Browse Articles

Assessing the influence of the modifiable areal unit problem on Bayesian disease mapping in Queensland, Australia

Background Spatial data are often aggregated by area to protect the confidentiality of individuals and aid the calculation of pertinent risks and rates. However, the analysis of spatially aggregated data is susceptible to the modifiable areal unit problem (MAUP), which arises when inference varies with boundary or aggregation changes. While the impact of the MAUP has been examined previously, typically these studies have focused on well-populated areas. Understanding how the MAUP behaves when data are sparse is particularly important for countries with less populated areas, such as Australia. This study aims to assess different geographical regions’ vulnerability to the MAUP when data are relatively sparse to inform researchers’ choice of aggregation level for fitting spatial models. Methods To understand the impact of the MAUP in Queensland, Australia, the present study investigates inference from simulated lung cancer incidence data using the five levels of spatial aggregation defined by the Australian Statistical Geography Standard. To this end, Bayesian spatial BYM models with and without covariates were fitted. Results and conclusion The MAUP impacted inference in the analysis of cancer counts for data aggregated to coarsest areal structures. However, area structures with moderate resolution were not greatly impacted by the MAUP, and offer advantages in terms of data sparsity, computational intensity and availability of data sets.

Room temperature magnetocaloric effects in monoclinic Cr3Te4

We report a systematic investigation of anisotropic magnetocaloric effects in a crystalline, monoclinic Cr3Te4 sample grown by the chemical vapor transport (CVT) method. The maximum magnetic entropy change −ΔSmaxM is 3.31 J kg−1 K−1 for the c axis (3.16 J kg−1 K−1 for the ab-plane) and the relative cooling power (RCP) is 340 J kg−1 for the c axis (350 J kg−1 for the ab-plane) near the Curie temperature with a magnetic field (μ0H) change of 9 T. With the scaling analysis of ΔSM, all rescaled ΔSM(T, H) curves collapse onto a single universal curve, indicating a second-order magnetic phase transition in Cr3Te4. Furthermore, −ΔSmaxM follows the power law of Hn with n = 0.656 ± 0.005. The RCP and δTFWHM have Hc and Hb dependence on field, with c = 1.179 ± 0.011 and b = 0.498 ± 0.005, respectively, which led us to estimate the critical exponents of β = 0.359 ± 0.013, γ = 1.646 ± 0.057, and δ = 5.578 ± 0.190.

Life history is a key driver of temporal fluctuations in tropical tree abundances

The question of what mechanisms maintain tropical biodiversity is a critical frontier in ecology, intensified by the heightened risk of biodiversity loss faced in tropical regions. Ecological theory has shed light on multiple mechanisms that could lead to the high levels of biodiversity in tropical forests. But variation in species abundances over time may be just as important as overall biodiversity, with a more immediate connection to the risk of extirpation and biodiversity loss. Despite the urgency, our understanding of the primary mechanisms driving fluctuations in species abundances has not been clearly established. Here, we introduce a theoretical framework based around life history; the schedule of birth, growth, and mortality over a lifespan, and its systematic variation across species. We develop a mean field model to predict expected fluctuations in abundance for a focal species in a larger community, and we quantify empirical life history variation among 90 tropical forest species in a 50 ha plot in Panama. Putting theory and data together, we show that life history provides a critical piece of this puzzle, allowing us to explain patterns of abundance fluctuations more accurately than previous models incorporating demographic stochasticity without life history variation, and without introducing unobserved couplings between species and their environment. This framework provides a starting point for more general models that incorporate multiple factors in addition to life history variation, and suggests the potential for a fine-grained assessment of extirpation risk based on the impacts of anthropogenic change on demographic rates across life stages.

A novel MADM model integrating hybrid information for evaluating the development prospects of urban new energy vehicles

As an effective approach to mitigating urban environmental issues, New Energy Vehicles (NEVs) have become a focal point of research regarding their current development status and future prospects in China. Addressing the significant disparities in the development of the NEVs industry across different cities, this study focuses on ten typical Chinese cities and develops a novel multi-attribute decision-making (MADM) framework to evaluate the prospects of NEVs promotion in these cities. The study first establishes a comprehensive indicator system that covers key dimensions such as economy, policy support, infrastructure, technological innovation, and environment, encompassing five different types of evaluation information. This system incorporates five different types of evaluation information: exact numbers, interval numbers, triangular fuzzy numbers, hesitant fuzzy numbers, and probabilistic linguistic term sets (PLTS), enhancing the framework’s ability to handle diverse data types. Subsequently, the improved entropy (IEntropy) weight method is employed to determine the objective weights of the evaluation indicators. These objective weights are then integrated with the Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, facilitating a structured group decision-making approach that synthesizes hybrid evaluation information. Based on modular thinking, hybrid evaluation information is synthesized to evaluate and rank the NEVs development prospects of each city. Sensitivity analysis and comparative analysis further demonstrate the robustness and reliability of the proposed MADM framework. The ranking results indicate that Shanghai and Guangzhou lead in NEVs promotion, while cities like Harbin and Zhengzhou lag behind. Based on these findings, the study proposes targeted policy recommendations to promote the sustainable development of the NEVs industry in major Chinese cities.

Mn doped in SOD-BN: A half-metallic ferromagnet with high Curie temperature and large magnetic anisotropy

Searching for practicable half-metallic ferromagnets (HMFs) with a high Curie temperature and large magnetic anisotropic energy is crucial for advancing next-generation spintronic devices. Here, we predict a promising material, Mn-doped sodalite-like boron nitride (Mn@SOD-BN), using density functional theory. Specifically, Mn@SOD-BN possesses 100% spin polarization with a large half-metal direct bandgap of about 2.05 eV, which can effectively prevent spin-flip scattering during spin transport. Mn@SOD-BN exhibits a robust ferromagnetic ground state under carrier doping and external strain. Monte Carlo simulations based on the classical Heisenberg model predict a Curie temperature of 670 K for Mn@SOD-BN, which is attributed to the strong exchange interactions between Mn-3d and N-2p orbitals. Moreover, Mn@SOD-BN exhibits a sizable magnetic anisotropy energy of 365 μeV per Mn atom. Therefore, Mn@SOD-BN is a promising HMF for practical spintronic devices. In addition, the significant value of the absorption coefficient in the ultraviolet region of Mn@SOD-BN poses it as a potential candidate for ultraviolet optoelectronic devices.

Heterogeneous and multiple conformational transition pathways between pseudoknots of the SARS-CoV-2 frameshift element

Frameshifting is an essential mechanism employed by many viruses including coronaviruses to produce viral proteins from a compact RNA genome. It is facilitated by specific RNA folds in the frameshift element (FSE), which has emerged as an important therapeutic target. For SARS-CoV-2, a specific 3-stem pseudoknot has been identified to stimulate frameshifting. However, prior studies and our RNA-As-Graphs analysis coupled to chemical reactivity experiments revealed other folds, including a different pseudoknot. Although structural plasticity has been proposed to play a key role in frameshifting, paths between different FSE RNA folds have not been yet identified. Here, we capture atomic-level transition pathways between two key FSE pseudoknots by transition path sampling coupled to Markov State Modeling and our BOLAS free energy method. We reveal multiple transition paths within a heterogeneous, multihub conformational landscape. A shared folding mechanism involves RNA stem unpairing followed by a 5 ′ -chain end release. Significantly, this pseudoknot transition critically tunes the tension through the RNA spacer region and places the viral RNA in the narrow ribosomal channel. Our work further explains the role of the alternative pseudoknot in ribosomal pausing and clarifies why the experimentally captured pseudoknot is preferred for frameshifting. Our capturing of this large-scale transition of RNA secondary and tertiary structure highlights the complex pathways of biomolecules and the inherent multifarious aspects that viruses developed to ensure virulence and survival. This enhanced understanding of viral frameshifting also provides insights to target key transitions for therapeutic applications. Our methods are generally applicable to other large-scale biomolecular transitions.

Use of evidence-based health professions education: Attitudes and practices of academic leaders

Purpose The objective of this study was to explore the attitudes, practices, supports, and barriers of academic leaders regarding the use of Evidence-Based Health Professional Education (EBHPE). Methods A cross-sectional survey was conducted on 79 faculty members in leadership positions, from four different undergraduate colleges at Qassim University. A pre-validated questionnaire was distributed electronically. The e-questionnaire was comprised of 38 questions regarding participants’ demographics, attitudes, practices, and perceived barriers/supports towards EBHPE. Data was analyzed using SPSS. Descriptive statistics were calculated for demographic characteristics and responses to survey items. The frequency distribution of the subjects was analyzed, and the median and means were calculated. Kruskall-Wallis and Mann-Whitney U tests were used for comparison of the means between the demographic groups. Spearman correlation was utilized to determine any relationships between the questionnaire’s three sections. Results Of the 79 participants, 24 were Department Heads and 48 were female. The mean±SD values for Attitude, Practices and Support/Barriers were found to be 3.47±0.40, 2.72±0.84 and 3.34±0.43, respectively. The mean value of Attitude Score was > 3.41, therefore, it was interpreted that respondents had positive attitude towards EBHPE. Conversely, the values for Practices and Support/Barriers were interpreted as neutral (range = 2.61–3.40), neither good nor bad. The correlation coefficients between ’attitudes’ and ’supports and barriers’ (0.388) and ‘practices’ and ‘supports and barriers’ (0.388) indicated the weak association between these factors. The Cronbach’s α value for questionnaire was found to be 0.887 indicating its reliability. Conclusions This study concludes that the respondents had positive attitude towards EBHPE. However, this positive attitude was not reflected in their practices. Healthcare professionals should be committed to educational excellence, and endeavour to rely on evidence-based literature regarding the planning and review of learning, teaching, and assessment strategies.

Efficient methods for extracting superconducting resonator loss in the single-photon regime

Superconducting micro-resonators have application in sensors and quantum computing. Measurement of the resonator internal loss in the single-photon regime is a common tool to study the origins of dissipation, noise, and decoherence in quantum circuits, as well as characterization of materials used for quantum devices. However, such measurements are challenging and time-consuming with large uncertainties due to the poor signal-to-noise ratio when measured at single-photon power levels. We developed methods to extract a subset of the resonator fitting parameters at high power and fix them in the analysis of low power data, which reduce the parameter space in the regression analysis. By comparing the analysis with and without partial extraction, we show that these methods reduce the uncertainty of the results, while improving the robustness and efficiency of the loss measurement.

Evidence that ARK2N is not a core factor in transcription-coupled DNA repair

Correction: Comparative analysis of chloroplast genomes of seven Juniperus species from Kazakhstan

Acceleration of a dielectric flyer by underwater electrical explosions of a metallic foil or by the generated shockwave and waterflow

The results of experiments and numerical modeling show that a polyoxymethylene (Delrin) flyer is accelerated to nearly the same velocity (∼800 m/s) by either the underwater electrical sub-μs timescale explosion of 15 μm thick Al and Cu foils, or by the shock and water flow generated by the explosion of these foils. Experiments were carried out on the high-current generator delivering to the foil, a current of ∼280 kA with a rise time of ∼450 ns. The velocity of the flyer was determined using a photonic Doppler velocimeter and multi-frame shadow images of the flyer. It was shown that thermal expansion of the foil leads to the destruction of the flyer but it is not so when the flyer is accelerated by the shock and the water flow. Additionally, spallation of the methyl methacrylate disk used as a support to the flyer was observed, with a spall velocity of up to ∼1200 m/s.

Reply to van Schie et al.: ARK2N in TCR: Across in vivo and in vitro studies

Translation and cultural adaption of MacLeod Clark professional identity scale among Chinese therapy students

Background Fostering a strong professional identity (PI) enhances career fulfillment. In China, therapy education is undergoing development, integrating both Western and traditional health concepts, causing inconsistent PI among therapy students. To date, no validated tools exist to measure and monitor PI of Chinese therapy students. This study aimed to translate and validate the 9-item MacLeod Clark Professional Identity Scale (MCPIS-9) for this purpose. Design This study involved translation and cultural adaptation of the MCPIS-9, followed by a rigorous assessment of its model fit and psychometric properties using data collected via an online questionnaire. Methods A forward- and backward- translation process was conducted. Content validity was evaluated using item-level content validity index (I-CVI) and scale level content validity index average method (S-CVI/Ave). Therapy students across all grades at undergraduate and postgraduate levels in China were eligible. Exploratory factor analysis (EFA) examined the underlying factor structure. Model fit was evaluated through confirmatory factor analysis (CFA) using the Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), Standardized Root Mean Square Residual (SRMR) and Root Mean Square of Error of Approximation (RMSEA). Convergent validity was assessed through Pearson’s correlations coefficient (r) with the Professional Identity Scale for Health Students and Professionals (PISHSP). Internal consistency was examined using Cronbach’s Alpha (Cα) and McDonald’s Omega (ω). Results A total of 1054 students participated. Content validity was excellent (I-CVI = 0.86–1.0, S-CVI/Ave = 0.98). EFA indicated a two-factor structure with acceptable model fit (CFI = 0.978; TLI = 0.968; SRMR = 0.033; RMSEA = 0.063). Reliability was strong (Cα = 0.835; ω = 0.817). Convergent validity demonstrated a strong correlation (r = 0.75) with the PISHSP. Conclusions The Chinese MCPIS-9 is a reliable and valid tool for assessing PI among therapy students. Future research could focus on refining item 4 of this tool, potentially through further exploration of therapy students’ perceptions of PI within the unique context of the Chinese healthcare system.

Evaluation of the device characteristics of Bi2Sr2CaCu2O8+<i>δ</i> terahertz-wave emitters using wet-etching techniques

Understanding the device characteristics associated with the shape and size of crystal chips is a key requirement for developing high-performance terahertz (THz) wave-emitting devices made of high-temperature superconductor Bi2Sr2CaCu2O8+δ(Bi2212) crystal chips, because these parameters reflect the emission frequency, emission power, self-heating conditions, and impedance matching. Wet-etching techniques are beneficial for creating comparable emitting chips from the same crystal fragment to further understand the above points regarding using Bi2212-crystal chips. Using wet-etching techniques, we prepared rectangular crystal chips with the same area using three different width (w) and length (L) aspect ratios and compared their emission characteristics. The range of the observed emission frequencies tended to be less dependent on the w/L ratio. However, the three samples differed significantly in terms of the excitation modes expected from the w/L ratio. When the aspect ratio approached one, the results indicated a tendency to resonate in the higher excitation modes. The excitation modes along the width of the chip were suppressed by decreasing the w/L ratio owing to the increased resonance frequencies of the transverse magnetic TM(m,0) modes. Although further studies are required, especially in terms of output enhancement, the results obtained herein are expected to aid in producing devices that can operate in the desired excitation mode.

Macromolecular interactions and geometrical confinement determine the 3D diffusion of ribosome-sized particles in live <i>Escherichia coli</i> cells

The crowded bacterial cytoplasm is composed of biomolecules that span several orders of magnitude in size and electrical charge. This complexity has been proposed as the source of the rich spatial organization and apparent anomalous diffusion of intracellular components, although this has not been tested directly. Here, we use biplane microscopy to track the 3D motion of self-assembled bacterial genetically encoded multimeric nanoparticles (bGEMs) with tunable size (20 to 50 nm) and charge (−3,240 to +2,700 e) in live Escherichia coli cells. To probe intermolecular details at spatial and temporal resolutions beyond experimental limits, we also developed a colloidal whole-cell model that explicitly represents the size and charge of cytoplasmic macromolecules and the porous structure of the bacterial nucleoid. Combining these techniques, we show that bGEMs spatially segregate by size, with small 20-nm particles enriched inside the nucleoid, and larger and/or positively charged particles excluded from this region. Localization is driven by entropic and electrostatic forces arising from cytoplasmic polydispersity, nucleoid structure, geometrical confinement, and interactions with other biomolecules including ribosomes and DNA. We observe that at the timescales of traditional single molecule tracking experiments, motion appears subdiffusive for all particle sizes and charges. However, using computer simulations with higher temporal resolution, we find that the apparent anomalous exponents are governed by the region of the cell in which bGEMs are located. Molecular motion does not display anomalous diffusion on short time scales and the apparent subdiffusion arises from geometrical confinement within the nucleoid and by the cell boundary.

Impact of antibiotics, iron oxide, and sodium sulfate on microbial community composition in laboratory-built municipal solid waste microcosms

Municipal solid waste (MSW) landfills represent underexplored microbial ecosystems. Landfills contain variable amounts of antibiotic and construction and demolition (C&amp;D) wastes, which have the potential to alter microbial metabolism due to biocidal or redox active components, and these effects are largely underexplored. To circumvent the challenge of MSW heterogeneity, we conducted a 65-day time series study on simulated MSW microcosms to assess microbiome changes using 16S rRNA sequencing in response to 1) Fe(OH)3 and 2) Na2SO4 to represent redox active components of C&amp;D waste as well as 3) antibiotics. The addition of Fe(OH)3 altered the overall community composition and increased Shannon diversity and Chao1 richness. The addition of a mixture of seven antibiotics (1000 ng/L each) altered the community composition without affecting diversity metrics. Sulfate addition had little effect on microbial community composition or diversity. These results suggest that the microbial community composition in fresh MSW may be significantly impacted by influxes of iron waste and a single application of antibiotics.

Publisher's note: “Phase tailoring of silver oxide thin films for improved antimicrobial activity” [J. Appl. Phys. 136, 235301 (2024)]

Automating alloy design and discovery with physics-aware multimodal multiagent AI

The design of new alloys is a multiscale problem that requires a holistic approach that involves retrieving relevant knowledge, applying advanced computational methods, conducting experimental validations, and analyzing the results, a process that is typically slow and reserved for human experts. Machine learning can help accelerate this process, for instance, through the use of deep surrogate models that connect structural and chemical features to material properties, or vice versa. However, existing data-driven models often target specific material objectives, offering limited flexibility to integrate out-of-domain knowledge and cannot adapt to new, unforeseen challenges. Here, we overcome these limitations by leveraging the distinct capabilities of multiple AI agents that collaborate autonomously within a dynamic environment to solve complex materials design tasks. The proposed physics-aware generative AI platform, AtomAgents, synergizes the intelligence of large language models (LLMs) and the dynamic collaboration among AI agents with expertise in various domains, including knowledge retrieval, multimodal data integration, physics-based simulations, and comprehensive results analysis across modalities. The concerted effort of the multiagent system allows for addressing complex materials design problems, as demonstrated by examples that include autonomously designing metallic alloys with enhanced properties compared to their pure counterparts. Our results enable accurate prediction of key characteristics across alloys and highlight the crucial role of solid solution alloying to steer the development of advanced metallic alloys. Our framework enhances the efficiency of complex multiobjective design tasks and opens avenues in fields such as biomedical materials engineering, renewable energy, and environmental sustainability.

Climate change heterogeneity: A new quantitative approach

Climate change is a spatial and temporarily non-uniform phenomenon that requires understanding its evolution to better evaluate its potential societal and economic impact. The value added of this paper lies in introducing a quantitative methodology grounded in the trend analysis of temperature distribution quantiles to analyze climate change heterogeneity (CCH). By converting these quantiles into time series objects, the methodology empowers the definition and measurement of various relevant concepts in climate change analysis (warming, warming typology, warming amplification and warming acceleration) in a straightforward and robust testable linear regression format. It also facilitates the introduction of new testable concepts like warming dominance to compare (globally or partially) the warming process experienced by different regions. Furthermore, the methodology holds the added significance of concurrently encompassing both temporal and spatial dimensions in temperature analysis, owing to the close alignment between unconditional quantiles and latitude measures. Applying our quantitative methodology for the period 1950-2019 to the Globe (2192 stations) and Spain (30 stations) as a benchmark region, we find that both experience a distributional warming process (beyond the standard average) but of very different types. While the Globe experiences a stronger warming in the lower temperatures than in the upper ones, Spain evolves from equal warming in the whole distribution toward a stronger warming in the upper quantiles (similar to the warming process experienced in the African continent). In the two cases, the warming process accelerates (non-linear behavior) over time and is asymmetrically amplified. Overall, although both the Globe and Spain suffer an equivalent warming process in the median (mean) temperature, Spain’s warming dominates the Globe in the upper quantiles and is dominated in the lower tail of the global temperature distribution that corresponds to the Arctic region. Our climate change heterogeneity results open the door to the need for a non-uniform causal-effect climate analysis that goes beyond the standard causality in mean and for a more efficient design of the mitigation-adaptation policies. In particular, the heterogeneity found suggests these policies should contain a common global component and a clear local-regional idiosyncratic element. The latter is usually more straightforward to implement.

Resistive switching and synaptic characteristics in ZnO@β-SiC composite-based RRAM for neuromorphic computing

The advancement of neuromorphic computing in resistive random-access memory (RRAM) is crucial for the rapid expansion of artificial intelligence. Conventional metal oxide-based RRAM faces challenges in mimicking synaptic activity, leading to the exploration of new resistive switching (RS) materials. This study introduces a ZnO@β-SiC composite-based RRAM device that exhibits biological synapse-like functionality. The device shows self-compliance and forming-free RS at ∼0.8 V, where it also mimics synaptic responses such as potentiation, depression, and paired-pulse facilitation at low voltage stimuli (∼0.6 V, 40 ms) with learning and forgetting behavior. Moreover, the synaptic plasticity is analyzed through spike rate dependent plasticity, spike number dependent plasticity, and spike time dependent plasticity. Further, the transition from short-term plasticity to long-term plasticity is observed under more training pulses and lower interval stimuli. The observed RS mechanism and synaptic functionalities are explained by the electric field-driven formation and dissolution of conducting filaments of oxygen vacancies. The chemical properties and local electronic structure have been examined by x-ray photoelectron spectroscopy and x-ray absorption spectroscopy. To elucidate the atomistic memristive behavior and the contribution of different electrical parameters in RRAM, detailed conductive atomic-force microscopy and impedance analysis have been carried out.