bluuebunny/crossref_metadata_2025 huggingface dataset:
The Growth-Promoting and Colonization of the Pine Endophytic Pseudomonas abietaniphila for Pine Wilt Disease Control
Authors: Peng Yueyuan , Tang Yuwei , Li Da , Ye Jianren
Published: May 2024

In this study, we focused on evaluating the impact of Pseudomonas abietaniphila BHJ04 on the growth of Pinus massoniana seedlings and its biocontrol efficacy against pine wilt disease (PWD). Additionally, the colonization dynamics of P. abietaniphila BHJ04 on P. massoniana were examined. The growth promotion experiment showed that P. abietaniphila BHJ04 significantly promoted the growth of the branches and roots of P. massoniana. Pot control experiments indicated that strain BHJ04 significantly inhibited the spread of PWD. There were significant changes in the expression of several genes related to pine wood nematode defense in P. massoniana, including chitinase, nicotinamide synthetase, and triangular tetrapeptide-like superfamily protein isoform 9. Furthermore, our results revealed significant upregulation of genes associated with the water stress response (dehydration-responsive proteins), genetic material replication (DNA/RNA polymerase superfamily proteins), cell wall hydrolase, and detoxification (cytochrome P450 and cytochrome P450 monooxygenase superfamily genes) in the self-regulation of P. massoniana. Colonization experiments demonstrated that strain BHJ04 can colonize the roots, shoots, and leaves of P. massoniana, and the colonization amount on the leaves was the greatest, reaching 160,000 on the 15th day. However, colonization of the stems lasted longer, with the highest level of colonization observed after 45 d. This study provides a preliminary exploration of the growth-promoting and disease-preventing mechanisms of P. abietaniphila BHJ04 and its ability to colonize pines, thus providing a new biocontrol microbial resource for the biological control of plant diseases.
Endometrial Cancer: A Pilot Study of the Tissue Microbiota
Authors: Leoni Claudia , Vinci Lorenzo , Marzano Marinella , D’Erchia Anna Maria , Dellino Miriam , Cox Sharon Natasha , Vitagliano Amerigo , Visci Grazia , Notario Elisabetta , Filomena Ermes , Cicinelli Ettore , Pesole Graziano , Ceci Luigi Ruggiero
Published: May 2024

Background: The endometrium remains a difficult tissue for the analysis of microbiota, mainly due to the low bacterial presence and the sampling procedures. Among its pathologies, endometrial cancer has not yet been completely investigated for its relationship with microbiota composition. In this work, we report on possible correlations between endometrial microbiota dysbiosis and endometrial cancer. Methods: Women with endometrial cancer at various stages of tumor progression were enrolled together with women with a benign polymyomatous uterus as the control. Analyses were performed using biopsies collected at two specific endometrial sites during the surgery. This study adopted two approaches: the absolute quantification of the bacterial load, using droplet digital PCR (ddPCR), and the analysis of the bacterial composition, using a deep metabarcoding NGS procedure. Results: ddPCR provided the first-ever assessment of the absolute quantification of bacterial DNA in the endometrium, confirming a generally low microbial abundance. Metabarcoding analysis revealed a different microbiota distribution in the two endometrial sites, regardless of pathology, accompanied by an overall higher prevalence of pathogenic bacterial genera in cancerous tissues. Conclusions: These results pave the way for future studies aimed at identifying potential biomarkers and gaining a deeper understanding of the role of bacteria associated with tumors.
Interfacial Interaction in MeOx/MWNTs (Me–Cu, Ni) Nanostructures as Efficient Electrode Materials for High-Performance Supercapacitors
Authors: Yalovega Galina E. , Brzhezinskaya Maria , Dmitriev Victor O. , Shmatko Valentina A. , Ershov Igor V. , Ulyankina Anna A. , Chernysheva Daria V. , Smirnova Nina V.
Published: May 2024

Due to their unique physical and chemical properties, complex nanostructures based on carbon nanotubes and transition metal oxides are considered promising electrode materials for the fabrication of high-performance supercapacitors with a fast charge rate, high power density, and long cycle life. The crucial role in determining their efficiency is played by the properties of the interface in such nanostructures, among them, the type of chemical bonds between their components. The complementary theoretical and experimental methods, including dispersion-corrected density functional theory (DFT-D3) within GGA-PBE approximation, scanning electron microscopy (SEM), X-ray diffraction (XRD), Raman, X-ray photoelectron, and X-ray absorption spectroscopies, were applied in the present work for the comprehensive investigation of surface morphology, structure, and electronic properties in CuOx/MWCNTs and NiOx/MWCNTs. As a result, the type of interfacial interaction and its correlation with electrochemical characteristics were determined. It was found that the presence of both Ni–O–C and Ni–C bonds can increase the contact between NiO and MWCNTs, and, through this, promote electron transfer between NiO and MWCNTs. For NiOx/MWCNTs, better electrochemical characteristics were observed than for CuOx/MWCNTs, in which the interfacial interaction is determined only by bonding through Cu–O–C bonds. The electrochemical properties of CuOx/MWCNTs and NiOx/MWCNTs were studied to demonstrate the effect of interfacial interaction on their efficiency as electrode materials for supercapacitor applications.
Greatly Enhanced Thermoelectric Performance of Flexible Cu2−xS Composite Film on Nylon by Se Doping
Authors: Zuo Xinru , Han Xiaowen , Wang Zixing , Liu Ying , Li Jiajia , Zhang Mingcheng , Huang Changjun , Cai Kefeng
Published: May 2024

In this work, flexible Cu2−xS films on nylon membranes are prepared by combining a simple hydrothermal synthesis and vacuum filtration followed by hot pressing. The films consist of Cu2S and Cu1.96S two phases with grain sizes from nano to submicron. Doping Se on the S site not only increases the Cu1.96S content in the Cu2−xS to increase carrier concentration but also modifies electronic structure, thereby greatly improves the electrical properties of the Cu2−xS. Specifically, an optimal composite film with a nominal composition of Cu2−xS0.98Se0.02 exhibits a high power factor of ~150.1 μW m−1 K−2 at 300 K, which increases by ~138% compared to that of the pristine Cu2−xS film. Meanwhile, the composite film shows outstanding flexibility (~97.2% of the original electrical conductivity is maintained after 1500 bending cycles with a bending radius of 4 mm). A four-leg flexible thermoelectric (TE) generator assembled with the optimal film generates a maximum power of 329.6 nW (corresponding power density of 1.70 W m−2) at a temperature difference of 31.1 K. This work provides a simple route to the preparation of high TE performance Cu2−xS-based films.
Dietary Habits and Race Day Strategies among Flexitarian, Vegetarian, and Vegan Recreational Endurance Runners: A Cross-Sectional Investigation from The NURMI Study (Step 2)
Authors: Tanous Derrick R. , Motevalli Mohamad , Leitzmann Claus , Wirnitzer Gerold , Rosemann Thomas , Knechtle Beat , Wirnitzer Katharina
Published: May 2024

Many of today’s recreational runners have changed their diet from omnivorous to vegetarian or vegan for reasons like better sport performance, animal ethics, positive health, eco-aspects, or male infertility. Others have constructed the flexitarian diet due to current trends in sustainable eating. The aim of this investigation was to analyze the dietary habits and race day strategies of recreational endurance runners following current sustainable dietary trends. Recreational endurance runners (18+ years) were invited to complete the standardized online survey on socio-demography/anthropometry, motivations, running/racing history, food frequency, and race day dietary strategy. Chi-squared tests and Wilcoxon tests were used for the statistical analysis. In total, 289 participants submitted the survey; 146 subjects following flexitarian (n = 34), vegetarian (n = 50), or vegan (n = 62) diets were included in the final sample. Significant differences were found across the diet types: BMI (p = 0.018), fruit/vegetable consumption (p < 0.001), and the dietary motive of performance (p = 0.045). The findings suggest that the flexitarian diet may be appropriate for health- and environmentally conscious populations living in a meat-centered society and lacking social support to eat completely vegetarian/vegan. Following a plant-based diet is perceived as easy for health-conscious, athletic populations, and the vegan diet does not require a particularly effortful/complex race day strategy for endurance runners.
Celiac Disease: The Importance of Studying the Duodenal Mucosa-Associated Microbiota
Authors: Annunziato Alessandro , Vacca Mirco , Cristofori Fernanda , Dargenio Vanessa Nadia , Celano Giuseppe , Francavilla Ruggiero , De Angelis Maria
Published: May 2024

There is increasing evidence indicating that changes in both the composition and functionality of the intestinal microbiome are closely associated with the development of several chronic inflammatory diseases, with celiac disease (CeD) being particularly noteworthy. Thanks to the advent of culture-independent methodologies, the ability to identify and quantify the diverse microbial communities residing within the human body has been significantly improved. However, in the context of CeD, a notable challenge lies in characterizing the specific microbiota present on the mucosal surfaces of the intestine, rather than relying solely on fecal samples, which may not fully represent the relevant microbial populations. Currently, our comprehension of the composition and functional importance of mucosa-associated microbiota (MAM) in CeD remains an ongoing field of research because the limited number of available studies have reported few and sometimes contradictory results. MAM plays a crucial role in the development and progression of CeD, potentially acting as both a trigger and modulator of the immune response within the intestinal mucosa, given its proximity to the epithelial cells and direct interaction. According to this background, this review aims to consolidate the existing literature specifically focused on MAM in CeD. By elucidating the complex interplay between the host immune system and the gut microbiota, we aim to pave the way for new interventions based on novel therapeutic targets and diagnostic biomarkers for MAM in CeD.
Omega-3 Supplementation and Its Effects on Osteoarthritis
Authors: Shawl Megan , Geetha Thangiah , Burnett Donna , Babu Jeganathan
Published: May 2024

Osteoarthritis (OA) is a degenerative joint disease characterized by the destruction of the articular cartilage, resulting in a pro-inflammatory response. The progression of OA is multifactorial and is influenced by the underlying cause of inflammation, which includes but is not limited to trauma, metabolism, biology, comorbidities, and biomechanics. Although articular cartilage is the main tissue affected in osteoarthritis, the chronic inflammatory environment negatively influences the surrounding synovium, ligaments, and subchondral bone, further limiting their functional abilities and enhancing symptoms of OA. Treatment for osteoarthritis remains inconsistent due to the inability to determine the underlying mechanism of disease onset, severity of symptoms, and complicating comorbidities. In recent years, diet and nutritional supplements have gained interest regarding slowing the disease process, prevention, and treatment of OA. This is due to their anti-inflammatory properties, which result in a positive influence on pain, joint mobility, and cartilage formation. More specifically, omega-3 polyunsaturated fatty acids (PUFA) have demonstrated an influential role in the progression of OA, resulting in the reduction of cartilage destruction, inhibition of pro-inflammatory cytokine cascades, and production of oxylipins that promote anti-inflammatory pathways. The present review is focused on the assessment of evidence explaining the inflammatory processes of osteoarthritis and the influence of omega-3 supplementation to modulate the progression of osteoarthritis.
Impact of Body Mass Index in the Cardioverter Efficacy of Amiodarone in Persistent Atrial Fibrillation
Authors: Ligero Carmen , Riera Pau , El-Amrani Amine , Bazan Victor , Guerra José M. , Herraez Silvia , Viñolas Xavier , Alegret Josep M.
Published: May 2024

Background: Amiodarone is an anti-arrhythmic drug that has extensive tissue distribution and substantial storage in the fat tissue. Different studies have described some implications of body fat composition in its pharmacokinetics and pharmacodynamics. However, no clinical studies have described its implications for clinical efficacy. Methods: We studied 878 patients with persistent atrial fibrillation (AF) treated with a regimen of amiodarone and referred to electrical cardioversion (ECV), included prospectively in two Spanish registries. We analyzed the influence of body mass index (BMI), as well as overweight and obesity, in the efficacy of amiodarone for achieving pharmacologic cardioversion to sinus rhythm (SR) before ECV. Results: A total of 185 patients (21.1%) reverted to SR before ECV. Patients who reverted to SR had a lower BMI than those who did not revert (27.45 ± 4.36 kg/m2 vs. 29.11 ± 4.09 kg/m2; p < 0.001). We observed a progressively lower probability of reverting to SR in overweight and obese patients (normal weight 28.3%, overweight 21.3%, obesity 13.1%; p < 0.001). In the logistic regression, BMI (kg/m2) adjusted for other related variables remained as the main factor inversely related to reversion to SR (OR = 0.904 × kg/m2); CI 75% 0.864–0.946). Conclusions: We observed a negative relationship between an increased BMI and the efficacy of amiodarone for reversion to SR, suggesting a negative clinical impact of excess body fat in its efficacy.
Chiral Hydroxy Metabolite of Mebendazole: Analytical and Semi-Preparative High-Performance Liquid Chromatography Resolution and Chiroptical Properties
Authors: Guglielmi Paolo , Pulitelli Gaia , Arrighi Francesca , Secci Daniela , Pierini Marco , Cirilli Roberto
Published: May 2024

Mebendazole (MBZ) is a benzimidazole carbamate anthelmintic used worldwide for the treatment and prevention of parasitic disorders in animals and humans. A large number of in vivo and in vitro studies have demonstrated that MBZ also has anticancer activity in multiple types of cancers. After oral administration, the phenylketone moiety of MBZ is rapidly reduced to the hydroxyl group to form the chiral hydroxy metabolite (MBZ-OH). To the best of our knowledge, there is no information in the literature on the stereochemical course of transformation and the anthelmintic and antitumor activity of individual enantiomers of MBZ-OH. In the present study, we describe in detail the direct HPLC resolution of MBZ-OH on a 100 mm × 4.6 mm Chirapak IG-3 column packed with 3 μm silica particles containing amylose (3-chloro-5-methylphenylcarbamate) as a selector. At 25 °C and using pure methanol as the mobile phase, the enantioseparation and resolution factors were 2.38 and 6.13, respectively. These conditions were scaled up at a semi-preparative scale using a 250 mm × 10 mm Chiralpak IG column to isolate multi-milligram amounts of both enantiomeric forms of the chiral metabolite. The chiroptical properties of the collected enantiomers were determined and, through a theoretical study, were related to the more stable conformations of MBZ-OH. The first and second eluted enantiomers were dextrorotatory and levorotatory, respectively, in dimethylformamide solution. Finally, by recording the retention factors of the enantiomers as the water content in the water–acetonitrile mobile phases was progressively varied, U-shaped retention maps were generated, indicating a dual and competitive hydrophilic interaction liquid chromatography and reversed-phase liquid chromatography retention mechanism on the Chirapak IG-3 chiral stationary phase.
Simvastatin-Encapsulated Topical Liposomal Gel for Augmented Wound Healing: Optimization Using the Box-Behnken Model, Evaluations, and In Vivo Studies
Authors: Rahamathulla Mohamed , Pokale Rahul , Al-ebini Yousef , Osmani Riyaz Ali M. , Thajudeen Kamal Y. , Gundawar Ravi , Ahmed Mohammed Muqtader , Farhana Syeda Ayesha , Shivanandappa Thippeswamy Boreddy
Published: May 2024

Statins function beyond regulating cholesterol and, when administered systemically, can promote wound healing. However, studies have yet to explore the topical use of statins for wound healing. The present study demonstrated the topical administration of SIM and aimed to formulate, evaluate, and optimize Simvastatin (SIM)-encapsulated liposome gel carrier systems to facilitate successful topical wound healing. Liposomes containing SIM were formulated and optimized via a response surface methodology (RSM) using the thin-film hydration method. The effects of formulation variables, including the 1,2-dioleoyloxy-3-trimethylammoniumpropan (DOTAP) concentration, Span 80 concentration, and cholesterol concentration, on zeta potential (mV), entrapment efficacy (%), and particle size (nm) were studied. The optimized liposome formulation (F-07) exhibited a zeta potential value of 16.56 ± 2.51 mV, revealing robust stability and a high SIM encapsulation efficiency of 95.6 ± 4.2%, whereas its particle size of 190.3 ± 3.3 nm confirmed its stability and structural integrity. The optimized liposome gel demonstrated pseudoplastic flow behavior. This property is advantageous in topical drug delivery systems because of its ease of application, improved spreadability, and enhanced penetration, demonstrating prolonged SIM release. The assessment of the wound healing efficacy of the optimized liposomal gel formulation demonstrated a substantial decrease in wound size in mice on the sixteenth day post-wounding. These findings suggest that the use of liposomal gels is a potential drug delivery strategy for incorporating SIM, thereby augmenting its effectiveness in promoting wound healing.
Amino Acid Biosynthesis Inhibitors in Tuberculosis Drug Discovery
Authors: Guida Michela , Tammaro Chiara , Quaranta Miriana , Salvucci Benedetta , Biava Mariangela , Poce Giovanna , Consalvi Sara
Published: May 2024

According to the latest World Health Organization (WHO) report, an estimated 10.6 million people were diagnosed with tuberculosis (TB) in 2022, and 1.30 million died. A major concern is the emergence of multi-drug-resistant (MDR) and extensively drug-resistant (XDR) strains, fueled by the length of anti-TB treatment and HIV comorbidity. Innovative anti-TB agents acting with new modes of action are the only solution to counteract the spread of resistant infections. To escape starvation and survive inside macrophages, Mtb has evolved to become independent of the host by synthesizing its own amino acids. Therefore, targeting amino acid biosynthesis could subvert the ability of the mycobacterium to evade the host immune system, providing innovative avenues for drug discovery. The aim of this review is to give an overview of the most recent progress in the discovery of amino acid biosynthesis inhibitors. Among the hits discovered over the past five years, tryptophan (Trp) inhibitors stand out as the most advanced and have significantly contributed to demonstrating the feasibility of this approach for future TB drug discovery. Future efforts should be directed at prioritizing the chemical optimization of these hits to enrich the TB drug pipeline with high-quality leads.
Design of Machine Learning-Based Algorithms for Virtualized Diagnostic on SPARC_LAB Accelerator
Authors: Latini Giulia , Chiadroni Enrica , Mostacci Andrea , Martinelli Valentina , Serenellini Beatrice , Silvi Gilles Jacopo , Pioli Stefano
Published: May 2024

Machine learning deals with creating algorithms capable of learning from the provided data. These systems have a wide range of applications and can also be a valuable tool for scientific research, which in recent years has been focused on finding new diagnostic techniques for particle accelerator beams. In this context, SPARC_LAB is a facility located at the Frascati National Laboratories of INFN, where the progress of beam diagnostics is one of the main developments of the entire project. With this in mind, we aim to present the design of two neural networks aimed at predicting the spot size of the electron beam of the plasma-based accelerator at SPARC_LAB, which powers an undulator for the generation of an X-ray free electron laser (XFEL). Data-driven algorithms use two different data preprocessing techniques, namely an autoencoder neural network and PCA. With both approaches, the predicted measurements can be obtained with an acceptable margin of error and most importantly without activating the accelerator, thus saving time, even compared to a simulator that can produce the same result but much more slowly. The goal is to lay the groundwork for creating a digital twin of linac and conducting virtualized diagnostics using an innovative approach.
Sodium Hypochlorite Pentahydrate as a Chlorinating Reagent: Application to the Tandem Conversion of β,γ-Unsaturated Carboxylic Acids to α,β-Unsaturated Lactones
Authors: Iwaoka Michio , Shimada Reo , Kuroda Masaki , Ikeda Takehito , Alberto Eduardo E.
Published: May 2024

Sodium hypochlorite pentahydrate (NaClO·5H2O, 1) has recently been employed in organic synthesis as an oxidant for alcohols, sulfides, glycols, etc. In most of these reactions, however, reagent 1 functions just as a simple oxidant, and the variations of the reactions have not been well explored. In this study, we report another useful and fascinating reaction, in which reagent 1 functions as a green chlorinating reagent toward β,γ-unsaturated carboxylic acid (2). When substrate 2 was stirred at room temperature with 1 (2 eq) in acetonitrile for 1 h, α,β-unsaturated lactone (3) was obtained in moderate yields (up to 62%). The same reaction proceeded in various organic and aqueous solvents as well. When excess reagent 1 was employed, lactone 3 was further oxidized to the corresponding epoxide (4) for some cases. The conversion is initiated by electrophilic attack of HOCl to the C=C bond of 2 to generate a chloronium ion intermediate, which is cyclized to β-chlorolactone (5) and then 3 through the elimination of HCl. The usefulness of 1 as a chlorinating reagent was further demonstrated in the electrophilic substitution of activated aromatic compounds.
Recent Advancements in Photo-Bioreactors for Microalgae Cultivation: A Brief Overview
Authors: Penloglou Giannis , Pavlou Alexandros , Kiparissides Costas
Published: May 2024

Inspired by the vast potential of microalgae in the bioeconomy and the numerous applications and benefits associated with their cultivation, a multitude of pilot- and industrial-scale microalgae production systems have been developed in recent years. Both open and closed cultivation systems have been successfully utilized, with closed photo-bioreactors (PBRs) emerging as the most versatile option for various applications and products, enabling the implementation of advanced optimization strategies. Therefore, this short review provides a comprehensive overview of the different PBR configurations and their recent applications, primarily in large-scale but also in pilot- and laboratory-scale microalgae cultivation. A detailed discussion of the advantages, limitations, specific applications and recent advancements of each type of PBR is presented to aid researchers, engineers and industry stakeholders in selecting the most suitable PBR design for their specific goals and constraints. Moreover, this review highlights the major challenges impeding the full commercialization of microalgal products and forecasts future trends in the microalgae-based industry. The diverse potential applications of microalgae in various sectors, including biofuels, nutraceuticals, pharmaceuticals, agriculture and environmental remediation, underscore the versatility and significance of the relevant cultivation technologies. By offering valuable insights into the future commercial scale and trends of microalgal biotechnology, this work sheds light on the challenges and opportunities facing this burgeoning industry.
Colonial Catholicism and Jesuit Education in Ireland: Navigating Faith, Education, and Politics in the 19th Century
Authors: Hou Xiaoshan , Shen Fuying
Published: May 2024

Anchored in the Ignatian ethos of spirituality and education, Jesuit education initially emerged as a vehicle for spiritual development within the Catholic sphere. In Ireland, from the early 19th century onwards, it was strategically aligned with British colonial interests, fostering a unique form of colonial Catholicism. This article examines how Jesuit education served the domestic elite during British rule, employing education strategically to bolster Catholic interests in the 19th century. It focuses on how institutions like Tullabeg and Clongowes became instrumental in merging Catholic education with colonial aims, purportedly under a divine mandate. This scrutiny reveals that the colonial drive towards a Westernized, secular approach in religion and education unexpectedly strengthened religious identities and their political sway, countering the prevalent assumption that modernization equates to secularization. The analysis of the roles played by these premier boarding schools in cultivating colonial Catholicism demonstrates that Jesuit education in Ireland was significant in reshaping the dynamics of religion, education, and politics. This case study highlights the complex outcomes of colonial religious and educational strategies, highlighting the persistent impact of colonialism on Ireland’s religious character and societal conversation. It illuminates the intricate interplay between faith, education, and colonialism.
Parameter Extraction of Accelerated Moving Targets under Non-Quasi-Axial Incidence Conditions Based on Vortex Electromagnetic Wave Radar
Authors: Zhang Lingling , Zhu Yongzhong , Chen Yijun , Xie Wenxuan , Yuan Hang
Published: May 2024

Vortex electromagnetic wave radar carrying orbital angular momentum can compensate for the deficiency of planar electromagnetic wave radar in detecting motion parameters perpendicular to the direction of electromagnetic wave propagation, thus providing more information for target recognition, which has become a hot research field in recent years. However, existing research makes it difficult to obtain the acceleration and rotation centers of targets under non-quasi-axial incidence conditions of vortex electromagnetic waves. Based on this, this article proposes a variable speed motion target parameter extraction method that combines single element and total element echoes. This method can achieve three-dimensional information extraction of radar targets based on a uniform circular array (UCA). Firstly, we establish a non-quasi-axis detection echo model for variable-speed moving targets and extract echoes from different array elements. Then, a single element echo is used to extract the target’s range slow time profile and obtain the target’s rotation center z coordinate. We further utilize the target linear, angular Doppler frequency shift extremum, and median information to extract parameters such as target acceleration, tilt angle, rotation radius, and rotation center x and y coordinates. We analyzed the impact of different signal-to-noise ratios and motion states on parameter extraction. The simulation results have verified the effectiveness of the proposed algorithm.
BAMFORESTS: Bamberg Benchmark Forest Dataset of Individual Tree Crowns in Very-High-Resolution UAV Images
Authors: Troles Jonas , Schmid Ute , Fan Wen , Tian Jiaojiao
Published: May 2024

The anthropogenic climate crisis results in the gradual loss of tree species in locations where they were previously able to grow. This leads to increasing workloads and requirements for foresters and arborists as they are forced to restructure their forests and city parks. The advancements in computer vision (CV)—especially in supervised deep learning (DL)—can help cope with these new tasks. However, they rely on large, carefully annotated datasets to produce good and generalizable models. This paper presents BAMFORESTS: a dataset with 27,160 individually delineated tree crowns in 105 ha of very-high-resolution UAV imagery gathered with two different sensors from two drones. BAMFORESTS covers four areas of coniferous, mixed, and deciduous forests and city parks. The labels contain instance segmentations of individual trees, and the proposed splits are balanced by tree species and vitality. Furthermore, the dataset contains the corrected digital surface model (DSM), representing tree heights. BAMFORESTS is annotated in the COCO format and is especially suited for training deep neural networks (DNNs) to solve instance segmentation tasks. BAMFORESTS was created in the BaKIM project and is freely available under the CC BY 4.0 license.
Multi-Attack Intrusion Detection for In-Vehicle CAN-FD Messages
Authors: Gao Fei , Liu Jinshuo , Liu Yingqi , Gao Zhenhai , Zhao Rui
Published: May 2024

As an enhanced version of standard CAN, the Controller Area Network with Flexible Data (CAN-FD) rate is vulnerable to attacks due to its lack of information security measures. However, although anomaly detection is an effective method to prevent attacks, the accuracy of detection needs further improvement. In this paper, we propose a novel intrusion detection model for the CAN-FD bus, comprising two sub-models: Anomaly Data Detection Model (ADDM) for spotting anomalies and Anomaly Classification Detection Model (ACDM) for identifying and classifying anomaly types. ADDM employs Long Short-Term Memory (LSTM) layers to capture the long-range dependencies and temporal patterns within CAN-FD frame data, thus identifying frames that deviate from established norms. ACDM is enhanced with the attention mechanism that weights LSTM outputs, further improving the identification of sequence-based relationships and facilitating multi-attack classification. The method is evaluated on two datasets: a real-vehicle dataset including frames designed by us based on known attack patterns, and the CAN-FD Intrusion Dataset, developed by the Hacking and Countermeasure Research Lab. Our method offers broader applicability and more refined classification in anomaly detection. Compared with existing advanced LSTM-based and CNN-LSTM-based methods, our method exhibits superior performance in detection, achieving an improvement in accuracy of 1.44% and 1.01%, respectively.
A Study on Predicting the Deviation of Jet Trajectory Falling Point under the Influence of Random Wind
Authors: Cheng Hengyu , Zhu Jinsong , Wang Sining , Yan Ke , Wang Haojie
Published: May 2024

As one of the main external factors affecting the fire extinguishing accuracy of sprinkler systems, it is necessary to analyze and study random wind. However, in practical applications, there is little research on the impact of random wind on sprinkler fire extinguishing points. To address this issue, a new random wind acquisition system was constructed in this paper, and a method for predicting jet trajectory falling points in Random Forest (RF) under the influence of random wind was proposed, and compared with the commonly used prediction model Support Vector Machine (SVM). The method in this article reduces the error in the x direction of the 50 m prediction result from 2.11 m to 1.53 m, the error in the y direction from 0.64 m to 0.6 m, and the total mean absolute error (MAE) from 31.3 to 23.5. Simultaneously, predict the falling points of jet trajectory at different distances under the influence of random wind, to demonstrate the feasibility of the proposed method in practical applications. The experimental results show that the system and method proposed in this article can effectively improve the influence of random wind on the falling points of a jet trajectory. In summary, the image acquisition system and error prediction method proposed in this article have many potential applications in fire extinguishing.
Loom: A Modular Open-Source Approach to Rapidly Produce Sensor, Actuator, Datalogger Systems
Authors: Richards William , Selker John , Udell Chet
Published: May 2024

In the face of rising population, erratic climate, resource depletion, and increased exposure to natural hazards, environmental monitoring is increasingly important. Satellite data form most of our observations of Earth. On-the-ground observations based on in situ sensor systems are crucial for these remote measurements to be dependable. Providing open-source options to rapidly prototype environmental datalogging systems allows quick advancement of research and monitoring programs. This paper introduces Loom, a development environment for low-power Arduino-programmable microcontrollers. Loom accommodates a range of integrated components including sensors, various datalogging formats, internet connectivity (including Wi-Fi and 4G Long Term Evolution (LTE)), radio telemetry, timing mechanisms, debugging information, and power conservation functions. Additionally, Loom includes unique applications for science, technology, engineering, and mathematics (STEM) education. By establishing modular, reconfigurable, and extensible functionality across components, Loom reduces development time for prototyping new systems. Bug fixes and optimizations achieved in one project benefit all projects that use Loom, enhancing efficiency. Although not a one-size-fits-all solution, this approach has empowered a small group of developers to support larger multidisciplinary teams designing diverse environmental sensing applications for water, soil, atmosphere, agriculture, environmental hazards, scientific monitoring, and education. This paper not only outlines the system design but also discusses alternative approaches explored and key decision points in Loom’s development.
Development and Validation of Low-Cost Indoor Air Quality Monitoring System for Swine Buildings
Authors: Arulmozhi Elanchezhian , Bhujel Anil , Deb Nibas Chandra , Tamrakar Niraj , Kang Myeong Yong , Kook Junghoo , Kang Dae Yeong , Seo Eun Wan , Kim Hyeon Tae
Published: May 2024

The optimal indoor environment is associated with comfortable temperatures along with favorable indoor air quality. One of the air pollutants, particulate matter (PM), is potentially harmful to animals and humans. Most farms have monitoring systems to identify other hazardous gases rather than PM due to the sensor cost. In recent decades, the application of environmental monitoring systems based on Internet of Things (IoT) devices that incorporate low-cost sensors has elevated extensively. The current study develops a low-cost air quality monitoring system for swine buildings based on Raspberry Pi single-board computers along with a sensor array. The system collects data using 11 types of environmental variables along with temperature, humidity, CO2, light, pressure, and different types of gases, namely PM1, PM2.5, and PM10. The system is designed with a central web server that provides real-time data visualization and data availability through the Internet. It was tested in actual pig barns to ensure stability and functionality. In addition, there was a collocation test conducted by placing the system in two different pig barns to validate the sensor data. The Wilcoxon rank sum test demonstrates that there are no significant differences between the two sensor datasets, as all variables have a p-value greater than 0.05. However, except for carbon monoxide (CO), none of the variables exhibit correlation exceeding 0.5 with PM concentrations. Overall, a scalable, portable, non-complex, low-cost air quality monitoring system was successfully developed within a cost of USD 94.
Dynamic Coalition Formation among IoT Service Providers: A Systematic Exploration of IoT Dynamics Using an Agent-Based Model
Authors: Shakya Joshua , Chopin Morgan , Merghem-Boulahia Leila
Published: May 2024

This paper introduces an Agent-Based Model (ABM) designed to investigate the dynamics of the Internet of Things (IoT) ecosystem, focusing on dynamic coalition formation among IoT Service Providers (SPs). Drawing on insights from our previous research in 5G network modeling, the ABM captures intricate interactions among devices, Mobile Network Operators (MNOs), SPs, and customers, offering a comprehensive framework for analyzing the IoT ecosystem’s complexities. In particular, to address the emerging challenge of dynamic coalition formation among SPs, we propose a distributed Multi-Agent Dynamic Coalition Formation (MA-DCF) algorithm aimed at enhancing service provision and fostering collaboration. This algorithm optimizes SP coalitions, dynamically adjusting to changing demands over time. Through extensive experimentation, we evaluate the algorithm’s performance, demonstrating its superiority in terms of both payoff and stability compared to three classical coalition formation algorithms: static coalition, non-overlapping coalition, and random coalition. This study significantly contributes to a deeper understanding of the IoT ecosystem’s dynamics and highlights the potential benefits of dynamic coalition formation among SPs, providing valuable insights and opening future avenues for exploration.
A Compensation Method for the Geomagnetic Measurement Error of an Underwater Ship-Borne Magnetometer Based on Constrained Total Least Squares
Authors: Tong Yude , Huang Xiaoying , Chen Yongbing , Li Wenkui , Zha Feng
Published: May 2024

When magnetic matching aided navigation is applied to an underwater vehicle, the magnetometer must be installed inside the vehicle, considering the navigation safety and concealment of the underwater vehicle. Then, the interference magnetic field will seriously affect the accuracy of geomagnetic field measurement, which directly affects the accuracy of geomagnetic matching aided navigation. Therefore, improving the accuracy of geomagnetic measurements inside the vehicle through error compensation has become one of the most difficult problems that requires an urgent solution in geomagnetic matching aided navigation. In order to solve this problem, this paper establishes the calculation model of the internal magnetic field of the underwater vehicle and the geomagnetic measurement error model of the ship-borne magnetometer. Then, a compensation method for the geomagnetic measurement error of the ship-borne magnetometer, based on the constrained total least square method, is proposed. To verify the effectiveness of the method proposed in this paper, a simulation experiment of geomagnetic measurement and compensation of a ship-borne three-axis magnetometer was constructed. Among them, to be closer to the real situation, a combination of the geomagnetism model, the elliptic shell model and the magnetic dipole model was used to simulate the internal magnetic field of the underwater vehicle. The experimental results indicated that the root mean square error of geomagnetic measurement in an underwater vehicle was less than 5 nT after compensation, and the accuracy of geomagnetic measurement met the requirements of geomagnetic matching aided navigation.
FedKG: A Knowledge Distillation-Based Federated Graph Method for Social Bot Detection
Authors: Wang Xiujuan , Chen Kangmiao , Wang Keke , Wang Zhengxiang , Zheng Kangfeng , Zhang Jiayue
Published: May 2024

Malicious social bots pose a serious threat to social network security by spreading false information and guiding bad opinions in social networks. The singularity and scarcity of single organization data and the high cost of labeling social bots have given rise to the construction of federated models that combine federated learning with social bot detection. In this paper, we first combine the federated learning framework with the Relational Graph Convolutional Neural Network (RGCN) model to achieve federated social bot detection. A class-level cross entropy loss function is applied in the local model training to mitigate the effects of the class imbalance problem in local data. To address the data heterogeneity issue from multiple participants, we optimize the classical federated learning algorithm by applying knowledge distillation methods. Specifically, we adjust the client-side and server-side models separately: training a global generator to generate pseudo-samples based on the local data distribution knowledge to correct the optimization direction of client-side classification models, and integrating client-side classification models’ knowledge on the server side to guide the training of the global classification model. We conduct extensive experiments on widely used datasets, and the results demonstrate the effectiveness of our approach in social bot detection in heterogeneous data scenarios. Compared to baseline methods, our approach achieves a nearly 3–10% improvement in detection accuracy when the data heterogeneity is larger. Additionally, our method achieves the specified accuracy with minimal communication rounds.
Study on the Impact of Implementing an Exercise Program Using Fitlight Technology for the Development of Upper Limb Coordinative Abilities in Basketball Players
Authors: Steff Norbert , Badau Dana , Badau Adela
Published: May 2024

The aim of this study was to evaluate the impact of implementing a basketball-specific exercise program using Fitlight technology on the coordinative abilities (reactive coordination, reactive reaction time, and reactive movement combination capacity) of U14 and U16 junior basketball players. This study included 70 male basketball players, 36 subjects U14 and 34 subjects U16, divided into two equal groups for each age category: the experimental group (EG) and the control group (CG). This study included an initial and a final test, between which, training was conducted over a period of 18 weeks. For the EG, the program aimed to develop coordinative abilities through an experimental program that utilized Fitlight technology, while the control groups underwent an identically timed program, but their training did not include the use of technology. Four tests were adapted and applied: the Reactive Reaction Test, Choice Reactive Reaction Test, Reactive Hand–Eye Coordination Test, and a test to evaluate the reactive capacity for combining movements. The results of this study showed statistically significant progress between the initial and final tests for the experimental group, p < 0.05. The Cohen’s d values for the experimental groups were above 0.8, indicating a very large effect size, while for the control group, these values were small to medium. The comparative analysis of the experimental groups U14 and U16 and control groups shows statistically significant differences in favor of the experimental groups U14 and U16. This study highlights the effectiveness of implementing specific training programs that use modern technologies in developing coordinative abilities in the training and evaluation process of junior basketball players.
Geometric Implications of Photodiode Arrays on Received Power Distribution in Mobile Underwater Optical Wireless Communication
Authors: Govinda Waduge Tharuka , Seet Boon-Chong , Vopel Kay
Published: May 2024

Underwater optical wireless communication (UOWC) has gained interest in recent years with the introduction of autonomous and remotely operated mobile systems in blue economic ventures such as offshore food production and energy generation. Here, we devised a model for estimating the received power distribution of diffused line-of-sight mobile optical links, accommodating irregular intensity distributions beyond the beam-spread angle of the emitter. We then used this model to conduct a spatial analysis investigating the parametric influence of the placement, orientation, and angular spread of photodiodes in array-based receivers on the mobile UOWC links in different Jerlov seawater types. It revealed that flat arrays were best for links where strict alignment could be maintained, whereas curved arrays performed better spatially but were not always optimal. Furthermore, utilizing two or more spectrally distinct wavelengths and more bandwidth-efficient modulation may be preferred for received-signal intensity-based localization and improving link range in clearer oceans, respectively. Considering the geometric implications of the array of receiver photodiodes for mobile UOWCs, we recommend the use of dynamically shape-shifting array geometries.
Effect of Edge Activator Combinations in Transethosomal Formulations for Skin Delivery of Thymoquinone via Langmuir Technique
Authors: Mohd Hana , Dopierała Katarzyna , Zidar Anze , Virani Amitkumar , Michniak-Kohn Bozena
Published: May 2024

Thymoquinone (TQ), a bioactive compound found in Nigella sativa seeds, possesses diverse therapeutic properties for skin conditions. However, formulating TQ presents challenges due to its hydrophobic nature and chemical instability, which hinder its skin penetration. Transethosomes, as a formulation, offer an environment conducive to enhancing TQ’s solubility, stability, and skin permeation. To optimize TQ transethosomal formulations, we introduced a combination of ionic and nonionic surfactants, namely Tween 20 and sodium lauryl sulfate (SLS) or sodium lauroyl glutamate (SLG). Surfactants play a crucial role in stabilizing the formulation, reducing aggregation, improving biocompatibility, and minimizing potential toxicity. We fine-tuned the formulation composition and gained insights into its interfacial behavior using the Langmuir monolayer technique. This method elucidated the interfacial properties and behavior of phospholipids in ethosome and transethosome formulations. Our findings suggest that monolayer studies can serve as the initial step in selecting surfactants for nanocarrier formulations based on their interfacial dilational rheology studies. It was found that the addition of surfactant to the formulation increased the elasticity considering the capability of transethosomes to significantly decrease their radius when permeating the skin barrier. The results of the dilational rheology experiments were most relevant to drug permeation through the skin for the largest amplitude of deformation. The combination of Tween 20 and SLS efficiently modified the rheological behavior of lipids, increasing their elasticity. This conclusion was supported by in vitro studies, where formulation F2 composed of Tween 20 and SLS demonstrated the highest permeation after 24 h (300.23 µg/cm2). Furthermore, the F2 formulation showed the highest encapsulation efficiency (EE) of 94%, surpassing those of the control and ethosomal formulations. Additionally, this transethosomal formulation exhibited antimicrobial activity against S. aureus, with a zone of inhibition of 26.4 ± 0.3 mm. Importantly, we assessed the cytotoxicity of both ethosomes and transethosomes at concentrations ranging from 3.5 µM to 50 µM on HaCaT cell lines and found no cytotoxic effects compared to TQ hydroethanolic solution. These results suggest the potential safety and efficacy of TQ transethosomal formulations.