bluuebunny/crossref_metadata_2025 huggingface dataset:
An Investigation of the Risk Factors Related to Frailty in Older Adults Receiving Home Care Services
Authors: Stratidaki Eirini , Mechili Enkeleint A. , Ouzouni Christina , Patelarou Athina E. , Savvakis Ioannis , Giakoumidakis Konstantinos , Laliotis Aggelos , Patelarou Evridiki
Published: November 2024

(1) Background: Frailty in older adults is a condition that involves an interaction of psychological, biological, and social factors. This study aimed to assess the frailty status of older adults (65 years old and above) who receive home care services. Additionally, this work aimed to explore the key factors that have a statistically significant impact on the frailty of this vulnerable population. (2) Methods: This study represents the first phase of an intervention trial involving individuals aged 65 and over who received primary healthcare services and resided in the municipality of Archanes-Asterousia in Crete, Greece. Frailty was assessed using the SHARE-Frailty Instrument, while nutritional status was evaluated with the Mini Nutritional Assessment. Diet-related factors were analyzed, including health factors (oral hygiene, depression, cognitive decline, impaired functioning, quality of life), social factors (educational attainment, marital status, type of work before the age of 60), and lifestyle factors (smoking, alcohol consumption, diet). (3) Results: A total of 730 older adults were evaluated (31.5% male), with an average age (±SD) of 76.83 (±6.68) years. The frailty status analysis revealed 108 (14.8%) to be frail, 249 (34.1%) to be pre-frail, and 373 (51.1%) to be non-frail. Statistically significant associations were found between the MNA and Barthel scores (rs = 0.822, p < 0.001). Higher nutritional evaluations (MNA) were revealed in non-frail adults (mean (±SD); 26.97 ± 1.96) compared to pre-fail (mean (±SD); 19.37 ± 3.36) and frail adults (mean (±SD); 13.08 ± 3.16), as well as in pre-fail compared to frail adults (F = 1338.08, p < 0.001). Functional independence (Barthel) significantly differed with the frailty status of older adults (H = 521.98, p < 0.001; median for non-frail: 20.00, pre-fail: 19.00, frail adults: 15.00). (4) Conclusions: This study demonstrated that good nutritional status, good oral health, functional independence, and good quality of life are strongly correlated with lower frailty. Additionally, having chronic conditions is positively associated with one’s frailty status. Educational programs for both healthcare personnel and older adults are recommended.
Establishment of an Immortalized Porcine Alveolar Macrophage Cell Line That Supports Efficient Replication of Porcine Reproductive and Respiratory Syndrome Viruses
Authors: Diep Nguyen Van , Hayakawa-Sugaya Yuiko , Ishikawa Shingo , Kawaguchi Hiroaki , Suda Yasuo , Esaki Mana , Okuya Kosuke , Ozawa Makoto
Published: November 2024

Porcine reproductive and respiratory syndrome (PRRS), which is caused by the porcine reproductive and respiratory syndrome virus (PRRSV), has a significant impact on the global pork industry. It results in reproductive failure in sows and respiratory issues in pigs of all ages. Despite the availability of vaccines, controlling the PRRSV remains challenging, partly owing to the limitations of cell culture systems. Current methods largely rely on primary porcine alveolar macrophages (PAMs), which must be harvested from piglets and have limited proliferative capacity. Although some simian cell lines support PRRSV replication, their inability to express porcine CD163, which is a key receptor for PRRSV entry, compromises their effectiveness, because the virus replicates differently in these non-target cells. To address these issues, we established an immortalized PAM cell line, PAM-T43, using SV40 large T antigen for immortalization and porcine serum as a culture supplement. PAM-T43 cells maintain essential macrophage functions, including CD163 expression and phagocytic activity, and exhibit high sensitivity to the PRRSV, efficiently supporting viral replication. This novel cell line offers significant potential for advancing PRRSV research, particularly in vaccine development and field strain isolation, by overcoming the limitations of current systems.
Prevalence of Non-Viral Bloodborne Pathogens Among Healthy Blood Donors in Western Mexico: Problems and Failures of Public Health Policy
Authors: Guerrero-García José de Jesús , Flores-González Alejandra , Sánchez-Sánchez Alma Marina , Magaña-Duarte Rafael , Mireles-Ramírez Mario Alberto , Ortiz-Lazareno Pablo Cesar , Sierra Díaz Erick , Ortuño-Sahagún Daniel
Published: November 2024

Background and Objectives: Non-viral bloodborne diseases are a group of infections that are a public health problem worldwide. The incidence of diseases such as brucellosis and syphilis is increasing in the Americas and Europe. Chagas disease is an endemic problem in Latin America, the United States and Europe. This study aims to determine the prevalence of non-viral bloodborne diseases in blood donors and to discuss some issues related to federal regulations for the control and prevention of these infectious diseases in Mexico. Material and methods: A cross-sectional study was conducted in the Western National Medical Center Blood Bank, including 228,328 blood donors (2018–2023). Frequencies, percentages, means, standard deviation and confidence intervals (CI) were calculated for demographic data. Prevalences were expressed as rates per 100,000 with 95% CI. Results: Of 3949 seroreactive or undetermined blood donors at the first screening, a total of 682 (0.299%) completed their follow-up test and were positive for Treponema pallidum (478), Trypanosoma cruzi (83), or Brucella spp. (121). The overall prevalence for non-viral bloodborne diseases was 299 per 100,000 blood donors. The prevalence for syphilis, Chagas disease, and Brucella was 209, 36, and 53 per 100,000 respectively. Conclusion: Federal regulations should be reviewed to formulate specific public health policies focused on controlling and preventing nonviral bloodborne diseases.
Gut Microbiome Implication and Modulation in the Management of Recurrent Urinary Tract Infection
Authors: Brigida Mattia , Saviano Angela , Petruzziello Carmine , Manetti Luca Luigi , Migneco Alessio , Ojetti Veronica
Published: November 2024

Urinary tract infections (UTIs) are one of the most common bacterial infections, affecting more than 150 million people each year in the world. UTIs have grown exponentially in the last few years. They represent a major load for both individuals and society. The highest incidence (about 55–60%) concerns women. Many pathogens are involved in UTIs, most of which are derived from the gut. Recent studies, together with recent diagnostic techniques (such as quantitative culture of urine or next-generation sequencing), have improved the knowledge of microbial communities in the urinary tract. It turned out that gut dysbiosis is strictly involved in the pathogenesis of UTIs. In particular, the human gut is the natural habitat for Escherichia coli (E. coli), the main bacterium responsible for UTIs. The overgrowth of E. coli pathogenic strains represents a risk factor for them. Furthermore, the human gut microbiota acts as a “global reservoir” for genes conferring resistance to clinically relevant antibiotics, thus influencing the treatment of UTIs. In addition, differently from the past, the idea of a sterile urinary environment has been replaced by the characterization of a urinary microbiome. The aim of our review is to explore recent studies on the association between gut microbiota and urinary microbiome and to summarize the current knowledge about the effects of interactions between gut and urinary microbial communities in the pathogenesis of UTIs, considering UTIs more as a “gut disease” and not only a urinary disease and providing new insight into the therapeutic options such as the use of probiotics.
Interplay Between Vitamin D Levels and Heavy Metals Exposure in Pregnancy and Childbirth: A Systematic Review
Authors: Flores-Bazán Tania , Izquierdo-Vega Jeannett Alejandra , Guerrero-Solano José Antonio , Castañeda-Ovando Araceli , Estrada-Luna Diego , Jiménez-Osorio Angélica Saraí
Published: November 2024

Background/Objectives: Vitamin D (VD) deficiency has been associated with increased risk of gestational disorders affecting the endocrine system, immune system, and neurodevelopment in offspring. Recent studies have focused on the interaction between toxic elements and micronutrients during pregnancy. This review analyzes the potential relationships between VD levels and heavy metals in pregnant women and their offspring. Methods: A systematic review was conducted according to PRISMA 2020 guidelines, using databases such as PubMed, ScienceDirect, Cochrane Library, and Google Scholar. Boolean operators ‘AND’ and ‘OR’ were applied with terms like ‘pregnancy’, ‘vitamin D’, ‘heavy metals’, and ‘newborns’. Results: From 4688 articles, 14 studies were selected based on relevance and quality. These studies measured the levels of metals like lead (Pb), cadmium (Cd), mercury (Hg), and arsenic (As), in biological samples including maternal blood, umbilical cord blood, placenta tissue, and meconium during different stages of pregnancy, showing an inverse relationship between VD deficiency and heavy metal concentrations, which could be related to the incidence of preterm birth. Conclusions: The review highlights the importance of maintaining adequate VD levels during pregnancy, suggesting that sufficient VD may mitigate the adverse effects of heavy metal exposure, potentially reducing pregnancy-related complications.
Enhanced Ocular Bioavailability and Prolonged Duration via Hydrophilic Surface Nanocomposite Vesicles for Topical Drug Administration
Authors: Huang Sa , Xu Yuan , Luo Yingyao , Wang Zhijiong , Li Fan , Qin Zhenmiao , Ban Junfeng
Published: November 2024

Background: Internal ocular diseases, such as macular edema, uveitis, and diabetic macular edema require precise delivery of therapeutic agents to specific regions within the eye. However, the eye’s complex anatomical structure and physiological barriers present significant challenges to drug penetration and distribution. Traditional eye drops suffer from low bioavailability primarily due to rapid clearance mechanisms. Methods: The novel ocular drug delivery system developed in this study utilizes poly(lactic-co-glycolic acid) (PLGA) nanoparticles modified with cell-penetrating peptides (CPPs). In vitro drug release studies were conducted to evaluate the sustained-release properties of the nanoparticles. Ex vivo experiments using MDCK cells assessed corneal permeability and uptake efficiency. Additionally, in vivo studies were performed in rabbit eyes to determine the nanoparticles’ resistance to elimination by tears and their retention time in the aqueous humor. Results: In vitro drug release studies demonstrated superior sustained-release properties of the nanoparticles. Ex vivo experiments revealed enhanced corneal permeability and increased uptake efficiency by MDCK cells. In vivo studies in rabbit eyes confirmed the nanoparticles’ resistance to elimination by lacrimal fluid and their ability to extend retention time in the aqueous humor. CPP modification significantly improved ocular retention, corneal penetration, and cellular endocytosis efficiency. Conclusions: The CPP-modified PLGA nanoparticles provide an effective and innovative solution for ocular drug delivery, offering improved bioavailability, prolonged retention, and enhanced drug penetration, thereby overcoming the challenges of traditional intraocular drug administration methods.
Simple Direct Measurement of the Orbital Stokes Parameters in Structured Vortex Beams
Authors: Volyar Alexander , Bretsko Mikhail , Khalilov Server , Akimova Yana
Published: November 2024

An analogy with the polarization Stokes parameters and symplectic methods of the second-order intensity moment matrix allowed us to develop a simple technique for measuring the orbital Stokes parameters followed by mapping the structured beam states onto the orbital Poincaré sphere. The measurement process involves only two shots of the beam intensity patterns in front of a cylindrical lens and in its double focus. Such a simple measurement approach is based on the reciprocity effect between the experimentally measured cross-intensity element Wxy and the orbital angular momentum of the intensity moment matrix. For experiments, we chose two types of two-parameter structured beams, namely, structured Laguerre–Gaussian beams and binomial beams. We obtained a good agreement between our theoretical background and the experiments, as well as the results of other authors.
Roles of Phyllosphere Microbes in Rice Health and Productivity
Authors: Danso Ofori Andrews , Su Wei , Zheng Tengda , Datsomor Osmond , Titriku John Kwame , Xiang Xing , Kandhro Abdul Ghani , Ahmed Muhammad Irfan , Mawuli Edzesi Wisdom , Awuah Richard Tuyee , Zheng Aiping
Published: November 2024

The phyllosphere, comprising the aerial portions of plants, is a vibrant ecosystem teeming with diverse microorganisms crucial for plant health and productivity. This review examines the functional roles of phyllosphere microorganisms in rice (Oryza sativa), focusing on their importance in nutrient uptake, disease resistance, and growth promotion. The molecular mechanisms underlying these interactions are explored along with their potential applications in enhancing sustainable rice production. The symbiotic relationships between rice plants and their associated microorganisms are highlighted, offering insights into improved agricultural practices. Furthermore, this review addresses the challenges and future developments in translating laboratory findings into practical applications. By synthesizing current research, this comprehensive analysis serves as a valuable resource for leveraging phyllosphere microbes in rice farming and related fields.
Unconventional Germination in Terrestrial Plants: A Counterintuitive Case in Desiccation-Sensitive Garcinia aristata (Clusiaceae) Seeds Showing Seedling Growth Without Roots
Authors: Jaganathan Ganesh K. , Sánchez Jorge A. , Pernús Mayté , Liu Baolin
Published: November 2024

Unconventional germination, wherein shoots emerge and establish true leaves before the root emerges, is only found in Zosteraceae. In Garcinia, germination proceeds with the primary root emerging, followed by shoot emergence on the opposite side, but before leaf differentiation, adventitious roots emerge at the base of the shoots. However, germination and survival mechanisms in several Garcinia species are still unclear. We subjected freshly collected G. aristata seeds to an imbibition test, and germination was evaluated at various temperatures and light conditions. Desiccation sensitivity assessments were made at different stages of drying. The effect of natural drying (ambient storage) on germination was assessed by leaving the seeds outside in natural conditions. Seeds of G. aristata with a moisture content (MC) of 67% had more than 95% germination only at 25 and 25/30 °C both in light/dark and darkness, but at 25/40 °C only 10% germinated. In 4% of the seeds, germination incepted with primary shoot emergence, and a secondary (adventitious) root emerged just before leaf differentiation. More than 95% of the seeds germinated with only a secondary root and shoot emerging concurrently. Drying fresh seeds above silica gel to 30% MC resulted in complete viability loss. Seeds stored at ambient conditions germinated without external water, and had no primary or secondary root, and the emerging shoot continued to grow into seedlings. A root develops in these seeds only when water becomes available. G. aristata seeds are desiccation-sensitive and non-dormant. When no external water is available, G. aristata seeds can germinate with shoots and establish seedlings. This is the first report on germination and successful seedling establishment without roots in Garcinia.
Nanostructure-Dependent Electrical Conductivity Model Within the Framework of the Generalized Effective Medium Theory Applied to Poly(3-hexyl)thiophene Thin Films
Authors: Bednarski Henryk , Ismail Ayman A. A. , Godzierz Marcin , Marcinkowski Andrzej , Khan Muhammad Raheel , Jarząbek Bożena , Hajduk Barbara , Kumari Pallavi
Published: November 2024

One of the key parameters characterizing the microstructure of a layer is its degree of order. It can be determined from optical studies or X-ray diffraction. However, both of these methods applied to the same layer may give different results because, for example, aggregates may contribute to the amorphous background in XRD studies, while in optical studies, they may already show order. Because we are usually interested in the optical and/or electrical properties of the layers, which in turn are closely related to their dielectric properties, determining the optical order of the layers is particularly important. In this work, the microstructure, optical properties and electrical conductivity of poly(3-hexyl)thiophene layers were investigated, and a model describing the electrical conductivity of these layers was proposed. The model is based on the generalized theory of the effective medium and uses the equation from the percolation theory of electrical conductivity for the effective medium of a mixture of two materials. The results indicate a key role of the aggregate size and limited conductivity of charge carriers, mainly due to structural imperfections that manifest themselves as an increase in the number of localized states visible in the subgap absorption near the optical absorption edge. The critical value of the order parameter and the corresponding values of the Urbach energy, excitonic linewidth and band gap energy are determined.
The Effect of Synthetic Zeolite on the Curing Process and the Properties of the Natural Rubber-Based Composites
Authors: Stojanov Sonja , Govedarica Olga , Milanović Marija , Žeravica Julijana , Barta Hollo Berta , Govedarica Dragan , Jovičić Mirjana
Published: November 2024

Zeolites, known for their unique structural and catalytic properties, are added to the natural rubber matrix to investigate their influence on the vulcanization process and the resultant properties of composites. The natural rubber-based composites were masticated with 4A synthetic zeolite (0, 5, 10, 15, 20, and 30 phr). The curing of the rubber compounds was monitored on a moving die rheometer at 150 °C. The isothermal DSC method was also used to study the curing process at 150 °C, 160 °C, and 170 °C. Based on the obtained results, it is assumed that there is an interaction between the components of the curing system and the surface of the zeolite particle, and that is why the vulcanization reaction starts earlier with an increase in zeolite in the rubber mixture. This underscores the significant role of zeolite in accelerating the curing reaction of natural rubber-based compounds. The composites were vulcanized in a press at 150 °C for 15 min. The chemical structure was analyzed using FTIR, and the sample morphology was examined using SEM. The degree of swelling in toluene and distilled water was determined. The tensile strength values, modulus of elasticity at 100% and 300% elongation, and elongation at break were measured using a universal testing machine. Hardness was assessed according to the Shore A scale. With a small addition of zeolite (up to 10 phr), there is no significant change in the tensile strength values. However, adding a considerable amount of zeolite to a natural rubber matrix results in a deterioration of the tested mechanical properties. It can be assumed that with large proportions of zeolite 4A MS in the composites, the mechanical properties deteriorated due to increased porosity. The amount of added zeolite affects the initial stages of thermal decomposition of the examined samples and the rest after the analysis at a temperature of 500 °C.
New Advances on the Dispersive and Polar Surface Properties of Poly(styrene-co-butadiene) Using Inverse Gas Chromatography
Authors: Hamieh Tayssir
Published: November 2024

The dispersive and polar properties of materials, and especially of polymers and copolymers, play an important role in several engineering applications implying their surfaces and interfaces. The surface energetic properties of poly(styrene-co-butadiene) have never been studied. We proposed in this study an accurate determination of such properties by using inverse gas chromatography (IGC) at infinite dilution. Background: The IGC surface technique led to the dispersive and polar properties of poly(styrene-co-butadiene) rubber (SBR) by adsorption of organic solvents at various temperatures. Methods: Our new methodology, based on the thermal Hamieh model and the London dispersion interaction energy, was used to determine the London dispersion surface energy, the polar acid–base surface energy, and the Lewis acid–base properties of the copolymer. Results: The different surface energy parameters of the SBR were obtained as a function of temperature from the chromatographic measurements. Conclusions: The dispersive and polar free energies of adsorption of the various n-alkanes and polar molecules on poly(styrene-co-butadiene) were determined at different temperatures. A decrease in the London dispersive surface energy and the polar Lewis acid–base surface energies of SBR was highlighted when the temperature increased. It showed a Lewis amphoteric character of poly(styrene-co-butadiene) with a highest basic constant 10 times larger than its acidic constant. This new and original method can better characterize the surface thermodynamic properties of poly(styrene-co-butadiene).
Overlooked Impact of Moisture on the Stability of Printing Ink and Its Impact on Recycled Low-Density Polyethylene (LDPE) Quality
Authors: Guo Jinyang , Wagner Willi , Atamaniuk Iryna , Chong Zhi Kai , Alassali Ayah , Kuchta Kerstin
Published: November 2024

Printing inks, composed of binders, pigments, and additives, are essential components in plastic packaging but complicate recycling due to plastic contamination and degradation. While polyolefins are resistant to hydrolytic degradation, moisture generated from upstream cleaning processes, which is often ignored, can accelerate the degradation of ink binders, affecting the recyclate quality. This study has examined the impact of 3 wt.% moisture, introduced before extrusion, on the degradation of nitrocellulose (NC), polyurethane (PU), polyvinyl butyral (PVB), and cellulose acetate propionate (CAP) binders mixed with virgin, low-density polyethylene (LDPE) at varying concentrations to simulate contamination levels. Control samples were prepared by extrusion under dry conditions and using p-xylene to compare with degradation-free conditions. Analyses, including the measurement of the melt–flow index (MFI), tensile testing, FTIR (Fourier transform infrared spectroscopy), TGA (thermogravimetry analysis), and gas chromatography mass spectroscopy (GC-MS) have established that NC is fully degraded, causing discoloration and altering the MFI. Moreover, PU degrades mainly in the presence of moisture, contrary to previous findings. In contrast, PVB does not degrade but exhibits modified mechanical properties; whereas, CAP shows minimal impact. The findings of this research demonstrate the critical role of moisture in determining recyclability, informing strategies for ink selection and recycling processes to facilitate plastic packaging circularity.
Toward Optimal Design of a Factory Air Conditioning System Based on Energy Consumption Prediction
Authors: Zhu Shuwei , Lv Siying , Wang Wenping , Cui Meiji
Published: November 2024

The Make-up Air Unit (MAU) is an air conditioning system which plays an important role in serving semiconductor cleanrooms. It provides constant temperature and humidity for fresh air through various sections, including fresh air filtration, preheating, precooling, humidification, recooling, reheating, air supply, and high-efficiency filtration. However, the commonly used PID control method of the MAU indicates a deficiency in energy consumption. Hence, this research introduces a proactive energy-saving optimization control method based on machine learning and intelligent optimization algorithms. Firstly, the machine learning methods are used to train historical data of the MAU, resulting in a data-driven prediction model of energy consumption for the system. Subsequently, the customized genetic algorithm (GA) is used to optimize energy in cold and hot water systems. It facilitates the dynamic adjustment of the regulating valve opening for the cold and hot water coil in the fresh air unit, responding to real-time variations in outdoor air conditions. Meanwhile, it ensures that the supply air temperature and humidification adhere to specified requirements, thereby reducing the energy consumption associated with cold and hot water usage in the MAU. The experimental results indicate that the proposed algorithm can provide significant energy conservation in the MAU.
The Late Villafranchian Absence of Pigs in Europe. Comment on Iannucci, A. The Occurrence of Suids in the Post-Olduvai to Pre-Jaramillo Pleistocene of Europe and Implications for Late Villafranchian Biochronology and Faunal Dynamics. Quaternary 2024, 7, 11
Authors: Martínez-Navarro Bienvenido , Madurell-Malapeira Joan , Ros-Montoya Sergio , Espigares M. Patrocinio , Rodríguez-Gómez Guillermo , Rook Lorenzo , Palmqvist Paul
Published: November 2024

On 2015, after the direct study of the most important Late Villafranchian fossil collections of Europe and Western Asia, including Orce (Spain), Pirro Nord and Upper Valdarno (Italy), Appollonia (Greece), Dmanisi (Georgia) and ‘Ubeidiya (Israel), among others, our team proposed the hypothesis that suids disappeared from Europe during the time span between 1.8 and 1.2 Ma. The implications of our conclusions were significant, the arrival of Early Homo into Western Europe, dated to 1.4 Ma at the site of Barranco León in Orce (Spain), preceded the return of pigs into the continent at 1.2 Ma. This hypothesis has been recently challenged because of the finding of an incomplete metatarsal ascribed to Sus sp., with no clear stratigraphic origin, found in the XIX Century Croizet collection of Peyrolles (France), which is housed in the Natural History Museum, London, together with other weak arguments based on the absence of reliable dating for many Early Pleistocene European sites, and other hypothetical records of pigs, with no real fossil support. We answer all these questions and defend that our 2015 hypothesis is correct.
Dynamic Programming for Designing and Valuing Two-Dimensional Financial Derivatives
Authors: Ben-Abdellatif Malek , Ben-Ameur Hatem , Chérif Rim , Rémillard Bruno
Published: November 2024

We use dynamic programming, finite elements, and parallel computing to design and evaluate two-dimensional financial derivatives. Our dynamic program is flexible, as it divides the evaluation process into two components: one related to the dynamics of the underlying process and the other to the characteristics of the financial derivative. It is efficient as it uses local polynomials at each step of the backward recursion to approximate the option value function, while it assumes only a numerical (but not a statistical) error and a state (but not a time) discretization. Parallel computing is used to speed up the model resolution and enhance its overall efficiency. To support our construction, we evaluate American options, which are subject to market risk, and exchangeable bonds, which are subject to default risk.
LH-YOLO: A Lightweight and High-Precision SAR Ship Detection Model Based on the Improved YOLOv8n
Authors: Cao Qi , Chen Hang , Wang Shang , Wang Yongqiang , Fu Haisheng , Chen Zhenjiao , Liang Feng
Published: November 2024

Synthetic aperture radar is widely applied to ship detection due to generating high-resolution images under diverse weather conditions and its penetration capabilities, making SAR images a valuable data source. However, detecting multi-scale ship targets in complex backgrounds leads to issues of false positives and missed detections, posing challenges for lightweight and high-precision algorithms. There is an urgent need to improve accuracy of algorithms and their deployability. This paper introduces LH-YOLO, a YOLOv8n-based, lightweight, and high-precision SAR ship detection model. We propose a lightweight backbone network, StarNet-nano, and employ element-wise multiplication to construct a lightweight feature extraction module, LFE-C2f, for the neck of LH-YOLO. Additionally, a reused and shared convolutional detection (RSCD) head is designed using a weight sharing mechanism. These enhancements significantly reduce model size and computational demands while maintaining high precision. LH-YOLO features only 1.862 M parameters, representing a 38.1% reduction compared to YOLOv8n. It exhibits a 23.8% reduction in computational load while achieving a mAP50 of 96.6% on the HRSID dataset, which is 1.4% higher than YOLOv8n. Furthermore, it demonstrates strong generalization on the SAR-Ship-Dataset with a mAP50 of 93.8%, surpassing YOLOv8n by 0.7%. LH-YOLO is well-suited for environments with limited resources, such as embedded systems and edge computing platforms.
Rapid Water Quality Mapping from Imaging Spectroscopy with a Superpixel Approach to Bio-Optical Inversion
Authors: Vaughn Nicholas R. , König Marcel , Hondula Kelly L. , Harrison Dominica E. , Asner Gregory P.
Published: November 2024

High-resolution water quality maps derived from imaging spectroscopy provide valuable insights for environmental monitoring and management, but the processing of all pixels of large datasets is extremely computationally intensive and limits the speed of map production. We demonstrate a superpixel approach to accelerating water quality parameter inversion on such data to considerably reduce time and resource needs. Neighboring pixels were clustered into spectrally similar superpixels, and bio-optical inversions were performed at the superpixel level before a nearest-neighbor interpolation of the results back to pixel resolution. We tested the approach on five example airborne imaging spectroscopy datasets from Hawaiian coastal waters, comparing outputs to pixel-by-pixel inversions for three water quality parameters: suspended particulate matter, chlorophyll-a, and colored dissolved organic matter. We found significant reduction in computational time, ranging from 38 to 2625 times faster processing for superpixel sizes of 50 to 5000 pixels (200 to 20,000 m2). Using 1000 paired output values from each example image, we found minimal reduction in accuracy (as decrease in R2 or increase in RMSE) of the model results when the superpixel size was less than 750 2 m × 2 m resolution pixels. Such results mean that this methodology could reduce the time needed to produce regional- or global-scale maps and thereby allow environmental managers and other stakeholders to more rapidly understand and respond to changing water quality conditions.
An Innovative Neighbor Attention Mechanism Based on Coordinates for the Recognition of Facial Expressions
Authors: Peng Cheng , Li Bohao , Zou Kun , Zhang Bowen , Dai Genan , Tsoi Ah Chung
Published: November 2024

For solving the facial expression recognition (FER) problem, we introduce a novel feature extractor called the coordinate-based neighborhood attention mechanism (CNAM), which uses the coordinate attention (CA) method to capture the directional relationships in separate horizontal and vertical directions, the input features from a preprocessing unit, and then passes this to two residual blocks, one consisting of the neighborhood attention (NA) mechanism, which captures the local interaction of features within the neighborhood of a feature vector, while the other one contains a channel attention implemented by a multilayer perceptron (MLP). We apply the feature extractor, the CNAM module, to four FER benchmark datasets, namely, RAF-DB, AffectNet(7cls), AffectNet(8cls), and CK+, and through qualitative and quantitative analysis techniques, we conclude that the insertion of the CNAM module could decrease the intra-cluster distances and increase the inter-cluster distances among the high-dimensional feature vectors. The CNAM compares well with other state-of-the-art (SOTA) methods, being the best-performing method for the AffectNet(7cls) and CK+ datasets, while for the RAF-DB and AffectNet(8cls) datasets, its performance is among the top-performing SOTA methods.
Quantum Privacy-Preserving Range Query Protocol for Encrypted Data in IoT Environments
Authors: Ye Chong-Qiang , Li Jian , Chen Xiao-Yu
Published: November 2024

With the rapid development of IoT technology, securely querying sensitive data collected by devices within a specific range has become a focal concern for users. This paper proposes a privacy-preserving range query scheme based on quantum encryption, along with circuit simulations and performance analysis. We first propose a quantum private set similarity comparison protocol and then construct a privacy-preserving range query scheme for IoT environments. By leveraging the properties of quantum homomorphic encryption, the proposed scheme enables encrypted data comparisons, effectively preventing the leakage of sensitive data. The correctness and security analysis demonstrates that the designed protocol guarantees users receive the correct query results while resisting both external and internal attacks. Moreover, the protocol requires only simple quantum states and operations, and does not require users to bear the cost of complex quantum resources, making it feasible under current technological conditions.
Numerical Simulation Study on Predicting the Critical Icing Conditions of Aircraft Pitot Tubes
Authors: Chen Qixi , Zhang Lifen , Zhou Chengxin , Liu Zhengang , Lyu Yaguo
Published: November 2024

Aircraft pitot tubes are sophisticated instruments designed to detect airflow pressure and relay this information to onboard computers and flight instruments, enabling the calculation of airspeed through the measurement of total-static pressure differences. The formation of ice on aircraft pitot tubes can compromise the acquisition of airspeed data, misguide pilots, and potentially cause catastrophic flight control failures. This article introduces a predictive methodology for identifying critical conditions that lead to icing on aircraft pitot tubes. Utilizing numerical simulation techniques, the methodology calculates the critical conditions for pitot tube icing across cruise flight regimes and atmospheric conditions, resulting in the generation of a critical condition envelope surface. By comparing these critical conditions against actual sensor data, a predictive danger zone can be established, offering an advanced warning system to ensure flight safety.
An Entropy-Based Clustering Algorithm for Real-Time High-Dimensional IoT Data Streams
Authors: Mutambik Ibrahim
Published: November 2024

The rapid growth of data streams, propelled by the proliferation of sensors and Internet of Things (IoT) devices, presents significant challenges for real-time clustering of high-dimensional data. Traditional clustering algorithms struggle with high dimensionality, memory and time constraints, and adapting to dynamically evolving data. Existing dimensionality reduction methods often neglect feature ranking, leading to suboptimal clustering performance. To address these issues, we introduce E-Stream, a novel entropy-based clustering algorithm for high-dimensional data streams. E-Stream performs real-time feature ranking based on entropy within a sliding time window to identify the most informative features, which are then utilized with the DenStream algorithm for efficient clustering. We evaluated E-Stream using the NSL-KDD dataset, comparing it against DenStream, CluStream, and MR-Stream. The evaluation metrics included the average F-Measure, Jaccard Index, Fowlkes–Mallows Index, Purity, and Rand Index. The results show that E-Stream outperformed the baseline algorithms in both clustering accuracy and computational efficiency while effectively reducing dimensionality. E-Stream also demonstrated significantly less memory consumption and fewer computational requirements, highlighting its suitability for real-time processing of high-dimensional data streams. Despite its strengths, E-Stream requires manual parameter adjustment and assumes a consistent number of active features, which may limit its adaptability to diverse datasets. Future work will focus on developing a fully autonomous, parameter-free version of the algorithm, incorporating mechanisms to handle missing features and improving the management of evolving clusters to enhance robustness and adaptability in dynamic IoT environments.
Comparison of Velocity and Estimated One Repetition Maximum Measured with Different Measuring Tools in Bench Presses and Squats
Authors: van den Tillaar Roland , Nygaard Falch Hallvard , Larsen Stian
Published: November 2024

The aim of this study was to compare barbell velocities at different intensities and estimated 1-RM with actual 1-RM measured with different measuring tools in bench presses and squats. Fourteen resistance-trained athletes (eight men, six women, age 28.1 ± 7.5 years, body mass 78.1 ± 12.2 kg, body height 1.73 ± 0.09 m) performed bench presses and squats at five loads varying from 45 to 85% of one repetition maximum (1-RM), together with 1-RM testing, while measuring mean, mean propulsive, and peak barbell velocity with six different commercially used inertial measurement units (IMUs) and linear encoder software systems attached to the barbell. The 1-RM was also estimated based upon the load–velocity regression, which was compared with the actual 1-RM in the bench press and squat exercises. The main findings were that GymAware revealed the highest reliability along with minimal bias, while Musclelab and Vmaxpro showed moderate reliability with some variability at higher loads. Speed4lifts and PUSH band indicated greater variability, specifically at higher intensities. Furthermore, in relation to the second aim of the study, significant discrepancies were found between actual and estimated 1-RM values, with Speed4lifts and Musclelab notably underestimating 1-RM. These findings underscore the importance of selecting reliable tools for accurate velocity-based training and load prescription.
Anomaly Detection Method for Harmonic Reducers with Only Healthy Data
Authors: Li Yuqing , Zhu Linghui , Xu Minqiang , Jia Yunzhao
Published: November 2024

A harmonic reducer is an important component of industrial robots. In practical applications, it is difficult to obtain enough anomaly data from error cases for the supervised training of models. Whether the information contained in regular features is sensitive to anomaly detection is unknown. In this paper, we propose an anomaly detection frame for a harmonic reducer with only healthy data. We considered an auto-encoder trained using only healthy features, such as feature mapping, in which the difference between the output and the input constitutes a new high-dimensional feature space that retained information relevant only to anomalies. Compared to the original feature space, this space was more sensitive to abnormal data. The mapped features were then fed into the OCSVM to preserve the feature details of the abnormal information. The effectiveness of this method was validated by multiple sets of data collecting from harmonic reducers. Three different residual calculations and four different AE models were used, showing that the method outperforms an AE or an OCSVM alone. It is also verified that the method outperforms other typical anomaly detection methods.
Developments in the Dry Fractionation of Plant Components: A Review
Authors: Meenakshi Sundaram Ganapathy Subramanian , Das Divyapratim , Emiola-Sadiq Tolu , Sajeeb Khan Abdullah , Zhang Lifeng , Meda Venkatesh
Published: November 2024

Over the years, pulses and cereals have been identified as promising sources of plant proteins. The intensive production of these crops and concerns about food security and malnutrition worldwide have intensified research into their separation. While wet extraction remains the standard protein isolation method, the search for more sustainable extraction methods is still ongoing. Two dry fractionation techniques, air classification and tribo-electrostatic separation, have been discussed in this review. This review highlights the design aspects of air classifiers including the cut-off point and flow rate, and for electrostatic separators, factors such as charger materials, the nature of the flow in charger tubes, and the strength of the electric field potential have been discussed in detail. Our analysis revealed that cascading the two techniques should help enhance the concentration and purity of the separated fractions. While limitations such as low purity and low yield exist, current research studies are focused on overcoming such drawbacks. Dry fractionation exhibits potential as a sustainable processing method while also preserving the native functionality of the proteins, making it easier to incorporate the fractions in commercial scale processes.
A Qualitative Analysis of Australian Perspectives Regarding the Cost of Groceries Using the Online Social Media Platform, Reddit
Authors: Chan Virginia , Roy Rajshri
Published: November 2024

Australia’s current food system does not equitably or sustainably feed all Australians. Coupled with the rising costs of essential goods, it raises concerns around the cost of living and food security. This study aimed to investigate Reddit user perspectives on the current cost of food and groceries in Australian subreddits. Posts related to the costs of groceries within Australian subreddits were collected using Reddit’s Application Programming Interface (API) and Python Reddit API Wrapper python package (version 7.7.1). Posts (n = 1727) were screened, and the included posts (n = 583) underwent thematic analysis. Australian Reddit users reported concerns over the increasing prices of groceries and identified supermarket pricing tactics including price gouging, shrinkflation, and misleading price displays. Reddit also served as an important platform providing support and a method to disseminate budgeting strategies to help others to overcome rising costs of living. The findings highlighted the challenges faced by Australians in managing food and grocery expenses and the strategies they employ to cope with rising costs, emphasizing the need for targeted interventions to improve food affordability and accessibility.
Editorial of “Sustainability of Transport Infrastructures”
Authors: Oliveira Joel R. M. , Silva Hugo M. R. D. , Williams R. Christopher , Dong Zejiao
Published: November 2024

Sustainability in transport infrastructures has become a key priority for governments, industries, and researchers worldwide [...]
Probabilistic Analysis of Electricity Production from a Photovoltaic–Wind Energy Mix for Sustainable Transport Needs
Authors: Małek Arkadiusz , Marciniak Andrzej , Bednarczyk Tomasz
Published: November 2024

Renewable Energy Sources (RESs) are characterized by high unevenness, cyclicality, and seasonality of energy production. Due to the trends in the production of electricity itself and the utilization of hydrogen, distributed generation systems are preferred. They can be connected to the energy distribution network or operate without its participation (off-grid). However, in both cases, such distributed energy sources should be balanced in terms of power generation. According to the authors, it is worth combining different RESs to ensure the stability of energy production from such a mix. Within the mix, the sources can complement and replace each other. According to the authors, an effective system for generating energy from RESs should contain at least two different sources and energy storage. The purpose of the analyses and calculations performed is to determine the characteristics of energy generation from a photovoltaic system and a wind turbine with a specific power and geographical location in the Lublin region in Poland. Another important goal is to determine the substitutability of the sources studied. Probabilistic analysis will be used to determine the share of given energy sources in the energy mix and will allow us to estimate the size of the stationary energy storage. The objective of these procedures is to strive for the highest possible share of renewable energy in the total energy required to charge electric vehicle fleets and to produce low-emission hydrogen for transportation. The article proves that the appropriately selected components of the photovoltaic and wind energy mix located in the right place lead to the self-balancing of the local energy network using a small energy storage. The conclusions drawn from the conducted research can be used by RES developers who intend to invest in new sources of power generation to produce low-emission hydrogen. This is in line with the current policy of the European Union aimed at climate and energy transformation of many companies using green hydrogen.
Sustainability of Agricultural and Forestry Systems: Resource Footprint Approach
Authors: Casas-Ledón Yannay , Silva Javiera , Larrere Sebastián , Martínez-Martínez Yenisleidy
Published: November 2024

Land management is critical for the conservation of natural resources, particularly in agroforestry systems which rely heavily on land productivity and availability. Optimizing land utilization is critical for sustainable biomass production and is a key component of achieving effective, long-term sustainable land management. This study assesses the resource efficiency of agroforestry production systems with a novel exergy-based indicator (ΔEF). The indicator was used in the Biobío and Ñuble regions to assess the resource balance between six agricultural and two forestry production systems. The ΔEF values ranged from positive to negative, with positive values indicating better resource usage and negative values suggesting the opposite. Eucalyptus globulus had higher ΔEF values (18.06–19.5 MJex/m2.yr) than Pinus radiata (−2.71 to −1.47 MJex/m2.yr), indicating better sustainability due to its high biomass yields and lower harvesting period and resource consumption. Sugar beet, wheat, and potatoes were the most sustainable (8.57–154.6 MJex/m2.yr) because of their high yields and less intensive harvesting methods. Disparities in biomass yield, potential net primary production (NPPpot), and land management intensity drive differences in ΔEF across regions. Our findings enhance the understanding of local and non-local resource efficiency in agroforestry systems, revealing significant drivers to encourage more sustainable land management practices.