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Understanding the formation mechanisms of three-phase products during biomass pyrolysis is essential for optimizing thermochemical conversion and enhancing the efficient utilization of renewable resources. In this study, wheat straw (WS) and pine sawdust (PS) were selected as representative feedstocks to investigate the thermal decomposition behavior and evolution characteristics of gas, liquid (tar), and solid (char) products during pyrolysis. Thermogravimetric analysis and kinetic modeling revealed that PS exhibited higher activation energy (75.44 kJ/mol) than WS (65.63 kJ/mol), indicating greater thermal resistance. Tar yield increased initially and then declined with temperature, peaking at 700 °C (37.79% for PS and 32.82% for WS), while the composition shifted from oxygenated compounds to polycyclic aromatic hydrocarbons as temperature rose. FTIR analysis demonstrated that most functional group transformations in char occurred below 400 °C, with aromatic structures forming above 300 °C and stabilizing beyond 700 °C. Gas product evolution showed that WS produced higher CO and H₂ yields due to its composition, with CH₄ generated in relatively lower amounts. These findings provide insights into biomass pyrolysis mechanisms and offer a theoretical basis for targeted regulation of product distributions in bioenergy applications. Full article

(This article belongs to the Special Issue Advances in Bioenergy and Biofuel Conversion: Designs and Optimization)

19 pages, 974 KB

Open AccessReview

Boosting Seed Performance with Cold Plasma

by Mohamed Ali Benabderrahim, Imen Bettaieb and Mokhtar Rejili

Appl. Sci. 2025, 15(20), 10996; https://doi.org/10.3390/app152010996 (registering DOI) - 13 Oct 2025

Abstract

In 2015, the global community set 17 Sustainable Development Goals (SDGs), with the second goal aiming to end hunger by 2030. In sustainable agriculture, seed treatment plays a crucial role and cold plasma (CP) has emerged as a promising, eco-friendly technology for improving seed performance. This review highlights CP as an innovative seed treatment method with significant potential to enhance seed vigor, germination, and crop yield, particularly under stress conditions such as drought, salinity, and biotic challenges. CP works by generating reactive oxygen and nitrogen species (RONS), which modulate key biochemical and physiological responses in seeds. These responses include improvements in water uptake, enhanced germination rates, and better stress tolerance. Moreover, CP exhibits strong antimicrobial properties, making it a chemical-free alternative for seed decontamination. Despite these benefits, the application of CP in large-scale agriculture faces several challenges. Also, this review critically examines the limitations of CP treatment, including the lack of standardized protocols and insufficient field validation. Additionally, it compares CP treatment with conventional chemical and microbial methods, offering insights into its potential advantages and remaining obstacles. This emerging technology holds promise for enhancing crop productivity while minimizing environmental impact, but further research and validation are essential for its broader adoption in sustainable agricultural practices. Full article

(This article belongs to the Special Issue Advanced Applications of Plasmas Technology in Materials and Diagnostics)

57 pages, 1829 KB

Open AccessSystematic Review

Artificial Intelligence and Machine Learning in Cold Spray Additive Manufacturing: A Systematic Literature Review

by Habib Afsharnia and Javaid Butt

J. Manuf. Mater. Process. 2025, 9(10), 334; https://doi.org/10.3390/jmmp9100334 (registering DOI) - 13 Oct 2025

Abstract

Due to its unique benefits over conventional subtractive manufacturing, additive manufacturing methods continue to attract interest in both academia and industry. One such method is called Cold Spray Additive Manufacturing (CSAM), a solid-state coating deposition technology to manufacture repair metallic components using a gas jet and powder particles. CSAM offers low heat input, stable phases, suitability for heat-sensitive substrates, and high deposition rates. However, persistent challenges include porosity control, geometric accuracy near edges and concavities, anisotropy, and cost sensitivities linked to gas selection and nozzle wear. Interdisciplinary research across manufacturing science, materials characterisation, robotics, control, artificial intelligence (AI), and machine learning (ML) is deployed to overcome these issues. ML supports quality prediction, inverse parameter design, in situ monitoring, and surrogate models that couple process physics with data. To demonstrate the impact of AI and ML on CSAM, this study presents a systematic literature review to identify, evaluate, and analyse published studies in this domain. The most relevant studies in the literature are analysed using keyword co-occurrence and clustering. Four themes were identified: design for CSAM, material analytics, real-time monitoring and defect analytics, and deposition and AI-enabled optimisation. Based on this synthesis, core challenges are identified as small and varied datasets, transfer and identifiability limits, and fragmented sensing. Main opportunities are outlined as physics-based surrogates, active learning, uncertainty-aware inversion, and cloud-edge control for reliable and adaptable ML use in CSAM. By systematically mapping the current landscape, this work provides a critical roadmap for researchers to target the most significant challenges and opportunities in applying AI/ML to industrialise CSAM. Full article

23 pages, 1034 KB

Open AccessReview

Purification, Structural Characteristics, Bioactive Properties, and Applications of Naematelia aurantialba Polysaccharides: A Comprehensive Review

by Ri-Na Wu, Yun-Yang Zhu, Run-Hui Ma, Zhi-Jing Ni, Xiao-Juan Deng, Kiran Thakur and Zhao-Jun Wei

Molecules 2025, 30(20), 4073; https://doi.org/10.3390/molecules30204073 (registering DOI) - 13 Oct 2025

Abstract

Jin’er (Naematelia aurantialba), commonly known as golden ear, is a traditional edible fungus that has long been recognized for its medicinal and culinary properties in China. Recently, it has been registered as a new cosmetic ingredient, drawing significant attention across various fields, including medicine, food, and cosmetics, due to its array of nutritional and medicinal benefits. N. aurantialba is rich in bioactive compounds, such as polysaccharides, dietary fiber, polyphenols, and active peptides. Among these, N. aurantialba polysaccharides (NAPs) are the primary active components, exhibiting a range of biological properties, including antioxidant, hypoglycemic, immunomodulatory, intestinal flora modulatory, anti-tumor, and anti-inflammatory effects. This comprehensive review summarizes the latest advancements in the extraction, purification, structural characteristics, functional activity, and related functional mechanisms of NAPs, as well as their industrial applications. Additionally, it discusses the current limitations in NAPs research and explores its potential future research directions. This review aims to provide up-to-date information and valuable references for researchers and industry professionals interested in the potential application of NAPs in the fields of food, medicine, healthcare, and cosmetics. Full article

(This article belongs to the Special Issue Research on Functional Active Ingredients of Edible Fungi)

11 pages, 581 KB

Open AccessArticle

Are Advanced Glycation End-Products and Skin Autofluorescence Associated with E-Selectin and Pulse Wave Velocity as Markers of Atherosclerosis Risk in Children with Obesity?

by Anna Medyńska, Anna Noczyńska and Danuta Zwolińska

Int. J. Mol. Sci. 2025, 26(20), 9966; https://doi.org/10.3390/ijms26209966 (registering DOI) - 13 Oct 2025

Abstract

Obesity is a risk factor for numerous complications, including atherosclerosis, the pathogenesis of which is complex. The aim of our study is to evaluate serum levels of E-selectin and hs-CRP and pulse wave velocity (PWV) as atherosclerosis risk factors and to explore their relationship with advanced glycation end products (AGEs), methylgioxal (MG) and skin autofluorescence (sAF). We evaluated 125 children aged 8–18 years with simple obesity, stratified into two subgroups based on SDS BMI (Group I: 2–4; Group II:> 4), and compared them with 33 age-matched peers of normal weight. Children with obesity exhibited significantly elevated serum concentrations of AGEs, MG, E-selectin, and hs-CRP relative to the control group. Additionally, both height-normalized pulse wave velocity (SDS PWV) and sAF values were significantly higher in the children with obesity compared to their normal-weight counterparts. Except for sAF, which was elevated in children with obesity with a higher SDS BMI, no significant differences were observed among the subgroups of children. Positive correlations were observed between E-selectin and AGEs, MG and SDS PWV, as well as sAF and SDS BMI. Our findings indicate that children with obesity exhibit early signs of atherosclerotic changes, regardless of the degree of obesity. Moreover, circulating AGEs may represent a more reliable biomarker of atherosclerosis risk than sAF, as suggested by the strong positive correlation between AGEs and E-selectin. Further studies are warranted to validate these findings. Full article

(This article belongs to the Collection Feature Papers in Molecular Pathology, Diagnostics, and Therapeutics)

15 pages, 500 KB

Open AccessArticle

Accuracy of an Overnight Axillary-Temperature Sensor for Ovulation Detection: Validation in 194 Cycles

by Yaniv Shpaichler, Alicia Thompson, Benedicte Fromager, Michael Vardi and Rene Ecochard

Sensors 2025, 25(20), 6327; https://doi.org/10.3390/s25206327 (registering DOI) - 13 Oct 2025

Abstract

Several studies have evaluated the reliability of using temperature sensors placed in different locations on the body to identify the day of ovulation. However, such demonstrations are lacking for axillary temperature wearable devices. This study aimed to evaluate the accuracy with which an axillary temperature armband sensor (Tempdrop) identifies the day of ovulation and the fertile window, using the Clearblue Connected Ovulation Test System as the reference method. A total of 194 cycles were analyzed from 125 women that participated in the study between April 2023 and June 2024. The performance parameters were high: the sensitivity (96.8% (95% CI 95.6; 97.7)), specificity (99.1% (98.8; 99.4)), accuracy (98.6% (98.2; 98.9)), positive predictive value (96.8% (95.6; 97.7)) and negative predictive value (99.1% (98.8; 99.4)). Furthermore, the results revealed a remarkably clear and better-than-expected change in temperature around the time of ovulation. This axillary temperature wearable sensor is an effective alternative to urine ovulation tests for determining the timing of ovulation. Another advantage is that it provides a clear temperature curve that can be used to evaluate the quality of the luteal phase. Full article

(This article belongs to the Section Biomedical Sensors)

18 pages, 2041 KB

Open AccessReview

Chiral Transition Metal Complexes Featuring Limonene-Derived Ligands: Roles in Catalysis and Biology

by Ghaita Chahboun, Mohamed El Hllafi, Eva Royo and Mohamed Amin El Amrani

Inorganics 2025, 13(10), 336; https://doi.org/10.3390/inorganics13100336 (registering DOI) - 13 Oct 2025

Abstract

Chiral coordination compounds are of growing interest due to their structural diversity and wide applicability. Besides chirality, alcohol and especially oxime-functionalized limonene derivatives confer water solubility, stability, and the appropriate reactivity to enable their use in asymmetric catalysis—such as allylic substitution, alkynylation, transfer hydrogenation, and selective C–C bond formation. Biologically, they have shown promising anticancer, antibacterial, and antibiofilm activity. This review presents an integrated overview of the synthesis, properties, and applications of chiral transition metal complexes featuring ligands derived from inexpensive, naturally occurring R- and S-limonene substrates, and explore their roles in catalysis and biological activity. Full article

(This article belongs to the Special Issue Editorial Board Members’ Collection Series in “Featuring Ligands and Their Applications in Coordination Chemistry”, 2nd Edition)

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14 pages, 942 KB

Open AccessArticle

Diversity of Escherichia coli from Faecal Samples of Danish Calves with Diarrhoea

by Anna Luiza Farias Alencar, Abdurrahman Hassan Jibril, Birgitta Svensmark, Lene Agerskov, Henrik Læssøe Martin, Marc Stegger, André Becker Saidenberg, Gang Liu, Yaovi Mahuton Gildas Hounmanou, Annette Sønderholm Juel, John Elmerdahl Olsen and Rikke Heidemann Olsen

Vet. Sci. 2025, 12(10), 987; https://doi.org/10.3390/vetsci12100987 (registering DOI) - 13 Oct 2025

Abstract

Several different pathogens, including Escherichia coli, are strongly associated with calf diarrhoea. The population diversity of intestinal E. coli within each diarrhetic calf and between diarrhetic calves is not well understood. In the present study, 391 faecal samples were obtained during 2023–2024 from Danish dairy calves with diarrhoea. Semi-quantified growth estimates of E. coli after culturing did not reflect the diarrhetic grade nor whether E. coli was the only pathogen observed in the sample. From each sample, five isolates were subjected to multiple-locus variable-number tandem repeat analysis (MLVA) and revealed that 70% of faecal samples contained more than one type of E. coli. Genotyping, sequence typing and in silico serotyping showed a large diversity of E. coli between faecal samples. Surprisingly, isolates with a genotype representing mixed features of Diffusely adhering E. coli/Extraintestinal pathogenic E. coli were found in 25% of the isolates, while the classic Enterotoxigenic E. coli genotype was only observed in 5% of the isolates, and only 4% of the faecal samples were positive for E. coli F5 (K99) fimbriae, as determined by PCR. In conclusion, a diverse population of (non-F5) E. coli is associated with diarrhoea in calves. High genomic diversity of E. coli within samples needs to be considered when selecting only one isolate for antimicrobial resistance profiling and vaccination measurements. Full article

(This article belongs to the Section Veterinary Microbiology, Parasitology and Immunology)

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14 pages, 1986 KB

Open AccessArticle

Responses of Growth and Secondary Metabolites in Fish Mint (Houttuynia cordata Thunb.) Cuttings to Far-Red Light

by Zi-Yi Wang, Kuan-Hung Lin, Yen-Chi Yin and Chang-Chang Chen

Horticulturae 2025, 11(10), 1237; https://doi.org/10.3390/horticulturae11101237 (registering DOI) - 13 Oct 2025

Abstract

Fish mint (Houttuynia cordata Thunb.) is an aromatic herb used as food and medicine across Asia. We evaluated how far-red (FR) light influences growth and secondary metabolites in the non-flowering cultivar ‘BCV02’ propagated by cuttings. Seedlings were grown for 14 days under FR at 35, 50, and 70 μmol m⁻² s⁻¹ (as FR35, 50, and 70, respectively) or without FR (as control, CK). All FR treatments increased plant height but reduced the shoot/rhizome ratio. Total chlorophyll and carotenoid contents were unchanged, while the chlorophyll a/b ratio declined from 2.37 (CK) to 2.15 (FR70). In shoots, combined 3-, 4-, and 5-O-caffeoylquinic acids with rutin, hyperoside, isoquercitrin, and quercitrin reached 12.61–13.83 mg g⁻¹ dry weight (DW) under FR treatments, exceeding CK (8.48 mg g⁻¹ DW). However, in rhizomes, these secondary metabolite contents ranged 0.82–1.00 mg g⁻¹ DW across all treatments. On a per-pot basis, the highest accumulated compounds (4.37 mg per pot) occurred at FR35. Overall, growth and secondary metabolite biosynthesis in fish mint cuttings respond differently to changes in FR treatments, with FR35 optimizing compound accumulation. Quercitrin in shoots was 0.09–0.20 mg g⁻¹ DW and not quantifiable in rhizomes, potentially below pharmacopeial thresholds specified in the Taiwan Herbal Pharmacopeia and Hong Kong Chinese Materia Medica Standards. These results underscore the importance of aligning cultivar choice, light regime, and market specifications to secure both yield and quality of H. cordata. Full article

(This article belongs to the Special Issue Breeding, Cultivation and Metabolic Regulation of Medicinal Plants—2nd Edition)

12 pages, 1237 KB

Open AccessArticle

HSP90 Inhibition Disrupts 27-Hydroxycholesterol-Induced Inflammatory Signaling in Monocytic Cells

by Jaesung Kim, Munju Kwon, Dongha Park, Nakyung Kang, Yonghae Son, Ninib Baryawno, Byoung Soo Kim, Sik Yoon, Sae-Ock Oh, Dongjun Lee and Koanhoi Kim

Int. J. Mol. Sci. 2025, 26(20), 9963; https://doi.org/10.3390/ijms26209963 (registering DOI) - 13 Oct 2025

Abstract

27-Hydroxycholesterol (27OHChol), a cholesterol metabolite, induces inflammatory responses in monocytic cells and promotes their differentiation into mature dendritic cells. Here, we examined whether inhibition of heat shock protein 90 (HSP90) modulates these responses. Treatment with ganetespib, a selective HSP90 inhibitor, significantly reduced chemokine CCL2 expression, lowering monocytic cell migration. It also suppressed matrix metalloproteinase-9 (MMP-9) expression and attenuated the lipopolysaccharide (LPS) response otherwise amplified by 27OHChol. Furthermore, ganetespib decreased mature dendritic cell markers (CD80, CD83, CD88) and restored endocytic activity, indicating a less activated state. These changes suggest that HSP90 regulates 27OHChol-induced pro-inflammatory activation via its client proteins. To explore this mechanism, we examined the phosphorylation status of signaling proteins. 27OHChol enhanced phosphorylation of Akt and its downstream targets, S6 and 4E-BP1 within the Akt/mTORC1 pathway. Ganetespib reduced total and phosphorylated Akt and 4E-BP1, and selectively inhibited S6 phosphorylation without altering total protein level. Collectively, these findings demonstrate that HSP90 inhibition by ganetespib mitigates 27OHChol-driven monocytic cell activation through suppression of the HSP90-Akt/mTORC1 axis. Targeting this pathway may provide a promising therapeutic strategy for metabolic inflammation associated with oxysterols. Full article

(This article belongs to the Special Issue Dialogue Between Inflammation and Immunity: From Mechanism to Therapy)

22 pages, 497 KB

Open AccessArticle

Trauma-Informed and Healing Architecture in Young People’s Correctional Facilities: A Comparative Case Study on Design, Well-Being, and Reintegration

by Nadereh Afzhool and Ayten Özsavaş Akçay

Buildings 2025, 15(20), 3687; https://doi.org/10.3390/buildings15203687 (registering DOI) - 13 Oct 2025

Abstract

This study investigates how trauma-informed and healing-centred architectural design is associated with rehabilitation and reintegration outcomes in young people’s correctional facilities. Drawing on international case studies, the analysis demonstrates that architecture is not a neutral backdrop but a contributing determinant within broader justice ecosystems. Trauma-informed environments are consistently linked to reductions in re-traumatisation and improvements in emotional regulation, while small-scale, community-oriented facilities are associated with enhanced skill development, autonomy, and reintegration potential. Culturally responsive designs that incorporate Indigenous practices and symbolic architecture are observed to support identity, resilience, and community belonging, underscoring the importance of cultural continuity in rehabilitation processes. In parallel, sustainable features such as biophilic design, renewable energy systems, and natural light are correlated with improvements in ecological performance and psychosocial well-being, indicating that sustainability and rehabilitation may be mutually reinforcing goals. Notably, the analysis highlights that supportive environments are also associated with staff well-being and institutional stability, underscoring the broader organisational benefits of healing architecture. The findings suggest that young people’s correctional facilities should not replicate adult prisons but instead provide safe, developmental, and culturally grounded spaces that respond to adolescents’ unique needs. This study contributes a novel conceptual model—the Trauma-Informed Healing Architecture (TIHA) framework—that integrates trauma-informed, cultural, and ecological design strategies within the Sustainable Development Goals (SDGs). The framework defines global standards as universal principles—safety, dignity, cultural responsiveness, and natural light—while remaining adaptable to local resources and justice systems. In this way, it provides internationally relevant yet context-sensitive guidance for young people’s correctional reform. Full article

(This article belongs to the Section Building Energy, Physics, Environment, and Systems)

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9 pages, 9003 KB

Open AccessArticle

Designs of Time-Resolved Resonant Inelastic X-Ray Scattering Branchline at S³FEL

by Weihong Sun, Chuan Yang, Kai Hu, Ye Zhu, Chen Wu, Yuhang Wang, Yinpeng Zhong, Zhongmin Xu and Weiqing Zhang

Photonics 2025, 12(10), 1009; https://doi.org/10.3390/photonics12101009 (registering DOI) - 13 Oct 2025

Abstract

With the rapid development of X-ray free-electron lasers (XFELs), time-resolved resonant inelastic X-ray scattering (tr-RIXS) has attracted more attention. The preliminary designs of the tr-RIXS branchline and expected performance characteristics at the Shenzhen Superconducting Soft X-ray Free Electron Laser (

S^{3} FEL

[...] Read more.

S^{3} FEL

) are presented. A start-to-end simulation of the tr-RIXS branchline based on the 6-D phase space ray-tracing method of beamline simulation software package FURION was performed. The simulation design satisfies the key requirements of the tr-RIXS branchline, including spatial dispersion in the vertical dimension, temporal resolution, energy resolution, efficient utilization of SASE spectral photons, and spatial uniformity of the beam spot sizes across different wavelengths. Full article

(This article belongs to the Special Issue Advances in X-Ray Coherent Imaging Technology)

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14 pages, 3067 KB

Open AccessArticle

The Phenomenon of Temperature Increase in Poland: A Machine Learning Approach to Understanding Patterns and Projections

by Anna Franczyk and Robert Twardosz

Appl. Sci. 2025, 15(20), 10994; https://doi.org/10.3390/app152010994 (registering DOI) - 13 Oct 2025

Abstract

This study presents an analysis of patterns in mean monthly air temperature increases in Poland using the deep learning model Neural Basis Expansion Analysis for Time Series (N-BEATS) algorithm. The dataset comprises mean monthly temperatures recorded between 1951 and 2024 at eight meteorological stations across Poland. The research was conducted in two phases. In the first phase, the 74-year period was divided into two distinct intervals: one characterized by relative temperature stability, and the other by a marked upward trend. In the second phase, the N-BEATS neural network was employed to extract temporal patterns directly from the data and to forecast future temperature values. The results confirm the capacity of machine learning methods to identify persistent climate trends and demonstrate their utility for long-term monitoring and prediction. Full article

(This article belongs to the Section Environmental Sciences)

22 pages, 700 KB

Open AccessArticle

Identifying Key Factors Influencing the Selection of Sustainable Building Materials in New Zealand

by Ali Hashemi Araghi, Eziaku Onyeizu Rasheed, Vishnupriya Vishnupriya and Jeff Seadon

Sustainability 2025, 17(20), 9071; https://doi.org/10.3390/su17209071 (registering DOI) - 13 Oct 2025

Abstract

The construction sector is a major contributor to climate change, with embodied carbon emissions from building materials representing a critical share of its environmental footprint. Selecting zero-carbon materials is therefore essential for reducing life-cycle emissions while advancing global climate goals. This study investigates six decision-making factors, including cost-effectiveness, durability, buildability, embodied carbon, availability, and aesthetics, and evaluates four alternative materials (wood, hemp, rammed earth, and straw bale) in the New Zealand context. A survey of 203 industry professionals was analysed using descriptive statistics, one-sample t-tests, and structural equation modelling (SEM). Using a 5-point Likert scale, the survey assessed six factors affecting material choice: cost-effectiveness, durability, buildability, embodied carbon, aesthetics, and material availability. Descriptive and inferential analyses were performed using SEM via Partial Least Squares analysis. The results revealed that embodied carbon and material availability were the most influential factors shaping zero-carbon material selection. Among the available alternatives, hemp emerged as the most preferred material, while cost-effectiveness and wood showed moderate impacts, and aesthetic considerations had the least influence. These findings highlight that environmental performance and practical accessibility are central drivers of decision-making when adopting zero-carbon materials. This study contributes to developing effective strategies for promoting the widespread adoption of zero-carbon materials, thereby supporting New Zealand’s progress toward achieving the Sustainable Development Goals and the 2030 Agenda for reducing greenhouse gas emissions. Full article

(This article belongs to the Special Issue Building Sustainability within a Smart Built Environment)

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24 pages, 518 KB

Open AccessArticle

Bayesian Inference on Stress–Strength Reliability with Geometric Distributions

by Mohammed K. Shakhatreh

Symmetry 2025, 17(10), 1723; https://doi.org/10.3390/sym17101723 (registering DOI) - 13 Oct 2025

Abstract

This paper investigates the estimation of the stress–strength reliability parameter

ρ = P (X \leq Y)

, where stress (X) and strength

(Y)

are independently modeled by geometric distributions. Objective Bayesian approaches are employed by developing Jeffreys, [...] Read more.

This paper investigates the estimation of the stress–strength reliability parameter

ρ = P (X \leq Y)

, where stress (X) and strength

(Y)

are independently modeled by geometric distributions. Objective Bayesian approaches are employed by developing Jeffreys, reference, and probability-matching priors for

ρ

, and their effects on the resulting Bayes estimates are examined. Posterior inference is carried out using the random-walk Metropolis–Hastings algorithm. The performance of the proposed Bayesian estimators is assessed through extensive Monte Carlo simulations based on average estimates, root mean squared errors, and frequentist coverage probabilities of the highest posterior density credible intervals. Furthermore, the applicability of the methodology is demonstrated using two real data sets. Full article

(This article belongs to the Section Mathematics)

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