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Factors associated with decision-making autonomy in healthcare utilization among married women from the Indonesia demographic health survey 2017

Abstract Women’s autonomy in healthcare decision-making is crucial not only for improving maternal health but also enhancing their overall health and well-being. However, most studies focused solely on fertility, child health, or maternal healthcare use, often overlooking the broader aspects of women’s health. Due to this reason, the magnitudes and factors associated with women’s autonomy in other types of healthcare remain unclear. Therefore, this study aimed to estimate the magnitude and identify factors associated with healthcare decision-making autonomy among married women in Indonesia. A national cross-sectional study was conducted among married women using the Indonesia Demographic and Health Surveys 2017. Women’s healthcare decision-making autonomy was measured based on responses regarding the individual typically responsible for making healthcare decisions on behalf of the respondent. Potential factors, such as intrapersonal, interpersonal, community, and policy-related were obtained. Multinomial logistic regression was used to determine the associations between potential factors and outcomes. The odds ratio (OR) and 95% confidence intervals (CI) of the analysis were reported. The respondents in this study comprised 16,050 married women across 34 provinces in Indonesia. Most respondents (46.4%) reported making healthcare decisions independently. The result showed that several factors were associated with either women’s full autonomy or jointly with the husbands in the healthcare decision-making. These factors included ownership of mobile telephones, urban living, residency in Java, Bali, Sulawesi, Maluku and Papua islands, participation of women in decision-making on how to spend their earnings, on large household purchases, no financial barrier in accessing treatment, and independence in visiting a medical center. Public health interventions should focus on vulnerable women, such as those who live in rural areas, participate less in the decision-making of earnings spending and household purchase, and are incapable of visiting a medical center alone to increase the healthcare decision-making autonomy. Collaborative efforts with health facilities in each region can support the implementation of this intervention.

SHARC-VQE: Simplified Hamiltonian approach with refinement and correction enabled variational quantum eigensolver for molecular simulation

Quantum computing is finding increasingly more applications in quantum chemistry, particularly to simulate electronic structure and molecular properties of simple systems. The transformation of a molecular Hamiltonian from the fermionic space to the qubit space results in a series of Pauli strings. Calculating the energy then involves evaluating the expectation values of each of these strings, which presents a significant bottleneck for applying variational quantum eigensolvers (VQEs) in quantum chemistry. Unlike fermionic Hamiltonians, the terms in a qubit Hamiltonian are additive. This work leverages this property to introduce a novel method for extracting information from the partial qubit Hamiltonian, thereby enhancing the efficiency of VQEs. This work introduces the SHARC-VQE (Simplified Hamiltonian Approximation, Refinement, and Correction-VQE) method, where the full molecular Hamiltonian is partitioned into two parts based on the ease of quantum execution. The easy-to-execute part constitutes the partial Hamiltonian, and the remaining part, while more complex to execute, is generally less significant. The latter is approximated by a refined operator and added up as a correction into the partial Hamiltonian. SHARC-VQE significantly reduces computational costs for molecular simulations. The cost of a single energy measurement can be reduced from O(N4ϵ2) to O(1ϵ2) for a system of N qubits and accuracy ϵ, while the overall cost of VQE can be reduced from O(N7ϵ2) to O(N3ϵ2). Furthermore, measurement outcomes using SHARC-VQE are less prone to errors induced by noise from quantum circuits, reducing the errors from 20%–40% to 5%–10% without any additional error correction or mitigation technique. In addition, the SHARC-VQE is demonstrated as an initialization technique, where the simplified partial Hamiltonian is used to identify an optimal starting point for a complex problem. Overall, this method improves the efficiency of VQEs and enhances the accuracy and reliability of quantum simulations by mitigating noise and overcoming computational challenges.

Synthetic healthcare data utility with biometric pattern recognition using adversarial networks

The synergy between compartmentalization and motorization in chromatin architecture

High-resolution techniques capable of manipulating from single molecules to millions of cells are combined with three-dimensional modeling followed by simulation to comprehend the specific aspects of chromosomes. From the theoretical perspective, the energy landscape theory from protein folding inspired the development of the minimal chromatin model (MiChroM). In this work, two biologically relevant MiChroM energy terms were minimized under different conditions, revealing a competition between loci compartmentalization and motor-driven activity mechanisms in chromatin folding. Enhancing the motor activity energy baseline increased the lengthwise compaction and reduced the polymer entanglement. Concomitantly, decreasing compartmentalization-related interactions reduced the overall polymer collapse, although compartmentalization given by the microphase separation remained almost intact. For multiple chromosome simulations, increased motorization intensified the territory formation of the different chains and reduced compartmentalization strength lowered the probability of contact formation of different loci between multiple chains, approximating to the experimental inter-contacts of the human chromosomes. These findings have direct implications for experimental data-driven chromosome modeling, specially those involving multiple chromosomes. The interplay between phase-separation and territory formation mechanisms should be properly implemented in order to recover the genome architecture and dynamics, features that might play critical roles in regulating nuclear functions.

Development and performance assessment of a novel scroll compressor-based oxygen generator integrated ventilator

Abstract Current ventilators rely on wall outlets or cylinders for oxygen supply, which limits their continuous use in the field or emergencies. In this study, we proposed a ventilator prototype that can achieve stand-alone oxygenated respiratory support, by designing and integrating a high-performance oxygen generator, and optimizing the control strategies of the whole system. Based on the designed oil-free scroll compressor and pressure swing adsorption (PSA) system, we first realized a mobile high-flow oxygen generator, which achieved an output flow greater than 17 L/min with an oxygen concentration of 93% ± 3%. The ventilator was also designed to synchronize with the respiratory state, to optimize the trigger performance for the pressure support of early inspiration, and reduce the gas supply in the late inspiratory phase to avoid pressure overshoot in the early expiratory phase. The respiratory synchronization of the integrated ventilator was estimated by the recorded chest movement of the subjects. Satisfactory respiratory synchronization was realized with an inspiratory trigger delay (ITD) time of less than 200 ms and sound respiratory waveform tracking. By regulating the PSA strategy, the oxygen generation and utilization efficiencies could be further improved. Ultimately, under the setting of inspiratory positive airway pressure (IPAP) at 10 cmH2O, and expiratory positive airway pressure (EPAP) at 4 cmH2O, we achieved non-invasive ventilation with a maximum oxygen concentration of 58% ± 1.75%. In conclusion, the proposed oxygen generator integrated ventilator could provide reliable oxygenated respiratory support in emergencies, such as on-site first aid, patient transport, and military field environments.

Hydrogen-bond induced non-linear size dependence of lysozyme under the influence of aqueous glyceline

Natural deep eutectic solvents (NADESs) are environmentally friendly green solvents and hold great promise in the pharmaceutical industry. The secondary structure of a protein, lysozyme, follows a non-monotonous behavior in aqueous glyceline (choline chloride + glycerol) as the wt. % of water is increased. However, it is unclear how the hydration affects the stability of the protein in a non-linear way. In this work, we have performed all-atom molecular dynamic simulations for 1 μs with the lysozyme protein in an aqueous glyceline deep eutectic solvent (DES) by varying the wt. % of water. The simulated radius of gyration, Rg, values can qualitatively reproduce the protein behavior such that the Rg increases initially with an increase in wt. % of water, reaches the peak at 40 wt. %, and then gradually decreases with dilution. Several other properties, including root mean square deviation, root-mean square fluctuation, secondary structure of the protein, and solvent accessible surface area, are examined to explore the NADES effect on the protein structure. Next, we analyze the hydrogen bond profile of intra-protein and among various interspecies, e.g., protein–DES, DES–DES, protein–water, and water–water. The variation in protein–protein hydrogen bonds with concentrations can qualitatively explain the non-linear conformational dependence of the protein. The radial distribution function analyses show various microscopic structures formed due to the DES and water interaction, which play a critical role in protein behavior. This study indicates that at lower wt. % of water, the protein is constrained in a strong hydrogen bond network formed by glycerol and water molecules, resulting in a lower Rg. As the wt. % of water increases, the protein–water interaction drives the protein to expand, reflecting an increasing Rg. At sufficiently higher wt. % of water, the DES constituent and the water molecules interact strongly with the protein, resulting in a decrease in Rg. Overall, the investigation offers a microscopic insight into the protein conformation in DES.

Comparison of anti-inflammatory and anti-angiogenic effects of JAK inhibitors in IL-6 and TNFα-stimulated fibroblast-like synoviocytes derived from patients with RA

Mid-infrared strong nonreciprocal thermal radiation with extremely small applied magnetic field

The ability to break the reciprocity between absorbance and emittance provides new ideas to develop advanced light harvesting devices and thermal management. However, the existing designs with magnetic optical (MO) materials typically require a magnetic excitation on the order of 1 T, which imposes a constraint on their practical application. Here, a photonic structure with a dielectric-MO material planar sandwiched between a dielectric resonator array and a metallic reflector is designed and studied. The results show that near-perfect nonreciprocity can be obtained with an extremely small magnetic excitation on the order of 0.2 T, which could be reached with permanent magnets. Moreover, the physical origin of such a phenomenon and the dependence of the thermal emission performances on the structural dimensions are also studied. The concepts and the results obtained here will pave the way for the development of nonreciprocal radiation devices with modest magnetic fields, which can be achieved in practice.

The influence of peripheral vision on driving performance in patients implanted with an inverted meniscus intraocular lens

Remote-sensing based control of 3D magnetic fields using machine learning for <i>in operando</i> applications

In operando techniques enable real-time measurement of intricate physical properties at the micro- and nano-scale under external stimuli, allowing the study of a wide range of materials and functionalities. In nanomagnetism, in operando techniques greatly benefit from precise three-dimensional (3D) magnetic field control, enabling access to complex magnetic states forming in systems where multiple energies are set to compete with each other. However, achieving such precision is challenging and uncommon, as specific applications impose constraints on the type and geometry of magnetic field sources, limiting their capabilities. Here, we introduce an approach that leverages machine learning algorithms to achieve precise 3D magnetic field control using a hexapole electromagnet that is composed of three independent, non-collinear dipole electromagnets. In our experimental setup, magnetic field sensors are placed at a distance from the sample position due to inherent constraints, leading to indirect field measurements that differ from the magnetic field experienced by the sample. We find that the existing relationship between the remote and sample frames of reference is non-linear, thus requiring a more complex calibration method. To address this, we employ a multi-layer perceptron neural network that processes multiple inputs from a dynamic magnetic field sequence, effectively capturing the time-dependent non-linear field response. The network achieves high calibration accuracy and demonstrates exceptional generalization to unseen magnetic field sequences. This study highlights the significant potential of machine learning in achieving high-precision control and calibration, crucial for in operando experiments where direct measurement at the point of interest is not possible.

Unraveling internal friction in a coarse-grained protein model

Understanding the dynamic behavior of complex biomolecules requires simplified models that not only make computations feasible but also reveal fundamental mechanisms. Coarse-graining (CG) achieves this by grouping atoms into beads, whose stochastic dynamics can be derived using the Mori–Zwanzig formalism, capturing both reversible and irreversible interactions. In liquid, the dissipative bead–bead interactions have so far been restricted to hydrodynamic couplings. However, friction does not only arise from the solvent but, notably, from the internal degrees of freedom missing in the CG beads. This leads to an additional “internal friction” whose relevance is studied in this contribution. By comparing with all-atom molecular dynamics (MD), we neatly show that in order to accurately reproduce the dynamics of a globular protein in water using a CG model, not only a precise determination of elastic couplings and the Stokesian self-friction of each bead is required. Critically, the inclusion of internal friction between beads is also necessary for a faithful representation of protein dynamics. We propose to optimize the parameters of the CG model through a self-averaging method that integrates the CG dynamics with an evolution equation for the CG parameters. This approach ensures that selected quantities, such as the radial distribution function and the time correlation of bead velocities, match the corresponding MD values.

A randomized controlled trial of the effectiveness of the mHealth program in improving the lifestyle of nursing students

Abstract Promoting healthy lifestyles is essential for preventing chronic diseases, yet a vast majority of university students regularly engage in unhealthy habits. Utilizing mobile smart devices for health interventions, known as mHealth, which integrate behavioral change theories with environmental interaction, offers a promising and cost-effective strategy to encourage lasting adoption of healthier habits. This study compared the effectiveness of the mHealth intervention program with a traditional face-to-face program in fostering healthy lifestyle changes. Through a randomized controlled trial involving 220 nursing students (110 in the mHealth intervention program and 110 in the traditional program), data were collected from May to December 2023 using predefined questionnaires. These questionnaires included the Global/International Physical Activity Questionnaire (GPAQ/IPAQ) for monitoring adult physical activity, a Food Frequency Questionnaire (FFQ) for dietary assessment, and a Sleep Quality Scale (SQS). Three months after the educational intervention program, lifestyle improvements were significantly more pronounced in the mHealth intervention group compared to the traditional group. The implementation of the mHealth intervention program aimed at improving lifestyle has proven to be a transformative approach in fostering positive behavioral changes among participants. The study was approved by the IRB of Zagazig Faculty of Medicine (IRB 10827/24-6-2023) and was registered at the ClinicalTrials.gov (NCT06404619, 08/05/2024).

Improving the wet-etching accuracy of Bi2Sr2CaCu2O8+<i>δ</i> crystal chips for high-temperature superconducting terahertz emitters using potassium hydroxide solution

The development of a technology for the microfabrication of Bi2Sr2CaCu2O8+δ (Bi2212) crystals is essential for realizing high-performance terahertz emitting devices based on Bi2212 single crystals. We developed an anisotropic wet-etching method using potassium hydroxide solution to improve the etching accuracy of Bi2212 crystal chips. Etching solutions with potassium hydroxide concentration of 10–13 wt. % and temperatures of approximately 40–45 °C are suitable for sample etching. The developed etching method enabled us to obtain crystal chips with sidewall angles of approximately 90°. In the case of a crystal chip with a thickness of ∼6 μm, the undercuts from the edges of the photomask were ∼1.5 μm, which were significantly shorter than those obtained in previous studies using acidic solutions (∼5–10 μm). The etching rate of the developed solution (0.1 μm/min) was lower than that of the acidic solutions (∼20 μm/min), which provided suitable etching conditions for the samples. Devices using Bi2212 crystal chips, fabricated using the developed technique, exhibited clear terahertz emissions, similar to those reported in previous studies. The enhanced accuracy of the proposed etching process is expected to improve the device characteristics of Bi2212 terahertz emitters, particularly in terms of the emission power and frequency.

The many faces of vibrational energy relaxation in N2(<i>v</i>) + O(1D) collisions: Dynamics on 1Π and 1Δ potential energy surfaces

Complete datasets of rate coefficients for the vibrational quenching of molecular nitrogen by collision with electronically excited atomic oxygen O(1D) over a wide temperature range are calculated for the first time. Such data are important ingredients in the modeling of non-local thermal equilibrium conditions that characterize the atmosphere, media of astronomical interest, and cold and hot plasmas, where O(1D), also formed when O2 molecules break, represents a significant fraction of the gas mixture. To this end, we developed analytical potential energy surfaces (PESs) for the 1Π and 1Δ electronic states of the N2–O(1D) system to accurately describe the interaction in the long, medium, and first repulsive range of intermolecular distances, the most effective regions in inelastic collisions under a variety of conditions of interest. The derived PESs are used to calculate the vibration-to-translation (V–T) and vibration-to-electronic (V–E) energy transfer rates by mixed quantum–classical dynamics and by the Landau–Zener formulation, respectively. In addition, the datasets are extended to cover the entire N2 vibrational ladder by using the Gaussian process regression. The results show that at low temperatures, where V–E relaxation dominates, N2 vibrational quenching by O(1D) collisions is faster than by O(3P) collisions.

Spatial pattern characteristics and influencing factors of state-level sports industry bases in China

Electroelastic guided wave dispersion in piezoelectric plates: Spectral methods and laser-ultrasound experiments

Electroelastic waves in piezoelectric media are widely used in sensing and filtering applications. Despite extensive research, computing the guided wave dispersion remains challenging. This paper presents semi-analytical approaches based on spectral methods to efficiently and reliably compute dispersion curves. We systematically assess the impact of electrical boundary conditions on a 128° Y-cut LiNbO3 wafer, examining open–open, open–shorted, and shorted–shorted surface configurations. Multi-modal dispersion maps obtained from laser-ultrasonic experiments for each boundary condition exhibit excellent agreement with the computational predictions. A straightforward implementation of the spectral collocation method is made available as GEW piezo plate (https://doi.org/10.5281/zenodo.14205789), while the spectral element method is integrated to GEWtool (http://doi.org/10.5281/zenodo.10114243) for multilayered plates. Therewith, we aim to make advanced semi-analytical techniques more accessible to physicists and engineers relying on dispersion analysis.

Pareto-based optimization of sparse dynamical systems

Sparse data-driven approaches enable the approximation of governing laws of physical processes with parsimonious equations. While significant effort has been made in this field over the last decade, data-driven approaches generally rely on the paradigm of imposing a fixed base of library functions. In order to promote sparsity, finding the optimal set of basis functions is a necessary condition but a challenging task to guess in advance. Here, we propose an alternative approach that consists of optimizing the very library of functions while imposing sparsity. The robustness of our results is not only evaluated by the quality of the fit of the discovered model but also by the statistical distribution of the residuals with respect to the original noise in the data. In order to avoid choosing one metric over the other, we would rather rely on a multi-objective genetic algorithm (NSGA-II) for systematically generating a subset of optimal models sorted in a Pareto front. We illustrate how this method can be used as a tool to derive microkinetic equations from experimental data.

Hyperactive ADHD symptoms are associated with increased variability in thought content in less constrained contexts

Temperature-based reactive flow model for triaminotrinitrobenzene (TATB) plastic bonded explosives

A new reactive flow model is presented for triaminotrinitrobenzene (TATB)-based plastic bonded explosives, applicable to shock initiation and steady detonation problems of differing initial temperature. Temperature disequilibrium is assumed between unreacted explosive, material in the vicinity of compressed defects (called hot spots), and reaction products. The model incorporates temperature-dependent decomposition reaction rates. Particularly, Arrhenius model parameters were derived from quantum-based molecular dynamics simulations of TATB decomposition. Further, a model of detonation carbon aggregation is incorporated, describing the slow release of energy inherent to detonation in TATB-based materials. Model parameters were calibrated against gas gun shock initiation experiments and steady detonation rate stick tests. The predictive ability of the model in the shock initiation regime is tested against recent thin pulse experiments. The model is found to perform equally well in predicting the size-effect curve of ambient, cold, and hot rate sticks. The present work demonstrates the viability of incorporating results from subscale simulations into a continuum-scale reactive flow model.

The puzzling structure and bonding of the methanol radical cation

Electron spin resonance indicates that the unpaired electron in the methanol radical cation is delocalized, however, the molecular geometry has not been experimentally resolved. In this work, high level, state-of-the-art computations at the finite temperature density functional theory and highly correlated CCSD(T) levels indicate that a syn-periplanar conformation of the H–C–O–H bonds, in which the C–H and O–H bonds eclipse each other, is a three-fold global minimum in the potential energy surface for internal rotation of the O–H bond. We show that vicinal hyperconjugation between the orbitals in the C–H bonds and in the oxygen atom is responsible for this puzzling conformational preference. The transition state for the rotation yields an ≈0.6 kcal/mol rotational barrier, which matches the thermal energy at room conditions and, therefore, renders the O–H bond a free rotor. The molecular wave function has a moderate multireference character with the oxygen atom acting as the preferred spot for static correlation.