Analysis Procedure Research Articles

A systematic evaluation of quenching, extraction and analysis procedures for metabolomics study of the mechanism of QYSLD intervention in A549 cells.

The preparation of cellular metabolomics samples and how to achieve comprehensive coverage of different polar metabolites in cell samples in the analysis pose a challenge for cellular metabolomics. In this study, we optimized a metabolomics protocol based on ultra-high-performance liquid chromatography high-resolution mass spectrometry (UPLC/HRMS) for theextraction and detection of metabolites in A549 cells and exploration of the intervention effect of Qi-Yu-San-Long decoction (QYSLD) on A549 cells. The results indicate that the lowest level of ATP leakage was observed when A549 cells were quenched under liquid nitrogen. MeOH/chloroform/H2O (1:2:1) extraction yielded more chromatographic peaks and excellent reproducibility, and the relative extraction efficiency of most target metabolites was also high. And we optimized thechromatographic separation conditions in both HILIC and RPLC modes, enabling comprehensive detection and analysis of metabolites with varying polarities. Then, we applied the optimized method to UPLC-Q-TOF/MS-based metabolomics of A549 cells to study the mechanism of QYSLD intervention in non-small cell lung cancer (NSCLC). The CCK-8, EdU staining, and cell cycle assay showed that QYSLD inhibited the proliferation of A549 cells by interfering with the cell cycle and blocking them in theG1 phase. A total of 36 differential metabolites associated with the antitumor effects of QYSLD on NSCLC were identified, mainly involving nicotinate and nicotinamide metabolism, sphingolipid metabolism, and glycerophospholipid metabolism. And western blotting confirmed that thechange in 1-methylnicotinamide levels after QYSLD intervention was associated with theinhibition of nicotinamide N-methyltransferase expression in A549 cells.

A covalent organic framework-derived pretreatment for pesticides in vegetables and fruits

Sample pretreatment is an essential procedure in pesticide analysis, as the matrix effect can significantly influence the results. In this study, a covalent organic framework (COF) was synthesized using 1,2,4,5-tetrakis-(4-formylphenyl)benzene (TFPB) and benzidine (BD) to mitigate the matrix effect in vegetable and fruit samples. This COF was then used to develop a solid-phase extraction (CSPE) method. In addition, the COF was used to create a magnetic COF (MCOF) for use in magnetic solid-phase extraction (MSPE). The synthesized COF and MCOF were thoroughly characterized using scanning electron microscopy (SEM) for morphological analysis, Fourier-transform infrared spectroscopy (FT-IR) for chemical bond identification, and N2 adsorption–desorption measurements for porosity and surface area assessment. Key pretreatment parameters such as buffers, dilution rate, sorbent dosage, extraction time, elution solvent, and reuse number were optimized. The developed CSPE and MSPE showed excellent purification ability for the matrix of vegetable and fruit samples. The reuse test demonstrated that the synthesized COF and MCOF can be reused up to 15 times. Moreover, the developed CSPE and MSPE showed acceptable recoveries in spiked recovery tests, suggesting that these pretreatment methods were feasible for sample purification in pesticide analysis.

Phytochemical Associes of Fungal Endophytes in Nigeria Riverine Mangrove Ecosystem

The interaction between endophytic fungi and phytochemicals in the dominant mangroves (Rhizophora mangle, Lacugularia racemosa, and Avicennia africana) of the Iko River Estuary in Nigeria was investigated. Standard analytical procedures were employed to measure antioxidant levels, while endophytic fungi were isolated, morphologically characterized, and identified using culture-dependent methods. The study identified various bioactive compounds, including alkaloids, saponins, tannins/phenols, flavonoids, deoxy-sugars, cardiac glycosides, and steroids, with their concentrations varying depending on the mangrove species and plant parts. Alkaloids were present in all mangrove samples, with particularly high concentrations in the leaves of white (5%) and red (4.2%) mangroves. Principal Component Analysis (PCA) was used to analyze the interaction between the endophytic fungi and phytochemicals, revealing a distinct affinity of certain fungal species for specific antioxidants in the mangroves. Fungal species such as Phoma sp., Rhizopus arrhizus, Aspergillus niger, and others exhibited a negative relationship with tannins, flavonoids, deoxysugars, and cardiac glycosides, but a positive affinity for saponins, alkaloids, and steroids. Conversely, Candida pseudotropicalis, Fusarium oxysporum, P. italicum, and others showed a positive affinity for tannins, flavonoids, cardiac glycosides, and deoxysugars, but a negative affinity for alkaloids, saponins, and steroids. Notably, Absidia sp. was the only frequently isolated species with a strong correlation (r value ≥75 at a 95% confidence limit) with deoxy-sugars, while Aspergillus niger, Aspergillus terreus, and Absidia sp. demonstrated significant relationships with alkaloids, saponins, and steroids. These phytochemicals, which serve as precursors to antioxidants with promising biotechnological applications, likely play a crucial role in determining the association of endophytic fungi with deltaic mangroves in Nigeria.

Influence of explosive type and constant γ in Mott’s stochastic model on terminal-ballistics parameters of high-explosive warheads using numerical simulations

The research examined the use of numerical simulations for high-explosive (HE) munitions. Lagrange and Euler solvers from Ansys Autodyn, whose brief theoretical synopsis is given, were utilized. Numerical program modeling of materials under dynamic loads (explosives and solid bodies) is also explained. The study also provides a brief summary of relevant research works that address numerical simulations of the fragmentation of HE projectiles (warheads). First, using data from other authors, the numerical model in this paper was effectively validated. The original research in the publication included an evaluation of the influence of explosive type on mass distribution, as well as velocity and the kinetic energy of fragments on cylindrical warheads, along with some recommendations and findings. Results show that ordered by values of initial fragment velocity are explosives: Trinitrotoluen (TNT), H6, Comp. B, Octol, PBX-9404-3, and LX-10-1. Explosives LX-10-1 and PBX-9404-3 showed similar performance because both explosives are HMX-based mixtures, with LX-10-1 having 0.5% more Octogen (HMX). The greatest (fastest) expansion of fragments (for the given time frame of 150 µs) is present in the most potent explosives (LX-10-1 and PBX-9404-3) since they have the largest detonation velocities. In the configurations with stronger explosives (Octol, LX-10-1, PBX-9404-3), the front and rear cover of the cylinder is more fragmented than in the case of weaker explosives. The highest number of fragments is obtained with PBX-9404-3 explosive, 142% higher than using TNT charge. Also, as part of the original research in the paper, an assessment of the influence of the constant γ in Mott’s stochastic fragmentation model on the mass distribution of fragments and their kinetic energy was made. Results indicate that constant γ has the greatest influence on the number of very small fragments, which can be used when calibrating this constant with experimental data. The masses of fragments are relatively uniform (for all γ values) up to the mass group of 50–100 g, above which the most massive fragments are obtained when γ = 5. Most of the fragments have relatively high energy where that is, fragments of mass 0.5–2 g have an average kinetic energy of 470–650 J, while fragments of masses 50–100 g have an average kinetic energy of 50–85 kJ. Described numerical simulations are a valuable tool for HE warhead designers, as they can minimize the time and expense associated with optimizing HE munition design and effectiveness evaluation when used in conjunction with available analytical techniques and experimentation procedures.

Comparative analysis of the physicochemical properties and trace metal content of palm oil, from selected markets in Jos south and Jos north LGA, Plateau state, Nigeria

The quality of palm oil samples collected from three different markets in Jos South and Jos North Local Government Area of Plateau State were analyzed and evaluated using standard analytical laboratory procedures. The relative ranges of the physicochemical values obtained were as follows; Moisture Content (MC): 0.56 - 1.89, Iodine value (IV); 51.88 - 55.57 g I2/100g, Peroxide Value (PV): 0.98 - 4.16 mEq02/kg, Saponification Values (SV): 198.46 - 201.54 mgKOH/g, Acid Value (AV): 9.93 - 57.65, and Refractive Index (RI), 1.4576 - 1.4580. The moisture content, iodin value, pH values and acid values were found to exceed the Standard Organization of Nigeria (SON) permissible limits of moisture content (0.29 mgKOH/g), iodine value (45 - 53 mg I2/100g), pH (5 - 7 mg/L), and acid value (0.7 max mg/L) for edible oils respectively while the refractive index, saponification values, peroxide values falls within the SON allowable limits of refractive index (1.4612-1.4707 mg/L), saponification value (195-205 mgKOH/g) and peroxide value (10 mEq02/kg) respectively . The amounts of trace metals (Cu, Zn, Fe, Pb and Cd) determined in the palm oil using the atomic absorption spectrophotometer ranged from Cu(0.34 - 0.52 mg/l), Zn(1.58 - 2.33 mg/l), Fe(19.18 - 26.74 mg/l), Pb(2.87 - 4.06 mg/l) and Cd(1.58 - 2.24 mg/l). However, the levels of Zn, Fe, Pb and Cd exceeded the WHO/FAO recommended values of (1.50, 1.00, 0.05 and 0.02 mg/L) respectively while only Cu concentration was below the WHO/FAO limits of 2.00 mg/L for trace metals in edible palm oil. Consequently, the results of this study shows that the palm oil consumed from these selected markets does not meet the standard quality specification for edible palm oils and hence can post significant health threat to consumers. Therefore, food regulatory agencies should strengthen their surveillance to promote food and health safety of the populace.

Enhancing Analytical Potential for Ultratrace Analysis of Inorganic Oxyanions Using Extraction Procedures with Layered Double Hydroxides

This article provides an overview of the use of layered double hydroxides (LDHs) as effective sorbents in various extraction methods, including column-based solid-phase extraction (SPE), dispersive solid-phase extraction (DSPE), and magnetic solid-phase extraction (MSPE), for the separation and preconcentration of inorganic oxyanions of chromium, arsenic, and selenium. The primary focus is on enhancing the analytical performance of spectrometric detection techniques, particularly in terms of sensitivity and selectivity when analyzing low concentrations of target analytes in complex matrices. LDHs, which can be readily prepared and structurally modified with various substances, offer promising potential for the development of novel analytical methods. When used in analytical extraction procedures and following careful optimization of experimental conditions, the developed methods have yielded satisfactory results, as documented by studies reviewed in this paper. This review is intended to assist analytical chemists in scientific laboratories involved in developing new extraction procedures.

An Equation Model on the Professional Knowledge and Confidence for Future Employment of Students in Programs Supported With Emerging Technologies

Students enrolled in interdisciplinary programs supported with modern information technologies may face more challenges in learning, because they must learn from at least two curricula, including courses of big data, new media technologies and intelligent platform use, etc. Taking students in these programs as an example, this study aims to investigate relationships among eight variables related to student career development. The research employed the quantitative method of Pearson bivariate analysis, ANOVA and Hayes (2017) regression procedure to test the direct and indirect relationship among variables. The researcher developed a moderated mediation model visualizing the relationship between professional knowledge and confidence for successful employment. Recommendations of early intervention targeting first-year students and different curriculum designing were proposed to facilitate planning in the acquisition of professional knowledge and the establishment of career goals, aiming to enhance the career development and success of tertiary vocational college students.

Shaking Table Test and Numerical Modeling of Seismic Behavior of Rectangular Tunnel Structures Embedded in Soft Clay

In this paper, a series of 1-g shaking table model tests were carried out to investigate the seismic behavior of a relatively stiff rectangular tunnel structure installed in soft clay bed, accounting for different ground motions with varying peak accelerations. Using a validated numerical analysis procedure, a suite of three-dimensional (3D) finite element (FE) analyses was performed to systematically study the factors of tunnel burial depth, seismic intensity, flexural rigidity of the middle column and tunnel wall thickness on the seismic response of rectangular tunnel structures installed in clayey ground. It was found that, with the increasing burial depth, the seismic response of rectangular tunnel structure became more intense due to the increased inertial force arising from the overlying clay; in terms of improving the seismic performance of tunnel structure, increasing tunnel wall thickness seemed more effective than increasing flexural rigidity of the middle column. Furthermore, it was found that the existing simplified approaches generally tended to overestimate the earthquake-induced racking distortions of rectangular tunnels installed in clayey ground. A new semi-empirical relationship was derived for better correlating the racking ratio with flexibility ratio for rectangular tunnels embedded in soft clays, which could provide a useful reference for the seismic design and risk assessment of similar clay-tunnel systems.

Stochastic error propagation with independent probability distributions in LCA does not preserve mass balances and leads to unusable product compositions—a first quantification

Abstract Purpose To mitigate the effects of the triple planetary crisis of climate change, pollution and biodiversity loss, a system-based approach to estimating environmental impacts—such as life cycle assessment (LCA)—is critical. International standards recommend using uncertainty analysis to improve the reliability of LCA, but there has been debate about how to do this for many years. In particular, in order to characterise uncertainty in the inputs and outputs of each unit process in an LCA, a prevalent approach is to represent each one by an independent probability distribution. Thus, any physical relationships between inputs and outputs are ignored, which causes two potential errors during Monte Carlo simulation (a popular method for propagating uncertainty through an LCA model). First, the sum of the inputs to a unit process may not equal the sum of the outputs (i.e. there may be a mass imbalance), and second, the proportions of each input and output may be unrealistic (e.g. too much cement in a concrete production unit process). However, while some literature has discussed the problem, it has not yet been quantified. Methods Therefore, this paper investigates the extent to which existing uncertainty characterisation approaches, where there is a lack of parameterisation or correlations in databases, lead to mass imbalances and unrealistic variations in unit process compositions when performing uncertainty analysis. The matrix-based structure of LCA and the standard uncertainty analysis procedure using Monte Carlo (MC) simulation to propagate uncertainty are described. We apply the procedure to a concrete production process. Two uncertainty characterisation approaches are also explored to assess the effect of data quality scoring on mass imbalances and the mass contribution of each exchange (i.e. production compositions). Results and discussion For median data quality scores and using a typical (basic + additional uncertainty) uncertainty characterisation approach, the 1000-iteration MC simulation leads to mass imbalances ranging from − 49 to + 30% of the original mass and found that the mass imbalance exceeded existing prescribed plausibility limits on 62.7% of MC runs. On average across all exchanges, the exchange mass exceeded the 5% plausible variation limit on 77.7% of MC runs. This means that the final concrete product compositions are unlikely to be realistic or functionally equivalent to one another. We discuss the appropriateness of using universal variances for the underlying normal distribution for data quality scores (“additional uncertainty”) when input exchange quantities are of different scales. Additionally, we discuss potential solutions to the mass imbalance problem and their suitability for implementation at a database scale. Conclusions We have quantified, for the first time, the significant impact that uncertainty characterisation via independent probability distributions has on maintaining mass balances and plausible product compositions in unit processes. To overcome these challenges, databases would need to be parameterised and have the ability to sum quantities to perform mass balance checks during uncertainty analysis.

Stakeholder mapping of precision weeding commercialization ecosystem in California

CONTEXTPrecision weeding, a sector of agricultural technology in which drones and/or automated weeders use chemical, mechanical, or thermal means to eradicate weeds, has moved from academic research settings to commercialization. Because of labor shortage pressures, the push to gain competitive advantages, and the environmental impacts of excessive chemical inputs, many California growers have been interested in adopting precision weeding technologies in their operations. OBJECTIVEUsing semi-structured qualitative interviews, this study investigated the viewpoints of three key stakeholder groups involved in the diffusion and adoption of precision weeding technologies: California growers, precision weeding startups, and agricultural technology venture capital firms. With the supplemental viewpoints of large agricultural firms and their corporate venture capital arms and government agencies, this study seeks to understand the compatible motivations between stakeholders, current collaborative models between stakeholders and their limitations, and the user journey for growers adopting precision weeding technology. METHODSWe conducted 17 semi-structured qualitative interviews with diverse stakeholders in the precision weeding sector to gather textual data and gain high data saturation. Data collection balanced rigorous criteria for participant selection with adaptive interview questions to ensure depth and relevance. The analysis procedure involved coding and thematic framework development, complemented by grounded theory for iterative data examination and stakeholder map creation for distilling cross-organizational insights and stakeholder dynamics. RESULTS AND CONCLUSIONSThe results indicated that compatible motivations include addressing current labor issues, reducing costs, and the potential of precision weeding to transform agriculture. Less cited but still popular motivations included having more weeding options, meeting specific field needs, and environmental sustainability. The individual and stakeholder group cognitive maps demonstrated that concerns such as startup longevity, the high expenses of precision weeding machinery, and some startups lacking a direct connection to growers commonly limit the growers' adoption of precision weeding technologies. SIGNIFICANCEThe procedure and cognitive mapping presented in this study can be applied to other emerging agtech technologies and ecosystems.

Morphometric Analysis of Actin Networks.

The organization of cytoskeletal elements is pivotal for coordinating intracellular transport in eukaryotic cells. Several quantitative measures based on image analysis have been proposed to characterize morphometric features of fluorescently labeled actin networks. While helpful in detecting differences in actin organization between treatments or genotypes, the accuracy of these measures could not be rigorously assessed due to a lack of ground-truth data to which they could be compared. To overcome this limitation, we utilized coarse-grained computer simulations of actin filaments and crosslinkers to generate synthetic actin networks with varying levels of bundling. We converted the simulated networks into pseudo-fluorescence images similar to images obtained using confocal microscopy. Using both published and novel analysis procedures, we extracted a series of morphometric parameters and benchmarked them against analogous measures based on the ground-truth actin configurations. Our analysis revealed a set of parameters that reliably reports on actin network density, orientation, ordering, and bundling. Application of these morphometric parameters to root epidermal cells of Arabidopsis thaliana revealed subtle changes in network organization between wild-type and mutant cells. This work provides robust measures that can be used to quantify features of actin networks and characterize changes in actin organization for different experimental conditions.

Reducing health disparities in providing care services in the intensive care unit: a critical ethnographic study

ObjectiveThe intensive care unit, with its structural complexity and the exposure of critically ill patients to various disparities, presents a significant setting for health disparities. This critical ethnographic study sought to uncover cultural knowledge and ethical practices for reducing health disparities in providing care services within the intensive care unit. The focus was on understanding how ethical considerations and cultural competence can address and mitigate these disparities effectively.MethodsThis critical ethnographic study was conducted in 2022–2023 at intensive care units in western Iran. Three interrelated phases were used to collect and analyze the data. More than 300 h of observation were done during the first phase. A horizon analysis was carried out in the next phase. To further enhance the dataset, 18 informants participated in semi-structured interviews and informal conversations. Following that, the analysis procedure was conducted to identify a culture of health disparities and factors that reduce it, as it had been in the prior stage. Trustworthiness data collection methods were implemented to ensure the validity and reliability of the study.FindingsTwo key themes emerged from the study: (A) Improved cultural competence, which encompassed empathy towards patients and their families, effective communication, prioritization of continuous learning, appropriate knowledge and awareness, sensitivity to cultural and religious beliefs, staff attitude and personality, and the delivery of customized care tailored to each patient’s needs. (B) Supporting role and compensating for disparities involved recommendations for upholding ethical standards, compensatory actions, maintaining professional behavior despite external factors, addressing gaps and deficiencies, and actively defending and supporting patients.ConclusionThe findings indicate that staff with high cultural competence can ethically mitigate health disparities through their supportive roles. Managers and health policymakers should create barriers to health disparity by improving staff cultural competence and knowledge about health disparities.

Evaluating overhanging slope failure mechanisms and rockfall trajectories through integrated UAV imagery and discrete element modeling

AbstractTo evaluate the threat of rockfall from an overhanging slope above a bridge, this study proposes a comprehensive analysis procedure to assess the failure mechanisms of the slope and the associated rockfall trajectories. The analysis utilizes high-resolution point cloud data obtained through integrated UAV-based imagery technology, enabling a detailed evaluation of joint configurations and slope stability. The geometric reconstruction of unstable rock blocks, combined with stereographic projections, provides an in-depth analysis of potential failure modes. Discrete element modeling (DEM) is employed to simulate the failure processes and predict rockfall trajectories, with particular emphasis on the potential risks to the underlying bridge. The results indicate that rockfall events near the bridge are primarily driven by wedge-shaped failures, a finding confirmed by both the proposed inverted three-dimensional projection method and DEM simulations. The analysis identifies critical rock blocks near the bridge, underscoring the need for targeted mitigation strategies. This case study demonstrates the effectiveness of integrating UAV-derived data with DEM for assessing overhanging slope failures and managing rockfall risks in similar geological settings.

Providing quality-assessed and standardised soil data to support global mapping and modelling (WoSIS snapshot 2023)

Abstract. Snapshots derived from the World Soil Information Service (WoSIS) are served freely to the international community. These static datasets provide quality-assessed and standardised soil profile data that can be used to support digital soil mapping and environmental applications at broad scale levels. Since the release of the preceding snapshot in 2019, refactored ETL (extract, transform and load) procedures for screening, ingesting and standardising disparate source data have been developed. In conjunction with this, the WoSIS data model was overhauled, making it compatible with the ISO 28258 and Observations and Measurements (O&M) domain models. Additional procedures for querying, serving and downloading the publicly available standardised data have been implemented using open software (e.g. GraphQL API). Following up on a short discussion of these methodological developments we discuss the structure and content of the “WoSIS 2023 snapshot”. A range of new soil datasets was shared with us, registered in the ISRIC World Data Centre for Soils (WDC-Soils) data repository and subsequently processed in accordance with the licences specified by the data providers. An important effort has been the processing of forest soil data collated in the framework of the EU-HoliSoils project. We paid special attention to the standardisation of soil property definitions, description of the soil analytical procedures and standardisation of the units of measurement. The 2023 snapshot considers soil chemical properties (total carbon, organic carbon, inorganic carbon (total carbonate equivalent), total nitrogen, phosphorus (extractable P, total P and P retention), soil pH, cation exchange capacity and electrical conductivity) and physical properties (soil texture (sand, silt and clay), bulk density, coarse fragments and water retention), grouped according to analytical procedures that are operationally comparable. Method options are defined for each analytical procedure (e.g. pH measured in water, KCl or CaCl2 solution, molarity of the solution, and soil / solution ratio). For each profile we also provide the original soil classification (i.e. FAO, WRB and USDA system with their version) and pedological horizon designations as far as these have been specified in the source databases. Three measures for “fitness for intended use” are provided to facilitate informed data use: (a) positional uncertainty of the profile's site location, (b) possible uncertainty associated with the operationally defined analytical procedures and (c) date of sampling. The most recent (i.e. dynamic) dataset, called wosis_latest, is freely accessible via various web services. To permit consistent referencing and citation, we also provide a static snapshot (in this case, December 2023). This snapshot comprises quality-assessed and standardised data for 228 000 geo-referenced profiles. The data come from 174 countries and represent more than 900 000 soil layers (or horizons) and over 6 million records. The number of measurements for each soil property varies (greatly) between profiles and with depth, this generally depending on the objectives of the initial soil sampling programmes. In the coming years, we aim to gradually fill gaps in the geographic distribution of the profiles, as well as in the soil observations themselves, this subject to the sharing of a wider selection of “public” soil data by prospective data contributors; possible solutions for this are discussed. The WoSIS 2023 snapshot is archived and freely available at https://doi.org/10.17027/isric-wdcsoils-20231130 (Calisto et al., 2023).

Deformation behaviour of strain-softening rock mass in tunnels considering deterioration model of elastic modulus

By analyzing the composite effects of the plastic shear strain and confining stress according to the laboratory test results, a model adopting a deteriorating elastic modulus for the intact rock is proposed. Soft rock such as coal and the strong rock such as granite with different quality are investigated. Geological Strength Index (GSI) is adopted to represent the integrity of rock, to be specific, from intact rock to the rock mass. Specifically, for the strain-softening rock mass, the elastic modulus is gained by introducing GSI into the deterioration model. The strength parameters are obtained by fitting GSI into Hoek-Brown failure criterion. Then, the elastic modulus and strength parameters of the rock mass are employed in the numerical procedure for solving out the rock deformation, the radii of the plastic softening and residual zones of the tunnels. The rationality of the numerical procedure is verified with the existing semi-analytical and analytical procedures. In the discussion, the influences of the critical plastic parameters and GSI, on the elastic modulus, rock deformation, radii of the plastic softening and residual zones are investigated. Five models for the variation of the modulus including the proposed deterioration model are defined. The rock mass deformation behaviours of the five models are compared. The results indicate that, in the plastic softening zone that is far away from the tunnel periphery, the elastic modulus is more sensitive to the plastic shear strain, whereas near the tunnel periphery, the elastic modulus is primarily affected by the confining stress. Regarding a linear decrease of the elastic modulus versus the plastic shear strain overestimates the elastic modulus to some extent, especially for the soft rock mass.

Electrochemical Acid-Base Transport Limitation Principle for Low Electroactive Analyte Sensing in Wastewater Monitoring.

Electrochemical sensing (ES) is crucial for improving data acquisition in wastewater treatment, but obtaining the signal for a low electroactive analyte is challenging. Here, we propose an electrochemical acid-base transport limitation (eABTL) principle for inertness-based sensing, offering a new insight into generating ES signals from an interfacial transport process rather than electron transfer. This principle enables potential ES application for various weak acids and bases (WABs) without reactions themselves. We established an eABTLP method for detecting orthophosphate in solutions as a proof of concept, demonstrating commendable accuracy and precision, and a wide detection range from 10 μM to over 300 mM. Endogenous interferences were identified using 23 weak acids, indicating no significant endogenous interfering factors in typical wastewaters. Of them, volatile fatty acids are the main interference, but their effect can be eliminated by adjusting pH above 6.0. Exogenous factors like anions, cations, ion strength, temperature, organic load, and dissolved oxygen were examined, and most of their effects can be ignored by maintaining consistent analytical procedures between calibration curve and sample. Furthermore, measurement of wastewater samples confirmed the applicability toward domestic wastewater and demonstrated its wide applicability when combined with digestion pretreatment. Given the merits of inertness-based sensing, the eABTL-based methods have the potential to be a crucial part of ES techniques for environmental and industrial monitoring.

A novel optimization‐based modal pushover analysis procedure for estimating the response of structures

AbstractIn recent years, studies have focused on the seismic behavior of various structural systems, including single‐ and double‐layered spatial structures. While nonlinear dynamic analyses are common for these studies, they are time‐consuming and complex. To address this, many pushover procedures have been developed, but their effectiveness in spatial structures remains underexplored. This study introduces an optimized lateral loading profile for evaluating the seismic response of walled bilayer spatial structures. By combining dominant inertial forces and optimizing their corresponding coefficients with the particle swarm optimization (PSO) algorithm, an optimal loading profile is derived. The method's accuracy was tested on models with varying arch height‐to‐span ratios and a constant wall height‐to‐span ratio, as well as a 15‐story frame structure. The results obtained showed that the proposed method closely matches incremental dynamic analyses (IDAs) in predicting base shear, initial stiffness, and displacements, especially for higher arch height‐to‐span ratios. Additionally, the method accurately estimates drift profiles and nodal displacements on roofs and walls, and performs better than similar mode‐based methods for frame structures.

Patterns of Sexuality, Adjustment to Aging and Satisfaction with Life: A Cluster Analysis of Adults Across the Lifespan

AbstractSexual satisfaction, adjustment to aging, and satisfaction with life are relevant dimensions of overall well-being across the life cycle. Through cluster analysis procedures, this study aims to describe the specific profile of adjustment to aging, sexual satisfaction and satisfaction with life of adults across the life span. This cross-sectional study involved a community-based sample of 619 Portuguese individuals, aged between 18 and 92 years old (M = 47.53 SD = 18.34) evaluated using a two-step cluster analysis. Fours clusters emerged. The most adjusted participants were mostly of a younger age, women and had a high education. The least adjusted participants globally presented low education, poor perceived health, and poor engagement in leisure activities. Well-being focused participants were mostly women of older age, with high education and spirituality. Finally, moderately satisfied participants were mostly men of older age, had a lower education, and presented poor reported health. Complementary comparative analysis among the identified subgroups was performed. The most adjusted participants had the highest perceived overall sexual well-being, sexual attractiveness, sexual openness and communication, and sexual satisfaction. These data characterize the profile of this population and can be used as the basis for developing efficient strategies aimed a combining adjustment to aging, satisfaction with life and sexual satisfaction for tailored interventions to the specific needs of populations across the lifespan.

Selective Sorption of Noble Metals on Polymer Gel Modified with Ionic Liquid.

The solid phase extraction of Au, Ir, Pd, Pt, and Rh on a polymer gel modified with ionic liquid containing methylimidazolium groups (MIA-PG) has been investigated. The positively charged surface of the sorbent is highly suitable for the sorption of stable chlorido complexes of the studied analytes, while the retention of base metals Cu, Fe, Ni, Zn, and Mn is negligible. Optimization experiments performed showed that, at 0.05 M HCl, the degree of sorption of Au, Ir, Pd, and Pt is above 95%, and only for Rh, the maximum degree is 65%; complete elution is achieved in the mixture of thiourea in HCl. The results obtained from the equilibrium adsorption studies are fitted in various adsorption models, such as Langmuir and Freundlich, and the model parameters have been evaluated. The kinetics analysis indicated that the adsorption of Au, Ir, Pd, Pt, and Rh onto the sorbent follows the pseudo-second-order model. Intraparticle diffusion and ion exchange reactions were the rate-limiting steps. Analytical procedures were developed for Pd, Pt, and Rh determination in road dust and soil and for Au determination in copper ore and copper concentrate. The procedures are validated by the analysis of certified reference materials. Analytical figures of merit confirmed their applicability in routine laboratory practice.

Augmented Reality for Air Quality Monitoring: Case Study in the Marche Region (Italy)

Abstract. Augmented Reality (AR) allows the real world to be enhanced through the overlapping of digital information generated by an algorithm or software amplifying the user's perception. In this research, the potential of AR is exploited by applying it to the problem of air pollution visualization to raise awareness of the issue. It is well known that the principal sources of air pollution include industry, domestic heating, traffic, production processes and more others. According to European Environment Agency, air pollution is the largest environmental health risk in Europe in 2022 affecting respiratory and cardiovascular diseases and premature deaths. A suitable combination of GIS-based procedures for data analysis and georeferencing, AR systems for the visualization and exploitation of the results, can be a strategic driver. The research presented in this paper has been experimented in the Marche Region, in the central part of Italy, and in particular the city of Ancona. The pollutant data collected come from 17 Agenzia Regionale per la Protezione Ambientale delle Marche (ARPAM) meteorological ground-based stations located in Marche Region. The data processing have been executed using the software ArcGis Pro instead of a 3D City Model has been acquired from the online 3D ArcGIS platform. According to the Dlgs.155/2010 regulation, the AQI index (Air Quality Index) has been provided by the interpolation of the meteorological ground stations data. The visualization phase has been tackled exploiting in a WebGIS platform and an APP by AR. A 3D immersive visualization is made using five AQI level of air quality (excellent, good, fair, poor, bad) in order to increase the urban sensing.