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Community health volunteers’ experiences during the COVID-19 pandemic in Kiambu county, Kenya: A qualitative study

Background For already overburdened health systems in low- and middle-income countries (LMICs), the COVID-19 pandemic presented an almost impossible challenge. In Kenya, efforts to mitigate the impact of the pandemic included the mobilization of community health volunteers (CHVs), a cadre that has been historically understaffed and under-resourced. These volunteers were required to sustain the delivery of routine community-based health services while also taking on additional responsibilities related to COVID-19 mitigation. This study explored the challenges faced by CHVs during the COVID-19 response in Kiambu County; focusing on their experiences with control measures, impacts on community-level healthcare delivery, and perspectives on the government’s pandemic response within the community health framework. Methods This study employed a phenomenological exploratory qualitative design. Due to logistical constraints, only two focus group discussions could be conducted with 24 CHVs, representing 48% of eligible participants who met the inclusion criteria: a minimum of five years of experience, active involvement in the pandemic response, and availability for the interview. Data were digitally recorded, transcribed, translated, and coded for thematic analysis. Results Specific themes from the experiences of the CHVs during the COVID-19 lockdown were: (1) dedication and commitment to serving the community; (2) overcoming demoralization; and (3) community barriers to health care delivery and access. In regards to the community perspectives of COVID-19, the CHVs relayed widespread misinformation among community members, with experiences of stigma due to COVID-19 misconceptions. They also gave second-person accounts of the economic strife the community went through as a result of mitigation measures. The CHVs were skeptical in the county’s preparedness in dealing with both the COVID-19 and future pandemics. Conclusion Despite facing stigma, misinformation, limited resources, and economic hardships, CHVs demonstrated commitment to their roles. Their efforts not only underscored their resilience but also revealed critical gaps in preparedness and resource allocation within the healthcare system. However, the small number of FGDs and insufficent data saturation should be considered when interpreting the findings. Nonetheless, our study provides a starting point for further research and comparative analysis across other counties in Kenya.

Quadrupolar NMR relaxation as a local probe of collective dynamics in aqueous alkaline and alkaline-earth chloride solutions

While nuclear magnetic resonance (NMR) provides valuable insights into the local environment of many nuclei, the unambiguous interpretation of the signal in terms of microscopic dynamics is often difficult, particularly when the quadrupolar relaxation mechanism comes into play. Here, we investigate the quadrupolar NMR relaxation of cations and anions in aqueous alkaline and alkaline-earth chloride solutions across a broad range of salt concentrations. Using a combination of density functional theory calculations and classical molecular dynamics simulations, we compute the electric field gradient (EFG) fluctuations over the relevant time scales. Predicted NMR relaxation rates are in good agreement with experiments from the literature. As previously reported for NaCl, we find that the increase in relaxation rate with salt concentration is primarily driven by the slowing of EFG fluctuations, while changes in the static variance of the EFG play a minor role. We highlight some specific features for smaller and divalent cations compared to the other monovalent ones. In addition, we assess the relevance of the Stokes–Einstein–Debye model, frequently used to analyze NMR relaxation experiments, for these aqueous electrolytes and highlight the link between the collective dynamics of the liquid underlying the EFG fluctuations at the ion positions and the stress fluctuations. Our results generalize observations for Na+ in aqueous NaCl solutions, showing that models assuming a viscous model of the solvent dynamics are insufficient to describe EFG fluctuations in these systems and illustrate the relevance of molecular simulations to interpret NMR relaxation experiments in terms of microscopic dynamics.

A Foundational Shift in Models for Enzyme Function

Resilience to abrupt global catastrophic risks disrupting trade: Combining urban and near-urban agriculture in a quantified case study of a globally median-sized city

Background Abrupt global catastrophic risks (GCRs) are not improbable and could massively disrupt global trade leading to shortages of critical commodities, such as liquid fuels, upon which industrial food production, processing and distribution depends. Previous studies have suggested urban agriculture as a resilience measure in the context of climate change and other natural hazards. Aims To estimate the contribution a radical pivot to urban agriculture could have in building resilience to GCRs and the near-urban industrial agriculture needed to supplement urban food production. Methods We determined optimum crops through mathematical optimization for food calorie and protein supply per land area for both urban and near-urban (industrial) agriculture. We calculated the land area available for food production within a temperate globally median-sized city using Google Earth image analysis of residential lots and open city spaces. We calculated the population that could be fed through urban agriculture alone, and the extra near-urban land required for cropping with industrial agriculture to feed the remaining city population, under both normal climate, and potential nuclear winter conditions. Results The optimal crops for urban agriculture were peas (normal climate), and sugar beet/spinach (nuclear winter); while those optimal for industrial near-urban production were potatoes (normal climate), and wheat/carrots (nuclear winter). Urban agriculture could feed a fifth (20%) of the population. At least 1140 hectares of near-urban cultivation could make up the shortfall. Another 110 hectares of biofuel feedstock like canola (rapeseed) could provide biodiesel to run agricultural machinery without fuel trade. Significantly more cultivated area is needed in nuclear winter scenarios due to reduced yields. Conclusion Relatively little optimized near-urban industrial agriculture, along with intensified urban agriculture could feed a median-sized city in a GCR, while minimizing fuel requirements. Governments and municipal authorities could consider land use policy that encourages development of urban agriculture and near-urban cultivation of optimal crops, along with processing and local biofuel refining capacity.

Schrödinger cat ground state representing two enantiomers of H3O2−

The vibronic ground state of HO–H–OH− represents axial Ra and Sa enantiomers, with equal probabilities. It can be prepared thermodynamically at low temperatures (4K). If the chirality is measured to be Ra, then wavefunction collapse induces periodic quantum stereo-mutation from Ra to Sa to Ra to Sa and so on. Similarly, the observation of Sa induces chirality flips from Sa to Ra to Sa to Ra and so on. The period of stereo-mutation is τ = 2.554 ps. The phenomenon is supported by the low energy barrier 174.6 hc cm−1 between the enantiomers and by the light masses of the hydrogen atoms, which interchange positions during stereo-mutation. Interchanges of heavier atoms and higher energy barriers would prohibit Schrödinger cat ground states. This is demonstrated for the counter example, isotopically substituted 12CDH13CH2–Si–12C13C. The results are obtained by means of quantum chemical calculations and quantum dynamics simulations.

Unveiling the Biosynthetic Logic of Nosiheptide Based on Reconstitution of Its Bicyclic Thiopeptide Scaffold

Retraction: Corporate social responsibility: A key driver of sustainable development in China’s post-COVID economy

Considerations in the use of machine learning force fields for free energy calculations

Machine learning force fields (MLFFs) promise to accurately describe the potential energy surface of molecules at the ab initio level of theory with improved computational efficiency. Within MLFFs, equivariant graph neural networks (EQNNs) have shown great promise in accuracy and performance and are the focus of this work. The capability of EQNNs to recover free energy surfaces (FES) remains to be thoroughly investigated. In this work, we investigate the impact of collective variables (CVs) distribution within the training data on the accuracy of EQNNs predicting the FES of butane and alanine dipeptide. A generalizable workflow is presented in which training configurations are generated with classical molecular dynamics simulations, and energies and forces are obtained with ab initio calculations. We evaluate how bond and angle constraints in the training data influence the accuracy of EQNN force fields in reproducing the FES of the molecules at both classical and ab initio levels of theory. Results indicate that the model’s accuracy is unaffected by the distribution of sampled CVs during training, given that the training data includes configurations from characteristic regions of the system’s FES. However, when the training data is obtained from classical simulations, the EQNN struggles to extrapolate the free energy for configurations with high free energy. In contrast, models trained with the same configurations on ab initio data show improved extrapolation accuracy. The findings underscore the difficulties in creating a comprehensive training dataset for EQNNs to predict FESs and highlight the importance of prior knowledge of the system’s FES.

Oxidative Strong Metal–Support Interaction Stabilized Single-Atom Catalysts for Heterogeneous Hydroformylation

Comparing the diagnostic accuracy of the newly introduced and existing malaria tests in Northwest Ethiopia

Background Malaria is an important public health issue in Ethiopia. Accurate malaria diagnosis plays a vital role in effective treatment. However, there is limited data on the diagnostic accuracy of the newly introduced rapid diagnostic test (LDH-based RDT) and existing diagnostic methods. Objective This study aimed to compare the diagnostic accuracy of the LDH-based RDT and existing diagnostic methods among uncomplicated malaria patients, 2024. Methods The health-facility-based cross-sectional study was conducted in Dembia and North Achefer districts of the Amhara region. A systematic sampling technique was employed to recruit 460 febrile patients. Each patient’s blood sample was investigated for Plasmodium species by RDT, followed by microscopy by different laboratory professionals. The collected blood film slide was sent to the reference laboratory center, Ethiopian Public Health Institute, for confirmatory analysis. The diagnostic accuracy was assessed, and a kappa value > 0.6 was considered as having good agreement between diagnostic techniques. Results The sensitivity and specificity of pLDH-based RDT were 99.6 and 100% compared to reference laboratory results. There was a very good consensus between pLDH-based RDT and blood film (Kappa: 0.97, p-value = 0.0001). There was also a good consensus between blood film at the local laboratory and pLDH-based RDT (Kappa: 0.748, p-value = 0.0001). However, there was the worst disagreement between clinical diagnosis, pLDH-based RDT, and blood film (Kappa range: -0.987 to -0.739). Conclusion This study revealed that pLDH-based RDT and microscopy had higher accuracy as per the WHO recommendation standard. This study implied that clinical diagnosis of malaria must be supported either by RDT or microscopy.

On the origin of the breakloose friction force

We discuss the origin of the static or breakloose friction force and describe a kinetic effect that can manifest itself as an (effective) breakloose friction force. The kinetic effect is important if the kinetic friction force Fk(v) has a maximum at low sliding speed, say for v = vc. If the driving speed v is higher than vc, the friction force at the onset of slip will first increase rapidly to approximately Fk(vc) and then rapidly decrease to Fk(v), resulting in an effective breakloose friction force larger than the kinetic friction force. We present experimental results for sliding friction of a racer rubber tread compound and a passenger car tread compound, which exhibit very different breakloose friction as a result of this kinetic effect. We show that pre-slip in the contact makes the breakloose friction be less than the product of the true contact area and static shear stress. For elastically soft materials, in the absence of the kinetic effect described above, this may result in a breakloose friction force equal to the kinetic friction force. We present experimental results for a passenger car tread compound, which illustrate this effect.

Hydrophilic Single-Atom Interface Empowered Pure Formic Acid Fuel Cells

A study on the relationship between college students’ physical exercise and feelings of inferiority: The mediating effect of social support

Objective This study explores the relationships among physical exercise, social support, and feelings of inferiority among college students, with a particular focus on the mediating role of social support. Using a sample of Chinese college students, the results demonstrate that physical exercise significantly reduces feelings of inferiority, both directly and indirectly through enhanced social support. Method Pearson correlation analysis confirmed the positive correlation between physical exercise and social support, while also showing that both physical exercise and social support negatively correlate with feelings of inferiority. Structural equation modeling further supported the hypothesized relationships, revealing that the mediation pathway through social support accounted for 51.95% of the total effect. Additionally, multi-group invariance testing indicated that these relationships were consistent across genders, underscoring the universal applicability of the model. Results The findings highlight the dual pathways through which physical exercise alleviates feelings of inferiority: by fostering personal competence and enhancing social resources. Conclusion This study emphasizes the importance of integrating physical exercise and social support, providing evidence-based intervention recommendations for improving students’ mental health. By validating the dual-pathway model, the research offers theoretical support and practical significance for promoting students’ mental health through physical exercise and social support.

Acidifying the Madrid-2019 force field: A rigid model for H3O+ with scaled charges

A classical and rigid force field for the oxonium cation, H3O+, optimized in solutions of TIP4P/2005 water, is introduced. While the charges of both H3O+ and the selected counteranions (i.e., Cl−, Br−, I−, and NO3−) are scaled by a factor of 0.85, following the philosophy of the so-called Madrid-2019 model for ions, the charge distribution of H3O+ was derived within the framework of the self-consistent atomic dipole-corrected Hirshfeld approach. Considering the simplicity of the model, the agreement between experimental data and molecular dynamics simulation results for the curvature of the solution density as a function of the solute concentration is remarkable. However, limitations persist in capturing ion-pairing behavior and long-range hydrogen-bonding dynamics in polyatomic systems. We found that a scaled charge of 0.85e provides an accurate description of the local structure of hydrogen halides but is detrimental to predicting the viscosity of the solution. The opposite effect is observed for HNO3. Nonetheless, the newly optimized potential parameters for H3O+ expand the family of ions with scaled charges in the Madrid–2019 force field, providing a computationally efficient and versatile platform to study electrolyte solutions in acidic environments. These findings contribute to the advancement of molecular modeling techniques and to improving our understanding of the interplay between local structure (solvation, ion pairing) and transport properties in complex systems.

Fourteen-Membered Macrocyclic Cobalt Complex Structure as a Potential Basis for Durable and Active Non-platinum Group Metal Catalysts for Oxygen Reduction and Hydrogen Evolution Reactions

Enhanced human pose estimation using YOLOv8 with Integrated SimDLKA attention mechanism and DCIOU loss function: Analysis of human body behavior and posture

Pose estimation is a crucial task in the field of human motion analysis, and detecting poses is a topic of significant interest. Traditional detection algorithms are not only time-consuming and labor-intensive but also suffer from deficiencies in accuracy and objectivity. To address these issues, we propose an improved pose estimation algorithm based on the YOLOv8 framework. By incorporating a novel attention mechanism, SimDLKA, into the original YOLOv8 model, we enhance the model’s ability to selectively focus on input data, thereby improving its decoupling and flexibility. In the feature fusion module of YOLOv8, we replace the original Bottleneck module with the SimDLKA module and integrate it with the C2F module to form the C2F-SimDLKA structure, which more effectively fuses global semantics, especially for medium to large targets. Furthermore, we introduce a new loss function, DCIOU, based on the YOLOv8 loss function, to improve the forward propagation of model training. Results indicate that our new loss function has a 3–5 loss value reduction compared to other loss functions. Additionally, we have independently constructed a large-scale pose estimation dataset, HP, employing various data augmentation strategies, and utilized the open-source COCO and MPII datasets for model training. Experimental results demonstrate that, compared to the traditional YOLOv8, our improved YOLOv8 algorithm increases the mAP value on the pose estimation dataset by 2.7% and the average frame rate by approximately 3 frames. This method provides a valuable reference for pose detection in pose estimation.

Free energy profiles for chemical reactions in solution from high-dimensional neural network potentials: The case of the Strecker synthesis

Machine learning potentials (MLPs) have become a popular tool in chemistry and materials science as they combine the accuracy of electronic structure calculations with the high computational efficiency of analytic potentials. MLPs are particularly useful for computationally demanding simulations such as the determination of free energy profiles governing chemical reactions in solution, but to date, such applications are still rare. In this work, we show how umbrella sampling simulations can be combined with active learning of high-dimensional neural network potentials (HDNNPs) to construct free energy profiles in a systematic way. For the example of the first step of Strecker synthesis of glycine in aqueous solution, we provide a detailed analysis of the improving quality of HDNNPs for datasets of increasing size. We find that, in addition to the typical quantification of energy and force errors with respect to the underlying density functional theory data, the long-term stability of the simulations and the convergence of physical properties should be rigorously monitored to obtain reliable and converged free energy profiles of chemical reactions in solution.

An Experimental and Theoretical Investigation into [2π + 2π] Cycloaddition Reactions Catalyzed by a Cationic Cobalt(I) Complex Containing a Strong-Field PC_NHCP Pincer Ligand

The long-term effects of parental marriage age on children’s educational human capital

This paper focuses on micro-level Chinese households and studies the impact of parental marriage age on the education outcomes of their children, utilizing data from the China Family Panel Studies (2020). Through OLS model regression, it is found that parents who get married later are better prepared to have children, marital stability is also stronger, and their children have a longer education period. But this positive effect will turn negative after the age of marriage exceeds 30. Further analysis reveals that parental age at marriage has a heterogeneous effect on their children’s educational attainment, which means mothers have a more significant impact on their children’s education outcomes than fathers.

Energy-specific Bethe–Salpeter equation implementation for efficient optical spectrum calculations

We present an energy-specific Bethe–Salpeter equation (BSE) implementation for efficient core and valence optical spectrum calculations. In the energy-specific BSE, high-lying excitation energies are obtained by constructing trial vectors and expanding the subspace targeting excitation energies above the predefined energy threshold in the Davidson algorithm. To calculate optical spectra over a wide energy range, energy-specific BSE can be applied to multiple consecutive small energy windows, where trial vectors for each subsequent energy window are made orthogonal to the subspace of preceding windows to accelerate the convergence of the Davidson algorithm. For seven small molecules, energy-specific BSE combined with G0W0 provides small errors around 0.8 eV for absolute and relative K-edge excitation energies when starting from a hybrid PBEh solution with 45% exact exchange. We further showcase the computational efficiency of this approach by simulating the N 1s K-edge excitation spectrum of the porphine molecule and the valence optical spectrum of silicon nanoclusters involving 6000 excited states using G0W0-BSE. This work expands the applicability of the GW-BSE formalism for investigating high-energy excited states of large systems.