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<i>Ab initio</i> spin-mapping non-adiabatic dynamics simulations of photochemistry
We perform on-the-fly non-adiabatic molecular dynamics simulations using the recently developed spin-mapping formalism. Two quantum dynamics approaches based on this mapping formalism, (i) the fully linearized Spin-LSC and (ii) the partially linearized Spin-PLDM, are explored using the quasi-diabatic propagation scheme. We have performed dynamics simulations in four ab initio molecular models for which benchmark ab initio multiple spawning (AIMS) data have been published. We find that the spin-LSC and the previously reported symmetric quasi-classical (SQC) approaches provide nearly equivalent population dynamics. While we expected the more involved spin-PLDM method to provide superior accuracy compared to the other mapping-based approaches, SQC and spin-LSC, we found that it performed with equivalent accuracy compared to the AIMS benchmark results. We further explore the underpinnings of the spin-PLDM correlation function by decomposing its N2 density matrix-focused initial conditions, where N is the number of states in the quantum subsystem. Finally, we found an approximate form of the spin-PLDM correlation function, which simplifies the simulation and reduces the computational costs from N2 to N.
Exploring the narrative landscape: The discursive construction of identity for Chinese enterprises in Africa
This study investigates the construction of corporate identities by Chinese enterprises in Africa, employing the Three-dimensional Model of Fairchough in conjunction with the corporate communication strategies outlined by Kim and Rader. Through an extensive analysis of official website content from 200 Chinese companies, this study explores how these corporations utilize communication strategies to project their identities. The findings reveal a strategic use of discourse to align corporate practices with local cultures and business norms, facilitating their expansion and acceptance in African markets. This study contributes to understanding the dynamic and constructed nature of corporate identities in cross-cultural settings and provides insights into the strategic communication practices of Chinese firms in Africa.
Acute and chronic gene expression activation following medial forebrain bundle DBS and selective dopamine pathway stimulation
Abstract Deep brain stimulation (DBS) of the medial forebrain bundle (mfb) demonstrated anti-depressant effects both clinically and experimentally. Modulation of mesocorticolimbic dopaminergic (DA) activity could contribute—in part—to the therapeutic effects. By comparing selective and pathway specific midbrain DA optogenetic stimulation with the global, non-pathway specific mfb-DBS, the study explored changes in gene-expression of key biomarkers associated with neurocircuitry of depression. Rats received either optogenetic DAergic or mfb-DBS, delivered as acute/single or chronic/repeated stimulation. Micro-dissected regions were prepared for in situ hybridization targeting biomarkers of GABAergic, glutamatergic, and dopaminergic systems. Mfb-DBS mediated DA independent pathway increased GABAergic biomarkers (GABAA, GAD1) in frontal and accumbal regions, not in midbrain. The combinations of low frequency/high pulse width and high frequency/low pulse width stimulation generally increased biomarker expression similarly, but chronic/repetitive stimulation had no accumulative effect. Interestingly, unilateral stimulation had bilateral effects, but stimulation modalities had little impact on DAT and Vglut2 expression. In conclusion, both low and high frequency, acute/single and chronic/repetitive mfb-DBS—but not selective optogenetic stimulation -activated gene expression of biomarkers associated with GABAergic transmission. The increased expression was transitory and less chronic than predicted. Importantly, the study provides evidence that the anti-depressant therapeutic effects of clinical medial forebrain bundle DBS occurs—in part—be via modulation of GABAergic signalling which in turn could regulate the release of dopamine in frontal and accumbal regions. In addition, clinical implication of the data is that unilateral stimulation had bilateral consequences on the gene expression, although the physiological and functional sequelae of this are yet unknown.
Accelerated linear algebra for large scale DFT calculations of materials on CPU/GPU architectures with CRYSTAL
We discuss the implementation strategy, numerical accuracy, and computational performance of the acceleration of linear algebra operations through graphics processing units (GPUs) for the self-consistent field driver of the Crystal electronic structure package for solid state density functional theory simulations. Accelerated tasks include matrix multiplication, diagonalization, and inversion, as well as Cholesky decomposition. The scaling of the implemented strategy over multiple accelerating devices is assessed in the range of 1–8 GPUs per node and found to be remarkably regular. Tests are performed on three systems: α-quartz, a microporous zeolitic imidazolate framework (ZIF-8), and a giant mesoporous metal–organic framework (bio-MOF). Scaling with system size is investigated via supercells of increasing size of both α-quartz and ZIF-8 (up to 648 and 2208 atoms per cell, respectively). The bio-MOF model structure has 2808 atoms per cell, with 33 672 basis functions. We test the performance of the accelerated code with both generalized gradient approximation (GGA) and hybrid GGA exchange–correlation functionals. The efficiency of the new accelerated code is compared to the previous central processing unit (CPU)-only parallelization strategies based on MPI or MPI/OpenMP within either replicated or distributed memory (i.e., massively parallel) approaches. Such a comparison highlights how the new GPU-accelerated code enables calculations on large systems at a significantly reduced computational cost relative to CPU-only strategies. For instance, we find that for the bio-MOF system, the computing time of the linear algebra tasks from a single GPU is comparable to that from the reference approach in the range of 512–1024 CPU cores and 4–8 nodes.
Why are critical event checklists not always used in the perioperative setting?: A retrospective survey
Introduction During surgery and anesthesia, life-threatening critical events, including cardiac arrest, may occur. By facilitating recall of key management steps, suggesting diagnostic possibilities, and providing dose and drug information, cognitive aids may improve clinician performance during such events. In actual clinical practice, however, cognitive aids may be available but inconsistently used. One possibility explaining aid non-use during critical events is a lack of familiarity with how cognitive aids may be helpful. We hypothesized that introduction of critical event cognitive aids along with implementation of cognitive aid resources would change the quantitative incidence of cognitive aid use and qualitative reasons for aid non-use. We surveyed members of an academic anesthesia department before and after implementation of critical event cognitive aid resources. Methods All anesthesia clinicians at a single academic medical center were surveyed. Participants were surveyed both pre- and post-training with a focused program to introduce critical event cognitive aid resources. Incidences of and reasons for cognitive aid use and non-use were collected and analyzed. Survey responses were compared pre- and post-implementation. Results The response rate was 64.5%. One-hundred eighty-five reasons for non-use were collected before the focused program and 149 after. Overall, 80% of clinicians had encountered at least one critical event during the study period and use of cognitive aids during all reported events was 7%. Six categories of reasons for non-use were identified: ‘Not Available’, ‘Not Needed’, ‘No Time’, ‘Another Person In Charge’, ‘Used In Another Way’, ‘No Reason Given’. After implementation, a decrease in the number of respondents who cited availability and who cited ‘another person running crisis,’ as reasons for non-use was observed (p < 0.001). Conclusions Implementation of cognitive aids for critical events in an academic anesthesia environment improved the perception of cognitive aid availability and decreased the number of subjects who chose to not use the aid due to another person running the crisis response. Looking at the multiple reasons for cognitive aid non-use may guide implementation, training, and design.
Carbonate mineral precipitation induced by microorganisms enriched from the cave water and biofilm in a lime-decorated lava tube
Research on PVDF/BNNSs/MXene multilayer films with high energy density and thermal conductivity for dielectric capacitors
Polyvinylidene fluoride (PVDF) has promising applications in the field of dielectric capacitors. However, its low dielectric constant and thermal conductivity limit energy storage density. To address this, three multilayer composite topologies were designed with PVDF/boron nitride nanosheets as insulation and PVDF/MXene as polarization layers. A performance evaluation framework based on the analytic hierarchy process technique for order preference by similarity to the ideal solution method identified the insulation–polarization–polarization–insulation topology as the optimal configuration. This structure enhanced the dielectric performance (εr/tan δ) by 239.44% over pure PVDF at 103 Hz, increased thermal conductivity by 60.45%, and improved breakdown field strength. In addition, charge–discharge efficiency at 300 MV/m reached 75%, with a discharge density of 6.3 J/cm3, which is 152% higher than PVDF. The multilayer design effectively integrates the strengths of each layer to significantly enhance the overall performance, demonstrating that operational research methods are practical for evaluating dielectric materials and guiding design.
Restoration of angiogenic capacity in senescent endothelial cells by a pharmacological reprogramming approach
Senescent endothelial cells (EC) are key players in the pathophysiology of cardiovascular diseases and are characterized by a reduced angiogenic and regenerative potential. Therefore, targeting these cells has been suggested as an effective therapeutic strategy to reduce vascular disease burden and potentially improve health and lifespan of humans. Here, we aimed to establish a pharmacological, partial reprogramming strategy to improve replicative senescent endothelial cell function in the context of angiogenesis. We demonstrate that our treatment improves tube formation and sprouting capacity but also increases proliferation and migration capacity in vitro. Further, inflammation and DNA damage were reduced in the replicative senescent cells. These processes were initiated by a short and timely-restricted overexpression of the Yamanaka-factors induced by our pharmacological strategy. The advantage of these compounds is that they are FDA approved in their respective concentrations which could pave the way for use in a clinical setting.
Ultrasound-assisted green synthesized ZnO nanoparticles with different solution pH for water treatment
Prediction of hydration energies of adsorbates at Pt(111) and liquid water interfaces using machine learning
Aqueous phase heterogeneous catalysis is important to various industrial processes, including biomass conversion, Fischer–Tropsch synthesis, and electrocatalysis. Accurate calculation of solvation thermodynamic properties is essential for modeling the performance of catalysts for these processes. Explicit solvation methods employing multiscale modeling, e.g., involving density functional theory and molecular dynamics have emerged for this purpose. Although accurate, these methods are computationally intensive. This study introduces machine learning (ML) models to predict solvation thermodynamics for adsorbates on a Pt(111) surface, aiming to enhance computational efficiency without compromising accuracy. In particular, ML models are developed using a combination of molecular descriptors and fingerprints and trained on previously published water–adsorbate interaction energies, energies of solvation, and free energies of solvation of adsorbates bound to Pt(111). These models achieve root mean square error values of 0.09 eV for interaction energies, 0.04 eV for energies of solvation, and 0.06 eV for free energies of solvation, demonstrating accuracy within the standard error of multiscale modeling. Feature importance analysis reveals that hydrogen bonding, van der Waals interactions, and solvent density, together with the properties of the adsorbate, are critical factors influencing solvation thermodynamics. These findings suggest that ML models can provide rapid and reliable predictions of solvation properties. This approach not only reduces computational costs but also offers insights into the solvation characteristics of adsorbates at Pt(111)–water interfaces.
Contribution of health system governance in delivering primary health care services for universal health coverage: A scoping review
Background The implementation of the primary health care (PHC) approach requires essential health system inputs, including structures, policies, programs, organization, and governance. Effective health system governance (HSG) is crucial in PHC systems and services, as it can significantly influence health service delivery. Therefore, understanding HSG in the context of PHC is vital for designing and implementing health programs that contribute to universal health coverage (UHC). This scoping review explores how health system governance contributes to delivering PHC services aimed at achieving UHC. Methods We conducted a scoping review of published evidence on HSG in the delivery of PHC services toward UHC. Our search strategy focused on three key concepts: health system governance, PHC, and UHC. We followed Arksey and O’Malley’s scoping review framework and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist to guide our methodology. We used the World Health Organization’s framework on HSG to organize the data and present the findings. Results Seventy-four studies were included in the final review. Various functions of HSG influenced PHC systems and services, including:1) formulating health policies and strategic plans (e.g., addressing epidemiological and demographic shifts and strategic financial planning), 2) implementing policy levers and tools (such as decentralization, regulation, workforce capacity, and supply chain management), 3) generating intelligence and evidence (including priority setting, monitoring, benchmarking, and evidence-informed decision-making), 4) ensuring accountability (through commitments to transparency), and 5) fostering coordination and collaboration (via subnational coordination, civil society engagement, and multisectoral partnerships). The complex interplay of these HSG interventions operates through intricate mechanisms, and has synergistic effects on PHC service delivery. Conclusion PHC service delivery is closely linked to HSG functions, which include formulating strategic policies and plans responsive to evolving epidemiological and demographic needs, utilizing digital tools, decentralizing resources, and fostering multisectoral actions. Effective policy implementation requires robust regulation, evidence-based decision-making, and continuous monitoring. Accountability within health systems, alongside community engagement and civil society collaboration, is vital for realizing PHC principles. Local health institutions should collaborate with communities—end users of these systems—to implement formal rules and ensure PHC service delivery progresses toward UHC. Sociocultural contexts and community values should inform decision-making aligning health needs and services to achieve universal access to PHC services.
Retrospective analysis of clinical outcomes and early complications of conventional circumcision techniques and thermocautery-assisted circumcision
Application of the noncollinear Scalmani–Frisch formalism to current density functional theory
We generalize the noncollinear formalism proposed by Scalmani and Frisch [J. Chem. Theory Comput. 8, 2193 (2012)] to include the particle and spin current densities for meta-generalized gradient approximations and local hybrid functionals. This allows us to fully include the impact of spin–orbit coupling in relativistic calculations and for applications to finite magnetic fields. For the latter, we use London atomic orbitals to ensure gauge origin invariance. It is shown that this formalism is superior to the more common canonical noncollinear approach in relativistic calculations, as it naturally includes all three spin current densities in the closed-shell limit and avoids the projection onto the spin magnetization vector. This is important to easily restore rotational invariance in this limit. In addition, the Scalmani–Frisch approach can be made numerically stable and may lead to a nonvanishing local magnetic torque. However, both formalisms are rotationally invariant for open-shell systems and in finite magnetic fields.
Development and application of a binary medium bond contact model for calcareous sands
In the construction process of islands and reefs in the South China Sea, calcareous sand, as an important foundation and building material, has been widely used in engineering practice. It is crucial to explore the mechanical properties of calcareous sands to ensure the stability and maintenance of these islands and reefs. To study the effects of the bonding progressive failure on its macroscopic mechanical properties, a binary media bonding contact model is developed. This model can describe the gradual deterioration process of the intergranular cementation. Additionally, a discrete elemental contact subroutine (DLL) is created by C++ language program for the particle flow program (PFC2D) to utilize. The compression and direct shear testing of single contact was subjected. The computational accuracy of the proposed binary media contact model was confirmed by the comparison of the theoretical and numerical results. The biaxial shear discrete element simulations were conducted to study the behaviors of calcareous sand under different confining pressure conditions. The stress-strain curves obtained are in good agreement with the experimental results. The results show that the proposed binary media bonding contact model can accurately reflects the mechanical properties of calcareous sand. Based on calibrated discrete element contact mesoscopic parameters, the biaxial shear discrete element numerical simulations with different damage parameters were carried out. The effects of damage parameters on the stress-strain curves and shear strength are discussed. The evolution of effective coordination number, fabric anisotropy and force chain number are also analyzed. The research results can provide a basis for the study of macro-micromechanical properties of calcareous sand
Early warning system of the seasonal west nile virus infection risk in humans in northern greece, 2020–2024
Metastable states assisted homogeneous nucleation in supercooled liquid aluminum alloys: Insights from a phenomenologically coupled atomistic, phase-field, and machine learning investigation
Crystallization due to liquid → solid transformation is observed in many natural and engineering processes. Extant literature indicates that crystallization in supercooled liquids is initiated by precursory metastable phases or states, also called non-classical nucleation. For face-centered cubic (FCC) materials, latest experimental and computational studies suggest that metastable hexagonal-closed packed (HCP) structures facilitate equilibrium FCC formation. However, the underlying nucleation mechanism remains unclear. Here, we examine structural changes and energetic barriers associated with such a non-classical mechanism, by performing molecular dynamics (MD) simulations using pure Al, Al-0.5 at. %Cu, and Al-0.5 at. %Ni (all FCC-formers) and phenomenologically coupling MD results with phase-field (PF) modeling. Such a coupling involved initializing PF simulation domains and constructing Landau polynomials—consistent with MD observations. Unsupervised machine learning was utilized to capture nuclei structures from MD simulations, while neural networks helped in extracting equilibrium interfacial energies from PF modeling. Atomistic simulations showed that precursory nuclei are comprised of collection of metastable-HCP states with medium ranged ordering. The pockets of HCP states later transform to critical nuclei—containing an FCC core and an outer layer of HCP. PF modeling qualitatively replicated the precursory-to-critical nuclei transformation and showed that the energetic barriers between the precursory and critical nuclei are substantially smaller than predictions obtained from classical nucleation theory. Together, these observations permitted us to propose a holistic non-classical mechanism that links triangular motifs within Al-based supercooled liquids to the critical nuclei via in-liquid structural transformations.
How can a top-down government program can be sustainable: A case study of horticulture village program in South Sulawesi Province
The horticulture village program is one of the activities in increasing sustainable vegetable production. The activity was carried out in 2021 and one of the provinces that carried it out was the province of South Sulawesi. The purpose of the paper is to evaluate the sustainability of the horticulture village program from four dimensions, namely input, process, product, context/outcome, using the Rapfish analysis tool, and strengthened by partial budget analysis to see the magnitude of changes in revenue. From the results of the Rapfish analysis, it could be seen that horticultural village activities are less sustainable, with the lowest value in the product dimension. The main reason for this is that the planning and implementation of the program lacked a well-thought-out social process. It requires the need for improvement in terms of quantity and quality of seeds, which considers the suitability and habits of farmers. Assistance from extension workers related to the use of appropriate and periodic technology for plant conditions (product) which will have an impact on productivity and income (context) needs to be considered. The increase in income for chili and shallots due to following the recommendations of cultivation technology, including reducing the use of chemical fertilizers, increasing the use of organic fertilizers, reducing the use of chemical pesticides and using plastic mulch, can be an entry point to convince farmers of the sustainability of this program with further improvements.
Enhanced object detection in remote sensing images by applying metaheuristic and hybrid metaheuristic optimizers to YOLOv7 and YOLOv8
Abstract Developments in object detection algorithms are critical for urban planning, environmental monitoring, surveillance, and many other applications. The primary objective of the article was to improve detection precision and model efficiency. The paper compared the performance of six different metaheuristic optimization algorithms including Gray Wolf Optimizer (GWO), Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Remora Optimization Algorithm (ROA), Aquila Optimizer (AO), and Hybrid PSO–GWO (HPSGWO) combined with YOLOv7 and YOLOv8. The study included two distinct remote sensing datasets, RSOD and VHR-10. Many performance measures as precision, recall, and mean average precision (mAP) were used during the training, validation, and testing processes, as well as the fit score. The results show significant improvements in both YOLO variants following optimization using these strategies. The GWO-optimized YOLOv7 with 0.96 mAP 50, and 0.69 mAP 50:95, and the HPSGWO-optimized YOLOv8 with 0.97 mAP 50, and 0.72 mAP 50:95 had the best performance in the RSOD dataset. Similarly, the GWO-optimized versions of YOLOv7 and YOLOv8 had the best performance on the VHR-10 dataset with 0.87 mAP 50, and 0.58 mAP 50:95 for YOLOv7 and with 0.99 mAP 50, and 0.69 mAP 50:95 for YOLOv8, indicating greater performance. The findings supported the usefulness of metaheuristic optimization in increasing the precision and recall rates of YOLO algorithms and demonstrated major significance in improving object recognition tasks in remote sensing imaging, opening up a viable route for applications in a variety of disciplines.
Perturbative spin–orbit couplings for the simulation of extended framework materials
A comprehensive description of photo-chemical processes in materials, comprising spin-forbidden processes such as intersystem crossing and phosphorescence, implies taking into account spin–orbit coupling. We present an efficient implementation of a perturbative spin–orbit coupling correction for the Tamm–Dancoff approximation of linear-response time-dependent density functional theory within a mixed Gaussian and plane wave framework relying on spin–orbit coupling corrected pseudopotentials. The implementation is validated for a benchmark set of small aromatic molecules, with mean errors in excitation energies and spin–orbit coupling matrix elements being in the range of 0.1–0.6 eV and 1.0–14.4 cm−1, respectively, in comparison with density functional theory and density functional theory multi-reference configuration interaction reference results. Computational timings are given for a bismuth-containing metal–organic framework.