection, remote sensing imaging, and medical imaging.
A Self-Configurable BUS Network Topology Based on LoRa Nodes for the Transmission of Data and Alarm Messages in Power Line-Monitoring Systems
Authors: Alorda-Ladaria Bartomeu , Pons Marta , Isern Eugeni
Published: February 2025

Power transmission lines transfer energy between power plants and substations by means of a linear chain of towers. These towers are often situated over extensive distances, sometimes in regions that are difficult to access. Wireless sensor networks present a viable solution for monitoring these long chains of towers due to their wide coverage, ease of installation and cost-effectiveness. The proposed LoRaBUS approach implements and analyses the benefits of a linear topology using a mixture of LoRa and LoRaWAN protocols. This approach is designed to enable automatic detection of nearby nodes, optimise energy consumption and provide a prioritised transmission mode in emergency situations. On remote, hard-to-reach towers, a prototype fire protection system was implemented and tested. The results demonstrate that LoRaBUS creates a self-configurable linear topology which proves advantageous for installation processes, node maintenance and troubleshooting node failures. The discovery process collects data from a neighbourhood to construct the network and to save energy. The network’s autonomous configuration can be completed within approximately 2 min. In addition, energy consumption is effectively reduced 25% by dynamically adjusting the transmission power based on the detected channel quality and the distance to the nearest neighbour nodes.
Urban Traffic’s Influence on Noise and Particulate Matter Pollution
Authors: Avram Simona Elena , Tudoran Lucian Barbu , Borodi Gheorghe , Filip Miuta Rafila , Petean Ioan
Published: February 2025

Noise level and atmospheric pollutants such as particulate matter (PM) and combustion gases depend on car traffic. A highly circulated area in Cluj-Napoca City (Romania) was investigated based on sustainable principles. The noise level at the source was about 77 dB due to intense traffic of 214 units/10 min including cars, buses, trucks and pedestrians. It decreased slowly to 62 dB in the proximity of the first wall from the roadside (20 m distance) and significantly to about 50 dB beyond the buildings near the road (135 m from the source). The noise level was correlated with a high pollutant emission at the source: 25 µg/m3 (PM2.5), 45 µg/m3 (PM10) and 1.023 µg/m3 (total volatile organic compounds (TVOCs)). The PM10 level decreased to 38 µg/m3, while PM2.5 remained at a high level at 22 µg/m3 and TVOC slightly decreased to 0.974 µg/m3 at the distance of 10 m from the road. The PM2.5 and PM10 levels decreased significantly to 5 µg/m3 (PM10) and 18 µg/m3 (PM2.5) at a distance of 135 m from the road, and the TVOC level also decreased significantly to about 0.705 µg/m3. The PM crystalline structure was investigated by XRD coupled with mineralogical microscopy. Microstructure and elemental composition were assessed via high-resolution SEM coupled with EDS spectroscopy. It was found that PM2.5 was dominated by the finest clay fraction (e.g., kaolinite and muscovite), while PM10 was dominated by quartz and calcite. A large amount of organic matter was found adsorbed onto the finest particles by FTIR spectroscopy. The correlation between PM emissions and sound intensity indicates that intense noise extended for a long time facilitates the ultra-structural PM fraction sustentation into the atmosphere. A large number of clay nanoparticles (kaolinite 40 nm and muscovite 60 nm) were detected by AFM in the samples collected at the noise source, becoming sparser at a distance of 135 m from the source.
Gender Profiles of Local Government Heads and Economic Capacity of Territorial Communities: Evidence from Ukraine
Authors: Karyy Oleh , Hlynskyy Nazar , Gvozd Maryiana , Horbal Natalia , Skowron Łukasz , Golec Ewa , Artyukhova Nadiia
Published: February 2025

Achieving the 2030 Sustainable Development Goals set by the United Nations Conference on Sustainable Development requires proactive measures at different levels worldwide. In particular, increasing equality and women’s empowerment (SDG 5 “Gender equality”) in public governance is a crucial step in boosting economic growth and the sustainable development of communities, regions, and countries. This research investigates the relationship between gender equality in local governance and communities’ economic development. It is based on the correlation and regression analysis of statistical data pertaining to 118 territorial communities (TCs) in Ukraine and depicts the dependence between the gender composition of the local governments and the economic capacity of the territorial communities. These findings may influence comprehensive sustainable development at the community level globally.
Transforming Traditional Villages into Sustainable Communities: Evaluating Ecovillage Potential in Bursa, Turkey
Authors: Zeybek Osman , Erdoğan Elmas
Published: February 2025

Converting traditional villages into ecovillages provides a sustainable path for rural development by integrating ecological, social, and cultural aspects. This study utilizes the Community Sustainability Assessment (CSA) tool from the Global Ecovillage Network to evaluate the potential of six villages in Bursa, Turkey, across coastal, lowland, and mountain typologies using 21 themes and 900 criteria. Within the scope of the research, one-way analysis of variance (ANOVA) was applied to the quantitative data obtained from the CSA using IBM SPSS V28. The results indicate that coastal villages show greater potential for transition to a more sustainable lifestyle, while mountain villages face challenges with resource management and infrastructure. The villages show strong cultural and spiritual resilience, having existed for centuries, but many ecological practices have been lost due to urban migration. Recommendations include creating a national ecovillage database, training experts, supporting local projects, and convincing villagers of the transformation’s benefits. This study highlights the significance of the CSA for measuring sustainability potential and suggests future research on traditional villages in various geographies, along with developing region-specific methodologies. This approach focuses on enhancing existing villages rather than starting new ecovillages from scratch.
The Ecodesign Transformation of Smart Clothing: Towards a Systemic and Coupled Social–Ecological–Technological System Perspective
Authors: Zhu Shiqian , Liu Xiaogang
Published: February 2025

Smart clothing integrates advanced technologies such as textile materials, flexible electronics, and data communication systems, playing a pivotal role in driving productivity innovation within the textile and apparel industry. However, this emerging field faces substantial challenges, including high resource consumption, high disposal rates, and difficulties in material recycling and management. This paper presents an integrative review, analyzing 263 studies to examine the ecodesign transformation framework for smart clothing. The findings highlight multiple sustainability challenges associated with the linear lifecycle of traditional smart clothing. By assessing ecodesign strategies across various stages of the lifecycle, the study emphasizes the need for a shift from a product-focused approach to system-level innovation in the ecodesign of smart clothing. Building on this, we propose a systematic, coupling ecodesign framework to facilitate the sustainable transformation of smart clothing. This framework is grounded in the principles of circular economy and Social–Ecological–Technological Systems (SETSs). Our work not only aims to contribute to the achievement of the United Nations 2030 Agenda for Sustainable Development Goals but also aligns with the core objectives of the European Green Deal, focusing on resource efficiency and low environmental impact. We seek to provide a feasible theoretical framework to guide the sustainable transformation of smart clothing.
Navigating Unreasonable, Unsustainable and Unjust Financial Practices: Experiences of Indigenous Small Business Owners
Authors: Blue Levon , Brimble Mark , Bodle Kerry , Frazer Lorelle , Weaven Scott , Hunt Douglas
Published: February 2025

Indigenous peoples continue to be underrepresented in small businesses in Australia. The aim of this paper was to explore the financial practices impacting the sustainability of Indigenous small business owners. We sought to find out how Indigenous Australian small business owners sustain their small businesses by exploring the associated financial practices. To achieve this, we conducted 45 interviews with Indigenous small business owners and stakeholders. We analysed the interviews to identify themes and then grouped the themes into three categories: (1) personal, relational and institutional considerations; (2) operational (internal and external) challenges; and (3) development challenges (that hinder business operations). We found unreasonable, unsustainable and/or unjust financial practices across the personal, relational and institutional considerations that Indigenous Australian small business owners face. Based on these findings, we recommend changes to provide government-funded opportunities for Indigenous graduates to offer business training. We also advocate for increased access to funding for Indigenous small businesses and analysis of loan frameworks nationally to identify ways to transform financial practices associated with lending. Our recommendations, if adopted, could help to further strengthen support initiatives that benefit Indigenous Australians.
Unmanned Aerial Vehicle Path Planning Method Based on Improved Dung Beetle Optimization Algorithm
Authors: Lv Fengjun , Jian Yongbo , Yuan Kai , Lu Yubin
Published: February 2025

To address the problem of UAV path planning in complex mountainous terrains, this paper comprehensively considers constraints such as natural mountain and obstacle collision threats, the shortest path, and flight altitude. We propose a more practical UAV path planning model that better reflects the actual UAV path planning situation in complex mountainous areas. In order to solve this model, this paper improves the traditional dung beetle optimization (DBO) algorithm and proposes an improved dung beetle optimization (IDBO) algorithm. The IDBO algorithm optimizes the population initialization method based on the concept of symmetry, ensuring that the population is more evenly distributed within the solution space. Additionally, the algorithm introduces a sine–cosine function-based movement strategy, inspired by the symmetry principle, to enhance the search efficiency of individual population members. Furthermore, a population evolution strategy is incorporated to prevent the algorithm from getting stuck in local optima. To demonstrate the algorithm’s performance, tests were conducted using 23 commonly used benchmark functions provided by the CEC 2005 competition and six commonly used engineering problem models provided by the CEC 2020 competition. The results indicate that IDBO significantly outperforms DBO in terms of convergence performance, effectively solving various engineering optimization problems. Finally, experimental tests under three different threat scenarios show that the proposed IDBO algorithm has scientific validity when applied to UAV path planning. This solution method effectively reduces UAV flight energy consumption costs and obstacle collision threats while improving the efficiency and accuracy of UAV path planning.
The Influence of Intellectual Humility in External Successor CEOs on Corporate Strategic Change
Authors: Niu Aiwen , Gao Changchun , Yu Chenhui
Published: February 2025

Research shows that strategic change can reshape a company’s competitive advantage and significantly impact organizational performance. This study examines the role of Intellectual Humility (IH) in driving strategic change, particularly in the context of external successor CEOs. The overall aim of the study is to explore how external successor CEOs’ IH influences strategic change, and to uncover the underlying mechanisms at play. Based on the Upper Echelons Theory, the paper proposes a moderated mediation model to explore how strategic change occurs during external succession. It highlights the mediating role of strategic execution between IH and strategic change, and the moderating effect of organizational learning (OL). Data from 391 valid responses to electronic questionnaires from CEOs of companies established for over two years were analyzed. The results show that external successor CEOs’ IH positively influences strategic change, with strategic execution mediating this effect. However, organizational learning was found to have no significant moderating effect on this relationship. Our study fills a gap in the literature by highlighting IH as a key factor in external CEO succession. It challenges traditional views on succession and demonstrates how IH can enhance strategic execution and innovation. The findings suggest that IH should be a critical criterion in CEO selection, especially during leadership transitions, to optimize strategic change and improve long-term organizational success.
New Combination and Two Synonyms of Indocalamus Nakai (Poaceae: Bambusoideae) from China Based on Morphological Characters and Phylogenetic Evidence
Authors: Gao Liqin , Li Yonglong , Wang Chengkun , Wang Jianqing , Yang Guangyao , Zhang Wengen
Published: February 2025

Based on several sources of evidence from morphology, the micromorphology of the abaxial leaf epidermis, and a phylogenetic analysis using complete chloroplast genome data, a new combination and two new synonyms are reported in the genus Indocalamus Nakai. Indocalamus cordatus T. H. Wen et Y. Zou is synonymized with I. tessellatus (Munro) P. C. Keng, and I. multinerus (W. T. Lin et Z. M. Wu) W. T. Lin is synonymized with I. chebalingensis W. T. Lin. As a new combination, I. mollis (H. R. Zhao et Y. L. Yang) L. Q. Gao, W. G. Zhang et G. Y. Yang was created and is supplementally described. In addition, the lectotype of I. chebalingensis is designated herein.
Temporal and Spatial Analysis of Rabies Virus Lineages in South Africa
Authors: Viljoen Natalie , Sabeta Claude , Markotter Wanda , Weyer Jacqueline
Published: February 2025

Rabies virus (RABV; species Lyssavirus rabies) causes rabies, a disease of the central nervous system that invariably results in the death of the host. In South Africa, studies have indicated that RABV is maintained by animal species that include four wildlife carnivore species—the black-backed jackal (Canis mesomelas), bat-eared fox (Otocyon megalotis), yellow mongoose (Cynictis penicillata), and aardwolf (Proteles cristatus)—and domestic dogs (Canis lupus familiaris). The complex natural ecology holds significant implications for the control and elimination of rabies. In this study, confirmed animal rabies case data, including geospatial features, were analyzed for 12,879 laboratory-confirmed animal cases reported on a database managed by the Department of Agriculture, Land Reform and Rural Development (DALRRD). Sequence data generated from animal rabies cases in South Africa were also analyzed, which included 1374 cytoplasmic domain of the glycoprotein and the G-L intergenic sequences using maximum likelihood (ML) and Bayesian inference. The analysis provides insights into the transmission dynamics involving several wildlife species and domestic dogs in South Africa. This information is crucial for the strategic planning for rabies control and elimination programs, and particularly in understanding the interlinked nature of some lineages and the importance of the cross-border spread of rabies. This analysis provided an improved understanding of the distribution of the RABV lineages in South Africa and identified areas that can be targeted for rabies control strategies to limit future spread of RABV, which is important due to the limited available resources that must be carefully managed to allow optimal control.
MCP-1 Reduction by L-SIGN Expression in Dengue Virus-Infected Liver Endothelial Cells
Authors: Liu Keh-Sen , Wang Lin , Chen Po-Ming , Lee Ing-Kit , Yang Kuender D. , Chen Rong-Fu
Published: February 2025

(1) Background: The C-type lectin domain family 4 member M (CLEC4M, also known as L-SIGN) is a crucial pathogen-recognition receptor for the dengue virus (DENV). Our previous study has exhibited a polymorphism in its extracellular neck region, specifically within the long tandem repeats of exon 4, which correlates with DHF in DENV infection and causes liver damage. (2) Methods: Using monocyte-derived dendritic cells (MDDCs) and SK-HEP1 liver endothelial cell lines to compare viral replication relative to L-SIGN expression. (3) Results: Results indicated that SK-HEP1 cells were more susceptible to DENV infection than MDDCs, and L-SIGN transfection significantly increased viral replication in SK-HEP1 cell lines. The study also found that L-SIGN-enhanced DENV infection is mediated by the decrease in monocyte chemoattractant protein-1 (MCP-1) but not interferon gamma inducible protein-10 (IP-10). These findings reveal that L-SIGN-induced DENV infection leads to reduced MCP-1 levels, which, in turn, enhances DENV replication velocity. (4) Conclusions: This study offers insights into the molecular mechanisms of DENV replication and identifies potential therapeutic targets involving MCP-1 and L-SIGN pathways.