bluuebunny/crossref_metadata_2025 huggingface dataset:
Algorithm for Topology Search Using Dilution of Precision Criterion in Ultra-Dense Network Positioning Service Area
Authors: Fokin Grigoriy , Koucheryavy Andrey
Published: May 2023

User equipment (UE) location estimation in emerging 5G/B5G/6G Ultra-Dense Networks (UDNs) is a breakthrough technology in future wireless info-communication ecosystems. Apart from communication aspects, network infrastructure densification promises significant improvement in UE positioning accuracy. Unlike networks of previous generations, an increased number of gNodeBs (gNBs) per unit area and/or volume in UDNs allows to perform measurements for UE positioning only with those base stations whose topologies are most suitable from the geometric point of view. Quantitative measurements of gNB topology suitability include horizontal (HDOP), vertical (VDOP), and position (PDOP) dilution of the precision (DOP) criteria on the plane, in height, and in space, respectively. In the current work, we formalize a set of methods for gNB topology search using time of arrival (TOA), time difference of arrival (TDOA), angle of arrival (AOA), and combined TOA–AOA and TDOA-AOA measurements. The background of the topology search using DOP criteria is a significantly increased number of gNBs per unit volume in UDNs. Based on a simulation, we propose a novel approach for a topology search in a positioning service area, resulting in a PDOP less than one for the Gazprom Arena with only five gNBs. The contribution of the current research includes algorithm and software for an iterative search of all possible gNB and UE locations in space, minimizing UE geometric DOP. The practical application of the algorithm is the gNB topology substantiation for the given positioning scenarios in 5G/B5G/6G UDNs.
Influence of Flow-Gas Composition on Reaction Products of Thermally Treated NMC Battery Black Mass
Authors: Stallmeister Christin , Friedrich Bernd
Published: May 2023

The recycling of lithium-ion batteries (LIBs) is becoming increasingly important regarding the expansion of electromobility and aspects of raw material supply. Pre-treatment and liberation are crucial for a sufficient recovery of all relevant materials from LIBs. Organic removal and phase transformations by thermal pre-treatment are beneficial in many respects. This study deals with the influence of flow-gas composition on reaction products and water-based lithium recovery after thermal treatment. Therefore, a spent NMC black mass was thermally treated at 610 °C in a moved bed batch reactor under an N2 atmosphere and mixtures of N2 with 2.5% and 5% O2. Since the phase transformation of the lithium content to Li2CO3 is targeted for water leaching, a treatment under a CO2 atmosphere was studied as well. The resulting off-gas was analyzed by FTIR, and the black mass was characterized by XRD. Afterward, water washing of the black mass was carried out for selective lithium recovery. The gained lithium product was analyzed for the purity and phases present. The addition of O2 resulted in reduced reduction reactions of lithium metal oxides and lower Li-yields in the water leaching compared to the other two atmospheres. In the case of CO2, the formation of Li2CO3 is favored compared to LiF, but the Li-yield of 56% is comparable to N2 treatment.
Multiple-Beam Steering Using Graphene-Based Coding Metasurfaces
Authors: Zheng Bin , Rao Xin , Shan Yuyu , Yu Chuandong , Zhang Jingke , Li Na
Published: May 2023

Recently, the coding metasurface has gained significant attention due to its exceptional potential in controlling electromagnetic (EM) waves with the rapid development of wireless communication systems. Meanwhile, graphene shows tremendous promise for the implementation of reconfigurable antennas due to its high tunable conductivity and its unique property that makes it a very suitable material for realizing steerable coded states. In this paper, we first propose a simple structured beam reconfigurable millimeter wave (MMW) antenna using a novel graphene-based coding metasurface (GBCM). Different from the previous method, its coding state can be manipulated by altering the sheet impedance of graphene instead of bias voltage. Then, we design and simulate several most popular coding sequences, including dual-, quad-and single-beam-generated implement, 30° beam deflection, as well as a random coding sequence for radar cross-section (RCS) reduction. The theoretical and simulation results show that graphene has great potential for MMW manipulation applications, which lay a foundation for the subsequent development and fabrication of GBCM.
Chemical Characterization and Cytotoxic and Antioxidant Activity Evaluation of the Ethanol Extract from the Bulbs of Pancratium maritimun Collected in Sicily
Authors: Cicio Adele , Sut Stefania , Dall’Acqua Stefano , Bruno Maurizio , Luparello Claudio , Serio Rosa , Zizzo Maria Grazia
Published: May 2023

P. maritimum L., belonging to the Amaryllidaceae family, is a species that grows on beaches and coastal sand dunes mainly on both sides of the Mediterranean Sea and Black Sea, the Middle East, and up to the Caucasus region. It has been largely investigated due to its several interesting biological properties. With the aim of providing new insights into the phytochemistry and pharmacology of this species, the ethanolic extract of the bulbs from a local accession, not previously studied, growing in Sicily (Italy), was investigated. This chemical analysis, performed by mono- and bi-dimensional NMR spectroscopy, as well as LC-DAD-MSn, allowed to identify several alkaloids, three of which were never detected in the genus Pancratium. Furthermore, the cytotoxicity of the preparation was assessed in differentiated human Caco-2 intestinal cells by trypan blue exclusion assay, and its antioxidant potential was evaluated using the DCFH-DA radical scavenging method. The results obtained demonstrate that P. maritimum bulbs’ extract exerts no cytotoxic effect and is able to remove free radicals at all the concentrations tested.
Determination of Minerals in Soft and Hard Cheese Varieties by ICP-OES: A Comparison of Digestion Methods
Authors: Deshwal Gaurav K. , Gómez-Mascaraque Laura G. , Fenelon Mark , Huppertz Thom
Published: May 2023

For sample preparation prior to mineral analysis, microwave digestion (~2 h) is quicker and requires lower acid volume as compared to dry (6–8 h) and wet digestion (4–5 h). However, microwave digestion had not yet been compared systematically with dry and wet digestion for different cheese matrices. In this work, the three digestion methods were compared for measuring major (Ca, K, Mg, Na and P) and trace minerals (Cu, Fe, Mn and Zn) in cheese samples using inductively coupled plasma optical emission spectrometry (ICP-OES). The study involved nine different cheese samples with moisture content varying from 32 to 81% and a standard reference material (skim milk powder). For the standard reference material, the relative standard deviation was lowest for microwave digestion (0.2–3.7%) followed by dry (0.2–6.7%) and wet digestion (0.4–7.6%). Overall, for major minerals in cheese, strong correlation was observed between the microwave and the dry and wet digestion methods (R2 = 0.971–0.999), and Bland–Altman plots showed best method agreement (lowest bias), indicating the comparability of all three digestion methods. A lower correlation coefficient, higher limits of agreement and higher bias of minor minerals indicate possibilities of measurement error.
Advanced Algorithm for Reliable Quantification of the Geometry and Printability of Printed Patterns
Authors: Lee Jongsu , Kim Chung Hwan
Published: May 2023

In nanoparticle-based printed electronic devices, the printability of the patterns constituting the device are crucial factors. Although many studies have investigated the printability of patterns, only a few have analyzed and established international standards for measuring the dimensions and printability of shape patterns. This study introduces an advanced algorithm for accurate measurement of the geometry and printability of shape patterns to establish an international standard for pattern dimensions and printability. The algorithm involves three core concepts: extraction of edges of printed patterns and identification of pixel positions, identification of reference edges via the best-fitting of the shape pattern, and calculation of different pixel positions of edges related to reference edges. This method enables the measurement of the pattern geometry and printability, including edge waviness and widening, while considering all pixels comprising the edges of the patterns. The study results revealed that the rectangle and circle patterns exhibited an average widening of 3.55% and a maximum deviation of 1.58%, based on an average of 1662 data points. This indicates that the algorithm has potential applications in real-time pattern quality evaluation, process optimization using statistical or AI-based methods, and foundation of International Electrotechnical Commission standards for shape patterns.
Lower-Strength Alcohol Products and Public Health
Authors: Anderson Peter
Published: May 2023

The World Health Organization has called on economic operators to “substitute, whenever possible, higher-alcohol products with no-alcohol and lower-alcohol products in their overall product portfolios, with the goal of decreasing the overall levels of alcohol consumption in populations and consumer groups, while avoiding the circumvention of existing regulations for alcoholic beverages and the targeting of new consumer groups with alcohol marketing, advertising and promotional activities” (see [...]
Dietary, Lifestyle, and Children Health
Authors: Yu Xiaoran , Zou Zhiyong
Published: May 2023

Childhood is a critical period for the development of a healthy lifestyle and the prevention of chronic diseases in adulthood [...]
Does the Mediterranean Diet Have Any Effect on Lipid Profile, Central Obesity and Liver Enzymes in Non-Alcoholic Fatty Liver Disease (NAFLD) Subjects? A Systematic Review and Meta-Analysis of Randomized Control Trials
Authors: Del Bo’ Cristian , Perna Simone , Allehdan Sabika , Rafique Ayesha , Saad Sara , AlGhareeb Fahad , Rondanelli Mariangela , Tayyem Reema F. , Marino Mirko , Martini Daniela , Riso Patrizia
Published: May 2023

The effectiveness of the Mediterranean diet (MD) in non-alcoholic fatty liver disease (NAFLD) subjects has been evaluated in several randomized controlled trials (RCTs). This systematic review and meta-analysis aimed to evaluate the overall effects of MD intervention in a cohort of NAFLD patients targeting specific markers such as central obesity, lipid profile, liver enzymes and fibrosis, and intrahepatic fat (IHF). Google Scholar, PubMed, and Scopus were explored to collect relevant studies from the last 10 years. RCTs with NAFLD subjects were included in this systematic review with a mean intervention duration from 6 weeks to 1 year, and different intervention strategies, mainly including energy restriction MD (normal or low glycaemic index), low-fat MD with increased monounsaturated and polyunsaturated fatty acids, and increased exercise expenditure. The outcomes measured in this meta-analysis were gamma-glutamyl transferase (GGT), alanine aminotransferase (ALT), total cholesterol (TC), waist circumference (WC), and liver fibrosis. Ten randomized controlled trials, which involved a total of 737 adults with NAFLD, were included. According to the results, the MD seems to decrease the liver stiffness (kPa) by –0.42 (CI95% –0.92, 0.09) (p = 0.10) and significantly reduce the TC by –0.46 mg/dl (CI95% –0.55, −0.38) (p = 0.001), while no significant findings were documented for liver enzymes and WC among patients with NAFLD. In conclusion, the MD might reduce indirect and direct outcomes linked with NAFLD severity, such as TC, liver fibrosis, and WC, although it is important to consider the variations across trials. Further RCTs are necessary to corroborate the findings obtained and provide further evidence on the role of the MD in the modulation of other disorders related to NAFLD.
Parsing the Q-Markers of Baoyin Jian to Treat Abnormal Uterine Bleeding by High-Throughput Chinmedomics Strategy
Authors: Li Qiuhan , Ren Junling , Yang Le , Sun Hui , Zhang Xiwu , Yan Guangli , Han Ying , Wang Xijun
Published: May 2023

Abnormal uterine bleeding (AUB) is a common and frequently occurring disease in gynecology, seriously threatening women’s health. Baoyin Jian (BYJ) is a classical prescription for treating AUB. However, the lack of quality control standards of BYJ for AUB have limited the development and applications of BYJ. This experiment aims to explore the mechanism of action and screen the quality markers (Q-markers) of BYJ against AUB through the Chinmedomics strategy to improve the quality standards of Chinese medicine and provide scientific basis for its further development. BYJ has hemostatic effects in rats, as well as the ability to regulate the coagulation system following incomplete medical abortion. According to the results of histopathology, biochemical indexes and urine metabolomics, a total of 32 biomarkers of ABU in rats were identified, 16 of which can be significantly regulated by BYJ. Using traditional Chinese medicine (TCM) serum pharmacochemistry technology, 59 effective components were detected in vivo, of which 13 were highly correlated with efficacy, and 9 components, namely catalpol, rehmannioside D, paeoniflorin, berberine, phellodendrine, baicalin, asperosaponinVI, liquiritin, and glycyrrhizic acid, were screened out as the Q-markers of BYJ based on the “Five Principles” of Q-markers. In sum, BYJ can effectively alleviate abnormal bleeding symptoms and metabolic abnormalities in AUB rats. The study shows that Chinmedomics is an effective tool for screening Q-markers and provides scientific support for the further development and clinical use of BYJ.
3D Printing Technology as a Promising Tool to Design Nanomedicine-Based Solid Dosage Forms: Contemporary Research and Future Scope
Authors: Ahmad Javed , Garg Anuj , Mustafa Gulam , Mohammed Abdul Aleem , Ahmad Mohammad Zaki
Published: May 2023

3D printing technology in medicine is gaining great attention from researchers since the FDA approved the first 3D-printed tablet (Spritam®) on the market. This technique permits the fabrication of various types of dosage forms with different geometries and designs. Its feasibility in the design of different types of pharmaceutical dosage forms is very promising for making quick prototypes because it is flexible and does not require expensive equipment or molds. However, the development of multi-functional drug delivery systems, specifically as solid dosage forms loaded with nanopharmaceuticals, has received attention in recent years, although it is challenging for formulators to convert them into a successful solid dosage form. The combination of nanotechnology with the 3D printing technique in the field of medicine has provided a platform to overcome the challenges associated with the fabrication of nanomedicine-based solid dosage forms. Therefore, the major focus of the present manuscript is to review the recent research developments that involved the formulation design of nanomedicine-based solid dosage forms utilizing 3D printing technology. Utilization of 3D printing techniques in the field of nanopharmaceuticals achieved the successful transformation of liquid polymeric nanocapsules and liquid self-nanoemulsifying drug delivery systems (SNEDDS) to solid dosage forms such as tablets and suppositories easily with customized doses as per the needs of the individual patient (personalized medicine). Furthermore, the present review also highlights the utility of extrusion-based 3D printing techniques (Pressure-Assisted Microsyringe—PAM; Fused Deposition Modeling—FDM) to produce tablets and suppositories containing polymeric nanocapsule systems and SNEDDS for oral and rectal administration. The manuscript critically analyzes contemporary research related to the impact of various process parameters on the performance of 3D-printed solid dosage forms.
A New Fluorescence Detection Method for Tryptophan- and Tyrosine-Derived Allelopathic Compounds in Barley and Lupin
Authors: Leite Dias Sara , Garibay-Hernández Adriana , Brendel Fabian Leon , Gabriel Chavez Benjamin , Brückner Elena , Mock Hans-Peter , Franke Jakob , D’Auria John Charles
Published: May 2023

Barley (Hordeum vulgare) is one of the most widely cultivated crops for feedstock and beer production, whereas lupins (Lupinus spp.) are grown as fodder and their seeds are a source of protein. Both species produce the allelopathic alkaloids gramine and hordenine. These plant-specialized metabolites may be of economic interest for crop protection, depending on their tissue distribution. However, in high concentrations they pose a health risk to humans and animals that feed on them. This study was carried out to develop and validate a new method for monitoring these alkaloids and their related metabolites using fluorescence detection. Separation was performed on an HSS T3 column using slightly acidified water-acetonitrile eluents. Calibration plots expressed linearity over the range 0.09–100 pmol/µL for gramine. The accuracy and precision ranged from 97.8 to 123.4%, <7% RSD. The method was successfully applied in a study of the natural range of abundance of gramine, hordenine and their related metabolites, AMI, tryptophan and tyramine, in 22 barley accessions and 10 lupin species. This method provides accurate and highly sensitive chromatographic separation and detection of tryptophan- and tyrosine-derived allelochemicals and is an accessible alternative to LC-MS techniques for routine screening.
Beta vulgaris L.—A Source with a Great Potential in the Extraction of Natural Dyes Intended for the Sustainable Dyeing of Wool
Authors: Popescu Vasilica , Blaga Alexandra Cristina , Cașcaval Dan , Popescu Andrei
Published: May 2023

Beta vulgaris L. is a biennial plant easily accessible all over the world, rich in various biologically active compounds, especially a class of extremely bioactive pigments known as betalains. These dyes predominate in the pulp and peels of beetroot, which is why they can be valorized in food, medicine or in the textile industry. In this work, betalains extractions were carried out applying 3 sustainable options: (1) dissolving/solubilizing betalains in water; (2) extraction under pressure; (3) extraction assisted by an enzyme/pectinase. The obtained extracts were analyzed in the UV-Vis domain, which allowed their characterization by determining the total monomeric anthocyanins, color density (control), polymeric density and browning index. The HPLC-MS analysis highlighted the extracts composition. The colors characteristics were determined through CIELab measurements. The performances of these 3 extracts, during green dyeing (without mordants), were evaluated according to the color characteristics (L*, a*, b* and K/S) of the dyed wool samples under different conditions: pH, temperature, duration of dyeing and volume of extract and stabilizers (Vitamin E and EDTA). Betalains can be considered acid dyes, with a low affinity for wool, which in a pronounced acidic environment dye the wool in an intense, uniform way and with good resistance to washing and rubbing.
Genome-Wide Identification and Expression Analysis of Calmodulin (CaM) and Calmodulin-Like (CML) Genes in the Brown Algae Saccharina japonica
Authors: Xue Nianchao , Sun Minghui , Gai Zihan , Bai Meihan , Sun Juan , Sai Shan , Zhang Linan
Published: May 2023

Calmodulins (CaMs) and Calmodulin-like proteins (CMLs) are vital in plant growth, development, and stress responses. However, CaMs and CMLs have not been fully identified and characterized in brown algae, which has been evolving independently of the well-studied green plant lineage. In this study, whole-genome searches revealed one SjCaM and eight SjCMLs in Saccharina japonica, and one EsCaM and eleven EsCMLs in Ectocarpus sp. SjCaM and EsCaM encoded identical protein products and shared 88.59–89.93% amino acid identities with Arabidopsis thaliana AtCaMs, thereby indicating that brown algae CaMs retained a similar Ca2+ sensors function as in plants. The phylogenetic and gene structure analysis results showed that there was significant divergence in the gene sequences among brown algae CMLs. Furthermore, evolutionary analysis indicated that the function of brown alga CMLs was relatively conserved, which may be related to the fact that brown algae do not need to face complex environments like terrestrial plants. Regulatory elements prediction and the expression analysis revealed the probable functioning of SjCaM/CML genes in gametophyte development and the stress response in S. japonica. In addition, the SjCaM/SjCMLs interacting proteins and chemicals were preliminarily predicted, suggesting that SjCaM/SjCMLs might play putative roles in Ca2+/CaM-mediated growth and development processes and stimulus responses. Therefore, these results will facilitate our understanding of the evolution of brown algae CaMs/CMLs and the functional identification of SjCaM/SjCMLs.
Genetic Regulation of Mitosis–Meiosis Fate Decision in Plants: Is Callose an Oversighted Polysaccharide in These Processes?
Authors: Somashekar Harsha , Nonomura Ken-Ichi
Published: May 2023

Timely progression of the meiotic cell cycle and synchronized establishment of male meiosis in anthers are key to ascertaining plant fertility. With the discovery of novel regulators of the plant cell cycle, the mechanisms underlying meiosis initiation and progression appear to be more complex than previously thought, requiring the conjunctive action of cyclins, cyclin-dependent kinases, transcription factors, protein–protein interactions, and several signaling components. Broadly, cell cycle regulators can be classified into two categories in plants based on the nature of their mutational effects: (1) those that completely arrest cell cycle progression; and (2) those that affect the timing (delay or accelerate) or synchrony of cell cycle progression but somehow complete the division process. Especially the latter effects reflect evasion or obstruction of major steps in the meiosis but have sometimes been overlooked due to their subtle phenotypes. In addition to meiotic regulators, very few signaling compounds have been discovered in plants to date. In this review, we discuss the current state of knowledge about genetic mechanisms to enter the meiotic processes, referred to as the mitosis-meiosis fate decision, as well as the importance of callose (β-1,3 glucan), which has been unsung for a long time in male meiosis in plants.
Biological Activities and Chemical Profiles of Kalanchoe fedtschenkoi Extracts
Authors: Mejía-Méndez Jorge L. , Bach Horacio , Lorenzo-Leal Ana C. , Navarro-López Diego E. , López-Mena Edgar R. , Hernández Luis Ricardo , Sánchez-Arreola Eugenio
Published: May 2023

In this study, the leaves of Kalanchoe fedtschenkoi were consecutively macerated with hexane, chloroform, and methanol. These extracts were used to assess the bioactivities of the plant. The antimicrobial activity was tested against a panel of Gram-positive and -negative pathogenic bacterial and fungal strains using the microdilution method. The cytotoxicity of K. fedtschenkoi extracts was investigated using human-derived macrophage THP-1 cells through the MTT assay. Finally, the anti-inflammatory activity of extracts was studied using the same cell line by measuring the secretion of IL-10 and IL-6. The phytoconstituents of hexane and chloroform extracts were evaluated using gas chromatography–mass spectrometry (GC/MS). In addition, high-performance liquid chromatography (HPLC) was used to study the phytochemical content of methanol extract. The total flavonoid content (TFC) of methanol extract is also reported. The chemical composition of K. fedtschenkoi extracts was evaluated using Fourier-transform infrared spectroscopy (FTIR). Results revealed that the chloroform extract inhibited the growth of Pseudomonas aeruginosa at 150 μg/mL. At the same concentration, methanol extract inhibited the growth of methicillin-resistant Staphylococcus aureus (MRSA). Regarding their cytotoxicity, the three extracts were highly cytotoxic against the tested cell line at IC50 < 3 μg/mL. In addition, the chloroform extract significantly stimulated the secretion of IL-10 at 50 μg/mL (p < 0.01). GC/MS analyses revealed that hexane and chloroform extracts contain fatty acids, sterols, vitamin E, and triterpenes. The HPLC analysis demonstrated that methanol extract was constituted by quercetin and kaempferol derivatives. This is the first report in which the bioactivities and chemical profiles of K. fedtschenkoi are assessed for non-polar and polar extracts.
Whole-Genome Sequence Insight into the Plant-Growth-Promoting Bacterium Priestia filamentosa Strain AZC66 Obtained from Zygophyllum coccineum Rhizosphere
Authors: Khalifa Ashraf , Alsowayeh Noorah
Published: May 2023

This study aimed to isolate, screen the plant-growth-enhancing features, and explore the whole-genome sequence of AZC66 isolated from the rhizosphere of Zygophyllum coccineum and determine its biostimulating effects on the growth of cowpea under greenhouse conditions. Salkowski reagent was used to measure AZC66’s indole acetic acid production. AZC66’s inorganic phosphate solubility on Pikovskaya agar was evaluated using tricalcium phosphate. The results indicated the ability of AZC66 to fix nitrogen, produce IAA (66.33 ± 0.44 μg mL−1), solubilize inorganic phosphate, and exhibit the activity of ACC deaminase (278.40 ± 21 mol -ketobutyrate mg−1 h−1). Cowpea’s root and shoot dry weights were also significantly increased after in vitro inoculation with AZC66. The identity of AZC66 was confirmed as Priestia filamentosa, and 4840 genes were predicted in its genome. The gene sequences were compared against the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, and the results showed that the top three pathways wherein the maximum number of genes are involved are signaling and cellular processes, genetic information processing, and carbohydrate metabolism. The genome sequencing of the strain AZC66 revealed a number of genes implicated in plant biostimulation activities such as nitrogen fixation (nifU), phytohormone synthesis (trpAB genes), phosphate solubilization (PhbCEF, pstABCS, and phoU), and siderophore formation (FbpA, feoAB, and fetB). The AZC66 genome contained numerous genes involved in nitrogen metabolism, nitrogen regulation, and the nitrate reduction pathway. The phenazine biosynthetic gene in AZC66 demonstrated biocontrol and soil survival properties. The trehalose synthesis genes in AZC66 may help plants resist osmotic and salt stress. The discovery of glycine betaine, cold shock, and heat shock protein genes demonstrated that AZC66 could withstand harsh conditions. AZC66 might be used to create robust, sustainable biological fertilizers for future agricultural use in Saudi Arabia. Furthermore, the predicted adaptable metabolic pathways might serve as the basis for potential biotechnological applications in agriculture and industry.
Low-Carbon Energy Transition for the Sarawak Region via Multi-Period Carbon Emission Pinch Analysis
Authors: Rajakal Jaya Prasanth , Saleem Nor Nazeelah , Wan Yoke Kin , Ng Denny K. S. , Andiappan Viknesh
Published: May 2023

The Paris agreement in 2015 has required that countries commit to global carbon emission reduction by setting their national targets. In most countries, the electricity sector is identified as one of the major contributors to carbon emissions. Therefore, the governments count on decarbonizing the electricity sector to achieve their carbon reduction targets. However, this could be challenging as it is complex and involves multi-stakeholders in implementing the decarbonization plan. This work presents a mathematical optimization model to determine multi-period electricity generation planning to achieve the electricity demand and the carbon reduction target. A multi-period analysis allows long-term planning for decarbonizing the electricity sector by the gradual phasing out of coal-based power plants and the introduction of renewable-based electricity generation. To illustrate the proposed approach, the developed model is solved to strategize low-carbon energy transition planning for the Sarawak region in Malaysia. The model determines the optimal amount of new renewables required during each of the time periods, from 2020–2040, to meet the carbon reduction target. The optimal results are generated under two scenarios—no co-firing and co-firing. The generated results show that the co-firing scenario resulted in a 14.09% reduction in new renewable additions and a 5.78% reduction in the total costs. The results also determined a 66% reduction in coal consumption in 2050 when compared to the base year in 2020.
A Quantitative Risk Assessment Model for Domino Accidents of Hazardous Chemicals Transportation
Authors: Cheng Jinhua , Wang Bing , Cao Chenxi , Lang Ziqiang
Published: May 2023

In recent years, hazardous materials transportation accidents have received increasing attention. Previous studies have focused on accidents involving a single vehicle. When vehicles loaded with materials gather on a stretch of road, a potential domino accident might cause terrible incidents. This paper prompts a quantitative risk assessment (QRA) model to estimate the risk of multi-vehicle incidents. The model calculates the possibility of leakage and explosion of hazardous chemicals using a dynamic Bayesian network (DBN). For different types of hazardous chemicals, the model uses event trees to list different scenarios and analyzes the probability of domino accidents caused by each scenario. The FN-curve and potential loss of life (PLL) are used as an index to evaluate social risk. A case involving multiple vehicles in the JinShan District, Shanghai, is analyzed. The result of the case shows that the state of the driver, the type of road, weather factors and the distance between vehicles have vital impacts on the societal risk resulting from hazardous materials transportation accidents.
Female Practitioners’ Religious Lives: The First Generation of Female Wŏn Buddhist Clerics
Authors: Yun Sung Ha
Published: May 2023

For Korean women, the Japanese colonial period was a transitional period in which Confucian patriarchal culture still prevailed, but some options for a social identity outside the home as “new women” were beginning to emerge. In this era, Sot’aesan, the founder of Wŏn Buddhism, put forward the teaching of “equal rights for men and women” as one of the core doctrines of Wŏn Buddhism and opened the way for many women to find their true selves through Buddhist teachings and practices. This path was that of becoming a kyomu (Wŏn Buddhist ordained clerics). By analyzing the biographies of the first 146 female kyomus, this paper sheds light on how these devotees were transformed from women with no identities outside the home into Buddhist masters or mothers of the world.
Contribution of Landscape Transformation in the Development of Heat Islands and Sinks in Urban and Peri-Urban Regions in the Chota–Nagpur Plateau, India
Authors: Kumar Amit , Upreti Manjari , Pandey Arvind Chandra , Saikia Purabi , Khan Mohammed Latif
Published: May 2023

Cities in the contemporary world are experiencing shifts in local climatic conditions that are primarily linked to rapid urban growth, carbon emissions, and environmental degradation. In the present study, land surface temperature (LST) in urban and peri-urban regions of the city of Ranchi was estimated and correlated with land use/land cover (LULC) using temporal LANDSAT satellite images from 2000 to 2014 on a bi-annual basis. The study exhibited a gradual increase in built-up land with total growth of 47.65 sq. km (135%) at the cost of vegetation (−6.8%), rock outcrops (−44.16%), and other LULCs (0.81%). Spatiotemporal LST variability exhibited an increase in area under high-temperature (>38 °C) zones as compared to moderate (30 °C to 38 °C) and low-temperature (<30 °C) zones. Although the LST distinctively escalated in all LULC in the month of May from 2000 to 2014, urban areas exhibited cooler conditions than their environs at a regional scale, except for 2006. A higher surface temperature was observed over bare rock (min./max.: 28–43 °C), fallow land (25–42 °C), and industrial built-up areas (31–43 °C), followed by vegetation (24–34 °C) and waterbodies (22–30 °C). The rapid land transformation to an impervious surface, degradation of vegetation coverage and its health, deforestation due to urbanization, the dumping of non-treated wastewater into reservoirs, and pollution altogether led to an increase in urban heat islands (UHI). The study demonstrated that the LST increased in urban regions but appeared cooler than those of its peri-urban counterparts because of the presence of barren land and rock outcrops. The existing tenancy act had an indirect impact on maintaining natural landscapes and controlling the LST within the Ranchi region. The study recommends nature-based solutions in terms of plantation and green roofing within the rising LST zones located in the urban core and in peripheral rock outcrops collectively to minimize the rising impact of LST in urban and peri-urban regions.
Spatial Prediction of Soil Organic Carbon Stock in the Moroccan High Atlas Using Machine Learning
Authors: Meliho Modeste , Boulmane Mohamed , Khattabi Abdellatif , Dansou Caleb Efelic , Orlando Collins Ashianga , Mhammdi Nadia , Noumonvi Koffi Dodji
Published: May 2023

Soil organic carbon (SOC) is an essential component, which soil quality depends on. Thus, understanding the spatial distribution and controlling factors of SOC is paramount to achieving sustainable soil management. In this study, SOC prediction for the Ourika watershed in Morocco was done using four machine learning (ML) algorithms: Cubist, random forest (RF), support vector machine (SVM), and gradient boosting machine (GBM). A total of 420 soil samples were collected at three different depths (0–10 cm, 10–20 cm, and 20–30 cm) from which SOC concentration and bulk density (BD) were measured, and consequently SOC stock (SOCS) was determined. Modeling data included 88 variables incorporating environmental covariates, including soil properties, climate, topography, and remote sensing variables used as predictors. The results showed that RF (R2 = 0.79, RMSE = 1.2%) and Cubist (R2 = 0.77, RMSE = 1.2%) were the most accurate models for predicting SOC, while none of the models were satisfactory in predicting BD across the watershed. As with SOC, Cubist (R2 = 0.86, RMSE = 11.62 t/ha) and RF (R2 = 0.79, RMSE = 13.26 t/ha) exhibited the highest predictive power for SOCS. Land use/land cover (LU/LC) was the most critical factor in predicting SOC and SOCS, followed by soil properties and bioclimatic variables. Both combinations of bioclimatic–topographic variables and soil properties–remote sensing variables were shown to improve prediction performance. Our findings show that ML algorithms can be a viable tool for spatial modeling of SOC in mountainous Mediterranean regions, such as the study area.
An Overview of Key SLAM Technologies for Underwater Scenes
Authors: Wang Xiaotian , Fan Xinnan , Shi Pengfei , Ni Jianjun , Zhou Zhongkai
Published: May 2023

Autonomous localization and navigation, as an essential research area in robotics, has a broad scope of applications in various scenarios. To widen the utilization environment and augment domain expertise, simultaneous localization and mapping (SLAM) in underwater environments has recently become a popular topic for researchers. This paper examines the key SLAM technologies for underwater vehicles and provides an in-depth discussion on the research background, existing methods, challenges, application domains, and future trends of underwater SLAM. It is not only a comprehensive literature review on underwater SLAM, but also a systematic introduction to the theoretical framework of underwater SLAM. The aim of this paper is to assist researchers in gaining a better understanding of the system structure and development status of underwater SLAM, and to provide a feasible approach to tackle the underwater SLAM problem.
Towards Digital Twins of the Oceans: The Potential of Machine Learning for Monitoring the Impacts of Offshore Wind Farms on Marine Environments
Authors: Schneider Janina , Klüner André , Zielinski Oliver
Published: May 2023

With an increasing number of offshore wind farms, monitoring and evaluating the effects of the wind turbines on the marine environment have become important tasks. Here we conducted a feasibility study with the focus on monitoring these effects by utilizing different machine learning methods. A multi-source dataset for a study site in the North Sea is created by combining satellite data, local in situ data and a hydrodynamic model. The machine learning algorithm DTWkNN, which is based on dynamic time warping and k-nearest neighbor, is used for multivariate time series data imputation. Subsequently, unsupervised anomaly detection is performed to identify possible inferences in the dynamic and interdepending marine environment around the offshore wind farm. The anomaly results are analyzed in terms of location, density and temporal variability, granting access to information and building a basis for explanation. Temporal detection of anomalies with COPOD is found to be a suitable method. Actionable insights are the direction and magnitude of potential effects of the wind farm on the marine environment, depending on the wind direction. This study works towards a digital twin of offshore wind farms and provides a set of methods based on machine learning to monitor and evaluate offshore wind farm effects, supporting stakeholders with information for decision making on future maritime energy infrastructures.
Improved YOLOv5 Network for Real-Time Object Detection in Vehicle-Mounted Camera Capture Scenarios
Authors: Ren Zuyue , Zhang Hong , Li Zan
Published: May 2023

Object detection in the process of driving is a convenient and efficient task. However, due to the complex transformation of the road environment and vehicle speed, the scale of the target will not only change significantly but also be accompanied by the phenomenon of motion blur, which will have a significant impact on the detection accuracy. In practical application scenarios, it is difficult for traditional methods to simultaneously take into account the need for real-time detection and high accuracy. To address the above problems, this study proposes an improved network based on YOLOv5, taking traffic signs and road cracks as detection objects and conducting separate research. This paper proposes a GS-FPN structure to replace the original feature fusion structure for road cracks. This structure integrates the convolutional block attention model (CBAM) based on bidirectional feature pyramid networks (Bi-FPN) and introduces a new lightweight convolution module (GSConv) to reduce the information loss of the feature map, enhance the expressive ability of the network, and ultimately achieve improved recognition performance. For traffic signs, a four-scale feature detection structure is used to increase the detection scale of shallow layers and improve the recognition accuracy for small targets. In addition, this study has combined various data augmentation methods to improve the robustness of the network. Through experiments using 2164 road crack datasets and 8146 traffic sign datasets made by LabelImg, compared to the baseline model (YOLOv5s), the modified YOLOv5 network improves the mean average precision (mAP) result of the road crack dataset and small targets in the traffic sign dataset by 3% and 12.2%, respectively.
Pixel-Grouping G(E) Functions for Estimating Dose Rates from Unknown Source Distributions with a Position-Sensitive Detector
Authors: Kim Hojik , Kim Junhyeok , Hwang Jisung , Ko Kilyoung , Cho Gyuseong
Published: May 2023

Estimating accurate radiation doses when a radioactive source’s location is unknown can protect workers from radiation exposure. Unfortunately, depending on a detector’s shape and directional response variations, conventional G(E) function can be prone to inaccurate dose estimations. Therefore, this study estimated accurate radiation doses regardless of source distributions, using the multiple G(E) function groups (i.e., pixel-grouping G(E) functions) within a position-sensitive detector (PSD), which records the response position and energy inside the detector. Investigations revealed that, compared with the conventional G(E) function when source distributions are unknown, this study’s proposed pixel-grouping G(E) functions improved dose estimation accuracy by more than 1.5 times. Furthermore, although the conventional G(E) function produced substantially larger errors in certain directions or energy ranges, the proposed pixel-grouping G(E) functions estimate doses with more uniform errors at all directions and energies. Therefore, the proposed method estimates the dose with high accuracy and provides reliable results regardless of the location and energy of the source.
Pipelined Key Switching Accelerator Architecture for CKKS-Based Fully Homomorphic Encryption
Authors: Duong Phap Ngoc , Lee Hanho
Published: May 2023

The increasing ubiquity of big data and cloud-based computing has led to increased concerns regarding the privacy and security of user data. In response, fully homomorphic encryption (FHE) was developed to address this issue by enabling arbitrary computation on encrypted data without decryption. However, the high computational costs of homomorphic evaluations restrict the practical application of FHE schemes. To tackle these computational and memory challenges, a variety of optimization approaches and acceleration efforts are actively being pursued. This paper introduces the KeySwitch module, a highly efficient and extensively pipelined hardware architecture designed to accelerate the costly key switching operation in homomorphic computations. Built on top of an area-efficient number-theoretic transform design, the KeySwitch module exploited the inherent parallelism of key switching operation and incorporated three main optimizations: fine-grained pipelining, on-chip resource usage, and high-throughput implementation. An evaluation on the Xilinx U250 FPGA platform demonstrated a 1.6× improvement in data throughput compared to previous work with more efficient hardware resource utilization. This work contributes to the development of advanced hardware accelerators for privacy-preserving computations and promoting the adoption of FHE in practical applications with enhanced efficiency.
Development of a Real-Time Pixel Array-Type Detector for Ultrahigh Dose-Rate Beams
Authors: Jang Young Jae , Yang Tae Keun , Kim Jeong Hwan , Jang Hong Suk , Jeong Jong Hwi , Kim Kum Bae , Kim Geun-Beom , Park Seong Hee , Choi Sang Hyoun
Published: May 2023

Although research into ultrahigh dose-rate (UHDR) radiation therapy is ongoing, there is a significant lack of experimental measurements for two-dimensional (2D) dose-rate distributions. Additionally, conventional pixel-type detectors result in significant beam loss. In this study, we developed a pixel array-type detector with adjustable gaps and a data acquisition system to evaluate its effectiveness in measuring UHDR proton beams in real time. We measured a UHDR beam at the Korea Institute of Radiological and Medical Sciences using an MC-50 cyclotron, which produced a 45-MeV energy beam with a current range of 10–70 nA, to confirm the UHDR beam conditions. To minimize beam loss during measurement, we adjusted the gap and high voltage on the detector and determined the collection efficiency of the developed detector through Monte Carlo simulation and experimental measurements of the 2D dose-rate distribution. We also verified the accuracy of the real-time position measurement using the developed detector with a 226.29-MeV PBS beam at the National Cancer Center of the Republic of Korea. Our results indicate that, for a current of 70 nA with an energy beam of 45 MeV generated using the MC-50 cyclotron, the dose rate exceeded 300 Gy/s at the center of the beam, indicating UHDR conditions. Simulation and experimental measurements show that fixing the gap at 2 mm and the high voltage at 1000 V resulted in a less than 1% loss of collection efficiency when measuring UHDR beams. Furthermore, we achieved real-time measurements of the beam position with an accuracy of within 2% at five reference points. In conclusion, our study developed a beam monitoring system that can measure UHDR proton beams and confirmed the accuracy of the beam position and profile through real-time data transmission.
Young’s Modulus-Independent Determination of Fibre Parameters for Rayleigh-Based Optical Frequency Domain Reflectometry from Cryogenic Temperatures up to 353 K
Authors: Girmen Caroline , Dittmar Clemens , Siedenburg Thorsten , Gastens Markus , Wlochal Michael , König Niels , Schröder Kai-Uwe , Schael Stefan , Schmitt Robert H.
Published: May 2023

The magnetic spectrometer AMS-100, which includes a superconducting coil, is designed to measure cosmic rays and detect cosmic antimatter in space. This extreme environment requires a suitable sensing solution to monitor critical changes in the structure such as the beginning of a quench in the superconducting coil. Rayleigh-scattering-based distributed optical fibre sensors (DOFS) fulfil the high requirements for these extreme conditions but require precise calibration of the temperature and strain coefficients of the optical fibre. Therefore, the fibre-dependent strain and temperature coefficients KT and Kϵ for the temperature range from 77 K to 353 K were investigated in this study. The fibre was integrated into an aluminium tensile test sample with well-calibrated strain gauges to determine the fibre’s Kϵ independently of its Young’s modulus. Simulations were used to validate that the strain caused by changes in temperature or mechanical conditions was the same in the optical fibre as in the aluminium test sample. The results indicated a linear temperature dependence of Kϵ and a non-linear temperature dependence of KT. With the parameters presented in this work, it was possible to accurately determine the strain or temperature of an aluminium structure over the entire temperature range from 77 K to 353 K using the DOFS.
The Vulnerability of European Roma to the Socioeconomic Crisis Triggered by the COVID-19 Pandemic
Authors: Macías León Almudena , Del Pino-Brunet Natalia
Published: May 2023

The Roma are the most significant ethnic minority in the EU, subject to severe discrimination, social exclusion, and poverty. Due to their deplorable living conditions, isolation, and widespread antigypsyism, Roma are among the most affected by the socioeconomic crisis triggered by the COVID-19 pandemic. This article aims to assess the impact of this crisis on the Roma population from a multidimensional perspective. A thematic review of recent studies and reports on the pandemic’s effects on the Roma ethnic minority in Europe was carried out. In this work, the COVID-19 pandemic has been identified as a new global factor that influences the pre-existing exclusion dynamics and Roma mobility within Europe. Results show that these precarious living conditions have deteriorated to alarming levels in most European countries, leading to increased food insecurity and new forms of discrimination and stigmatization. The Roma ethnic minority has been disproportionately affected by mobility restrictions imposed by COVID-19. In all European nations, racist and xenophobic attitudes toward the Roma ethnic minority have increased during the socioeconomic and health crisis. The pandemic has intensified a process of ethnicization, fostering anti-Roma sentiment among the general population.