bluuebunny/crossref_metadata_2025 huggingface dataset:
Investigating Non-Native Ribbon Worm Cephalothrix simula as a Potential Source of Tetrodotoxin in British Bivalve Shellfish
Authors: Dhanji-Rapkova Monika , Hatfield Robert G. , Walker David I. , Hooper Chantelle , Alewijnse Sarah , Baker-Austin Craig , Turner Andrew D. , Ritchie Jennifer M.
Published: October 2024

Tetrodotoxin (TTX) is a potent marine neurotoxin found in several phylogenetically diverse organisms, some of which are sought as seafood. Since 2015, TTX has been reported in bivalve shellfish from several estuarine locations along the Mediterranean and European Atlantic coasts, posing an emerging food safety concern. Although reports on spatial and temporal distribution have increased in recent years, processes leading to TTX accumulation in European bivalves are yet to be described. Here, we explored the hypothesis that the ribbon worm species Cephalothrix simula, known to contain high levels of TTX, could play a role in the trophic transfer of the toxin into shellfish. During a field study at a single location in southern England, we confirmed C. simula DNA in seawater adjacent to trestle-farmed Pacific oysters Magallana gigas (formerly Crassostrea gigas) with a history of TTX occurrence. C. simula DNA in seawater was significantly higher in June and July during the active phase of toxin accumulation compared to periods of either no or continually decreasing TTX concentrations in M. gigas. In addition, C. simula DNA was detected in oyster digestive glands collected on 15 June 2021, the day with the highest recorded C. simula DNA abundance in seawater. These findings show evidence of a relationship between C. simula and TTX occurrence, providing support for the hypothesis that bivalves may acquire TTX through filter-feeding on microscopic life forms of C. simula present in the water column at particular periods each year. Although further evidence is needed to confirm such feeding activity, this study significantly contributes to discussions about the biological source of TTX in European bivalve shellfish.
Marine Staurosporine Analogues: Activity and Target Identification in Triple-Negative Breast Cancer
Authors: Chen Ru-Yi , Ding Li-Jian , Liu Yan-Jun , Shi Jin-Jin , Yu Jing , Li Chang-Yun , Lu Jian-Fei , Yang Guan-Jun , Chen Jiong
Published: October 2024

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with high mortality and drug resistance and no targeted drug available at present. Compound 4, a staurosporine alkaloid derived from Streptomyces sp. NBU3142 in a marine sponge, exhibits potent anti-TNBC activity. This research investigated its impact on MDA-MB-231 cells and their drug-resistant variants. The findings highlighted that compound 4 inhibits breast cancer cell migration, induces apoptosis, arrests the cell cycle, and promotes cellular senescence in both regular and paclitaxel-resistant MDA-MB-231 cells. Additionally, this study identified mitogen-activated protein kinase kinase kinase 11 (MAP3K11) as a target of compound 4, implicating its role in breast tumorigenesis by affecting cell proliferation, migration, and cell cycle progression.
The Antioxidant Effects of Trypsin-Hydrolysate Derived from Abalone Viscera and Fishery By-Products, and the Angiotensin-I Converting Enzyme (ACE) Inhibitory Activity of Its Purified Bioactive Peptides
Authors: Heo Jun-Ho , Kim Eun-A , Kang Nalae , Heo Seong-Yeong , Ahn Ginnae , Heo Soo-Jin
Published: October 2024

Abalone is a rich source of nutrition, the viscera of which are discarded as by-product during processing. This study explored the biological activities of peptides derived from abalone viscera (AV). Trypsin-hydrolysate of AV (TAV) was purified into three fractions using a Sephadex G-10 column. Nine bioactive peptides (VAR, NYER, LGPY, VTPGLQY, QFPVGR, LGEW, QLQFPVGR, LDW, and NLGEW) derived from TAV-F2 were sequenced. LGPY, VTPGLQY, LGEW, LDW, and NLGEW exhibited antioxidant properties, with IC50 values of 0.213, 0.297, 0.289, 0.363, and 0.303 mg/mL, respectively. In vitro analysis determined that the peptides VAR, NYER, VTPGLQY, QFPVGR, LGEW, QLQFPVGR, and NLGEW inhibited ACE, with IC50 values of 0.104, 0.107, 0.023, 0.023, 0.165, 0.004, and 0.146 mg/mL, respectively. The binding interactions of ACE-bioactive peptide complexes were investigated using docking analysis with the ZDCOK server. VTPGLQT interacted with HIS513 and TYR523, and QLQFPVGR interacted with HIS353, ALA354, GLU384, HIS513, and TYR523, contributing to the inhibition of ACE activity. They also interacted with amino acids that contribute to stability by binding to zinc ions. QFPVGR may form complexes with ACE surface sites, suggesting indirect inhibition. These results indicate that AV is a potential source of bioactive peptides with dual antioxidant and anti-hypertensive dual effects.
One-Step Cannulation and Distance Measurement during Aortic Branched Endograft Repair: The Neuron Catheter Trick
Authors: Simonte Gioele , Fino Gianluigi , Parlani Gianbattista , Simonte Rachele , Isernia Giacomo
Published: October 2024

Purpose: This paper aims to describe a straightforward, efficient, and reliable technique to simplify cannulation maneuvers during aortic branched endograft repair. Technique: The suggested approach utilizes the Penumbra Neuron Select catheter, which combines diagnostic, sizing, and support capabilities in one. This has the potential to reduce procedural time and minimize the need for serial catheter and guidewire exchanges. Conclusions: The proposed technique offers a simple yet effective tool to mitigate the risk of vessel loss and injury, and to streamline complex aortic repair procedures.
Sandwich-Type Electrochemical Aptasensor with Supramolecular Architecture for Prostate-Specific Antigen
Authors: Villalonga Anabel , Díaz Raúl , Ojeda Irene , Sánchez Alfredo , Mayol Beatriz , Martínez-Ruiz Paloma , Villalonga Reynaldo , Vilela Diana
Published: October 2024

A novel sandwich-type electrochemical aptasensor based on supramolecularly immobilized affinity bioreceptor was prepared via host–guest interactions. This method utilizes an adamantane-modified, target-responsive hairpin DNA aptamer as a capture molecular receptor, along with a perthiolated β-cyclodextrin (CD) covalently attached to a gold-modified electrode surface as the transduction element. The proposed sensing strategy employed an enzyme-modified aptamer as the signalling element to develop a sandwich-type aptasensor for detecting prostate-specific antigen (PSA). To achieve this, screen-printed carbon electrodes (SPCEs) with electrodeposited reduced graphene oxide (RGO) and gold nanoferns (AuNFs) were modified with the CD derivative to subsequently anchor the adamantane-modified anti-PSA aptamer via supramolecular associations. The sensing mechanism involves the affinity recognition of PSA molecules on the aptamer-enriched electrode surface, followed by the binding of an anti-PSA aptamer–horseradish peroxidase complex as a labelling element. This sandwich-type arrangement produces an analytical signal upon the addition of H2O2 and hydroquinone as enzyme substrates. The aptasensor successfully detected the biomarker within a concentration range of 0.5 ng/mL to 50 ng/mL, exhibiting high selectivity and a detection limit of 0.11 ng/mL in PBS.
Structural and Dynamical Effects of the CaO/SrO Substitution in Bioactive Glasses
Authors: Fabian Margit , Krzystyniak Matthew , Khanna Atul , Kovacs Zsolt
Published: October 2024

Silicate glasses containing silicon, sodium, phosphorous, and calcium have the ability to promote bone regeneration and biodegrade as new tissue is generated. Recently, it has been suggested that adding SrO can benefit tissue growth and silicate glass dissolution. Motivated by these recent developments, the effect of SrO/CaO–CaO/SrO substitution on the local structure and dynamics of Si-Na-P-Ca-O oxide glasses has been studied in this work. Differential thermal analysis has been performed to determine the thermal stability of the glasses after the addition of strontium. The local structure has been studied by neutron diffraction augmented by Reverse Monte Carlo simulation, and the local dynamics by neutron Compton scattering and Raman spectroscopy. Differential thermal analysis has shown that SrO-containing glasses have lower glass transition, melting, and crystallisation temperatures. Moreover, the addition of the Sr2+ ions decreased the thermal stability of the glass structure. The total neutron diffraction augmented by the RMC simulation revealed that Sr played a similar role as Ca in the glass structure when substituted on a molar basis. The bond length and the coordination number distributions of the network modifiers and network formers did not change when SrO (x = 0.125, 0.25) was substituted for CaO (25-x). However, the network connectivity increased in glass with 12.5 mol% CaO due to the increased length of the Si-O-Si interconnected chain. The analysis of Raman spectra revealed that substituting CaO with SrO in the glass structure dramatically enhances the intensity of the high-frequency band of 1110–2000 cm−1. For all glasses under investigation, the changes in the relative intensities of Raman bands and the distributions of the bond lengths and coordination numbers upon the SrO substitution were correlated with the values of the widths of nuclear momentum distributions of Si, Na, P, Ca, O, and Sr. The widths of nuclear momentum distributions were observed to soften compared to the values observed and simulated in their parent metal-oxide crystals. The widths of nuclear momentum distributions, obtained from fitting the experimental data to neutron Compton spectra, were related to the amount of disorder of effective force constants acting on individual atomic species in the glasses.
Exploration of Specific Fluoroquinolone Interaction with SARS-CoV-2 Main Protease (Mpro) to Battle COVID-19: DFT, Molecular Docking, ADME and Cardiotoxicity Studies
Authors: Khan Muhammad Asim , Mutahir Sadaf , Tariq Muhammad Atif , Almehizia Abdulrahman A.
Published: October 2024

Herein, the pharmacokinetic profiles, binding interactions, and molecular properties of fluoroquinolone derivatives as prospective antiviral drugs are examined using a combination of docking, ADME, and DFT simulations. The effectiveness of the ligands is compared with the clinically tested and FDA-authorized medicine remdesivir. The findings demonstrated encouraging binding energies, indicating possible inhibitory effectiveness against SARS-CoV-2 Mpro. The fluoroquinolone derivatives also exhibit promising ADME characteristics, although compounds 5, 6, 9, 12–20 possess poor values, suggesting that oral administration may be possible. The potential of the selected compounds as SARS-CoV-2 Mpro inhibitors is thoroughly understood because of the integrated analysis of DFT, with compound 11 demonstrating the highest energy gap of 0.2604 eV of, docking with viral targets with docking scores of −7.9 to −5.9 kcal/mol, with compound 18 demonstrating the highest docking score, which is at the 13th position in energy difference in the DFT data. Their favorable electrical properties, robust binding interactions with viral targets, and attractive pharmacokinetic profiles boost their potential as prospective study subjects. These substances have the potential to be transformed into cutting-edge antiviral therapies that specifically target SARS-CoV-2 Mpro and related coronaviruses.
Effect of Roasting Level on the Development of Key Aroma-Active Compounds in Coffee
Authors: Obando Andrea M. , Figueroa Jorge G.
Published: October 2024

Coffee roasting is considered the most critical process in the development of sensory characteristics. During this stage, a substantial number of compounds are generated. Nevertheless, only a limited number of these compounds are responsible for the aroma, referred to as key aroma-active compounds. This study aimed to assess the impact of roasting levels on the formation of these compounds. Coffee was roasted at four different levels: very light (RL85), light (RL75), medium (RL55), and extremely dark (RL25), according to the Specialty Coffee Association (SCA) guidelines. The extraction, olfactory evaluation, and identification of compounds were performed using solid-phase microextraction (SPME), gas chromatography–olfactometry (GC-O), and gas chromatography–mass spectrometry (GC-MS), respectively. A total of 74 compounds were successfully identified, of which 25 were classified as aroma-active compounds. RL75 and RL85 displayed similar aromatic profiles. RL55 was characterized by pleasant notes such as sweet, toasted hazelnut, and caramel. In contrast, RL25 was marked by undesirable odors including burnt notes, putrid, and sulfurous scents. This study is the first to identify key odorant compounds in coffee based on SCA roasting standards.
Research Progress on the Mechanisms of Protocatechuic Acid in the Treatment of Cognitive Impairment
Authors: Liang Shuzhi , Zhao Zhongmin , Liu Leilei , Zhang Yan , Liu Xijian
Published: October 2024

Cognitive impairment (CI) is a type of mental health disorder that mainly affects cognitive abilities, such as learning, memory, perception, and problem-solving. Currently, in clinical practice, the treatment of cognitive impairment mainly focuses on the application of cholinesterase inhibitors and NMDA receptor antagonists; however, there is no specific and effective drug yet. Procatechuic acid (PCA) possesses various functions, including antibacterial, antiasthmatic, and expectorant effects. In recent years, it has received growing attention in the cognitive domain. Therefore, by summarizing the mechanisms of action of procatechuic acid in the treatment of cognitive impairment in this paper, it is found that procatechuic acid has multiple effects, such as regulating the expression of neuroprotective factors, inhibiting cell apoptosis, promoting the autophagy-lysosome pathway, suppressing oxidative stress damage, inhibiting inflammatory responses, improving synaptic plasticity dysfunction, inhibiting Aβ deposition, reducing APP hydrolysis, enhancing the cholinergic system, and inhibiting the excitotoxicity of neuronal cells. The involved signaling pathways include activating Pi3K-akt-mTor and inhibiting JNK, P38 MAPK, P38-ERK-JNK, SIRT1, and NF-κB/p53, etc. This paper aims to present the latest progress in research on procatechuic acid, including aspects such as its chemical properties, sources, pharmacokinetics, mechanisms for treating neurodegenerative diseases.
Regulatory Effects of Chlormequat Chloride on the Yield and Chemical Composition of Angelica sinensis Radix
Authors: Qin Honghan , Xu Juan , Ma Xiaojun , Wei Rongchang , Luo Zuliang
Published: October 2024

Chlormequat chloride (CCC), as a commonly used plant growth regulator in the production of rhizomatous medicinal herbs, can effectively control the bolting phenomenon in Angelica sinensis, significantly increasing the yield of underground rhizomes (medicinal part). However, its specific effects on the intrinsic quality of Angelica sinensis, especially medicinal components, require further investigation. The objective of this study is to conduct a thorough examination of CCC residue and its influence on the yield and medicinal components of Angelica sinensis. By spraying different concentrations of CCC on Angelica sinensis, we systematically monitored the final yield of Angelica sinensis Radix (ASR) in each treatment group and the residual concentration of CCC in ASR. Using UPLC-QTOF-MS technology, we conducted an in-depth analysis of the metabolic profile of ASR. Subsequently, UFLC-MS/MS was employed to accurately quantify the changes in the content of nine key active components in ASR. The results of this study indicate that the application of CCC significantly improves the yield of ASR, with the best effect observed at 0.1 g/L, resulting in a yield increase of 24.8%. Meanwhile, the residual amount of CCC in ASR is positively correlated with the application concentration, with the residual levels as high as 7.12 mg/kg in the high-concentration treatment group. Metabolomic analysis preliminarily identified 21 chemical components in ASR, including four organic acids and 13 phthalides. It is worth noting that the quantitative analysis results indicate significant changes in active components such as butylphthalide, Z-ligustilide, and ferulic acid after the application of CCC. Specifically, high-concentration CCC significantly increased the content of butylphthalide and levistolide A, while low-concentration CCC significantly promoted the accumulation of coniferyl ferulate and senkyunolide A, accompanied by a significant decrease in Z-ligustilide and ferulic acidy. In conclusion, while CCC use can increase yield, the associated increase in residues and imbalanced composition ratios may threaten the quality and safety of ASR. Therefore, it is crucial to control the amount of CCC used rationally to balance yield enhancement and quality assurance.
Updated Risk Assessment of Cannabidiol in Foods Based on Benchmark Dose–Response Modeling
Authors: Wisotzki Eva , Franke Heike , Sproll Constanze , Walch Stephan G. , Lachenmeier Dirk W.
Published: October 2024

Cannabidiol (CBD), a non-psychotropic main component of the Cannabis plant, has been approved as a drug in the European Union (EU) under the name “Epidyolex”. However, its approval process as a food ingredient under the Novel Food Regulation was paused by the European Food Safety Authority (EFSA) due to a lack of safety data. Nevertheless, there is a growing, unregulated market in which CBD is advertised with various health claims and dosage instructions. Of particular concern is its toxic effect on the liver and possible reproductive toxicity in humans. Studies suitable for calculating the benchmark dose were identified from the available data. Animal studies yielded a benchmark dose lower confidence limit (BMDL) of 43 mg/kg bw/day, which translates into a safe human dose of approximately 15 mg/day. Only the Lowest-Observed-Adverse-Effect Level (LOAEL) of 4.3 mg/kg bw/day could be identified from the human data. This updated risk assessment confirmed a health-based guidance value (HBGV) of 10 mg/day based on human LOAEL. Despite the existing data gaps, preliminary regulation appears advisable because the current form of the gray CBD market is unacceptable from the standpoint of consumer safety and protection.
Ecotoxicity and Mutagenicity Assessment of Novel Antifungal Agents VT-1161 and T-2307
Authors: Padilla Suarez Edith Guadalupe , Siciliano Antonietta , Spampinato Marisa , Maione Angela , Guida Marco , Libralato Giovanni , Galdiero Emilia
Published: October 2024

Antifungal substances are essential for managing fungal infections in humans, animals, and plants, and their usage has significantly increased due to the global rise in fungal infections. However, the extensive application of antifungal agents in pharmaceuticals, personal care products, and agriculture has led to their widespread environmental dissemination through various pathways, such as excretion, improper disposal, and agricultural runoff. Despite advances in wastewater treatment, many antifungal compounds persist in the environment, affecting non-target organisms and contributing to resistance development. This study investigates the environmental impact of two novel antifungal agents, VT-1161 and T-2307, recently introduced as alternatives for treating resistant Candida spp. We assessed their ecotoxicity and mutagenicity using multiple bioassays: immobilization of Daphnia magna, growth inhibition of Raphidocelis subcapitata, luminescence inhibition of Aliivibrio fischeri, and mutagenicity on Salmonella typhimurium strain TA100. Results indicate that both VT-1161 and T-2307 exhibit lower toxicity compared to existing antifungal compounds, with effective concentrations (EC50) causing 50% response ranging from 14.34 to 27.92 mg L−1. Furthermore, both agents were classified as less hazardous based on the Globally Harmonized System of Classification and Labeling of Chemicals. Despite these favorable results, further research is needed to understand their environmental behavior, interactions, and potential resistance development among non-target species. Our findings highlight the importance of comprehensive environmental risk assessments to ensure the sustainable use of new antifungal agents.
Biofortification of Mushrooms: A Promising Approach
Authors: Słyszyk Klaudia , Siwulski Marek , Wiater Adrian , Tomczyk Michał , Waśko Adam
Published: October 2024

Mushrooms exhibit a broad spectrum of pharmacological activities and are widely used for medical purposes and in nutrition. Numerous bioactive metabolites are responsible for these activities. Their distribution and biological effects differ depending on the fungal species and their chemical composition. Biofortification is a sustainable process that aims to improve the nutritional profile of food crops, as most of them are low in key nutrients. This review aims to delve into the process of fungal biofortification and review the most commonly used elements and species. Through biofortification, it is possible to combat hidden hunger, which affects as many as 2 billion people worldwide. “Hidden hunger” is a phenomenon in which the organism lacks the minerals and vitamins needed for development, growth, and good overall health. Mushrooms are increasingly being considered for biofortification due to their ability to accumulate various elements (both micro- and macroelements).
Authenticity and Divine Accommodation in a 19 Century Māori Context
Authors: Haami Bradford Joseph
Published: October 2024

How did early 19th Century Māori assess the authenticity of the gospel narrative based on their own traditional worldview? This essay explores the thoughts of Whangataua, an ancestor of the author from the Ngāi Tahu and Rangitāne tribes of the upper Manawatū River region in the North Island of New Zealand. How might Whangataua and his contemporaries have negotiated the authenticity of the gospel narrative shared by the missionary William Colenso between 1846 and 1852? This paper explores the cultural and intellectual negotiation that took place when Māori first heard the gospel message by comparing the story of the virgin birth of Jesus from the book of Luke with the traditional narrative of Tamatea-ure-haea and his wife Iwipupu. The intersection between the virgin conception narrative and Māori tribal beliefs held by 19th Century rangatira (principal chiefs) reveals an overlapping of realities where Māori worldview could become an agent of divine accommodation and authenticity for the gospel narratives.
Unbinding Genesis 3:16: A Theocentric Critique of Sex-Based Power
Authors: Drew Arlyn S.
Published: October 2024

The judgment of Eve in Genesis 3:16 has traditionally been construed as an etiological curse on the relationship dynamics between genders, garnering scholarly scrutiny on the terms for desire and rule. Many exegetes regard this verse as the biblical rationale for patriarchal cultures throughout history. Despite attempts to ameliorate the notion of husbandly rule to protectorship, guidance, and loving servant-leadership, the power asymmetry between genders hinges on the interpretation of a simple Hebrew preposition be, commonly translated as “over” at the end of Genesis 3:16 as “he shall rule over you”. This article re-examines the semantics of the linguistic pairing of the particular ruling verb māšal followed by the preposition be through three verses in close proximity: Genesis 1:18, Genesis 3:16, and Genesis 4:7. Given the contextual sensitivity inherent in flexible prepositions, a theocentric reinterpretation of the surrounding narrative opens the possibility for a new redemptive reading by rendering the preposition as “with,” a meaning well within its semantic spectrum. In that case, to a woman hurt by betrayals from the animal, botanical, and human realms of her new existence, God promises help in healing her damaged marriage by intensifying her emotional desire for her husband, then chiding Eve to include him in her future decisions: “and he must rule with you”.
Is an Ambulatory Biofeedback Device More Effective than Instructing Partial Weight-Bearing Using a Bathroom Scale? Results of a Randomized Controlled Trial with Healthy Subjects
Authors: Merkle Tobias Peter , Hofmann Nina , Knop Christian , Da Silva Tomas
Published: October 2024

So far, there have been no high-quality studies examining the efficacy of outpatient biofeedback devices in cases of prescribed partial weight-bearing, such as after surgery on the lower limbs. This study aimed to assess whether a biofeedback device is more effective than using a personal scale. Two groups of healthy individuals wearing an insole orthosis were trained to achieve partial loading in a three-point gait within a target zone of 15–30 kg during overground walking and going up and down stairs. The treatment group (20 women and 22 men) received continuous biofeedback, while the control group (26 women and 16 men) received no information. Findings were compared in a randomized controlled trial. Compliance with partial loading without biofeedback was poor; on level ground and stairs, only one in two steps fell within the target area, and overloading occurred on at least one in three steps. The treatment group reduced the percentage of steps taken in the overload zone to ≤8.4% (p < 0.001 across all three courses) and achieved more than two-thirds of their steps within the target zone (p < 0.001 on level ground, p = 0.008 upstairs, and p = 0.028 downstairs). In contrast, the control group did not demonstrate any significant differences in the target zone (p = 0.571 on level ground, p = 0.332 upstairs, and p = 0.392 downstairs). In terms of maintaining partial load, outpatient biofeedback systems outperform bathroom scales.
Validity and Concordance of a Linear Position Transducer (Vitruve) for Measuring Movement Velocity during Resistance Training
Authors: González-Galán Jaime , Herrera-Bermudo José Carlos , González-Badillo Juan José , Rodríguez-Rosell David
Published: October 2024

This study aimed to analyze the intra-device agreement of a new linear position transducer (Vitruve, VT) and the inter-device agreement with a previously validated linear velocity transducer (T-Force System, TF) in different range of velocities. A group of 50 healthy, physically active men performed a progressive loading test during a bench press (BP) and full-squat (SQ) exercise with a simultaneous recording of two VT and one TF devices. The mean propulsive velocity (MPV) and peak of velocity (PV) were recorded for subsequent analysis. A set of statistics was used to determine the degree of agreement (Intraclass correlation coefficient [ICC], Lin’s concordance correlation coefficient [CCC], mean square deviation [MSD], and variance of the difference between measurements [VMD]) and the error magnitude (standard error of measurement [SEM], smallest detectable change [SDC], and maximum errors [ME]) between devices. The established velocity ranges were as follows: >1.20 m·s−1; 1.20–0.95 m·s−1; 0.95–0.70 m·s−1; 0.70–0.45 m·s−1; ≤0.45 m·s−1 for BP; and >1.50 m·s−1; 1.50–1.25 m·s−1; 1.25–1.00 m·s−1; 1.00–0.75 m·s−1; and ≤0.75 m·s−1 for SQ. For the MPV, the VT system showed high intra- and inter-device agreement and moderate error magnitude with pooled data in both exercises. However, the level of agreement decreased (ICC: 0.790–0.996; CCC: 0.663–0.992) and the error increased (ME: 2.8–13.4% 1RM; SEM: 0.035–0.01 m·s−1) as the velocity range increased. For the PV, the magnitude of error was very high in both exercises. In conclusion, our results suggest that the VT system should only be used at MPVs below 0.45 m·s−1 for BP and 0.75 m·s−1 for SQ in order to obtain an accurate and reliable measurement, preferably using the MPV variable instead of the PV. Therefore, it appears that the VT system may not be appropriate for objectively monitoring resistance training and assessing strength performance along the entire spectrum of load-velocity curve.
Characterizing and Implementing the Hamamatsu C12880MA Mini-Spectrometer for Near-Surface Reflectance Measurements of Inland Waters
Authors: Jechow Andreas , Bumberger Jan , Palm Bert , Remmler Paul , Schreck Günter , Ogashawara Igor , Kiel Christine , Kohnert Katrin , Grossart Hans-Peter , Singer Gabriel A. , Nejstgaard Jens C. , Wollrab Sabine , Berger Stella A. , Hölker Franz
Published: October 2024

In recent decades, inland water remote sensing has seen growing interest and very strong development. This includes improved spatial resolution, increased revisiting times, advanced multispectral sensors and recently even hyperspectral sensors. However, inland waters are more challenging than oceanic waters due to their higher complexity of optically active constituents and stronger adjacency effects due to their small size and nearby vegetation and built structures. Thus, bio-optical modeling of inland waters requires higher ground-truthing efforts. Large-scale ground-based sensor networks that are robust, self-sufficient, non-maintenance-intensive and low-cost could assist this otherwise labor-intensive task. Furthermore, most existing sensor systems are rather expensive, precluding their employability. Recently, low-cost mini-spectrometers have become widely available, which could potentially solve this issue. In this study, we analyze the characteristics of such a mini-spectrometer, the Hamamatsu C12880MA, and test it regarding its application in measuring water-leaving radiance near the surface. Overall, the measurements performed in the laboratory and in the field show that the system is very suitable for the targeted application.
PointCloud-At: Point Cloud Convolutional Neural Networks with Attention for 3D Data Processing
Authors: Umar Saidu , Taherkhani Aboozar
Published: October 2024

The rapid growth in technologies for 3D sensors has made point cloud data increasingly available in different applications such as autonomous driving, robotics, and virtual and augmented reality. This raises a growing need for deep learning methods to process the data. Point clouds are difficult to be used directly as inputs in several deep learning techniques. The difficulty is raised by the unstructured and unordered nature of the point cloud data. So, machine learning models built for images or videos cannot be used directly on point cloud data. Although the research in the field of point clouds has gained high attention and different methods have been developed over the decade, very few research works directly with point cloud data, and most of them convert the point cloud data into 2D images or voxels by performing some pre-processing that causes information loss. Methods that directly work on point clouds are in the early stage and this affects the performance and accuracy of the models. Advanced techniques in classical convolutional neural networks, such as the attention mechanism, need to be transferred to the methods directly working with point clouds. In this research, an attention mechanism is proposed to be added to deep convolutional neural networks that process point clouds directly. The attention module was proposed based on specific pooling operations which are designed to be applied directly to point clouds to extract vital information from the point clouds. Segmentation of the ShapeNet dataset was performed to evaluate the method. The mean intersection over union (mIoU) score of the proposed framework was increased after applying the attention method compared to a base state-of-the-art framework that does not have the attention mechanism.
A Time–Frequency Domain Analysis Method for Variable Frequency Hopping Signal
Authors: Zeng Zhengzhi , Jiang Chunshan , Zhou Yuanming , Zhou Tianwei
Published: October 2024

A variable frequency hopping (VFH) signal is a kind of frequency hopping (FH) signal that varies both in frequency and dwell time. However, in radio surveillance, the existing methods for unidentified signals using VFH cannot be effectively handled. In this paper, we proposed an improved joint analysis method based on time–frequency domain features, which adopts multi-level processing to solve the time–frequency domain feature analysis problem of the VFH signal. First, the received signal is pre-processed by Short-Time Fourier Transform (STFT) and binarization, and a highly discriminative time–frequency image is obtained; then, the fixed frequency signal is removed based on the feature of connected domains, and the conventional frequency hopping (CFH) signal is removed by density-based spatial clustering of applications with noise (DBSCAN); finally, the overlapping region is cropped by the joint energy peak time–domain continuity properties. After the above multi-level joint processing method, the problem of VFH signal processing is effectively solved. The simulation result shows that the Mean Square Error (MSE) between the output results and the time–frequency image of the original VFH signal tends to be close to 0 when the Signal-to-Noise ratio (SNR) is 5 dB.
Investigating the Internal Deterioration of the Auriga Statue of Mozia Island, Sicily, through Ultrasonic and Ground-Penetrating Radar Studies
Authors: Capizzi Patrizia , Martorana Raffaele , Carollo Alessandra
Published: October 2024

The Greek marble statue of the Auriga of Mozia Island, in Sicily, is the most important artwork displayed at the Whitaker Foundation Archaeological Museum. It underwent geophysical investigations twice, in 2012 and 2021, to assess the marble’s degradation. The 2012 investigation prepared the statue for transfer to the Paul Getty Museum in New York and repositioning on an anti-seismic pedestal. The 2021 investigation evaluated potential new damage before another transfer. Both investigations utilized 3D ultrasonic tomography (UST) to detect degraded marble areas and ground-penetrating radar (GPR) to identify internal discontinuities, such as fractures or lesions, and locate metal pins that were previously inserted to reassemble the statue and its pedestal. Results from the UST indicate an average marble velocity of approximately 4700 m/s, suggesting good mechanical strength, with some areas showing lower velocities (~3000 m/s) within the material’s variability range. The GPR profiles demonstrated internal signal homogeneity, excluding internal fracture surfaces or lesions, and confirmed the presence of metallic pins. This study highlights the effectiveness of integrating UST and GPR for non-invasive diagnostics of marble sculptures, providing detailed insights into the marble’s condition and identifying hidden defects or damage.
Indirect Thermographic Measurement of the Temperature of a Transistor Die during Pulse Operation
Authors: Hulewicz Arkadiusz , Dziarski Krzysztof , Drużyński Łukasz
Published: October 2024

This paper presents aspects related to the indirect thermographic measurement of a C2M0280120D transistor in pulse mode. The tested transistor was made on the basis of silicon carbide and is commonly used in many applications. During the research, the pulse frequency was varied from 1 kHz to 800 kHz. The transistor case temperature was measured using a Flir E50 thermographic camera and a Pt1000 sensor. The transistor die temperature was determined based on the voltage drop on the body diode and the known characteristics between the voltage drop on the diode and the temperature of the die. The research was carried out in accordance with the presented measuring standards and maintaining the described conditions. The differences between the transistor case temperature and the transistor die temperature were also determined based on simulation work performed in Solidworks 2020 SP05. For this purpose, a three-dimensional model of the C2M0280120D transistor was created and the materials used in this model were selected; the methodology for selecting the model parameters is discussed. The largest recorded difference between the case temperature and the junction temperature was 27.3 °C. The use of a thermographic camera allows the transistor’s temperature to be determined without the risk of electric shock. As a result, it will be possible to control the C2M0280120D transistor in such a way so as not to damage it and to optimally select its operating point.
Time Series Prediction of Gas Emission in Coal Mining Face Based on Optimized Variational Mode Decomposition and SSA-LSTM
Authors: Zhang Jingzhao , Cui Yuxin , Yan Zhenguo , Huang Yuxin , Zhang Chenyu , Zhang Jinlong , Guo Jiantao , Zhao Fei
Published: October 2024

The accurate prediction of gas emissions has important guiding significance for the prevention and control of gas disasters in order to further improve the prediction accuracy of gas emissions in the mining face. According to the absolute gas emission monitoring data of the 1417 working face in a coal mine in Shaanxi Province, a GA-VMD-SSA-LSTM gas emission prediction model (GVSL) based on genetic algorithm (GA)-optimized variational mode decomposition (VMD) and sparrow search algorithm (SSA)-optimized long short-term memory (LSTM) is proposed. Firstly, a VMD evaluation standard for evaluating the amount of decomposition loss is proposed. Under this standard, the GA is used to find the optimal parameters of the VMD. Then, the SSA is used to optimize the key parameters of the LSTM to establish a GVSL prediction model. The model predicts each component and finally superimposes the prediction results for each component to obtain the final gas emission result. The results show that the accuracy of the evaluation indexes of the GVSL model and VMD-LSTM model, as well as the SSA-LSTM model and Gaussian process regression (GPR) model, are compared and analyzed horizontally and vertically under three scenarios with prediction sets of 121,94 and 57 groups. The GVSL model has the best prediction effect, and its fitting degree R2 values are 0.95, 0.96, and 0.99, which confirms the effectiveness of the proposed GVSL model for the time series prediction of gas emission in the mining face.
Tools, Technologies and Frameworks for Digital Twins in the Oil and Gas Industry: An In-Depth Analysis
Authors: Meza Edwin Benito Mitacc , Souza Dalton Garcia Borges de , Copetti Alessandro , Sobral Ana Paula Barbosa , Silva Guido Vaz , Tammela Iara , Cardoso Rodolfo
Published: October 2024

The digital twin (DT), which involves creating a virtual replica of a physical asset or system, has emerged as a transformative set of tools across various industries. In the oil and gas (O&G) industry, the development of DTs represents a significant evolution in how companies manage complex operations, enhance safety, and optimize decision-making processes. Despite these significant advancements, the underlying tools, technologies, and frameworks for developing DTs in O&G applications remain non-standardized and unfamiliar to many O&G practitioners, highlighting the need for a systematic literature review (SLR) on the topic. Thus, this paper offers an SLR of the existing literature on DT development for O&G from 2018 onwards, utilizing Scopus and Web of Science Core Collection. We provide a comprehensive overview of this field, demonstrate how it is evolving, and highlight standard practices and research opportunities in the area. We perform broad classifications of the 98 studies, categorizing the DTs by their development methodologies, implementation objectives, data acquisition, asset digital development, data integration and preprocessing, data analysis and modeling, evaluation and validation, and deployment tools. We also include a bibliometric analysis of the selected papers, highlighting trends and key contributors. Given the increasing number of new DT developments in O&G and the many new technologies available, we hope to provide guidance on the topic and promote knowledge production and growth concerning the development of DTs for O&G.
An Ontology-Based Vehicle Behavior Prediction Method Incorporating Vehicle Light Signal Detection
Authors: Xu Xiaolong , Shi Xiaolin , Chen Yun , Wu Xu
Published: October 2024

Although deep learning techniques have potential in vehicle behavior prediction, it is difficult to integrate traffic rules and environmental information. Moreover, its black-box nature leads to an opaque and difficult-to-interpret prediction process, limiting its acceptance in practical applications. In contrast, ontology reasoning, which can utilize human domain knowledge and mimic human reasoning, can provide reliable explanations for the speculative results. To address the limitations of the above deep learning methods in the field of vehicle behavior prediction, this paper proposes a front vehicle behavior prediction method that combines deep learning techniques with ontology reasoning. Specifically, YOLOv5s is first selected as the base model for recognizing the brake light status of vehicles. In order to further enhance the performance of the model in complex scenes and small target recognition, the Convolutional Block Attention Module (CBAM) is introduced. In addition, so as to balance the feature information of different scales more efficiently, a weighted bi-directional feature pyramid network (BIFPN) is introduced to replace the original PANet structure in YOLOv5s. Next, using a four-lane intersection as an application scenario, multiple factors affecting vehicle behavior are analyzed. Based on these factors, an ontology model for predicting front vehicle behavior is constructed. Finally, for the purpose of validating the effectiveness of the proposed method, we make our own brake light detection dataset. The accuracy and mAP@0.5 of the improved model on the self-made dataset are 3.9% and 2.5% higher than that of the original model, respectively. Afterwards, representative validation scenarios were selected for inference experiments. The ontology model created in this paper accurately reasoned out the behavior that the target vehicle would slow down until stopping and turning left. The reasonableness and practicality of the front vehicle behavior prediction method constructed in this paper are verified.
Research on Pipeline Stress Detection Method Based on Double Magnetic Coupling Technology
Authors: Wang Guoqing , Xia Qi , Yan Hong , Bei Shicheng , Zhang Huakai , Geng Hao , Zhao Yuhan
Published: October 2024

Oil and gas pipelines are subject to soil corrosion and medium pressure factors, resulting in stress concentration and pipe rupture and explosion. Non-destructive testing technology can identify the stress concentration and defect corrosion area of the pipeline to ensure the safety of pipeline transportation. In view of the problem that the traditional pipeline inspection cannot identify the stress signal at the defect, this paper proposes a detection method using strong and weak magnetic coupling technology. Based on the traditional J-A (Jiles–Atherton) model, the pinning coefficient is optimized and the stress demagnetization factor is added to establish the defect of the ferromagnetic material. The force-magnetic relationship optimization model is used to calculate the best detection magnetic field strength. The force-magnetic coupling simulation of Q235 steel material is carried out by ANSYS 2019 R1 software based on the improved J-A force-magnetic model. The results show that the effect of the stress on the pipe on the magnetic induction increases first and then decreases with the increase in the excitation magnetic field strength, and the magnetic signal has the maximum proportion of the stress signal during the excitation process; the magnetic induction at the pipe defect increases linearly with the increase in the stress trend. Through the strong and weak magnetic scanning detection of cracked pipeline materials, the correctness of the theoretical analysis and the validity of the engineering application of the strong and weak magnetic detection method are verified.
Integrating Automated Labeling Framework for Enhancing Deep Learning Models to Count Corn Plants Using UAS Imagery
Authors: Katari Sushma , Venkatesh Sandeep , Stewart Christopher , Khanal Sami
Published: October 2024

Plant counting is a critical aspect of crop management, providing farmers with valuable insights into seed germination success and within-field variation in crop population density, both of which are key indicators of crop yield and quality. Recent advancements in Unmanned Aerial System (UAS) technology, coupled with deep learning techniques, have facilitated the development of automated plant counting methods. Various computer vision models based on UAS images are available for detecting and classifying crop plants. However, their accuracy relies largely on the availability of substantial manually labeled training datasets. The objective of this study was to develop a robust corn counting model by developing and integrating an automatic image annotation framework. This study used high-spatial-resolution images collected with a DJI Mavic Pro 2 at the V2–V4 growth stage of corn plants from a field in Wooster, Ohio. The automated image annotation process involved extracting corn rows and applying image enhancement techniques to automatically annotate images as either corn or non-corn, resulting in 80% accuracy in identifying corn plants. The accuracy of corn stand identification was further improved by training four deep learning (DL) models, including InceptionV3, VGG16, VGG19, and Vision Transformer (ViT), with annotated images across various datasets. Notably, VGG16 outperformed the other three models, achieving an F1 score of 0.955. When the corn counts were compared to ground truth data across five test regions, VGG achieved an R2 of 0.94 and an RMSE of 9.95. The integration of an automated image annotation process into the training of the DL models provided notable benefits in terms of model scaling and consistency. The developed framework can efficiently manage large-scale data generation, streamlining the process for the rapid development and deployment of corn counting DL models.
Expanding the Accessible Forest Areas by Improving Forest Road Standards and Utilizing Mobile Fire-fighting Teams
Authors: Kasap Caner Yavuz , Akay Abdullah Emin , Arıcak Burak , Bilici Ebru , Uçar Zennure , Erkan Neşat , Güney Coşkun Okan
Published: October 2024

In Turkiye, insufficient technical standards of the forest roads limit the speed of the fire truck, leading to increase in the arrival time of the initial response team to the fire areas. Improving forest road standards will increase the design speed and expand the accessible forest areas within the critical response time. In this study, the effect of improving forest road standards on expanding accessible forest areas was investigated. Considering the forest areas in Antalya Forestry Regional Directorate in Turkiye, accessible areas by the stationary initial response teams (103) and mobile teams (71) were determined from the existing road network, and then, the possible increase in the accessible forest areas was investigated when the road standards are improved. Within the scope of the study, the impact of mobile teams used in emergencies on forest areas reached during the critical response period was also evaluated. According to the results, in the scenario where current road standards and stationary teams were evaluated, it was determined that only 59.54% of the forest areas could be reached by initial response teams during the critical response time. When the road standards were improved, this rate increased to 71.69%. On the other hand, when the current road standards and stationary and mobile teams were evaluated together, it was determined that initial response teams could reach 70.40% of the forest areas during the critical response time, and if road standards were improved, this rate increased to 78.17%. Also, utilizing mobile teams increased the accessible forest areas within the critical response time by 9.03%. The results have shown that improvements in road standards and the presence of mobile teams have a very effective role in combating forest fires.