bluuebunny/crossref_metadata_2025 huggingface dataset:
Experimental Study of Alkali-Activated Cementitious Materials Using Thermally Activated Red Mud: Effect of the Si/Al Ratio on Fresh and Mechanical Properties
Authors: Guo Kai , Dong Haifeng , Zhang Junyi , Zhang Liqing , Li Zhiping
Published: February 2025

Bayer red mud (RM)-based geopolymers are economical and ecofriendly alternatives to cement because of their superior performance. This study investigated alkali-activated cementitious materials by combining RM, fly ash (FA) and slag, and the mixtures were used to produce ecofriendly composites. The influence of the Si/Al molar ratio (3.30–3.79) on the initial properties (setting time and flowability) and hardened properties (compressive strength, drying shrinkage and water permeability) of the composite materials was studied. The Na2O content was fixed at 4 wt%, and the thermal activation temperature was 800 °C. The phase evolution and geopolymerization mechanism of the effect of the initial Si/Al molar ratio on the material properties was investigated by FTIR, XRD, TG–DTG and SEM–EDS. The results of M1.2Si333 indicated that the compressive strength of the blends can reach 33.5 MPa at 28 days, with a drying shrinkage rate of 1.20%. Compressive strength decreases, while drying shrinkage increases with a higher initial Si/Al ratio. Microstructural analyses revealed that a low Si/Al ratio and alkali activator modulus enhance the dissolution of precursors to form C–(A)–S–H gels, which increase the compressive strength. The results promoted the application of RM-based geopolymer-engineered cementitious composite and enhanced the resource efficiency of the bauxite residue.
Nanoparticle Air Filtration Using MXene-Coated Textiles
Authors: Upadhyay Prastuti , Ippolito Stefano , Mohammadlou Bita Soltan , Waring Michael S. , Gogotsi Yury
Published: February 2025

Nanoparticles with aerodynamic diameters of less than 100 nm pose serious problems to human health due to their small size and large surface area. Despite continuous progress in materials science to develop air remediation technologies, efficient nanoparticle filtration has appeared to be challenging. This study showcases the great promise of MXene-coated polyester textiles to efficiently filter nanoparticles, achieving a high efficiency of ~90% within the 15–30 nm range. Using alkaline earth metal ions to assist textile coating drastically improves the filter performance by ca. 25%, with the structure–property relationship thoroughly assessed by electron microscopy and X-ray computed tomography. Such techniques confirm metal ions’ crucial role in obtaining fully coated and impregnated textiles, which increases tortuosity and structural features that boost the ultimate filtration efficiency. Our work provides a novel perspective on using MXene textiles for nanoparticle filtration, presenting a viable alternative to produce high-performance air filters for real-world applications.
Applications of Artificial Intelligence for the Prediction and Diagnosis of Cancer Therapy-Related Cardiac Dysfunction in Oncology Patients
Authors: Scalia Isabel G. , Pathangey Girish , Abdelnabi Mahmoud , Ibrahim Omar H. , Abdelfattah Fatmaelzahraa E. , Pietri Milagros Pereyra , Ibrahim Ramzi , Farina Juan M. , Banerjee Imon , Tamarappoo Balaji K. , Arsanjani Reza , Ayoub Chadi
Published: February 2025

Cardiovascular diseases and cancer are the leading causes of morbidity and mortality in modern society. Expanding cancer therapies that have improved prognosis may also be associated with cardiotoxicity, and extended life span after survivorship is associated with the increasing prevalence of cardiovascular disease. As such, the field of cardio-oncology has been rapidly expanding, with an aim to identify cardiotoxicity and cardiac disease early in a patient who is receiving treatment for cancer or is in survivorship. Artificial intelligence is revolutionizing modern medicine with its ability to identify cardiac disease early. This article comprehensively reviews applications of artificial intelligence specifically applied to electrocardiograms, echocardiography, cardiac magnetic resonance imaging, and nuclear imaging to predict cardiac toxicity in the setting of cancer therapies, with a view to reduce early complications and cardiac side effects from cancer therapies such as chemotherapy, radiation therapy, or immunotherapy.
IER5 Promotes Ovarian Cancer Cell Proliferation and Peritoneal Dissemination
Authors: Krishnaraj Jayaraman , Ueno Sayaka , Nakamura Moe , Tabata Yuko , Yamamoto Tatsuki , Asano Yoshinori , Tanaka Tomoaki , Kuzuyama Tomohisa , Saya Hideyuki , Ohki Rieko
Published: February 2025

Background/Objective: Ovarian cancer (OC) is one of the most lethal gynecological cancers, having a worldwide mortality rate of 66% in 2020. The overall 5-year relative survival rate is only 21% for distant stages, due to the lack of early diagnosis. Epithelial OC, the most common high-grade serous carcinoma, carries p53 mutations in most cases. However, we found that the immediate early response 5 gene (IER5), a p53 target gene, is overexpressed in ovarian cancer cells. The molecular mechanism underlying the role of IER5 in OC has not been well studied. We previously reported that IER5 promotes the dephosphorylation and activation of heat shock factor-1 (HSF1), the master regulator of proteostasis, which induces heat shock protein (HSP) expression. Methods/Results: Here we show that Ier5 mRNA expression is higher in ovarian cancer cells (MOV, ID8G, and HM-1) compared to normal ovarian cells. We also show that OC cells floating in the ascites have higher Ier5 expression than the parental strain. Knockdown of Ier5 suppressed HSP upregulation and proliferation of OC, while overexpression of IER5 promoted HSP upregulation. Knockdown of Hsf1 showed results similar to Ier5 knockdown. Conclusions: These results indicate that the IER5-HSF1 pathway contributes to the proliferation and peritoneal dissemination of OC cells. We also found that higher expression of IER5 family genes is related to poorer prognosis of OC patients, suggesting the potential of the IER5 gene family as diagnostic markers for OC, as well as potential therapeutic targets.
Enhancing Photocatalytic Hydrogen Evolution with Oxygen Vacancy-Modified P/Ag/Ag2O/Ag3PO4/TiO2 by Using Optimized NaBH4 Reduction Strategy
Authors: Sun Xiang , Zhu Yunxin , An Guangqi , Chen Guoping , Yang Yingnan
Published: February 2025

The introduction of oxygen vacancies (OVs) is a promising strategy to enhance the hydrogen (H2) evolution efficiency of photocatalysts. Sodium borohydride (NaBH4) is widely used as a reducing agent to introduce OVs, particularly in composite materials. However, its impact on H2 evolution remains underexplored. In this study, by employing various mass ratios of NaBH4 to P/Ag/Ag2O/Ag3PO4/TiO2 (PAgT), OVs modified PAgT (R-PAgT) composites, which were synthesized and systematically characterized by XRD, FT-IR, and XPS. R-PAgT-10 with an optimal mass ratio exhibited a superior H2 evolution efficiency and stability, maintaining its performance over 20 cycles under visible light irradiation, while the higher mass ratio of NaBH4/PAgT led to the disruption of the crystal structure with excessive OVs amounts, resulting in poor stability. This study highlighted the importance of utilizing the optimal mass ratio of NaBH4 to prepare OVs-PAgT for successful and stable H2 evolution under visible light irradiation, which holds promise for developing efficient and durable photocatalysts for renewable energy applications.
Circular RNA ZNF277 Sponges miR-378d to Inhibit the Intracellular Survival of Mycobacterium tuberculosis by Upregulating Rab10
Authors: Zhu Yifan , Zhang Lei , Wang Zijian , Li Ting , Chen Yingyu , Lu Lu , Liu Han , Kong Delai , Peng Yongchong , Chen Xi , Hu Changmin , Chen Huanchun , Guo Aizhen
Published: February 2025

Circular RNAs (circRNAs) are covalently closed non-coding RNAs formed by back-splicing, lacking a 5′ cap and poly-A tail. They could act as important regulatory factors in the host’s anti-tuberculosis immune process, but only a few have been identified, and their molecular mechanisms remain largely unclear. Here, we identified a novel circRNA, circ-ZNF277, which responds to Mycobacterium tuberculosis (Mtb) infection in THP-1 cells. Circ-ZNF277 binds microRNA-378d (miR-378d) in vivo. The expression level of circ-ZNF277 affects the clearance of the intracellular Mtb in THP-1 cells. Mechanistically, more circ-ZNF277 molecules could absorb more miR-378d, thereby competitively activating the NF-κB signaling pathway, promoting the release of pro-inflammatory cytokines including interleukins IL-1β and IL-6, and tumor necrosis factor-α (TNF-α), and inhibiting the survival of intracellular Mtb. Expressing miR-378d or si-Rab10 targeting the transcription of Rab10 could antagonize the effects of overexpression of circ-ZNF277, resulting in the reduced intracellular survival of Mtb. In summary, circ-ZNF277 inhibits the intracellular survival of Mtb via the miR-378d/Rab10 axis. This finding represents a novel mechanism of circular RNA in regulating host immune responses during Mtb infection.
Clinical Associations with Lenticulostriatal Vasculopathy (LSV) at Birth: A Case–Control Study
Authors: Kyriakopoulou Aikaterini , Samikos Kyriakos , Kanavaki Aikaterini , Alexopoulou Efthymia , Argyropoulou Maria , Psaltopoulou Theodora , Kanaka-Gantenbein Christina , Dinopoulos Argyrios , Giorgi Melpomene , Antoniadou Anastasia , Filippa Iliani , Siafakas Nikolaos , Serghiou Stylianos , Papaevangelou Vassiliki
Published: February 2025

Objective: To investigate the clinical characteristics associated with the presence of LSV at birth. Design: Prospective 1:1 case–control study. Setting: Two tertiary neonatal units in Athens, Greece. Patients: Premature neonates (≤36 weeks gestational age) who underwent cerebral ultrasound within the first 3 weeks of life, where LSV was detected. Main outcome measure: Associations between LSV and clinical characteristics at birth. Both unmatched and matched analyses stratifying the study population by gestational week were conducted. Two-sided p-values were computed using the likelihood ratio test. Results: This study included 166 participants (83 cases and 83 controls). Neonates with LSV exhibited more concurrent cerebral findings, notably periventricular echogenicity. LSV was correlated with higher z-scores for head circumference and body length. LSV was not associated with congenital CMV. Conclusions: This study indicated a relationship between LSV and increased head circumference and body length. Further research is warranted to explore LSV’s pathophysiological mechanisms.
Changes in Seagrass Landscape Configuration in a Caribbean Reef Lagoon Indicate an Ecosystem Shift After Repeated Disturbances
Authors: Ávila-Mosqueda S. Valery , van Tussenbroek Brigitta I. , Garza-Pérez Joaquín Rodrigo
Published: February 2025

Since 2011, recurring Sargassum Brown Tides (SBTs), caused by periodic massive influxes of holopelagic Sargassum spp., have impacted seagrass meadows in the 50–200 m wide nearshore fringes of Mexican Caribbean reef lagoons. The present study aimed to assess the cumulative effects of SBTs in 2015 and 2018–2019 through a spatial–temporal analysis of seagrass meadows in the Puerto Morelos reef lagoon. We hypothesized that the impacts of the SBTs likely extended beyond the near-shore fringe and were detectable across the seagrass landscape throughout the entire reef lagoon. Through time, the spatial configuration of the seagrass meadows presented a new self-organized configuration linked to spatial fragmentation, an increase in the number of patches but a decrease in size, and changes in vegetation communities, indicating a shift in ecosystem state. This shift may serve as an early warning signal of reef system deterioration. Monitoring seagrass meadow status using this approach provides a deeper understanding of their dynamics, shifts and resilience, and will facilitate the development of timely management strategies.
Environmental Impact of Physical Vapour Deposition and Plasma-Enhanced Chemical Vapour Deposition Technologies for Deposition of Diamond-like Carbon Coatings for Green Tribology
Authors: Ihara Larissa , Wu Guizhi , Cavaleiro Albano , Morina Ardian , Yang Liuquan
Published: February 2025

With low friction and high hardness, diamond-like carbon (DLC) coatings are a prominent surface engineering solution for tribosystems in various applications. Their versatility stems from their varying composition, facilitated by different deposition techniques, which affect their properties. However, environmental impact is often overlooked in coating design. The objective of this paper is to assess the resource efficiency of four different common deposition techniques, thus identifying critical factors for sustainable DLC deposition. The coatings were deposited in one single chamber, enabling a direct comparison of the resource consumption of each technology. Expenditure of electric energy and consumables per volumetric output accounted for the environmental impact of manufacturing the coatings, which was evaluated across the indicators of damage to human health, damage to ecosystems, and resource scarcity. Electric energy use, dictated by deposition rate, was demonstrated to be the most significant factor contributing to the environmental impact. The environmental impact of PECVD and μW-PECVD was comparable and remarkably lower than that of dcMS and HiPIMS, the latter being the least energy efficient process, with the lowest output rate but highest energy expenditure. Thus, μW-PECVD could be considered the ‘greenest’ production method. These findings are consequential for coaters to efficiently produce good-quality DLCs with low environmental impact.
IoT Integration Approaches into Personalized Online Learning: Systematic Review
Authors: Spaho Edlir , Çiço Betim , Shabani Isak
Published: February 2025

The integration of the Internet of Things (IoT) in education has fundamentally transformed personalized online learning (POL), enabling adaptive, context-aware environments that tailor learning based on real-time environmental data or device usage. This approach fosters learner-centered environments that customize content and pace according to individual needs and preferences. All are powered by interconnected devices and data analysis. This review systematically explores various technological and pedagogical approaches to integrate IoT in POL systems, including devices, communication technologies, context-aware mechanisms, integration frameworks, computing technologies, and implemented pedagogical methods. By examining 61 peer-reviewed studies, this research categorizes IoT technological and pedagogical approaches, evaluates their impacts on personalization, and identifies challenges such as data privacy and resource constraints. The key findings explore how IoT-enhanced POL significantly improves learner engagement, adaptive learning, and academic outcomes, assessed via performance analytics, tests, and questionnaires. However, gaps in interoperability standards, learner profiling, cognitive load modeling, and the ethical use of data highlight the need for a unified framework. In addition, it emphasizes the transformative potential of IoT in creating personalized and inclusive learning environments. The study concludes by proposing an IoT-based POL framework and recommends directions for future research and practical applications.
Understanding Diagnostic Costs Using Hospital-Based Encounters in the Year Before Diagnosis for Canadian Patients with Malignant Central Nervous System Tumours Compared to Common Cancers
Authors: Xu Linwan , Zhou Keyun , Yuan Yan , Walker Emily V.
Published: February 2025

Rare cancers pose significant diagnostic challenges, leading to more tests and higher healthcare expenditures (HEs). Understanding the financial implications of diagnosing rare cancers is crucial, particularly in Canada, where overall HEs are high (12% of the GDP in 2023). We investigated the pre-diagnostic hospital–based HE for patients with malignant central nervous system (CNS) tumours and compared it to patients with common cancers across Canadian provinces, using in-patient and ambulatory care data (2010–2014) from the Canadian Institute for Health Information. Pre-diagnostic HE was calculated as the change in total HE (in-patient and out-patient) during the 12 months before diagnosis, calculated as the HE within this period minus the average annual HE estimated over the two preceding years. Comparison groups included pediatric patients diagnosed with leukemia and patients aged over 15 diagnosed with colorectal cancer and lung cancer. We used quantile regression to estimate the adjusted effect of diagnosis with a CNS tumour on pre-diagnostic HE. The results indicated that HE for CNS patients was higher compared to those with common cancers. The top three factors contributing to HE variation were encounter type (in-patient/out-patient), province (Alberta/Ontario), and comorbidities (yes/no). Further investigation is warranted to understand the drivers of the cost differences.
Safety and Efficacy in the Transcortical and Transsylvian Approach in Insular High-Grade Gliomas: A Comparative Series of 58 Patients
Authors: Morello Alberto , Rizzo Francesca , Gatto Andrea , Panico Flavio , Bianconi Andrea , Chiari Giulia , Armocida Daniele , Greco Crasto Stefania , Melcarne Antonio , Zenga Francesco , Rudà Roberta , Morana Giovanni , Garbossa Diego , Cofano Fabio
Published: February 2025

Gliomas within the insular region represent one of the most challenging problems in neurosurgical oncology. There are two main surgical approaches to address the complex vascular network and functional areas around the insula: the transsylvian approach and the transcortical approach. In the literature, there is not a clear consensus on the best approach in terms of safety and efficacy. The purpose of this study is to evaluate the effectiveness of these approaches and to analyze prognostic factors on the natural history of insular gliomas. Patients with newly diagnosed high-grade insular gliomas who underwent surgery between January 2019 and June 2024 were analyzed. The series was analyzed according to the classification of Berger–Sanai and Yaşargil. The Karnofsky performance score (KPS), extent of resection (EOR), progression-free survival (PFS), and overall survival (OS) were considered the outcome measures. A total of 58 primary high-grade insular glioma patients were enrolled in this study. The IDH mutation was found in 13/58 (22.4%); specifically, 3/13 (23.1%) were grade 4, and 10/13 (76.9%) were grade 3. Furthermore, 40/58 patients (69%) underwent gross total resection (GTR), 15 patients (26%) subtotal resection, and 3 patients (5%) partial resection. Middle cerebral artery encasement negatively affected the OS. GTR, radiotherapy, KPS, and autonomous deambulation at a month after surgery positively affected the OS. The surgical approach used was transsylvian and transcortical in 11 and 47 cases, respectively. The comparison between the two different approaches did not display differences in terms of neurological deficits and OS (p > 0.05). The transcortical approach was related to the greater achievement of GTR (p = 0.031). According to the Berger–Sanai classification, the transcortical approach has higher EOR and postoperative KPS when the lesion is in zone III-IV (p = 0.029). Greater resection of insular gliomas can be achieved with an acceptable morbidity profile and is predictive of improved OS. Both the transsylvian and transcortical corridors to the insula are associated with low morbidity profiles. The transcortical approach with intraoperative mapping is more favorable for achieving greater EOR, particularly in gliomas within the inferior border of the Sylvian fissure.
The Impact of Climate Change and Human Activities on the Habitat Distribution and Ecological Corridors of Hoolock tianxing in Western Yunnan Province, China
Authors: Geng Junxi , Zhang Jian , Liu Xiaowei , Qin Shengdong
Published: February 2025

Climate change and human interference are major drivers of biodiversity loss, with profound implications for species distribution and ecosystem integrity. Among the most vulnerable groups, primates are particularly sensitive to climate change due to their specialized habitat requirements and reliance on stable environmental conditions. This study investigates the impact of climate change and human disturbance on the distribution patterns and ecological corridors of the Gaoligong hoolock gibbons (Hoolock tianxing) in Western Yunnan Province, China. Climatic variables, including elevation, temperature range, seasonality, and annual precipitation, were found to significantly influence the spatial distribution of suitable habitats for the species. Under current climatic conditions, the suitable habitat area was 9801.59 km2. However, future climate scenarios projected substantial reductions in habitat area, with the RCP2.6 scenario showing a decrease of 10.07%, and the RCP4.5 and RCP8.5 scenarios resulting in reductions of 29.75% and 69.02%, respectively. Spatially, Tengchong and Longyang supported the largest habitat areas, but these regions faced significant reductions under all future scenarios, while Longchuan and Fugong exhibited minimal to no suitable habitat, especially under higher-emissions scenarios. Furthermore, our analysis revealed that future climate change would cause a shift in habitat suitability toward higher elevations, with mid- and high-elevation areas becoming increasingly important. Ecological corridors, primarily located in the southern regions, showed a trend of fragmentation, with decreasing connectivity and increasing dispersal resistance across all future scenarios. By the 2070s, southern corridors would nearly disappear under the RCP8.5 scenario, with the dispersal paths contracting northward. These findings underscore the urgency of implementing comprehensive conservation strategies, such as habitat restoration, corridor enhancement, and cross-border cooperation between China and Myanmar, to mitigate climate change impacts and safeguard the long-term survival of Skywalker hoolock gibbons.
Effect of Drying Aids on the Quality Properties of Kefir Powder
Authors: Exarhopoulos Stylianos , Karipoglou Dimitris , Groztidou Olga , Georgiou Despoina , Kalogianni Eleni P. , Goulas Athanasios , Dimitreli Georgia
Published: February 2025

The biological and nutritional value of kefir makes it imperative to widen its customer reach by extending its shelf life, enabling its storage and transport at ambient temperatures, and reducing its packaging cost requirements. A well-documented and widely used food processing method that can achieve the above-mentioned outcomes is spray drying through the formulation of kefir powder, with quality attributes that will closely resemble that of the original product. In the present work, a variety of drying carriers (trehalose, fructo-oligosaccharides, maltodextrin, gum arabic, and whey proteins) were studied with regard to their effect on the properties of powdered and reconstituted kefir samples. Particularly, the physicochemical characteristics (moisture content, pH, acidity, color), powder properties (bulk density, tapped density, water solubility index, insoluble matter), adsorption isotherms, particle size distribution, microbiological properties, and structural characteristics of the samples were evaluated. Gum arabic and maltodextrin produced kefir powder samples with the lowest moisture content. Spray drying affected a reduced acidity and, as a consequence, an increased pH in the reconstituted samples, especially without any carrier addition and with trehalose and fructo-oligosaccharides irrespective of their concentration. Desirable color attributes were achieved on the kefir powder samples with trehalose, fructo-oligosaccharides, and maltodextrin regardless of their concentration in the product. Fructo-oligosaccharides, added at 3%, gave the highest values of bulk density, while whey proteins, due to their nature, exhibited the lowest. All carriers tested improved the water solubility index when compared to the control sample. The sample with 10% whey proteins exhibited the lowest moisture adsorption compared to the control at the highest relative humidity environments employed for the test. In the absence of agglomeration, powder granule size and structural morphology were not affected by the carriers. The survival of lactococci in the powdered kefir samples, in comparison to the control product, was higher in the case where 4% trehalose or 5 to 10% whey proteins were added. On the contrary, yeast populations decreased significantly during drying and they were not affected by the presence of the different carriers. As shown by the findings of the present study, trehalose proved to be the most effective carrier, among the others used, for producing high-quality kefir powder products. However, further work is required with regard to the keeping quality of the product during long-term storage.
Three-Dimensional Surgical Guides in Orthodontics: The Present and the Future
Authors: Pop Silvia Izabella , Bud Eugen , Jánosi Kinga Mária , Bud Anamaria , Kerekes-Máthé Bernadette
Published: February 2025

Surgical guides are integral tools in orthodontics, enhancing the precision and predictability of mini-implant placement. These guides facilitate accurate positioning, reduce risks to surrounding anatomical structures, and ensure proper angulation and depth during procedures. The aim of the present paper is to present a detailed review of the surgical guides used in orthodontics, focusing on their classification, mechanical properties, biocompatibility, and future developments. The advantages, disadvantages, clinical steps, and implications are also described based on the data in recent scientific literature. Future developments may incorporate artificial intelligence and augmented reality, further optimizing treatment planning and patient outcomes, thus solidifying the role of surgical guides in efficient orthodontic care.
Drone LiDAR Occlusion Analysis and Simulation from Retrieved Pathways to Improve Ground Mapping of Forested Environments
Authors: Miao Zhang , Gomez Christopher , Shinohara Yoshinori , Hotta Norifumi
Published: February 2025

Drone-mounted LiDAR systems have revolutionized forest mapping, but data quality is often compromised by occlusions caused by vegetation and terrain features. This study presents a novel framework for analyzing and predicting LiDAR occlusion patterns in forested environments, combining the geometric reconstruction of flight paths with the statistical modeling of ground visibility. Using field data collected at Unzen Volcano, Japan, we first developed an algorithm to retrieve drone flight paths from timestamped pointclouds, enabling post-processing optimization, even when original flight data are unavailable. We then created a mathematical model to quantify the shadow effects from obstacles and implemented Monte Carlo simulations to optimize flight parameters for different forest stand characteristics. The results demonstrate that lower-altitude flights (40 m) with narrow scanning angles achieve the highest ground visibility (81%) but require more flight paths, while higher-altitude flights with wider scanning angles offer efficient coverage (47% visibility) with single flight paths. For a forest stand with 250 trees per 25 hectares (heights 5–15 m), statistical analysis showed that scanning angles above 90 degrees consistently delivered 46–47% ground visibility, regardless of the flight height. This research provides quantitative guidance for optimizing drone LiDAR surveys in forested environments, though future work is needed to incorporate canopy complexity and seasonal variations.
Connectivity Preservation and Obstacle Avoidance Control for Multiple Quadrotor UAVs with Limited Communication Distance
Authors: Xue Xianghong , Yuan Bin , Yi Yingmin , Mu Lingxia , Zhang Youmin
Published: February 2025

This paper studies the distributed formation control problem for multiple unmanned aerial vehicles (UAVs), focusing on preserving connectivity and avoiding obstacles within the constraints of a limited communication distance and in the presence of multiple dynamic obstacles. The UAV network is modeled as a proximity graph, where the edges are defined by the distances between the UAVs. A hierarchical control strategy is employed to manage the position and attitude subsystems independently. A distributed position formation controller is developed for the position subsystems, utilizing bounded artificial potential functions to preserve the network connectivity and avoid collisions between UAVs while achieving the desired formation. The position controller also integrates a time-varying sliding manifold and obstacle avoidance potential functions to prevent collisions with dynamic obstacles. Additionally, an attitude controller is designed for the attitude subsystem to track the desired attitude angles generated by the positioning subsystem. Numerical simulations validate that the proposed controllers effectively preserve the communication network’s connectivity, avoid collisions between the UAVs and dynamic obstacles, and achieve the desired formation simultaneously.
Exploring Habitat Quality Dynamics in an Equatorial Andean Basin Under Scenarios of Land Use Change
Authors: González Lorena , Zhiña Darío Xavier , Avilés Alex , Astudillo Ana , Peralta Ximena , Verdugo Teodoro
Published: February 2025

Globally, ecosystem services face significant degradation due to land use and land cover change (LULC) driven by human development. Despite numerous habitat quality assessments, comprehensive studies in high-mountain equatorial region basins remain scarce. This research addresses assessing habitat quality in Ecuador’s sub-basins of the Aguilán and Tabacay Rivers, with projections extending to 2050. This study considered anthropogenic threats and examined two land use change scenarios. The “Integrated Valuation of Ecosystem Services and Tradeoffs” (InVEST) model was used for the evaluation. A habitat quality index (HQI) was developed and categorized into five classes. The results showed that in 2018, over 50% of the study area had medium, high, and very high habitat quality levels, partly due to implementing policies, such as Reciprocal Water Agreements, developed by local initiatives. However, future projections suggest a declining trend, particularly in urban and cropland areas, highlighting the need to reinforce proactive policies. The findings of this study contribute to addressing existing gaps in habitat quality research in high-mountain regions, providing key scientific evidence to support conservation strategies, land use planning, and watershed management.
Single-Level and Two-Level Circuit Solutions for Buck-Boost AC Voltage Regulators with Phase-by-Phase Switches
Authors: Udovichenko Aleksey , Grishanov Evgeniy , Kosykh Evgeniy , Filippov Maksim , Dybko Maksim
Published: February 2025

Forming required AC voltage levels is currently one of the most pressing problems. Unstable voltage levels can lead to the failure of household and industrial equipment. This can lead to a pure effect on the production cycle. In this regard, the development of AC voltage regulators has become relevant. Such regulators can perform the function of voltage level asymmetry compensators in a three-phase power supply network. In turn, new topologies should be energy-efficient and reliable. This can be achieved by reducing the number of semiconductor elements, thus reducing losses and increasing efficiency. Also, AC voltage regulators have found applications as soft-start devices for motors and have become relevant to frequency converters. The power level of such devices can vary from units to tens of kilowatts. This paper presents several circuit design solutions for AC voltage regulators with fewer switches. These solutions are made according to both a single-level and two-level system, where the level refers to the number of links that increase the transmission coefficient. The schemes were analyzed, and efficiency was evaluated through their harmonic coefficients, power factor, and efficiency coefficient. For the basic scheme, a photo of the experimental layout and its results are provided.
Passive Resistance Network Temperature Compensation for Piezo-Resistive Pressure Sensors
Authors: Lei Cheng , Liu Yuqiao , Liang Ting , Tang Mengxuan , Ghaffar Abdul , Musavi Sayed Hyder Abbas
Published: February 2025

The operating temperature can significantly affect the output voltage of high-temperature piezoresistive pressure sensors, presenting challenges to the measurement precision due to the intrinsic properties of semiconductor materials. This study developed a passive resistor network temperature compensation technique, utilizing differential equations to determine the compensation resistance parameters. Unlike conventional empirical algorithms, this method eliminated the need to account for variations among piezoresistors and addressed issues such as residual stress and mismatched coefficients of thermal expansion arising during manufacturing. The differential equation was simplified to derive the solution, and the calibration data were utilized to calculate the compensation resistance parameters, effectively compensating for the high-temperature piezoresistive pressure sensor. The results indicated that the passive resistance network successfully reduced the temperature drift, outperforming the traditional empirical algorithms.
Monitoring Parameters and Optimizing the Technological Process in the Grinding Machine
Authors: Śmigielski Grzegorz , Łazarska Małgorzata , Kaczmarek Mariusz
Published: February 2025

The paper presents the research results related to the operational parameters of a needle grinder for biological materials. The study focused particularly on monitoring the wear of the grinder’s working elements, the pins. During the operation of the device, the level and nature of vibrations in the grinding system were examined. In the next stage, after the grinding of 600 tons of biological material, an analysis of the wear of the metal pins was conducted. The degradation process of the pins was observed based on elements made of both untreated steel and heat-treated steel. The apparatus used to measure the grinder’s operational parameters consisted of three IEPE KS 80C piezoelectric accelerometers. The applied research methods enabled the identification of vibration components resulting from an improper grinder operation related to pin wear. Based on the conclusions from the conducted research, a low-budget device (prototype) was proposed for continuous machine monitoring, made using an ESP32 system and a capacitive three-axis accelerometer in the MPU6050 system. The applied monitoring method opens new possibilities for quality control and production efficiency in industries that use grinding.
High-Performance Acousto-Optic Modulators for Improving the Recognition Accuracy of Weak Microwave Signals by Radio Frequency Identification Systems
Authors: Zhang Weijia , Luo Xueting , Rao Qiancheng , Jiang Peng
Published: February 2025

By leveraging the high sensitivity of acousto-optic modulators to microwave signals, their integration into RFID systems can significantly improve the detection of faint microwave signals. Traditional acousto-optic modulators, which use bidirectional uniform comb transducers (IDTs), suffer from a 50% microwave signal loss due to the diffraction efficiency being less than 50%, complicating the accurate identification of already weak signals. This paper presents a solution to the 50% loss issue by replacing the IDT with a floating electrode unidirectional transducer (FEUDT), a key structure in detecting microwave signals. The resulting samples exhibited an optical waveguide insertion loss of 8.73 dB, a mode field diameter of 6.48 μm, an operating frequency of 141.2 MHz, and a diffraction efficiency of 61.72%, and required only 0.57 W of driving power. Comparative empirical tests with traditional transducers under identical conditions demonstrated that the FEUDT-based acousto-optic modulator surpassed the 50% diffraction efficiency limit of conventional modulators, which facilitated the detection of weak microwave signals.
Context-Aware Tomato Leaf Disease Detection Using Deep Learning in an Operational Framework
Authors: Karimanzira Divas
Published: February 2025

Tomato cultivation is a vital agricultural practice worldwide, yet it faces significant challenges due to various diseases that adversely affect crop yield and quality. This paper presents a novel tomato disease detection system within an operational framework that leverages an innovative deep learning-based classifier, specifically a Vision Transformer (ViT) integrated with cascaded group attention (CGA) and a modified Focaler-CIoU (Complete Intersection over Union) loss function. The proposed method aims to enhance the accuracy and robustness of disease detection by effectively capturing both local and global contextual information while addressing the challenges of sample imbalance in the dataset. To improve interpretability, we integrate Explainable Artificial Intelligence (XAI) techniques, enabling users to understand the rationale behind the model’s classifications. Additionally, we incorporate a large language model (LLM) to generate comprehensive, context-aware explanations and recommendations based on the identified diseases and other relevant factors, thus bridging the gap between technical analysis and user comprehension. Our evaluation against state-of-the-art deep learning methods, including convolutional neural networks (CNNs) and other transformer-based models, demonstrates that the ViT-CGA model significantly outperforms existing techniques, achieving an overall accuracy of 96.5%, an average precision of 93.9%, an average recall of 96.7%, and an average F1-score of 94.2% for tomato leaf disease classification. The integration of CGA and Focaler-CIoU loss not only contributes to improved model interpretability and stability but also empowers farmers and agricultural stakeholders with actionable insights, fostering informed decision making in disease management. This research advances the field of automated disease detection in crops and provides a practical framework for deploying deep learning solutions in agricultural settings, ultimately supporting sustainable farming practices and enhancing food security.
Study on Electromagnetic Focusing with Fully Phase-Adjustable High Transmittance Metasurface
Authors: Zhu Zhaoxuan , Zhou Xin
Published: February 2025

Electromagnetic beam focusing is usually controlled by phase. However, metasurfaces can effectively achieve phase control. This paper investigates electromagnetic focusing technology based on high-transmittance metasurfaces. Firstly, a high-transmittance metasurface unit was designed with an operating frequency of 10 GHz, a transmittance of over 80%, and a phase shift of 360°. Then, based on the phase compensation and lens focusing theory, a highly transparent metasurface array for electromagnetic focusing was obtained. Finally, through simulation verification, the half power bandwidth reached 10°, with a transmission efficiency of 43.2% @ 800 mm, and the feasibility of focusing was verified through the experiments.
Lightweight Denoising Diffusion Implicit Model for Medical Segmentation
Authors: Oh Rina , Gonsalves Tad
Published: February 2025

Automatic medical segmentation is crucial for assisting doctors in identifying disease regions effectively. As a state-of-the-art (SOTA) approach, generative AI models, particularly diffusion models, have surpassed GANs in generating high-quality images for tasks like segmentation. However, most diffusion-based architectures rely on U-Net designs with multiple residual blocks and convolutional layers, resulting in high computational costs and limited applicability on general-purpose devices. To solve this issue, we propose an enhanced denoising diffusion implicit model (DDIM) that incorporates lightweight depthwise convolution layers within residual networks and self-attention layers. This approach significantly reduces computational overhead while maintaining segmentation performance. We evaluated the proposed DDIM on two distinct medical imaging datasets: X-ray and skin lesion and polyp segmentation. Experimental results demonstrate that our model achieves, with reduced resource requirements, accuracy comparable to standard DDIMs in both visual representation and region-based scoring. The proposed lightweight DDIM offers a promising solution for medical segmentation tasks, enabling easier implementation on general-purpose devices without the need for expensive high-performance computing resources.
A Solution for the Health Data Sharing Dilemma: Data-Less and Identity-Less Model Sharing Through Federated Learning and Digital Twin-Assisted Clinical Decision Making
Authors: Wickramasinghe Nilmini , Ulapane Nalika
Published: February 2025

Digital twins are essentially digital replicas of physical entities. Their usage is becoming more common across various industries, including healthcare. However, the implementation of digital twins in healthcare is uniquely challenging. This is partly because of the sensitive nature of health data and privacy concerns. These concerns limit health data accessibility and shareability. This paper attempts to address this challenge of health data sharing. We propose a novel approach that leverages federated learning, model sharing, and digital twin-assisted clinical decision making. Our approach ensures that health data are kept federated with healthcare providers. Healthcare providers train machine learning models on their own data. Then, instead of sharing the data, the trained models are shared. This is enabled via an arrangement like a private blockchain that is accessible to subscribed healthcare providers. This approach allows healthcare providers to access and use machine learning models for clinical decision support without compromising sensitive data about patients. Certain information about machine learning models will be shared. These include indicators such as the sample size on which a model has been trained on, validation metrics, and model accuracy. Such information assists other healthcare providers in selecting the most effective models. We demonstrate the efficacy of this approach through a case study on chronic disease management (e.g., cancer) using Liquid Neural Networks. Our results show how federated learning and model sharing can enhance clinical decision making and improve patient outcomes while ensuring the privacy of data.
New Control Algorithms for Rearrangeable Wavelength–Space–Wavelength Switches in Elastic Optical Networks
Authors: Żal Mariusz , Abuelela Enass , Kabaciński Wojciech
Published: February 2025

The main objective of this paper is to propose a set of new algorithms for assigning frequency slots in the inter-stage links of the wavelength–space–wavelength switching networks used in nodes in elastic optical networks. The algorithms are based on decomposition of the set of inter-stage link frequency slots into subsets, which can be utilized for realizing conflict-free connections. Similar algorithms have previously been proposed for switching networks with two, three, or four inputs and outputs. The algorithms proposed in this paper have been adapted to work in switching networks with five inputs and outputs. These algorithms make it possible to reduce the required number of frequency slots in inter-stage links. From the comparison conducted in this work with the switching networks for three and four inputs and outputs, it follows that the new algorithms for networks with five inputs/outputs allow for a reduction in the number of frequency slots by about 20%. Additionally, the approximation of the proposed algorithms for switching networks with a larger number of inputs and outputs also leads to a reduction in the required frequency slots, compared to previously known algorithms. The proposed algorithms allow for reducing the number of frequency slots in inter-stage links, which is associated with reducing the capacity range of wavelength-selective switches and the tunability range of spectrum converters, and therefore also the costs of switching networks.
Dynamic Multi-Product Integrated Scheduling Algorithm with Urgent Delivery Date
Authors: Guo Jianing , Wang Dadong , Zhou Wei , Xie Zhiqiang , Sun Ming , Tan Zhenjiang
Published: February 2025

For the existing multi-product integrated scheduling algorithm considering the delivery date, the inability to fully consider the processing order of multiple products and the potential scheduling conflicts in the processing process causes problems such as equipment resource competition during the processing of products, ultimately resulting in the extension of delivery date and the failure to the deliver products on time. Aiming at this problem, a dynamic multi-product integrated scheduling algorithm with tight delivery date (ISA-TDD) is proposed. Firstly, the initial scheduling scheme of multi-product is established according to the strategy of ‘device priority + short time + layer priority’. Secondly, the product contribution value strategy is proposed to determine the scheduling order of multiple products and improve the parallel processing of products. Finally, the dynamic adjustment strategy of the game process is proposed, which solves the conflict problem of multi-product co-processing and further improves the intensity of compact scheduling of equipment. The comparative experimental results show that the algorithm achieves the optimization goal of shorter multi-product delivery date and higher overall utilization rate of equipment, and the scheduling effect is obviously better than the comparison algorithm.
DS-GAC: A Data-Sharing Scheme Based on Group Attribute Characteristics
Authors: Li Zhangbing , Xiao Jiantian , Xiao Mingyu , Zhang Shaobo
Published: February 2025

Data sharing has dramatically promoted the efficient use of data resources. The target sharing of confidential data is increasingly becoming urgent for enterprises or organizations to solve business problems, such as data sharing between group users with the same attribute characteristics. The confidentiality and relative privacy of shared data, whether in plaintext or ciphertext, largely depend on the encryption keys used during the sharing process and the storage security of the sharing platform. In order to solve the problem of secure sharing, this paper proposes a data-sharing scheme based on group attribute characteristics. The sharer segments and encrypts the data and stores most of the data and encryption keys on the cloud platform, while a small part of the residual is stored on the edge server. The sharer specifies group users by defining user attribute values and implements access control of encryption keys and shared data through CP-ABE. In particular, the private servers of the organizations involved in data sharing act as the edge servers, which are responsible for the storage of residuals with the final authorization of data access, and try their best to ensure that the data are shared with the target users. The security analysis and data collection time overhead experiments show that the scheme further guarantees data sharing with specified target users, which is one more layer of guarantee than sharing in multi-cloud environment and cloud-encrypted sharing, and the time overhead has about a 15% improvement over sharing in a multi-cloud environment.