bluuebunny/crossref_metadata_2025 huggingface dataset:
Design and Characterization of a Portable Multiprobe High-Resolution System (PMHRS) for Enhanced Inversion of Water Remote Sensing Reflectance with Surface Glint Removal
Authors: Liu Shuangkui , Jiang Ye , Wang Kai , Zhang Yachao , Wang Zhe , Liu Xu , Yan Shiyu , Ye Xin
Published: September 2024

Surface glint significantly reduces the measurement accuracy of remote sensing reflectance of water, Rrs, making it difficult to effectively use field measurements for studying water optical properties, accurately retrieving water quality parameters, and validating satellite remote sensing products. To accurately assess the effectiveness of various glint removal methods and enhance the accuracy of water reflectance measurements, a portable multiprobe high-resolution System (PMHRS) is designed. The system is composed of a spectrometer, fiber bundles, an irradiance probe, and three radiance probes. The reliability and measurement accuracy of the PMHRS are ensured through rigorous laboratory radiometric calibration and temperature correction. The comprehensive uncertainty of laboratory calibration ranges from 1.29% to 1.43% for irradiance calibration and from 1.47% to 1.59% for radiance calibration. Field measurement results show a strong correlation with both synchronous ASD data, and Sen2Cor-atmospherically corrected Sentinel-2B data (R2 = 0.949, RMSE = 0.013; R2 = 0.926, RMSE = 0.0105). The water-leaving radiance measurements obtained under different solar elevation angles using three methods (M99 method, polarization method, and SBA) demonstrate that the improved narrow field-of-view polarization probe effectively removes surface glint across various solar elevation angles (with overall better performance than the traditional M99 method). At a solar elevation angle of 69.7°, the MAPD and MAD between the measurements of this method and those of the SBA are 5.8% and 1.4 × 10−4, respectively. The results demonstrate that the PMHRS system outperforms traditional methods in sun glint removal, significantly enhancing the accuracy of water remote sensing reflectance measurements and improving the validation quality of satellite data. This work provides a crucial technical foundation for the development of high-resolution continuous observation platforms in complex aquatic environments. It holds significant implications for improving the accuracy of field-based water remote sensing reflectance measurements and for enhancing the quality of water ecological monitoring data and satellite validation data.
Microalgal Diversity and Molecular Ecology: A Comparative Study of Classical and Metagenomic Approaches in Ponds of the Eifel National Park, Germany
Authors: Linne von Berg Karl-Heinz , Keilholz Leonie , Küchenmeister Nadine , Pushkareva Ekaterina , Becker Burkhard
Published: September 2024

While molecular methods have begun to transform ecology, most algal biodiversity is still studied using the classical approach of identifying microalgae by light microscopy directly in sample material or using cultures. In this study, we compare both approaches (light microscopy and metagenomics as a molecular approach) using the freshwater ponds of the Eifel National Park in Germany as a case study. The ponds were found to be rich in desmids by light microscopy. A total of 299 species representing 81 genera were identified by light microscopy. While the molecular method does not currently allow species identification in most cases, we were able to identify 207 different algal genera. In total, 157 genera were detected only by metagenomics, 50 genera were found with both methods, and 31 genera were found by light microscopy, highlighting the need to continue using light microscopy in addition to a molecular approach. The metagenomics method has several advantages over the light microscopy method: (1) deeper assessment of alpha biodiversity, (2) better abundance numbers, and (3) complete coverage of all living matter. The latter is also a significant improvement over metabarcoding, as universal PCR primers are not available.
Isometric Fatigue Resistance of Lumbar Extensors and Cardiovascular Strain in Lower Back Pain Patients Are Associated with Angiotensin-Converting Enzyme and Tenascin-C Gene Polymorphisms
Authors: Flück Martin , Valdivieso Paola , Giraud Marie-Noëlle , Humphreys Barry Kim
Published: September 2024

Background: We tested whether gene polymorphisms for angiotensin-converting enzyme (ACE, rs1799752) and tenascin-C (TNC, rs2104772) are associated with variability in fatigue resistance and metabolic strain during static lumbar exercise through interactions with chronic nonspecific lower back pain and habitual physical exercise levels (PA). Methods: Forty-eight patients and matched controls performed an isometric endurance test for lumbar extensors. Metabolic strain to longissimus muscle (oxygen saturation, lactate) and cardiovascular system (muscle hemoglobin, blood pressure) and holding time were monitored. Subjects were genotyped for rs1799752 (II, ID, DD) and rs2104772 (AA, AT, TT). Associations of variance with group, genotype, and PA were analyzed under a 5% false discovery rate. Results: The holding time was lower in patients than in controls (150.9 vs. 188.6 s). This difference was associated with both genotypes, as patients with DD-rs1799752-genotype (p = 0.007) and TT-rs2104772-genotype (p = 0.041) showed lower fatigue resistance. Muscle deoxygenation during exercise varied in positive association with the rs2104772-genotype and PA (p = 0.010, η2 = 0.236). Mean arterial blood pressure (p = 0.028, η2 = 0.108) and recovery of hemoglobin concentration (p = 0.003, η2 = 0.907) demonstrated complex group x rs2104772 interactions. Conclusions: Polymorphisms rs1799752 and rs2104772 influence back pain-related variability in lumbar fatigue resistance. rs2104772 was linked to cardiovascular strain during isometric exercise and recovery via muscle perfusion.
Reducing Phosphorus Loss in Short-Cycle Horticultural Production Using Activated Aluminum-Amended Substrates and Modified Fertigation Practices
Authors: Abdi Damon Edward , Beasley Jeffrey , Fields Jeb
Published: September 2024

To support growth, short-cycle horticultural crops require readily available nutrients. However, this often leads to nutrient leaching. Implementing best management practices in production decisions like incorporating fertilizer retaining amendments to substrates or modifying fertilization programs can mitigate nutrient losses to the environment and associated costs. This study examined using an activated aluminum (AA) material as a substrate amendment to retain phosphorus (P) within containers while also assessing methods to reduce P fertilization in Tagetes production over a six-week production cycle. A commercial peat moss substrate (PL) pre-loaded with nutrients was amended with AA, enabling comparisons between substrates with and without AA. Enhanced fertilizer practices involved supplementing the initial nutrients by applying a weekly fertigation solution including nitrogen and potassium over the six weeks, but P for either 0, 2, 4, or 6 weeks. The incorporation of AA significantly reduced P leaching losses by 89.5–97.7%, compared to the PL substrates receiving P the entire six weeks. Regardless of substrate or fertilizer management, all Tagetes had equivalent sizes (growth index) and aboveground biomass. The results indicate that amending substrates with AA and/or reducing additional P inputs are effective strategies to minimize P leaching without compromising Tagetes quality.
Isolation and Characterization of β-Glucan Containing Polysaccharides from Monascus spp. Using Saccharina japonica as Submerged Fermented Substrate
Authors: Suraiya Sharmin , Jang Won Je , Haq Monjurul , Kong In-Soo
Published: September 2024

Beta-glucan (β-glucan), a naturally occurring complex polysaccharide, has drawn attention for its diverse health benefits, including immune system modulation. β-glucan was extracted from two fungi, Monascus purpureus (Mp) and Monascus kaoliang (Mk), cultured in Saccharina japonica via submerged fermentation. The yield, solubility, total sugar, reducing sugar, protein content, Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), Thermogravimetric analysis (TGA), Scanning Electron Microscopy (SEM), in vitro free radical scavenging activity, and cytotoxicity were analyzed. A significant yield of β-glucans, with the contents of 51.30 ± 1.54% in Mp and 44.24 ± 1.18% in Mk was observed on a dry weight basis. Water solubility slightly varied, measuring 36.25 ± 1.14% in Mp and 31.25 ± 0.94% in Mk. Total sugar and reducing sugar content in Mp and Mk derived β-glucans were 114.75 ± 2.54 mg/g and 100.25 ± 1.86 mg/g, 7.38 ± 0.78 mg/g, and 8.39 ± 0.46 mg/g, respectively. FTIR spectra resembled the standard, and TGA confirmed heat stability. XRD patterns indicated that the extracted β-glucans, including the standard one, showed the most prominent diffraction peaks in the lower 2θ range, suggesting similar crystalline phases; however, they differed in crystallinity and degree of amorphous content. SEM images displayed characteristic rough and fibrous shapes and surfaces for extracted β-glucans but it was uniform and of a regular shape in the standard sample. The isolated β-glucans exhibited in vitro free radical scavenging and no cytotoxicity was observed in the MTS assay. Therefore, utilizing S. japonica as a substrate in the fermentation process by Monascus spp. presents a unique opportunity in the production and utilization of β-glucans.
Color Modification of Silicone-Based Prosthetic Finger by 3D-Printed Mold
Authors: Tan Wilson Sutanto , Harito Christian , Andhini Grasheli Kusuma , Martawidjaja Marcel , Chainando Nico , Syafi’i Muhammad , Putra Ketut Bagus , Syafrudin Muhammad
Published: September 2024

Dissatisfaction among upper limb prosthetic users is high, reaching over 70%, and 52% of upper limb amputees abandon their prosthetic devices due to limitations such as limited functionality, poor design/aesthetic, and improper fit. The conventional procedure of making prosthetics is time-consuming and expensive. This study was conducted to provide an alternative solution for the several issues of current prosthetic devices. 3D printing technology offers a promising alternative, providing greater accuracy, reduced labor time, and improved fit and comfort. This research explores the application of 3D printing for creating custom silicone prosthetic fingers, using Fused Deposition Modelling (FDM) for the mold. A high-resolution 3D scanner was employed to capture the precise anatomy of the patient’s hand, and CAD software was used to design molds that satisfied the patient preference and were reusable. The resulting prosthetics demonstrated good fit and patient satisfaction, though exact color matching remains a challenge, but still, it did demonstrate that it is possible to fabricate colored prosthetics. Performance tests, such as the Jebsen–Taylor Hand Function Test, indicated that while initial performance with the prosthetic was slightly lower, patient satisfaction and potential for improved functionality over time were high. This study underscores the potential of 3D printing to enhance the customization, cost-effectiveness, and overall quality of prosthetic devices, contributing to Sustainable Development Goals related to health and industry innovation.
Accuracy and Fit of Ceramic Filled 3D-Printed Resin for Permanent Crown Fabrication: An In Vitro Comparative Study
Authors: Al-Ramadan Anwar , Abualsaud Reem , Al-Dulaijan Yousif A. , Al-Thobity Ahmad M. , Alalawi Haidar
Published: September 2024

This in vitro investigation aimed to compare the trueness, precision, internal fit, and marginal adaptation of Varseo Smile Crown Plus (VSCP), CROWNTEC (C), and milled Enamic crowns (E) using a 5-axis dental milling machine (prograMill PM7). 39 crowns (VSCP, E, C; n = 13) were designed and fabricated. Internal/marginal adaptation, precision, and trueness were assessed via die scans with/without a fit checker. Dimensional discrepancies were determined by superimposing the scans. One-way ANOVA (α = 0.05) analyzed the results. No significant differences were found in internal fit or marginal adaptation between groups. However, group E exhibited the best fit (axial: 82.9 µm). Trueness differed significantly (p < 0.05) across all groups and areas. Group E had the highest trueness (intaglio: 25.8 µm), while VSCP had the lowest (marginal: 31.9 µm). Precision varied significantly within the occlusal area of printed groups (highest for C: 17.8 µm) and the marginal area between printed/milled (VSCP vs. E) and C vs. E (lowest for E: 20.5 µm, highest for VSCP: 27.9 µm). In conclusion, both milled and 3D-printed crowns achieved comparable internal fit and marginal adaptation. However, group E displayed superior fit and trueness. While C exhibited higher occlusal precision, E had higher marginal precision. These findings suggest the potential for 3D-printed hybrid polymer crowns, warranting further investigation.
Assessing Popper Purity—Implications for the Regulation and Recreational Use of Alkyl Nitrites
Authors: Makarewicz Nathan S. , Albertson Brent G. , Sia Twan , Aggarwal Anuj
Published: September 2024

Alkyl nitrites (“poppers”) are a diverse class of volatile chemical compounds with a varied legal and medical history. Though once commonly prescribed to treat angina, popper use is now almost exclusively recreational. Currently, poppers are widely available and sold legally under labels like “solvent cleaner”, despite marketing suggesting they are meant to be consumed. As a result, there is little incentive for producers to implement robust quality controls to protect users. In this study, nine common popper brands were analyzed using hydrogen-1 and carbon-13 nuclear magnetic resonance spectroscopy to assess the presence of impurities. Physical labels on all nine samples indicated the contents were “pure” isobutyl nitrite, despite contradictory online marketing in several cases. Spectral results showed isobutyl nitrite was present in all popper samples. However, there was evidence that various unlabeled compounds were also present in all samples. The identity and concentration of these contaminants were not clear, but the seemingly ubiquitous presence of impurities and lack of consistency in the tested samples are concerning and may represent a threat to users’ health. We hope the results of this study draw attention to the potential dangers of recreational popper use and the need to reassess how these compounds are regulated.
Does the Maximum Initial Beam Energy for Proton Therapy Have to Be 230 MeV?
Authors: Beltran Chris J. , Perales Alvaro , Furutani Keith M.
Published: September 2024

Proton therapy is increasingly widespread and requires an accelerator to provide the high energy protons. Most often, the accelerators used for proton therapy are cyclotrons and the maximum initial beam energy (MIBE) is about 230 MeV or more to be able to achieve a range of approximately 30 cm in water. We ask whether such a high energy is necessary for adequate dosimetry for pathologies to be treated with proton beams. Eight patients of different clinical sites (brain, prostate, and head and neck cancers) were selected to conduct this study. We analyzed the tumor dose coverage and homogeneity, as well as healthy tissue protection for MIBE values of 120, 160, 180, 200 and 230 MeV. For each patient, a proton plan was developed using the particular MIBE and then using multifield optimization (MFO). In this way, 34 plans in total were generated to fulfill the unique clinical goals. This study found that MIBE of 120 MeV for brain tumors; 160 MeV for head and neck cancer; and remarkably, for prostate cancer, only 160 MeV for one patient case and 180 MeV for the remainder satisfied the clinical goals (words: 187 < approx. 200 words or less)
The Relationship between Proinflammatory Molecules and PD-L1 in Patients with Obesity Who Underwent Gastric Sleeve Surgery—A Pilot Study
Authors: Cucoreanu Ciprian , Muresan Ximena Maria , Tigu Adrian-Bogdan , Nistor Madalina , Moldovan Radu-Cristian , Pralea Ioana-Ecaterina , Iacobescu Maria , Iuga Cristina-Adela , Constantinescu Catalin , Dindelegan George-Calin , Ciuce Constatin
Published: September 2024

In the last few decades, obesity played a pivotal role by having a high impact on global economic and health systems due to its associated diseases, with cardiovascular, respiratory, musculoskeletal, oncological, mental, and social implications. One of the most incriminated physiopathological mechanisms in obesity is chronic inflammation. The primary goal of this pilot study was to determine the molecular aspects of inflammation among patients with obesity compared to participants with a normal BMI (≤25 kg/m2), as well as within a smaller subset of obese individuals who have been evaluated three months following sleeve gastrectomy. The research employs conventional blood tests and plasma measurements of particular molecules, such as proinflammatory cytokines and proteins that play critical roles in immune and inflammatory regulation. The results revealed a promising kinetic effect after bariatric surgery on IL-18, MCP-1, and PD-L1 molecules. The proinflammatory makers IL-18 (p = 0.006) and MCP-1 (p = 0.035) were elevated in the obese group compared to the control, while the follow-up group displayed lower levels of these molecules. Commonly investigated in oncology related studies, PD-L1 was recently linked to adipose tissue gain and its associated inflammatory effect. Until now, there is no clinical evidence for the relationship between circulating PD-L1 and proinflammatory markers derived from low-grade inflammation of the adipose tissue. The circulating PD-L1 levels were significantly lowered in the obese group compared to the control (p = 0.049), and after sleeve gastrectomy, the PD-L1 level increased. The present study is the first investigating this type of crosstalk and its potential involvement in bariatric patient management.
A Financial Stability Model for Iraqi Companies
Authors: Abdlkareem Ibrahim Narjis , Salehi Mahdi , Amran Naji Al-Refiay Hussen , Lari Dashtbayaz Mahmoud
Published: September 2024

The current study aims to develop a financial stability model in Iraq; after reviewing the relevant literature and sources related to financial stability and considering Iraq’s social, economic, political, and cultural conditions, a conceptual model and a research questionnaire have been developed. Based on the developed conceptual model, macro variables at the level of the economy, micro variables at the level of companies, the environmental variables of companies, and corporate governance have been selected as model dimensions. Each dimension has several components, including several indicators; 39 indicators were measured through questions in 2024. The research questionnaire was subjected to the opinion of 21 experts with sufficient experimental and academic records on this subject, and by using the Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods, the results were analyzed, and the final model was extracted. In this model, the scientific method used to analyze the results determines the weight of each dimension, component, and indicator. The results of this research show that the dimensions of corporate governance, the variables of the company environment, micro variables at the company level, and macro variables at the economic level with coefficients of 0.345, 0.251, 0.236, and 0.168, respectively, have the most significant impact on the ranking of the company’s financial stability. So far, research has yet to be conducted to present the financial stability model of Iraqi companies. Therefore, the present research is one of the first studies in this respect, which presents a model both qualitatively (by designing a questionnaire and conceptual model) and quantitatively (through a mathematical model) to measure financial stability that can help the development of science and knowledge in this field.
Prediction of Flavor Potential of Ocimum basilicum L. Side-Stream Phytoconstituents, Using Liquid Chromatography–Tandem Mass Spectrometry Analysis and In Silico Techniques
Authors: Kritsi Eftichia , Tsiaka Thalia , Boroboka Anna , Koletsou Garyfallia , Theofilatos Spyridon , Maggenaki Artemis , Christodoulou Paris , Ladika Georgia , Tsiantas Konstantinos , Sotiroudis Georgios , Sinanoglou Vassilia J.
Published: September 2024

Although post-distillation side-streams of basil (Ocimum basilicum L.) pose significant economic and environmental challenges, they also bring forth new opportunities in the flavor industry. Thus, the objective of the current study was to assess the phenolic profile of basil side-stream extracts to identify key compounds and to evaluate their taste properties, using liquid chromatography–tandem mass spectrometry (LC-MS/MS) analysis, flavor prediction tools and molecular docking. In particular, 52 phytoconstituents, mainly phenolic acids, salvianolic acids, flavonoids and fatty acids derivatives, were elucidated in the side-streams of two different basil varieties (Minimum and Genovese) harvested and distilled in early and late autumn, highlighting the effect of pre-harvest factors on basil’s phenolic fingerprint. Furthermore, the results of tests undertaken using taste prediction tools showed that most of the identified compounds were very likely to taste bitter, while six of them (caffeoylferuloyltartaric acid, isoquercetin, lithospermic acid A, sagerinic acid, salvianolic acids C and F) presented a high bitterant capacity (70–90%). Moreover, according to molecular docking studies, these compounds exhibited a stronger binding affinity to the hTAS2R46 bitter receptor compared to its known agonist, strychnine. This outcome and consequently their bitterness were mainly attributed to interactions with Glu265, Thr180 and/or Trp88 through the formation of direct hydrogen bonds. Therefore, the present results provide insights into the taste profiles of basil side-streams, leading to more sustainable and innovative uses of aromatic herbs residues.
Towards Next-Generation Urban Decision Support Systems through AI-Powered Construction of Scientific Ontology Using Large Language Models—A Case in Optimizing Intermodal Freight Transportation
Authors: Tupayachi Jose , Xu Haowen , Omitaomu Olufemi A. , Camur Mustafa Can , Sharmin Aliza , Li Xueping
Published: September 2024

The incorporation of Artificial Intelligence (AI) models into various optimization systems is on the rise. However, addressing complex urban and environmental management challenges often demands deep expertise in domain science and informatics. This expertise is essential for deriving data and simulation-driven insights that support informed decision-making. In this context, we investigate the potential of leveraging the pre-trained Large Language Models (LLMs) to create knowledge representations for supporting operations research. By adopting ChatGPT-4 API as the reasoning core, we outline an applied workflow that encompasses natural language processing, Methontology-based prompt tuning, and Generative Pre-trained Transformer (GPT), to automate the construction of scenario-based ontologies using existing research articles and technical manuals of urban datasets and simulations. From these ontologies, knowledge graphs can be derived using widely adopted formats and protocols, guiding various tasks towards data-informed decision support. The performance of our methodology is evaluated through a comparative analysis that contrasts our AI-generated ontology with the widely recognized pizza ontology, commonly used in tutorials for popular ontology software. We conclude with a real-world case study on optimizing the complex system of multi-modal freight transportation. Our approach advances urban decision support systems by enhancing data and metadata modeling, improving data integration and simulation coupling, and guiding the development of decision support strategies and essential software components.
Forecasting Population Migration in Small Settlements Using Generative Models under Conditions of Data Scarcity
Authors: Zakharov Kirill , Aghajanyan Albert , Kovantsev Anton , Boukhanovsky Alexander
Published: September 2024

Today, the problem of predicting population migration is essential in the concept of smart cities for the proper development planning of certain regions of the country, as well as their financing and landscaping. In dealing with population migration in small settlements whose population is below 100,000, data collection is challenging. In countries where data collection is not well developed, most of the available data in open access are presented as part of textual reports issued by authorities in municipal districts. Therefore, the creation of a more or less adequate dataset requires significant efforts, and despite these efforts, the outcome is far from ideal. However, for large cities, there are typically aggregated databases maintained by authorities. We used them to find out what factors had an impact on the number of people who arrived or departed the city. Then, we reviewed several dozens of documents to mine the data of small settlements. These data were not sufficient to solve machine learning tasks, but they were used as the basis for creating a synthetic sample for model fitting. We found that a combination of two models, each trained on synthetic data, performed better. A binary classifier predicted the migration direction and a regressor estimateed the number of migrants. Lastly, the model fitted with synthetics was applied to the other set of real data, and we obtained good results, which are presented in this paper.
Theorising Pandemic Necropolitics as Evil: Thinking Inequalities, Suffering, and Vulnerabilities with Arendt
Authors: Christou Anastasia
Published: September 2024

A conceptualisation of the COVID-19 pandemic through the analytic lens of a ‘necropolitics as evil’ brings to the fore Hannah Arendt’s theorisation that evil is both an expression of, and a threat to, humanity and its plurality as an intersectional assemblage, and by extension as freedom in political action. Arendt accepts that while evil—as an expression of our humanity—can never be eradicated, it must—as a threat to our common humanity—be confronted. From this perspective, the functioning of race, gender, and wider structural inequalities as operational hinges of COVID-19 capitalism required spaces for resistance and change within the political economy of global inequalities during the recent pandemic. This (concept) paper explores such a conceptualisation through stories of the pandemic and with a particular focus on Indigenous people, marginalised groups such as migrants and asylum seekers, as well as the homeless. It is through the viral logics of cytopathic COVID-19 capitalisms that we confront and resist theoretical pathologies by re-theorising evil as conceptual currency to confront this conjuncture, critique limitations, and meaningfully translate the current societal landscape through this lens. This allows for engaging in a particular kind of reading of Arendt that is contextualised in terms of the stakes of the paper: the importance of thinking about convivialising solidarities in the ongoing pandemic that has been perpetuated by ‘evil political formations/evil governance’ under capitalism, and as such, the structural pathologies that exacerbate COVID-19’s deathly effects.
Decarbonizing Industrial Steam Generation Using Solar and Wind Power in a Constrained Electricity Network
Authors: Meybodi Mehdi Aghaei , Beath Andrew C.
Published: September 2024

Australia aims to achieve net zero emissions by 2050, with an interim target of reducing emissions to 43% below 2005 levels by 2030. Electrification of industry processes currently reliant on fossil fuels is a necessary step to achieve these emission reduction goals. This study investigates electrification of steam generation relevant to major industrial operations in the southwest of Western Australia using different renewable energy input levels. The designed system incorporates thermal storage to ensure continuous steam generation. The optimized technology mix, including wind, PV, and concentrated solar thermal (CST) systems for each renewable energy input target, is presented. The optimization process also identifies optimal locations for new renewable energy plants. In summary, the optimization tends towards favouring the development of large CST plants near a demand point. This avoids the use of the transmission network by direct use of the CST system for heating of the storage media, to address the costs and efficiency reductions arising from electrical heating, but the scope of CST use is expected to be limited by site constraints. The levelized cost of heat (LCOH) for the studied renewable energy input targets (i.e., 30–90%) ranges from 15.34 to 36.92 AUD/GJ. This is promising for the 30% renewable energy target, as future natural gas prices in Western Australia are likely to match or exceed the expected LCOH. Cost reductions for renewable generation and storage technologies with further implementation at a large scale in the future may result in more competitive LCOH at higher decarbonization levels, but it is likely that additional technologies will be required for cost competitiveness at very high decarbonization levels.
Short-Term Load Forecasting for Regional Smart Energy Systems Based on Two-Stage Feature Extraction and Hybrid Inverted Transformer
Authors: Huang Zhewei , Yi Yawen
Published: September 2024

Accurate short-term load forecasting is critical for enhancing the reliability and stability of regional smart energy systems. However, the inherent challenges posed by the substantial fluctuations and volatility in electricity load patterns necessitate the development of advanced forecasting techniques. In this study, a novel short-term load forecasting approach based on a two-stage feature extraction process and a hybrid inverted Transformer model is proposed. Initially, the Prophet method is employed to extract essential features such as trends, seasonality and holiday patterns from the original load dataset. Subsequently, variational mode decomposition (VMD) optimized by the IVY algorithm is utilized to extract significant periodic features from the residual component obtained by Prophet. The extracted features from both stages are then integrated to construct a comprehensive data matrix. This matrix is then inputted into a hybrid deep learning model that combines an inverted Transformer (iTransformer), temporal convolutional networks (TCNs) and a multilayer perceptron (MLP) for accurate short-term load forecasting. A thorough evaluation of the proposed method is conducted through four sets of comparative experiments using data collected from the Elia grid in Belgium. Experimental results illustrate the superior performance of the proposed approach, demonstrating high forecasting accuracy and robustness, highlighting its potential in ensuring the stable operation of regional smart energy systems.
Surface Migration of Fatty Acid to Improve Sliding Properties of Hypromellose-Based Coatings
Authors: Brogly Maurice , Bistac Sophie , Fahs Armand
Published: September 2024

Hypromellose (HM) is a cellulose-derived polymer of pharmaceutical grade that forms easily from thin films and coatings. As few studies concern HM-formulated systems, this study focuses on the formulation of HM films by incorporating a fatty acid additive, making it possible to control surface properties such as wetting and slip behavior for pharmaceutical or medical applications. The results show that the addition of a very small amount (from 0.1 to 1% w/w) of fatty acid additive reduces HM film affinity for water and water vapor transmission rate, while film appearance and gloss are rather preserved. Surface properties were probed using wettability measurements, Tapping Mode AFM, ATR-FTIR spectrometry, and friction measurements. Tapping Mode AFM images show that the surface roughness reduces by up to 65%. Wettability results show that the surface energy decreases from 43 to 31 mJ.m−2, whereas surface FTIR spectrometry measurements demonstrate that fatty acid molecules migrate on the surface of the formulated films, the driving force being the microphase separation between the polar HM macromolecules and the hydrophobic additive, leading to the formation of a weak boundary layer with poor cohesion. As a consequence, the surface coefficient of friction significantly reduces from 0.38 to 0.08, and fatty acid molecules thus act as a lubricant, improving the sliding properties of HM-based coatings.
State of the Art Synthesis of Ag-ZnO-Based Nanomaterials by Atmospheric Pressure Microplasma Techniques
Authors: Khalid Ayesha , Naeem Muhammad , Atrooz Omar , Mozafari M. R. , Anari Fatemeh , Taghavi Elham , Rashid Umair , Aziz Bushra
Published: September 2024

Atmospheric pressure microplasma is a simple, cost-effective, efficient, and eco-friendly procedure, which is superior to the traditional nanomaterials synthesis techniques. It generates high yields and allows for a controlled growth rate and morphology of nanomaterials. The silver (Ag) nanomaterials, with their unique physical and chemical properties, exhibit outstanding antibacterial and antifungal properties. Similarly, zinc oxide (ZnO) nanomaterials, known for their low toxicity and relatively lower cost, find wide applications in wound repair, bone healing, and antibacterial and anticancer applications. The use of core–shell nanomaterials in certain situations where some nanoparticles can cause serious harm to host tissues or organs is a testament to their potential. A benign material is coated over the core to reduce toxicity in these cases. This review compares the numerous configurations of microplasma systems used for synthesizing nanomaterials and their use in producing Ag, ZnO, and their core–shell (Ag-ZnO) nanomaterials for biomedical applications. The summary also includes the effect of control parameters, including cathode diameter, gas flow rate, precursor concentration, voltage, and current, on the nanomaterial’s characteristics and applications. In addition, it provides a research gap in the synthesis of Ag, ZnO, and core–shell nanomaterials by this technique, as well as the development and limitations of this technique and the use of these nanoparticles for biomedical applications.
Explicit Form for the Most General Lorentz Transformation Revisited
Authors: Haber Howard E.
Published: September 2024

Explicit formulae for the 4×4 Lorentz transformation matrices corresponding to a pure boost and a pure three-dimensional rotation are very well known. Significantly less well known is the explicit formula for a general Lorentz transformation with arbitrary non-zero boost and rotation parameters. We revisit this more general formula by presenting two different derivations. The first derivation (which is somewhat simpler than previous ones appearing in the literature) evaluates the exponential of a 4×4 real matrix A, where A is a product of the diagonal matrix diag(+1,−1,−1,−1) and an arbitrary 4×4 real antisymmetric matrix. The formula for expA depends only on the eigenvalues of A and makes use of the Lagrange interpolating polynomial. The second derivation exploits the observation that the spinor product η†σ¯μχ transforms as a Lorentz four-vector, where χ and η are two-component spinors. The advantage of the latter derivation is that the corresponding formula for a general Lorentz transformation Λ reduces to the computation of the trace of a product of 2×2 matrices. Both computations are shown to yield equivalent expressions for Λ.
Sum-Rate Maximization for a Hybrid Precoding-Based Massive MIMO NOMA System with Simultaneous Wireless Information and Power Transmission
Authors: Sur Samarendra Nath , Tran Huu Q. , Imoize Agbotiname Lucky , Kandar Debdatta , Nandi Sukumar
Published: September 2024

Non-orthogonal multiple access (NOMA) has emerged as a key enabling technology in the realm of millimeter-wave (mmWave) massive MIMO (mMIMO) systems for enhancing spectral efficiency (SE). Furthermore, it is believed that simultaneous wireless information and power transmission (SWIPT) will allow for the system’s energy efficiency (EE) to be maximised. The effectiveness of the mmWave mMIMO-NOMA system along with SWIPT has been examined in this article under multi-user (MU) scenarios. This paper’s major goal is to construct a low-complexity hybrid-precoder (HP) while taking into account the sub-connected (SC) architecture. The linear precoder is a computationally demanding technique as a result of the matrix inversion. The authors of this paper have suggested a symmetric sequential over-relaxation (SSOR) complex regularised zero-forcing (CRZF) linear precoder. The power distribution for the mmWave mMIMO-NOMA system and power splitting factors for SWIPT are jointly tuned to maximize the sum rate along with the suggested SSOR-CRZF precoder. In regards to complexity, SE, and EE, the SSOR-CRZF-HP surpasses conventional linear precoders.
The Combination of Presurgical Cortical Gray Matter Volumetry and Cerebral Perfusion Improves the Efficacy of Predicting Postoperative Cognitive Impairment of Elderly Patients
Authors: Zhou Weijian , Zhu Binbin , Weng Yifei , Chen Chunqu , Ni Jiajing , Shen Wenqi , Lan Wenting , Wang Jianhua
Published: September 2024

Background: Postoperative cognitive dysfunction (POCD) is a common complication of the central nervous system in elderly surgical patients. Structural MRI and arterial spin labelling (ASL) techniques found that the grey matter volume and cerebral perfusion in some specific brain areas are associated with the occurrence of POCD, but the results are inconsistent, and the predictive accuracy is low. We hypothesised that the combination of cortical grey matter volumetry and cerebral blood flow yield higher accuracy than either of the methods in discriminating the elderly individuals who are susceptible to POCD after abdominal surgery. Materials and Methods: Participants underwent neuropsychological testing before and after surgery. Postoperative cognitive dysfunction (POCD) was defined as a decrease in cognitive score of at least 20%. ASL-MRI and T1-weighted imaging were performed before surgery. We compared differences in cerebral blood flow (CBF) and cortical grey matter characteristics between POCD and non-POCD patients and generated receiver operating characteristic curves. Results: Out of 51 patients, 9 (17%) were diagnosed with POCD. CBF in the inferior frontal gyrus was lower in the POCD group compared to the non-POCD group (p < 0.001), and the volume of cortical grey matter in the anterior cingulate gyrus was higher in the POCD group (p < 0.001). The highest AUC value was 0.973. Conclusions: The combination of cortical grey matter volumetry and cerebral perfusion based on ASL-MRI has improved efficacy in the early warning of POCD to elderly abdominal surgical patients.
Health-Related Quality of Life of People Living with HIV: Contributions of Emotion Regulation and Self-Compassion
Authors: Chukwuorji JohnBosco Chika , Odi Chinonso Perpetual , Chike-Okoli Adaeze , Morah Nwando Maryann , Osondu Oluchi Miracle , Rukmi Dwi Kartika , Victor-Aigbodion Vera , Eze John E.
Published: September 2024

Living with chronic health conditions such as HIV has implications for health-related quality of life (HRQoL) and improving the HRQoL of people living with HIV (PLWH) is becoming increasingly important for researchers, policymakers, and health practitioners. However, there is limited research on factors that help to explain HRQoL among persons with HIV in sub-Saharan Africa. We examined the contributions of emotion regulation and self-compassion in the HRQoL of 187 PLWH (56.1% female) drawn from the HIV clinic in a specialist hospital in southeast Nigeria. They completed the Brief Version of the Difficulties in Emotion Regulation Scale (DERS-18), Self-compassion Scale, and Patient-Reported Outcome Quality of Life-HIV (PROQOL-HIV). While controlling for participants’ demographic variables, the regression results showed that self-compassion was positively associated with HRQoL. Higher difficulties in emotion regulation were not associated with HRQoL in the presence of self-compassion. The findings extend the outcomes of previous research in other parts of the world and support the notion that enhancing self-compassion interventions may shore up the HRQoL of people living with chronic health conditions. HRQoL interventions that embody culturally informed self-compassion strategies and developmental level approach are needed for the health system in sub-Saharan Africa.
Evaluation of Blood C Reactive Protein (CRP) and Neutrophil-to-Lymphocyte Ratio (NLR) Utility in Canine Epilepsy
Authors: Despa Andreea , Musteata Mihai , Solcan Gheorghe
Published: September 2024

Background: The role of neuroinflammation in epileptogenesis has been previously explored, and several biomarkers have been identified as being relevant in assessing the intensity of the inflammatory process. In human medicine, an increased C reactive protein (CRP) blood concentration and/or neutrophil-to-lymphocyte ratio (NLR) is considered a constant finding of epileptic activity. In veterinary medicine, only a few studies have been published regarding both of these topics. Hypothesis/objectives: Our aim was to assess the C reactive protein blood concentration and the neutrophil-to-lymphocyte ratio in epileptic dogs, regardless of etiology. Method: This retrospective study was based on changes in routine blood parameters in 59 dogs with epileptic activity. Results: An increased C reactive protein concentration was observed mostly in the dogs affected by structural epilepsy, and all epileptic dogs displayed abnormal neutrophil-to-lymphocyte values. Conclusions: Based on the authors’ knowledge, this is the first report regarding the NLR in epileptic dogs. Both the CRP concentration and the NLR might be considered feasible non-specific markers of the neuroinflamation involved in epileptogenesis and might be used in the diagnosis of and therapeutic approach to cluster seizures in dogs with idiopathic epilepsy and in patients with structural epilepsy. Dogs diagnosed with IEis and high CRP concentrations and NLRs may be subject to non-documented cluster seizures. Both CRP and the NLR have limited diagnostic value in dogs with reactive seizures.
Fuzzy Logic-Based Autonomous Lane Changing Strategy for Intelligent Internet of Vehicles: A Trajectory Planning Approach
Authors: He Chao , Jiang Wenhui , Li Junting , Wei Jian , Guo Jiang , Zhang Qiankun
Published: September 2024

The autonomous lane change maneuver is a critical component in the advancement of intelligent transportation systems (ITS). To enhance safety and efficiency in dynamic traffic environments, this study introduces a novel autonomous lane change strategy leveraging a quintic polynomial function. To optimize the trajectory, we formulate an objective function that balances the time required for lane changes with the peak acceleration experienced during the maneuver. The proposed method addresses key challenges such as driver discomfort and prolonged lane change durations by considering the entire lane change process rather than just the initiation point. Utilizing a fifth-order polynomial for trajectory planning, the strategy ensures smooth and continuous vehicle movement, reducing the risk of collisions. The effectiveness of the method is validated through comprehensive simulations and real-world vehicle tests, demonstrating significant improvements in lane change performance. Despite its advantages, the model requires further refinement to address limitations in mixed traffic conditions. This research provides a foundation for developing intelligent vehicle systems that prioritize safety and adaptability.
Ethical Considerations of the Trolley Problem in Autonomous Driving: A Philosophical and Technological Analysis
Authors: Zhan Hao , Wan Dan
Published: September 2024

The trolley problem has long posed a complex ethical challenge in the field of autonomous driving technology. By constructing a general trolley problem model, this paper demonstrates that the default loss assumption is a necessary condition for the occurrence of trolley problems. However, an analysis of the differences between classical trolley problems and autonomous driving scenarios reveals that this assumption is not supported in the design of autonomous driving systems. This paper first provides a detailed definition of the trolley problem within the context of autonomous driving technology and establishes a general trolley problem model to better analyze the issue. We then discuss two solutions: the first solution acknowledges the existence of the trolley problem in the context of autonomous driving technology but does not recognize the existence of a “most acceptable decision”; the second solution denies that decision-makers are limited to a finite number of decisions, each resulting in a corresponding loss. Based on the second solution, we propose a “sufficient time” solution, illustrating that the interaction between planning and control systems in autonomous driving can avoid ethical dilemmas similar to the trolley problem. Finally, we analyze from a philosophical perspective why the trolley problem does not arise in the context of autonomous driving technology and discuss the ethical responsibilities associated with autonomous driving. The design goal of autonomous driving technology should be a zero-accident rate, which contradicts the unavoidable loss assumption in the traditional trolley problem. Therefore, the existence of the trolley problem is unrealistic in the practical application of autonomous driving technology.
Insights on the Optimization of Short- and Long-Term Maintenance Decisions for Floating Offshore Wind Using Nested Genetic Algorithms
Authors: Vieira Mário , Djurdjanovic Dragan
Published: September 2024

The present research explores the optimization of maintenance strategies for floating offshore wind (FOW) farms using nested genetic algorithms. The primary goal is to provide insights on the decision-making processes required for both immediate and strategic maintenance planning, crucial for the viability and efficiency of FOW operations. A nested genetic algorithm was coupled with discrete-event simulations in order to simulate and optimize maintenance scenarios influenced by various operational and environmental parameters. The study revealed that short-term maintenance timing is significantly influenced by wind conditions, with higher electricity prices justifying on-site spare parts storage to mitigate operational disruptions, suggesting economic incentives for maintaining on-site inventory of spare parts. Long-term strategic findings emphasized the impact of planned intervals between inspections on financial outcomes, identifying optimal strategies that balance operational costs with energy production efficiency. Ultimately, this study highlights the importance of integrating sophisticated predictive models for failure detection with real-time operational data to enhance maintenance decision-making in the evolving landscape of offshore wind energy, where future farms are likely to operate farther from onshore facilities and under potentially highly varying market conditions in terms of electricity prices.