bluuebunny/crossref_metadata_2025 huggingface dataset:
Ground Subsidence above Salt Caverns for Energy Storage: A Comparison of Prediction Methods with Emphasis on Convergence and Asymmetry
Authors: Babaryka Aleksandra , Benndorf Jörg
Published: June 2023

Mining-induced subsidence can have significant environmental and infrastructural impacts, making subsidence engineering a crucial consideration. However, the unique nature of salt caverns and the increasing demand for reliable subsidence prediction models in the context of energy storage require special attention. This study provides a comparative analysis of existing prediction models and highlights their advantages and disadvantages to determine the most appropriate approach. The study primarily focuses on theoretically developing an empirical influence function for asymmetrical subsidence prediction. It significantly contributes to the field by correcting and extending the existing method, providing a generalized solution applicable to any type of asymmetrical distribution around the cavern. Future research directions include implementing the proposed model in relation to real-world data. The insights gained from this study can help advance subsidence prediction models in the field of salt cavern energy storage, addressing a significant need in the industry.
Analysis of Network Pharmacological Efficacy and Therapeutic Effectiveness in Animal Models for Functional Dyspepsia of Foeniculi fructus
Authors: Choi Na-Ri , Jung Daehwa , Kim Sang-Chan , Park Jae-Woo , Choi Woo-Gyun , Kim Byung-Joo
Published: June 2023

For centuries, Foeniculi fructus (F. fructus) has been used as a traditional herbal medicine in China and Europe and is widely used as a natural therapy for digestive disorders, including indigestion, flatulence, and bloating. The mechanism of F. fructus that alleviates functional dyspepsia was analyzed through network pharmacology, and its therapeutic effect on an animal model of functional dyspepsia were investigated. The traditional Chinese medicine systems pharmacology (TCMSP) database was used to investigate the compounds, targets, and associated diseases of F. fructus. Information on the target genes was classified using the UniProtdatabase. Using the Cytoscape 3.9.1 software, a network was constructed, and the Cytoscape string application was employed to examine genes associated with functional dyspepsia. The efficacy of F. fructus on functional dyspepsia was confirmed by treatment with its extract in a mouse model of loperamide-induced functional dyspepsia. Seven compounds targeted twelve functional dyspepsia-associated genes. When compared to the control group, F. fructus exhibited significant suppression of symptoms in a mouse model of functional dyspepsia. The results of our animal studies indicated a close association between the mechanism of action of F. fructus and gastrointestinal motility. Based on animal experimental results, the results showed that F. fructus provided a potential means to treat functional dyspepsia, suggesting that its medical mechanism for functional dyspepsia could be described by the relationship between seven key compounds of F. fructus, including oleic acid, β-sitosterol, and 12 functional dyspepsia-related genes.
Early Nutrition Must Be Safe and Should Have Positive Impacts on Long-Term Health
Authors: Haiden Nadja , Haschke Ferdinand
Published: June 2023

The Special Issue entitled ‘The Role of Feeding Practice and Early Nutrition in Infant Growth, Metabolism and Body Composition’ examines the long-term outcomes of early nutrition in both preterm and term infants [...]
THC-Reduced Cannabis sativa L.—How Does the Solvent Determine the Bioavailability of Cannabinoids Given Orally?
Authors: Bartkowiak-Wieczorek Joanna , Mądry Edyta , Książkiewicz Michał , Winkler-Galicki Jakub , Szalata Milena , Szalata Marlena , Jiménez Ulises Elizalde , Wielgus Karolina , Grześkowiak Edmund , Słomski Ryszard , Bienert Agnieszka
Published: June 2023

The bioavailability levels of cannabidiol (CBD) and tetrahydrocannabinol (THC) determine their pharmacological effects. Therefore, for medical purposes, it is essential to obtain extracts containing the lowest possible content of the psychogenic component THC. In our extract, the CBD/THC ratio was 16:1, which is a high level compared to available medical preparations, where it is, on average, 1:1. This study assessed the bioavailability and stability of CBD and THC derived from Cannabis sativa L. with reduced THC content. The extract was orally administered (30 mg/kg) in two solvents, Rapae oleum and Cremophor, to forty-eight Wistar rats. The whole-blood and brain concentrations of CBD and THC were measured using liquid chromatography coupled with mass spectrometry detection. Much higher concentrations of CBD than THC were observed for both solvents in the whole-blood and brain after oral administration of the Cannabis sativa extract with a decreased THC content. The total bioavailability of both CBD and THC was higher for Rapae oleum compared to Cremophor. Some of the CBD was converted into THC in the body, which should be considered when using Cannabis sativa for medical purposes. The THC-reduced hemp extract in this study is a promising candidate for medical applications.
New Insights into Nutrients for Bone Health and Disease
Authors: Zhang Qian
Published: June 2023

Bone health includes the health of bone minerals, mass, geometry, and microstructure [...]
Towards Individually Tailored Diets in Prevention and Treatment of Diabetes?
Authors: Uusitupa Matti , Schwab Ursula
Published: June 2023

Type 2 diabetes (T2D) is a heterogenous disease regarding its phenotype and genotype [...]
Dietary Polyphenols and Their Role in Gut Health
Authors: Calabriso Nadia , Massaro Marika , Scoditti Egeria , Carluccio Maria Annunziata
Published: June 2023

Polyphenols are secondary plant metabolites derived from the shikimate/phenylpropanoid pathway, protecting plants from physical, chemical and biological stress [...]
Lactiplantibacillus plantarum OLL2712 Induces Autophagy via MYD88 and Strengthens Tight Junction Integrity to Promote the Barrier Function in Intestinal Epithelial Cells
Authors: Watanabe-Yasuoka Yumiko , Gotou Ayako , Shimizu Shigeomi , Sashihara Toshihiro
Published: June 2023

Autophagy is an important system conserved in eukaryotes that maintains homeostasis by degrading abnormal proteins. Autophagy incompetence in intestinal epithelial cells causes the abnormal function of intestinal stem cells and other cells and damages intestinal barrier function. The disruption of the intestinal barrier causes chronic inflammation throughout the body, followed by impaired glucose and lipid metabolism. Lactiplantibacillus plantarum OLL2712 (OLL2712) is a lactic acid bacterium that induces interleukin-10 production from immune cells, alleviates chronic inflammation, and improves glucose and lipid metabolism. In this study, we hypothesized that OLL2712 exerts anti-inflammatory effects by inducing autophagy and ameliorating intestinal barrier dysfunction, and we investigated its autophagy-inducing activities and functions. Caco-2 cells stimulated with OLL2712 for 24 h showed an increased number of autolysosomes per cell, compared with unstimulated cells. Therefore, the permeability of fluorescein isothiocyanate dextran 4000 (FD-4) was suppressed by inducing autophagy. In contrast, mucin secretion in HT-29-MTX-E12 cells was also increased by OLL2712 but not via autophagy induction. Finally, the signaling pathway involved in autophagy induction by OLL2712 was found to be mediated by myeloid differentiation factor 88 (MYD88). In conclusion, our findings suggest that OLL2712 induces autophagy in intestinal epithelial cells via MYD88, and that mucosal barrier function is strengthened by inducing autophagy.
Sucrosomial® Iron: An Updated Review of Its Clinical Efficacy for the Treatment of Iron Deficiency
Authors: Gómez-Ramírez Susana , Brilli Elisa , Tarantino Germano , Girelli Domenico , Muñoz Manuel
Published: June 2023

Iron deficiency (ID) and iron deficiency anemia (IDA) are highly prevalent worldwide. Oral iron salts, especially ferrous sulfate, are commonly used for the treatment of iron deficiency (ID). However, its use is associated with gastrointestinal side effects, thus compromising treatment compliance. Intravenous iron administration is a more costly and logistically complex alternative and is not risk-free, as infusion and hypersensitivity reactions may occur. Sucrosomial® iron is an oral formulation consisting of ferric pyrophosphate conveyed by a phospholipid and sucrester matrix (sucrosome®). Intestinal Sucrosomial® iron absorption is mediated by enterocytes and M cells, through the paracellular and transcellular routes, and occurs mostly as intact particles. These pharmacokinetic properties of Sucrosomial® iron result in higher iron intestinal absorption and excellent gastrointestinal tolerance compared to oral iron salts. The evidence derived from clinical studies supports the use of Sucrosomial® iron as a valid first option for the treatment of ID and IDA, especially for subjects who are intolerant or refractory to conventional iron salts. Newer evidence also demonstrates the effectiveness of Sucrosomial® iron, with a lower cost and fewer side effects, in certain conditions usually treated with IV iron in current clinical practice.
Meloxicam Targets COX-2/NOX1/NOX4/Nrf2 Axis to Ameliorate the Depression-like Neuropathology Induced by Chronic Restraint Stress in Rats
Authors: Arab Hany H. , Khames Ali , Mohammad Mostafa K. , Alsufyani Shuruq E. , Ashour Ahmed M. , El-Sheikh Azza A. K. , Darwish Hany W. , Gad Amany M.
Published: June 2023

Meloxicam has shown significant neuroprotection in experimental models of stroke, Alzheimer’s disease, and Parkinson’s disease. However, the potential of meloxicam to treat depression-like neuropathology in a chronic restraint stress (CRS) model and the associated molecular changes has been insufficiently explored. The current work aimed to explore the potential neuroprotective actions of meloxicam against CRS-evoked depression in rats. In the current experiments, animals received meloxicam (10 mg/kg/day; i.p.) for 21 days, and CRS was instigated by restraining the animals for 6 h/day during the same period. The sucrose preference test and the forced swimming test were used to explore the depression-linked anhedonia/despair, whereas the open-field test examined the animals’ locomotor activity. The current findings revealed that CRS elicited typical depression behavioral anomalies in the animals, including anhedonia, despair, and diminished locomotor activity; these findings were reinforced with Z-normalization scores. These observations were corroborated by brain histopathological changes and increased damage scores. In CRS-exposed animals, serum corticosterone spiked, and the hippocampi revealed decreased monoamine neurotransmitter levels (norepinephrine, serotonin, and dopamine). Mechanistically, neuroinflammation was evident in stressed animals, as shown by elevated hippocampal TNF-α and IL-1β cytokines. Moreover, the hippocampal COX-2/PGE2 axis was activated in the rats, confirming the escalation of neuroinflammatory events. In tandem, the pro-oxidant milieu was augmented, as seen by increased hippocampal 8-hydroxy-2′-deoxyguanosine alongside increased protein expression of the pro-oxidants NOX1 and NOX4 in the hippocampi of stressed animals. In addition, the antioxidant/cytoprotective Nrf2/HO-1 cascade was dampened, as evidenced by the lowered hippocampal protein expression of Nrf2 and HO-1 signals. Interestingly, meloxicam administration mitigated depression manifestations and brain histopathological anomalies in the rats. These beneficial effects were elicited by meloxicam’s ability to counteract the corticosterone spike and hippocampal neurotransmitter decrease while also inhibiting COX-2/NOX1/NOX4 axis and stimulating Nrf2/HO-1 antioxidant pathway. Together, the present findings prove the neuroprotective/antidepressant actions of meloxicam in CRS-induced depression by ameliorating hippocampal neuroinflammation and pro-oxidant changes, likely by modulating COX-2/NOX1/NOX4/Nrf2 axis.
Aptamers Versus Vascular Endothelial Growth Factor (VEGF): A New Battle against Ovarian Cancer
Authors: Mishra Yachana , Chattaraj Aditi , Mishra Vijay , Ranjan Abhigyan , Tambuwala Murtaza M.
Published: June 2023

Cancer is one of the diseases that causes a high mortality as it involves unregulated and abnormal cell growth proliferation that can manifest in any body region. One of the typical ovarian cancer symptoms is damage to the female reproductive system. The death rate can be reduced through early detection of the ovarian cancer. Promising probes that can detect ovarian cancer are suitable aptamers. Aptamers, i.e., so-called chemical antibodies, have a strong affinity for the target biomarker and can typically be identified starting from a random library of oligonucleotides. Compared with other probes, ovarian cancer targeting using aptamers has demonstrated superior detection effectiveness. Various aptamers have been selected to detect the ovarian tumor biomarker, vascular endothelial growth factor (VEGF). The present review highlights the development of particular aptamers that target VEGF and detect ovarian cancer at its earliest stages. The therapeutic efficacy of aptamers in ovarian cancer treatment is also discussed.
Structure-Based Design of Peptides Targeting VEGF/VEGFRs
Authors: Di Stasi Rossella , De Rosa Lucia , D’Andrea Luca Domenico
Published: June 2023

Vascular endothelial growth factor (VEGF) and its receptors (VEGFRs) play a main role in the regulation of angiogenesis and lymphangiogenesis. Furthermore, they are implicated in the onset of several diseases such as rheumatoid arthritis, degenerative eye conditions, tumor growth, ulcers and ischemia. Therefore, molecules able to target the VEGF and its receptors are of great pharmaceutical interest. Several types of molecules have been reported so far. In this review, we focus on the structure-based design of peptides mimicking VEGF/VEGFR binding epitopes. The binding interface of the complex has been dissected and the different regions challenged for peptide design. All these trials furnished a better understanding of the molecular recognition process and provide us with a wealth of molecules that could be optimized to be exploited for pharmaceutical applications.
Survey on Applications of Machine Learning in Low-Cost Non-Coherent Optical Systems: Potentials, Challenges, and Perspective
Authors: Alrabeiah Muhammad , Ragheb Amr M. , Alshebeili Saleh A. , Seleem Hussein E.
Published: June 2023

Direct Detection (DD) optical performance monitoring (OPM), Modulation Format Identification (MFI), and Baud Rate Identification (BRI) are envisioned as crucial components of future-generation optical networks. They bring to optical nodes and receivers a form of adaptability and intelligent control that are not available in legacy networks. Both are critical to managing the increasing data demands and data diversity in modern and future communication networks (e.g., 5G and 6G), for which optical networks are the backbone. Machine learning (ML) has been playing a growing role in enabling the sought-after adaptability and intelligent control, and thus, many OPM, MFI, and BRI solutions are being developed with ML algorithms at their core. This paper presents a comprehensive survey of the available ML-based solutions for OPM, MFI, and BFI in non-coherent optical networks. The survey is conducted from a machine learning perspective with an eye on the following aspects: (i) what machine learning paradigms have been followed; (ii) what learning algorithms are used to develop DD solutions; and (iii) what types of DD monitoring tasks have been commonly defined and addressed. The paper surveys the most widely used features and ML-based solutions that have been considered in DD optical communication systems. This results in a few observations, insights, and lessons. It highlights some issues regarding the ML development procedure, the dataset construction and training process, and the solution benchmarking dataset. Based on those observations, the paper shares a few insights and lessons that could help guide future research.
Preparation and Characterization of Alginate Hydrogels with High Water-Retaining Capacity
Authors: Savić Gajić Ivana M. , Savić Ivan M. , Svirčev Zorica
Published: June 2023

Hydrogels are very attractive materials due to their multifunctional properties. Many natural polymers, such as polysaccharides, are used for the preparation of hydrogels. The most important and commonly used polysaccharide is alginate because of its biodegradability, biocompatibility, and non-toxicity. Since the properties of alginate hydrogel and its application depend on numerous factors, this study aimed to optimize the gel composition to enable the growth of inoculated cyanobacterial crusts for suppressing the desertification process. The influence of alginate concentration (0.1–2.9%, m/v) and CaCl2 concentration (0.4–4.6%, m/v) on the water-retaining capacity was analyzed using the response surface methodology. According to the design matrix, 13 formulations of different compositions were prepared. The water-retaining capacity was defined as the system response maximized in optimization studies. The optimal composition of hydrogel with a water-retaining capacity of about 76% was obtained using 2.7% (m/v) alginate solution and 0.9% (m/v) CaCl2 solution. Fourier transform infrared spectroscopy was used for the structural characterization of the prepared hydrogels, while the water content and swelling ratio of hydrogels were determined using gravimetric methods. It was concluded that alginate and CaCl2 concentrations play the most important role regarding the gelation time, homogeneity, water content, and swelling ratio of the hydrogel.
Bio-Polyester/Rubber Compounds: Fabrication, Characterization, and Biodegradation
Authors: Frank Carina , Emmerstorfer-Augustin Anita , Rath Thomas , Trimmel Gregor , Nachtnebel Manfred , Stelzer Franz
Published: June 2023

Biobased and biodegradable polymers (BBDs) such as poly(3-hydroxy-butyrate), PHB, and poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) are considered attractive alternatives to fossil-based plastic materials since they are more environmentally friendly. One major problem with these compounds is their high crystallinity and brittleness. In order to generate softer materials without using fossil-based plasticizers, the suitability of natural rubber (NR) as an impact modifier was investigated in PHBV blends. Mixtures with varying proportions of NR and PHBV were generated, and samples were prepared by mechanical mixing (roll mixer and/or internal mixer) and cured by radical C–C crosslinking. The obtained specimens were investigated with respect to their chemical and physical characteristics, applying a variety of different methods such as size exclusion chromatography, Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), thermal analysis, XRD, and mechanical testing. Our results clearly indicate that NR–PHBV blends exhibit excellent material characteristics including high elasticity and durability. Additionally, biodegradability was tested by applying heterologously produced and purified depolymerases. pH shift assays and morphology analyses of the surface of depolymerase-treated NR–PHBV through electron scanning microscopy confirmed the enzymatic degradation of PHBV. Altogether, we prove that NR is highly suitable to substitute fossil-based plasticizers; NR–PHBV blends are biodegradable and, hence, should be considered as interesting materials for a great number of applications.
Multi-Component Biodegradable Materials Based on Water Kefir Grains and Yeast Biomasses: Effect of the Mixing Ratio on the Properties of the Films
Authors: Lago Agustina , Delgado Juan F. , Rezzani Guillermo D. , Cottet Celeste , Ramírez Tapias Yuly A. , Peltzer Mercedes A. , Salvay Andrés G.
Published: June 2023

The use of biopolymeric materials is restricted for some applications due to their deficient properties in comparison to synthetic polymers. Blending different biopolymers is an alternative approach to overcome these limitations. In this study, we developed new biopolymeric blend materials based on the entire biomasses of water kefir grains and yeast. Film-forming dispersions with varying ratios of water kefir to yeast (100/0, 75/25, 50/50 25/75 and 0/100) underwent ultrasonic homogenisation and thermal treatment, resulting in homogeneous dispersions with pseudoplastic behaviour and interaction between both biomasses. Films obtained by casting had a continuous microstructure without cracks or phase separation. Infrared spectroscopy revealed the interaction between the blend components, leading to a homogeneous matrix. As the water kefir content in the film increased, transparency, thermal stability, glass transition temperature and elongation at break also increased. The thermogravimetric analyses and the mechanical tests showed that the combination of water kefir and yeast biomasses resulted in stronger interpolymeric interactions compared to single biomass films. The ratio of the components did not drastically alter hydration and water transport. Our results revealed that blending water kefir grains and yeast biomasses enhanced thermal and mechanical properties. These studies provided evidence that the developed materials are suitable candidates for food packaging applications.
Effect of Crude Oil Quality on Properties of Hydrocracked Vacuum Residue and Its Blends with Cutter Stocks to Produce Fuel Oil
Authors: Kolev Iliyan , Stratiev Dicho , Shishkova Ivelina , Atanassov Krassimir , Ribagin Simeon , Sotirov Sotir , Sotirova Evdokia , Stratiev Danail D.
Published: June 2023

The production of heavy fuel oil from hydrocracked vacuum residue requires dilution of the residue with cutter stocks to reduce viscosity. The hydrocracked residue obtained from different vacuum residue blends originating from diverse crude oils may have divergent properties and interact with the variant cutter stocks in a dissimilar way leading to changeable values of density, sediment content, and viscosity of the obtained fuel oil. H-Oil hydrocracked vacuum residues (VTBs) obtained from different crude blends (Urals, Siberian Light (LSCO), and Basrah Heavy) were diluted with the high aromatic fluid catalytic cracking (FCC) light cycle, heavy cycle, and slurry oil, and the low aromatic fluid catalytic cracking feed hydrotreater diesel cutter stocks and their densities, sediment content, and viscosity of the mixtures were investigated. Intercriteria analysis evaluation of the data generated in this study was performed. It was found that the densities of the blends H-Oil VTB/cutter stocks deviate from the regular solution behavior because of the presence of attractive and repulsive forces between the molecules of the H-Oil VTB and the cutter stocks. Urals and Basrah Heavy crude oils were found to enhance the attractive forces, while the LSCO increases the repulsive forces between the molecules of H-Oil VTBs and those of the FCC gas oils. The viscosity of the H-Oil VTB obtained during hydrocracking of straight run vacuum residue blend was established to linearly depend on the viscosity of the H-Oil vacuum residue feed blend. The applied equations to predict viscosity of blends containing straight run and hydrocracked vacuum residues and cutter stocks proved their good prediction ability with an average relative absolute deviation (%AAD) of 8.8%. While the viscosity was found possible to predict, the sediment content of the blends H-Oil VTBs/cutter stocks was recalcitrant to forecast.
Recent Applications and Prospects of Nanowire-Based Biosensors
Authors: Tran Vy Anh , Vo Giang N. L. , Vo Thu-Thao Thi , Doan Van Dat , Vo Vien , Le Van Thuan
Published: June 2023

High-sensitivity biomedical sensors could make it possible to detect and classify chemical and biological species in a variety of applications, from disease diagnosis to medication discovery, thus, boosting the likelihood of life-saving intervention. Synthesized nanowires have already produced advancements in a variety of sectors, including biological sensors over the last decade. When compared to macro-sized materials, the nanowires’ large surface area-to-volume ratio increased sensitivity. Their applications for biomarker, viral, and DNA detection, as well as drug discovery, are also discussed. Self-powering, reusability, sensitivity in high ionic strength solvents, and long-term stability are all examples of recent developments. Shortly, the nanowire is likely to lead to major improvements in biomedical sensors. This review provides a full overview of the nanowire sensor’s working principle and production procedure. We have discussed how to produce nanowires that can be utilized as biosensors for different bacteria and pathogens, protease, DNA and RNA, neurotransmitters, and chemical compounds. Biosensing technology has dramatically improved because of the introduction of nanowires in biosensors. This is a result of the application of new biorecognition components and transducers, improvements in the manufacture, design, and miniaturization of nanostructured devices at the micron scale, and unique approaches for the synthesis of nanowires. The versatility, robustness, and dynamic nature of sensing technologies have all improved thanks to the usage of nanowires.
Thoughts of a Book Review Editor
Authors: Donovan Stephen Kenneth
Published: June 2023

What are the essential abilities that make proficient book review editors? They should preferably be a seasoned reviewer themselves, with the ability to read a book and write a review in short time in an emergency. They will develop a group of trusted reviewers—the ‘regulars’—which may include the editors themselves. However, there will also be a blacklist of failed reviewers not to be approached again. Recognising that book reviews were dropped by many journals, which were commonly wanting more printed space for research articles, does not mean that they will not be needed in the future. In the age of online publication, page space is no longer a valid limitation. If they are not on board already, electronic journals should be appointing new book review editors and expecting an influx of copy.
Experiments on the Artificial Potential Field with Local Attractors for Mobile Robot Navigation
Authors: Melchiorre Matteo , Salamina Laura , Scimmi Leonardo Sabatino , Mauro Stefano , Pastorelli Stefano
Published: June 2023

Obstacle avoidance is a challenging task in robot navigation, as it requires efficient and reliable methods to avoid collision and reach the desired goal. Artificial potential field methods are widely used for this purpose, as they are efficient, effective, and easy to implement. However, they are limited by the use of only one global attractor at the goal. This paper introduces and evaluates experimentally a novel technique that enhances the artificial potential field method with local attractors. Local attractors can be positioned around the obstacle so as to guide the robot detouring through preferred regions. Thus, the side the robot will pass by can be determined in advance, making the collision-free path predictable. The technique is formulated by modelling local attractors as optimal inflections, i.e., regions that do not show local minima, which coexist with the potential field generated by the obstacle and the global attractor. The method is validated using a laboratory setup that employs a camera and markers to track the poses of the robot, the obstacle, and the target. A series of experiments are conducted to examine the effect of the local attractor under different test conditions, obtained by varying the obstacle pose, the attraction intensity, and the robot velocity. The experimental results demonstrate the effectiveness of the proposed technique and highlight the aspects that require further investigation for its improvement and application.
Assessment and Projections of Marine Heatwaves in the Northwest Pacific Based on CMIP6 Models
Authors: Xue Jingyuan , Shan Haixia , Liang Jun-Hong , Dong Changming
Published: June 2023

To assess the abilities of global climate models (GCMs) on simulating the spatiotemporal distribution of marine heatwaves (MHWs), GCMs from the Coupled Model Intercomparison Program in Phase 6 (CMIP6) were evaluated from a historical period between 1985 and 2014 in the Northwest Pacific Ocean using a dataset that synthesizes remote sensing data. MHW simulation capabilities were assessed using Rank Score (RS) and Comprehensive Rating (MR) metrics that include both spatial and temporal scoring metrics. It was found that most CMIP6 models overestimate cumulative intensity, while mean and maximum intensities, in addition to the duration, were underestimated in the historical period. Possible future changes in MHWs were also examined based on the rank-based weighting ensembles under four shared socioeconomic pathways (SSPs) scenarios (SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). MHWs were identified using both a fixed 30-year baseline and a 30-year sliding baseline. In all scenarios, all MHWs metrics except frequency will have an increasing trend for the fixed baseline method. The frequency of MHWs will decrease after the 2050s. Days will first increase and then stabilize under various scenarios. MHWs will take place for more than 300 days by the end of the 21st century for the SSP5-8.5 scenario. The cumulative intensity in the SSP5-8.5 scenario is roughly six times higher than that in the SSP1-2.6 scenario by the end of the 21st century. A fixed baseline will result in near-permanent MHWs at the end of the 21st century. There will be no permanent MHWs at the end of the 21st century. Using the 30-year shifting baseline to define the MHWs can improve future MHW projections by capturing the spatiotemporal variability features of the MHWs.
Traffic Sign Detection and Recognition Using Multi-Frame Embedding of Video-Log Images
Authors: Xu Jian , Huang Yuchun , Ying Dakan
Published: June 2023

The detection and recognition of traffic signs is an essential component of intelligent vehicle perception systems, which use on-board cameras to sense traffic sign information. Unfortunately, issues such as long-tailed distribution, occlusion, and deformation greatly decrease the detector’s performance. In this research, YOLOv5 is used as a single classification detector for traffic sign localization. Afterwards, we propose a hierarchical classification model (HCM) for the specific classification, which significantly reduces the degree of imbalance between classes without changing the sample size. To cope with the shortcomings of a single image, a training-free multi-frame information integration module (MIM) was constructed, which can extract the detection sequence of traffic signs based on the embedding generated by the HCM. The extracted temporal detection information is used for the redefinition of categories and confidence. At last, this research performed detection and recognition of the full class on two publicly available datasets, TT100K and ONCE. Experimental results show that the HCM-improved YOLOv5 has a mAP of 79.0 in full classes, which exceeds that of state-of-the-art methods, and achieves an inference speed of 22.7 FPS. In addition, MIM further improves model performance by integrating multi-frame information while only slightly increasing computational resource consumption.
Combined CNN and RNN Neural Networks for GPR Detection of Railway Subgrade Diseases
Authors: Liu Huan , Wang Shilei , Jing Guoqing , Yu Ziye , Yang Jin , Zhang Yong , Guo Yunlong
Published: June 2023

Vehicle-mounted ground-penetrating radar (GPR) has been used to non-destructively inspect and evaluate railway subgrade conditions. However, existing GPR data processing and interpretation methods mostly rely on time-consuming manual interpretation, and limited studies have applied machine learning methods. GPR data are complex, high-dimensional, and redundant, in particular with non-negligible noises, for which traditional machine learning methods are not effective when applied to GPR data processing and interpretation. To solve this problem, deep learning is more suitable to process large amounts of training data, as well as to perform better data interpretation. In this study, we proposed a novel deep learning method to process GPR data, the CRNN network, which combines convolutional neural networks (CNN) and recurrent neural networks (RNN). The CNN processes raw GPR waveform data from signal channels, and the RNN processes features from multiple channels. The results show that the CRNN network achieves a higher precision at 83.4%, with a recall of 77.3%. Compared to the traditional machine learning method, the CRNN is 5.2 times faster and has a smaller size of 2.6 MB (traditional machine learning method: 104.0 MB). Our research output has demonstrated that the developed deep learning method improves the efficiency and accuracy of railway subgrade condition evaluation.
Tipping Bucket Rain Gauges in Hydrological Research: Summary on Measurement Uncertainties, Calibration, and Error Reduction Strategies
Authors: Segovia-Cardozo Daniel A. , Bernal-Basurco Carlota , Rodríguez-Sinobas Leonor
Published: June 2023

Tipping bucket rain gauges (TBRs) continue to be one of the most widely used pieces of equipment for rainfall monitoring; they are frequently used for the calibration, validation, and downscaling of radar and remote sensing data, due to their major advantages—low cost, simplicity and low-energy consumption. Thus, many works have focused and continue to focus on their main disadvantage—measurement biases (mainly in wind and mechanical underestimations). However, despite arduous scientific effort, calibration methodologies are not frequently implemented by monitoring networks’ operators or data users, propagating bias in databases and in the different applications of such data, causing uncertainty in the modeling, management, and forecasting in hydrological research, mainly due to a lack of knowledge. Within this context, this work presents a review of the scientific advances in TBR measurement uncertainties, calibration, and error reduction strategies from a hydrological point of view, by describing different rainfall monitoring techniques, summarizing TBR measurement uncertainties, focusing on calibration and error reduction strategies, discussing the state of the art and providing future perspectives of the technology.
Assessment of Spatial Variations in Pesticide, Heavy Metal, and Selenium Residues in Honey Bee (Apis mellifera L.) Products
Authors: Awad Mai M. , Boone Randall B.
Published: June 2023

Apis mellifera L. is considered one of the most important pollinators in nature. Unfortunately, in addition to other insect species, honey bee populations are decreasing at an alarming rate, urging researchers to investigate the causes and stressors that precipitated this decline. This study focuses on chemical stressors that are found to affect bee populations. We used pollen and honey samples to examine the variations in pesticides, selenium, and heavy metals in two different landscapes: urban and agricultural areas of northeastern Colorado, USA. Subsequently, we extrapolated the risks of these toxins’ residues to Apis spp. Based on the current literature, we found no spatial variations in metal and selenium concentrations in the pollen and honey samples collected from urban and agricultural areas. Moreover, we observed no spatial variations in pesticide concentrations in pollen and honey samples. Based on the previous literature and a comparison of the residues of heavy metals, selenium, and pesticides in our pollen and honey samples, we found that the heavy metal and selenium residues in some honey and pollen likely pose a severe health risk to honey bees. Although the levels of pesticide residues were below the documented thresholds of risk, we consider the possibility of synergistic chemical impacts. Our findings support future efforts to investigate the health risks associated with multiple-factor combinations.
Anthropometric Measures, Muscle Resistance, and Balance in Physically Active, Aged Adults
Authors: Rodrigues Filipe , Antunes Raul , Matos Rui , Jacinto Miguel , Monteiro Diogo , Forte Pedro , Monteiro António Miguel , Barbosa Tiago M.
Published: June 2023

Objectives: This study aimed to examine the relationship between age, body mass index, muscle strength, and balance in physically active, aged adults. Methods: Eighty-five participants were recruited for this study, having an average age of 70.31 years (SD = 9.90), ranging from 50 to 92 years. Twenty-six (30.6%) participants were male and fifty-nine (69.4%) were female. The participants had an average body mass index of 27.30 kg/m2 (SD = 3.62), ranging from 20.32 to 38.58 kg/m2. Participants undertook the Timed-Up and Go to test balance, and the chair-stand test to assess lower body strength. Hierarchical regression analyses were conducted. Three models (Model 1, 2, and 3) were tested to assess their relationships with balance: M1—Lower body muscle strength; M2—Lower body muscle strength and body mass index; M3—Lower body muscle strength, body mass index, and age. Results: All hierarchical models displayed significant variance. The third model explained 50.9% of the variance in dynamic balance, [F(3, 81) = 27.94, p < 0.001, R = 0.71, Ra2 = 0.51]. The difference in Ra2 between the first, second, and third models was statistically significant (p < 0.05). Age, body mass index, and lower body muscle strength had significant (p < 0.05) correlations with balance. In terms of the significant impact of each predictor, age had the strongest association with balance (p < 0.05). Conclusions: The results are useful to understand mechanisms or diagnose people at risk of fall.
A Study of Metaverse Exhibition Sustainability on the Perspective of the Experience Economy
Authors: Wang Minglu , Liu Shanshan , Hu Lingling , Lee Jong-Yoon
Published: June 2023

With the development of information technology, many well-known art museums and galleries have adopted metaverse exhibitions for online display and dissemination of art information, building sustainable ways to participate in and experience art. Users can access the metaverse exhibition platform through the internet and enjoy classic artworks in the virtual space, which has gained many forms of artistic perception and improved physical and mental health. Currently, the factors affecting user use intentions in existing metaverse exhibition studies still need to be clarified and need to be studied in depth. This paper explores the relationship between users’ entertainment experience, educational experience, presence, affective responses, and use intention through a survey of 536 users who had experienced a metaverse exhibition. The research results show that users’ use intentions are influenced by entertainment experiences and educational experiences. Presence mediates between entertainment experiences and educational experiences on use intention. Affective responses play a moderating role between the educational experience and use intention. This study provides a relevant theoretical basis for sustainable urban and socio-economic development from a digital perspective. At the same time, this study enables the metaverse exhibition platform to design and create valuable and healthy artistic content with higher quality. The emotional state of the user’s experience was better attended to so that mental health was enhanced and managed. Furthermore, it also provided a guidance program for the development of educational experience and economic sustainability of the exhibition industry.
Predictive Analysis and Correction Control of CCT for a Power System Based on a Broad Learning System
Authors: Yang Yude , Fang Huayi , Yang Lizhen
Published: June 2023

Transient stability is an important factor for the stability of a power system. With improvements in voltage levels, and the expansion of power network scales, the problem of transient stability is particularly prominent. When a power system circuit fails, if the operation time of the relay protection device is higher than the critical clearing time (CCT), the relay protection device cannot cut the fault line in a timely manner. It is essential to forecast and adjust the CCT to improve the stability of the system; therefore, a method is proposed in this paper to predict and evaluate the critical clearing time using the broad learning system (BLS). The sensitivity of the critical clearing time can be easily calculated based on the prediction results of the critical clearing time using BLS. Moreover, the critical clearing time can be modified using the BLS correction control model. The proposed method was verified using a 4-machine 11-node system and a 10-machine 39-node system. According to the experimental results, the proposed model can predict, evaluate, and correct the CCT very well.
Statistical Modelling of Biosorptive Removal of Hexavalent Chromium Using Dry Raw Biomasses of Dioscorea rotundata, Elaeis guineensis, Manihot esculenta, Theobroma cacao and Zea mays
Authors: Villabona-Ortíz Angel , Tejada-Tovar Candelaria , González-Delgado Ángel Darío
Published: June 2023

Hexavalent chromium [Cr (VI)] is a highly toxic and hazardous contaminant that poses serious health risks to both humans and the environment. Its presence in water sources can lead to severe health issues, including various types of cancer and respiratory ailments. Therefore, developing efficient and effective methods for Cr (VI) removal is crucial in ensuring safe and clean water supplies. The aim of this research is the environmentally responsible elimination of hexavalent chromium by bioadsorption using corn residues (CR), palm fiber (PF), and the peels of yam (YP), cassava (CP), and cocoa (CH). The study was conducted with varying levels of pH, bioadsorbent quantity, temperature, and adsorbent particle size at 200 rpm, with an initial concentration of 100 mg/L and 24 h of contact time to improve the adsorption efficiency. The process variables were evaluated and optimized using the statistical technique response surface methodology (RSM). The SEM-EDS analysis revealed that the predominant elements in the structure of the bioadsorbents were carbon and oxygen. Furthermore, the adsorption process led to the incorporation of Cr (VI) into the structure of the biomaterials, as indicated by their EDS spectra. The maximal adsorption efficiency of 99.11% was obtained at pH 2, bioadsorbent dose of 0.03 mg, 30 °C, and 0.5 mm of particle size. Various equilibrium isotherms were utilized to fit and analyze the adsorption data. The assessed maximum adsorption capacities were 38.84, 56.88, 52.82, 138.94, and 240,948.7 mg/g for YP, PF, CP, CH, and CR, respectively. The adsorption data exhibited conformity with the Freundlich and Redlich–Peterson isotherm models (R2 = 0.95), indicating that the phenomenon occurs in a multilayer. Pseudo-second order and Elovich kinetic models adjusted the kinetics of chromium (VI), suggesting that the mechanism could be controlled by chemisorption. Therefore, the residual biomasses evaluated can serve as a cost-effective adsorbent for Cr (VI) removal, and the use of RSM enables efficient modeling and prediction of the adsorption process.
Pleurotus ostreatus Mycelium and Sugarcane Bagasse as Substitute Environment-Friendly Material for Polystyrene Foam
Authors: Aranda-Calipuy Maria Melissa , Roncal-Lázaro Alexia , Quezada-Alvarez Medardo A. , Siche Raúl , Cabanillas-Chirinos Luis , Rojas-Villacorta Walter , Benites Santiago M. , Rojas-Flores Segundo
Published: June 2023

Biodiversity in ecosystems is threatened by plastic waste, a significant pollution problem. The research aims to use plastic, Pleorotus ostreatus mycelium, and sugarcane bagasse to develop an eco-friendly biomaterial. The preparation consisted of three phases: (1) Treatment of the underlying layer, (2) inoculation of the fungus (three different concentrations: 15%, M1; 20%, M2; and 25%, M3), and (3) dehydration of the biomaterial. The physical characterization results (density, water absorption, and texture) showed that the average density varies between 127.86 and 131.19 kg/m3; also, the M1 sample had a high percentage of water absorption (23.55%), while M2 obtained lower percentages (11.79%). In the bending test, samples M2 and M3 showed higher structural resistance with stress values of 0.682 and 0.68 MPa, respectively. Based on the results, the produced biomaterials may serve as an alternative to expanded polystyrene (EPS). Due to their moldable characteristics, they can be used in non-structural construction, packaging, and various architectural applications. The research provided promising results; however, additional parameters must be evaluated to be able to commercialize them.
Investigating the Potential Impact on Shallow Groundwater Quality of Oily Wastewater Injection in Deep Petroleum Reservoirs: A Multidisciplinary Evaluation at the Val d’Agri Oilfield (Southern Italy)
Authors: Rizzo Pietro , Bucci Antonio , Monaco Pamela , Sanangelantoni Anna Maria , Naclerio Gino , Rossi Mattia , Iacumin Paola , Bianchi Federica , Mucchino Claudio , Riboni Nicolò , Avagliano Dario , Coraggio Francesco , Caputi Antonella , Celico Fulvio
Published: June 2023

The increase in oil production from petroleum reservoirs has led to studies examining the effects of these activities on groundwater quality. Oily wastewater associated with oil production is often reinjected through abandoned wells into the unproductive portions of the reservoir to avoid its discharge on the surface. The reinjection process is designed to be environmentally friendly and to exclude direct interactions between injected fluids and the surrounding groundwater; nevertheless, the evaluation of the compatibility between this process and the protection of the surrounding environment is of utmost importance when oilfields are located within sensitive and protected areas. The present work aimed to evaluate the impact of the oily wastewater reinjection into a long-term and high-rate disposal well in the Val d’Agri oilfield (Southern Italy). Previous preliminary investigations carried out at the study site led researchers to hypothesize the possible hydrocarbon contamination of the shallower aquifer caused by reinjection well integrity issues. Our strategy is based on an integrated and multidisciplinary approach involving isotopic (stable isotopes 2H and 18O), chemical, and microbiological (characterization of bacterial and archaeal communities) analyses. After a comprehensive and meticulous examination of the research data, it has been ascertained that significant discrepancies exist between the shallow and reinjection water systems. This allowed us to clarify the area’s complex flow dynamics and exclude hydrocarbon contamination of spring waters caused by the reinjection process.