Search Results (62,184)

This article reflects on the translation of gallery space into a virtually immersive experience in an era of remote access. Curators and scholars such as Mary Nooter Roberts, Susan Vogel, Carol Duncan, Tony Bennet, Stephen Greenblatt, Judith Mastai, and Barbara Kirshenblatt-Gimblett have discussed the myriad of ways in which the experience of culturally significant objects and sites in person has been critical to the study of art and its history. Focusing on theories of curation and display, I utilize practice-based examples from six virtual reality (VR) exhibitions produced in three different institutional contexts: the International Journal of Digital Art History’s online gallery, the European Cultural Center’s Performance Art program, and the Digital Humanities program at the University of California, Los Angeles. By documenting and analyzing the extended reality (XR) methods employed and the methodological approaches to the digital curatorial work, I address some of the challenges and opportunities of presenting objects in virtual space, offering comparisons to those faced when building physical exhibitions. I also consider how digital modalities provide a distinctly different paradigm for epistemologies of art and culture that offer greater contextualized understandings and can reshape exhibition documentation and the teaching of curatorial practice and museum studies. Full article

Formal requirements modeling and traceability management are essential for effectively implementing Model-Based Systems Engineering (MBSE). However, few studies have explored the integration of requirement modeling, traceability management, and verification within MBSE-based systems engineering methodologies. Moreover, the predominant modeling language for MBSE, SysML, lacks sufficient capabilities for requirement description and traceability management and for depicting physical attributes and executable capabilities, making it challenging to verify functional and non-functional requirements collaboratively. This paper proposes an integrated approach for requirement modeling, traceability management, and verification, building on the previously proposed integrated modeling and the simulation language called X language. Our contributions primarily include defining the ReqXL specification for MBSE-oriented requirement modeling based on X language, proposing an algorithm for automatically generating requirement traces, and an integrated framework for requirements modeling, traceability management, and verification was developed by combining the X language with ReqXL. These functionalities were customized on the self-developed integrated modeling and simulation platform, XLab, which is specifically tailored for the X language. Furthermore, we showcase the efficacy and promise of our approach through a case study involving the design of an aircraft electrical system. Full article

China prioritizes ensuring drinking water safety, particularly in the water-scarce northwest region. This study, utilizing water quality data from 52 village and town water sources since August 2022, assesses water quality, with a specific focus on key indicators related to organic pollution sources. This study provides a scientific foundation for enhancing water quality in these sources. Employing category factor analysis for classification and grading, principal component analysis for qualitative analysis of key evaluation indicators, and the absolute principal component linear regression equation for quantitative calculation of pollution sources, this study reveals that all 52 water sources meet quality standards. Principal component analysis categorizes pollution sources as diverse types of organic compounds in surface water. Source analysis calculations highlight decay-type organic substances as major contributors to increased water color and permanganate index, with pollution contribution rates of 54.78% and 31.31%, respectively. Fecal-type organic substances dominate the increase in dissolved total solids and total coliforms, with pollution contribution rates of 56.65% and 40.16%, respectively. Additionally, high-molecular-weight organic substances exhibit lower concentrations in the water. This article presents a systematic water quality assessment methodology, which is used for the first time to qualitatively assess the types of water sources and to quantitatively trace specific sources of organic pollution in source water in northwest China. This systematic study’s results, involving initial assessment followed by traceability, recommend the adoption of a simple contact filtration and disinfection process to enhance water quality in the region. Full article

As consumer demands evolve for health supplements, traditional ginseng products are facing challenges in enhancing their powder characteristics and bioavailability. The objective of this study was to prepare a novel ginseng superfine powder using a high-pressure homogenization (HPH) process. Response surface methodology was employed to determine the effects of HPH parameters (pressure, number of passes, and concentration) on particle size and the dissolution of the saponin components of the superfine powders. The Box–Behnken design of experiments was applied to ascertain the optimal HPH parameters for the smallest particle size and the highest dissolution of the saponin components. For the powders obtained at different parameters, the characterization of tap density, bulk density, flowability, water-holding capacity, appearance, and taste were observed. The optimized experimental conditions for the HPH process were as follows: 15,000 psi (pressure), 3 (number of passes), and 1 kg/L (concentration). The optimized values were 55 μm (particle size) and 83 mg/g (dissolution of the saponin components), respectively. The method offered technical support for the application of the HPH process in the preparation of ginseng powders. The objects of this research could be broadened to include a diverse array of botanical materials, addressing contemporary demands for cost-effectiveness and sustainability within the industry. Full article

The Vilcanota is the second-largest snow-capped mountain range in Peru, featuring 380 individual glaciers, each with its own unique characteristics that must be studied independently. However, few studies have been conducted in the Vilcanota range to monitor and track the area and volume changes of the Suyuparina and Quisoquipina glaciers. Notably, there are only a few studies that have approached this issue using LIDAR technology. Our methodology is based on a combination of optical, radar and LIDAR data sources, which allowed for constructing coherent temporal series for the both the perimeter and volume changes of the Suyuparina and Quisoquipina glaciers while accounting for the uncertainty in the perimeter detection procedure. Our results indicated that, from 1990 to 2013, there was a reduction in snow cover of 12,694.35 m² per year for Quisoquipina and 16,599.2 m² per year for Suyuparina. This represents a loss of 12.18% for Quisoquipina and 22.45% for Suyuparina. From 2006 to 2013, the volume of the Quisoquipina glacier decreased from 11.73 km³ in 2006 to 11.04 km³ in 2010, while the Suyuparina glacier decreased from 6.26 km³ to 5.93 km³. Likewise, when analyzing the correlation between glacier area and precipitation, a moderate inverse correlation (R = −0.52, p < 0.05) was found for Quisoquipina. In contrast, the correlation for Suyuparina was low and nonsignificant, showing inconsistency in the effect of precipitation. Additionally, the correlation between the snow cover area and the annual mean air temperature (R = −0.34, p > 0.05) and annual minimum air temperature (R = −0.36, p > 0.05) was low, inverse, and not significant for Quisoquipina. Meanwhile, snow cover on Suyuparina had a low nonsignificant correlation (R = −0.31, p > 0.05) with the annual maximum air temperature, indicating a minimal influence of the measured climatic variables near this glacier on its retreat. In general, it was possible to establish a reduction in both the area and volume of the Suyuparina and Quisoquipina glaciers based on freely accessible remote sensing data. Full article

This study aimed to examine the role of travel-related motivations and preferences for activities (such as learning about local culture, relaxation and entertainment, status and social recognition, escape and curiosity, and experience) in the relationship between narcissistic personality traits and the preference for luxury tourism versus cultural tourism. A sample of 1342 Israeli community members was analyzed. The methodology utilized parallel mediation analyses to assess how different forms of narcissism (extraverted, antagonistic, neurotic, and communal) were associated with the desire for luxury tourism over cultural tourism, as mediated by various travel-related motivations. The results indicated that narcissistic personality traits were generally associated with a preference for luxury tourism, primarily through indirect associations via travel motivations such as relaxation and entertainment, status and social recognition, and experience. The conclusion highlights the implications for understanding how specific travel-related motivations influence tourism preferences among individuals with varying levels of narcissistic traits, suggesting that tourism management strategies could benefit from a nuanced approach to personality in marketing. Full article

For dealing with the energy consumption in multi-agent systems (MASs), an event-triggered (ET) methodology is promising, which relies on the activation of communication devices only when communication of data is needed. This paper explores the leaderless consensus for nonlinear MASs using an adaptive ET approach via an output feedback methodology. This adaptive ET scheme is preferred as it can adapt to the environment through setting a communication threshold. The proposed approach renders the observed states of agents by use of nonlinear observers in an output feedback control dilemma, making it more practical. Simple Luenberger observers are developed to avoid the problem of always measuring agents’ states. The strategy of adaptive ET-based control is employed to minimize resource use and information transmission. Design conditions for the observer-based adaptive ET consensus control of nonlinear MASs have been derived via a Lyapunov function, containing state estimation error, consensus error, adaptation term, and nonlinearity bounds. In contrast to the existing methods, the present approach applies a more practical output feedback schema, uses adaptive ET proficiency, and deals with nonlinear agents. An example of a formation of autonomous underwater vehicles achieving the basic consensus realization between displacement and velocity is included to illustrate the viability of the resultant approach. Full article

Clustering is a very common means of analysis of the data present in large datasets, with the aims of understanding and summarizing the data and discovering similarities, among other goals. However, despite the present success of the use of subsymbolic methods for data clustering, a description of the obtained clusters cannot rely on the intricacies of the subsymbolic processing. For clusters of data expressed in a Resource Description Framework (RDF), we extend and implement an optimized, previously proposed, logic-based methodology that computes an structure—called a Common Subsumer—describing the commonalities among all resources. We tested our implementation with two open, and very different, datasets: one devoted to public procurement, and the other devoted to drugs in pharmacology. For both datasets, we were able to provide reasonably concise and readable descriptions of clusters with up to 1800 resources. Our analysis shows the viability of our methodology and computation, and paves the way for general cluster explanations to be provided to lay users. Full article

The study of declarative and procedural knowledge in sport allows us to assess students’ tactical learning processes. The aim of this study was to analyze and compare the level of declarative and procedural knowledge acquired by students according to the pedagogical model and gender, after the application of two intervention programs for an alternative invasion sport, “Rosquilla”. This study involved 136 students distributed into six groups of Primary Education (fifth and sixth year) and Secondary Education (first year). Each group in the same year participated in a different intervention program, one based on the Game-Centered Model and the other on a hybrid model of the Game-Centered Model and the Sports Education Model. A descriptive analysis was carried out to determine the characteristics of the participants. Subsequently, an independent samples Mann–Whitney U-test was applied to compare the level of knowledge between the models and genders in the pre- and post-test periods. A Linear Mixed Model was used to analyze the level of knowledge of students within each group and compare them according to methodology and gender. The results indicate that both programs generated improvements in declarative and procedural knowledge. Therefore, students learn equally regardless of the methodological perspective and gender. Full article

Bacterial nanocellulose (BC) has attracted significant attention across a wide array of applications due to its distinctive characteristics. Recently, there has been increasing interest in leveraging waste biomass to improve sustainability in BC biogenesis processes. This study focuses on optimizing the citrus pulp waste (CPW) medium to enhance BC production using Komagataeibacter sucrofermentans. The screening of initial medium pH, yeast extract, CPW sugar and inoculum concentrations was conducted using the Plackett–Burman design, with BC yield (mgDW/gCPW) as the model response. The significant parameters, i.e., CPW sugars and yeast extract concentrations, were optimized using response surface methodology, employing a five-level, two-factor central composite design. The optimized CPW-based growth medium resulted in a final yield of 66.7 ± 5.1 mgDW/gCPW, representing a 14-fold increase compared to non-optimized conditions (4.3 ± 0.4 mgBC/gCPW). Material characterization analysis indicated that the produced BC showed high thermal stability (30% mass retained at 600 °C) and a crystallinity index value of 71%. Additionally, to enhance process sustainability, spent baker’s yeast hydrolysate (BYH) was assessed as a substitute for yeast extract, leading to a final BC titer of 9.3 ± 0.6 g/L. Full article

Background: Hip biomechanics are crucial in understanding movement disorders and joint pathologies. Pelvic tilt and femoral torsion are key factors influencing hip function and stability. This review aims to elucidate their effects on acetabular orientation, hip range of motion (ROM), and associated compensatory mechanisms. Methods: A comprehensive search of databases, including PubMed, Scopus, and Pedro, was conducted. Studies were selected based on Population, Concept, and Context (PCC) criteria, focusing on those examining the relationship between pelvic tilt, femoral torsion, and hip biomechanics. Eight studies were included, utilizing methodologies such as CT imaging, musculoskeletal modeling, and gait analysis, covering populations ranging from asymptomatic adults to elderly women with pelvic retroversion. Results: The review identified significant effects of pelvic retroversion on acetabular anteversion and hip extension. Some studies found no correlation between pelvic index (PI) and acetabular orientation, while others reported a linear increase in acetabular anteversion with pelvic retroversion. Subjects with pelvic retroversion showed greater hip extension. Additionally, femoral anteversion was linked to increased internal rotation and altered hip joint contact forces during gait, with changes in hip ROM and force distribution. No relationship was found between femoral and acetabular anteversion in patients with hip osteoarthritis. Conclusions: Pelvic tilt and femoral torsion significantly affect hip biomechanics, influencing acetabular orientation, ROM, and compensatory mechanisms. Future studies should include symptomatic populations to explore these relationships further. These findings emphasize the critical need for individualized clinical assessments and further research on symptomatic populations to enhance our understanding of pelvic tilt and femoral torsion’s impact on hip biomechanics. Full article

The analytical results from a study of 16 honey samples (extra white to dark honey color range) of phenolic compounds obtained using the single UV spectrum methodology and classical spectrophotometric methods (Folin–Ciocalteu and AlCl₃ methods) are presented. The first method quantified all classes of phenolic compounds in honey’s SPE-C18 extract: the total hydroxybenzoic acid content (concentrations between 0.37 ± 0.05 and 4.46 ± 0.37 mg of gallic acid/g of honey), total hydroxycinnamic acid content (0.13 ± 0.03 and 2.76 ± 0.13 mg of ferulic acid/g of honey), and total flavonoid content (0.15 ± 0.03 and 1.63 ± 0.17 mg of quercetin/g of honey). The total phenolic contents were, on average, 1.86 ± 0.72 and 1.78 ± 0.79 times higher than the results obtained for raw honey and the SPE-C18 extract, respectively, using the classical Folin–Ciocalteu method. The total flavonoid contents, on average, were 6.02 ± 3.14 times larger and 0.66 ± 0.33 times smaller than the results obtained using the classical AlCl₃ method for raw honey and SPE-C18 extract, respectively. Full article

Exosome-like nanovesicles (ELNs) derived from plants are nanoscale vesicles isolated from edible plant sources. Lycium ruthenicum Murray (LRM) has garnered growing attention for its dietary value and therapeutic benefits. In this study, a PEG6000-based method was developed to isolate LRM-ELNs. Response surface methodology (RSM) was used to optimize the extraction conditions to obtain the optimal extraction efficiency. When PEG6000 concentration was at 11.93%, relative centrifugal force was 9720 g, and incubation time was 21.12 h, the maximum LRM-ELN yield was 4.24 g/kg. This optimization process yielded LRM-ELNs with a particle size of 114.1 nm and a surface charge of −6.36 mV. Additionally, LRM-ELNs mitigated Aβ-induced apoptosis in HT22 cells by enhancing mitochondrial membrane potential (MMP), lowering the Bax/Bcl-2 ratio, and reducing Cleaved Caspase-3 expression. Furthermore, LRM-ELNs alleviated Aβ-induced oxidative stress in HT22 cells by promoting the nuclear translocation of Nrf2 and upregulating the expression of HO-1 and NQO1. These findings indicate that LRM-ELNs exert protective effects against Aβ-induced damage in HT22 cells and may be considered as a potential dietary supplement for Alzheimer’s disease prevention. Full article

This review highlights the critical role of software sensors in advancing biosystem monitoring and control by addressing the unique challenges biological systems pose. Biosystems—from cellular interactions to ecological dynamics—are characterized by intrinsic nonlinearity, temporal variability, and uncertainty, posing significant challenges for traditional monitoring approaches. A critical challenge highlighted is that what is typically measurable may not align with what needs to be monitored. Software sensors offer a transformative approach by integrating hardware sensor data with advanced computational models, enabling the indirect estimation of hard-to-measure variables, such as stress indicators, health metrics in animals and humans, and key soil properties. This article outlines advancements in sensor technologies and their integration into model-based monitoring and control systems, leveraging the capabilities of Internet of Things (IoT) devices, wearables, remote sensing, and smart sensors. It provides an overview of common methodologies for designing software sensors, focusing on the modelling process. The discussion contrasts hypothetico-deductive (mechanistic) models with inductive (data-driven) models, illustrating the trade-offs between model accuracy and interpretability. Specific case studies are presented, showcasing software sensor applications such as the use of a Kalman filter in greenhouse control, the remote detection of soil organic matter, and sound recognition algorithms for the early detection of respiratory infections in animals. Key challenges in designing software sensors, including the complexity of biological systems, inherent temporal and individual variabilities, and the trade-offs between model simplicity and predictive performance, are also discussed. This review emphasizes the potential of software sensors to enhance decision-making and promote sustainability in agriculture, healthcare, and environmental monitoring. Full article

The longitudinal and transverse nuclear magnetic resonance relaxivity dispersion (NMRD) of ¹H in water induced by the paramagnetic relaxation enhancement (PRE) of dissolved lanthanide ions (Ln³⁺) can become very strong. Longitudinal and transverse ¹H NMRD for Gd³⁺, Dy³⁺, Er³⁺ and Ho³⁺ were measured from 20 MHz/0.47 T to 1382 MHz/32.5 T, which extended previous studies by a factor of more than two in the frequency range. For the NMRD above 800 MHz, we used a resistive magnet, which exhibits reduced field homogeneity and stability in comparison to superconducting and permanent NMR magnets. These drawbacks were addressed by dedicated NMRD methods. In a comparison of NMRD measurements between 800 MHz and 950 MHz performed in both superconducting and resistive magnets, it was found that the longitudinal relaxivities were almost identical. However, the magnetic field fluctuations of the resistive magnet strongly perturbed the transverse relaxation. The longitudinal NMRDs are consistent with previous work up to 600 MHz. The transverse NMRD nearly scales with the longitudinal one with a factor close to one. The data can be interpreted within a PRE model that comprises the dipolar hyperfine interactions between the ¹H and the paramagnetic ions, as well as a Curie spin contribution that is dominant at high magnetic fields for Dy³⁺, Er³⁺ and Ho³⁺. Our findings provide a solid methodological basis and valuable quantitative insights for future high-frequency NMRD studies, enhancing the measurement accuracy and applicability of PRE models for paramagnetic ions in aqueous solutions. Full article