Browse Articles

Household perceptions, practices, and experiences with real-world alternating dual-pit latrines treated with storage and lime in rural Cambodia

Achieving universal safely managed sanitation (SMS) is an ambitious long-term goal in resource-limited rural areas. The non-governmental organization, iDE, introduced the alternating dual-pit latrine (ADP), which treats fecal sludge (FS) on-site using storage and lime to increase SMS in rural Cambodia. However, SMS via ADPs requires adherence to recommended practices (e.g., how and when to switch between pits). We surveyed 765 rural households with ADPs across five of 25 Cambodian provinces to understand how real-world household sanitation practices and knowledge affect and are related to adherence to recommended practices at scale. We calculated summary statistics of household survey responses and used regression models of composite indices to describe how households’ practices and attitudes related to ADPs affect adherence to recommended ADP practices. By 24 months after training, three in five households did not recall how long treatment must proceed until emptying can be performed safely. No household waited the recommended two years to empty their pits. While households appreciated the advantages of owning an ADP (e.g., reduced costs and required land area compared to single-pit latrines over time), no household followed recommended treatment practices. This lack of adherence could have health and environmental implications for households using ADPs. Household practices also varied by province, flood proneness, and education level, adding complexity to how to improve adherence; for example, having at least one household member that completed formal education surprisingly reduced compliance with recommended ADP practices. Household behaviors impact the use and maintenance of on-site sanitation systems in rural areas, with proper adherence is necessary to achieve sustained SMS. Increased access to affordable and safe emptying service providers could enable households to manage the pits of their ADPs and dispose of FS in-situ according to treatment duration, while also ensuring that household practices in operating on-site sanitation systems are integrated into the design, installation, and SMS monitoring of such systems.

Membrane-free CO2 electrolyzer design for economically efficient formic acid electro-synthesis

Improved non-invasive detection of sleep stages when combining skin sympathetic nerve activity and heart rate variability analysis with AI

Partial removal of visceral epididymal white adipose tissue in obese Ldlr-/-.Leiden mice impacts adipokine secretion, plasma free fatty acids, and improves cerebrovascular health

Visceral white adipose tissue (WAT) dysfunction may contribute to obesity-related brain impairments but causal relationship has not been demonstrated. We herein investigated the impact of visceral epididymal WAT (eWAT) lipectomy on brain health and obesity-associated comorbidities (liver steatosis, atherosclerosis, WAT dysfunction) in obese Ldlr-/-.Leiden mice. High-fat diet (HFD)-fed obese mice underwent sham surgery or partial removal (~70%) of eWAT. A separate group of mice was kept on chow diet (control). Liver disease, atherosclerosis and three WAT depots were examined histologically, and WAT biopsies were also cultured ex vivo . Brain structure and function were monitored longitudinally using cognitive tests and neuroimaging, paralleled by histological analysis of brain pathology and hippocampal RNA-sequencing. In ex vivo WAT culture, the surgically removed eWAT portion secreted many adipokines and pro-inflammatory factors. Histological analyses at the end of the study showed that eWAT-lipectomy did not affect liver disease and atherosclerosis development, but reduced the number of severely hypertrophic adipocytes in the residual-eWAT. This was consistent with reduced secretion of adipokines (e.g., leptin, adiponectin) and pro-inflammatory mediators (e.g., PAI-1, MIP-1α/CCL3, IL-17) from the residual-eWAT in the ex vivo culturing experiments. Importantly, lipectomy alleviated HFD-induced adverse effects on hippocampal vasoreactivity, increased cortico-hippocampal (resting-state) functional connectivity and prevented the development of sedentary behavior. Lipectomy did not significantly affect histological neuroinflammation or circulating cytokines/chemokines, but increased specific free fatty acids (e.g., eicosatrienoic acid and docosahexaenoic acid, known to have anti-inflammatory and vaso-protective properties). Hence, partial eWAT lipectomy in mice with manifest obesity partly prevents hippocampal cerebrovascular disturbances, demonstrating a causal involvement of visceral WAT in obesity-associated brain impairments. The beneficial effects of eWAT lipectomy may, at least partly, be mediated by anti-inflammatory free fatty acids, and possible changes in release of adipokines and inflammatory mediators.

Hydride formation pressures and kinetics in individual Pd nanoparticles with systematically varied levels of plastic deformation

Abstract Pd nanoparticles, together with bulk and thin film Pd, constitute the archetype model system for metal-hydrogen interactions. The density of defects in Pd nanoparticles, such as grain boundaries and dislocations, combined with their size, shape, composition and lattice strain, dictate their hydrogen sorption kinetics and thermodynamics. Despite decades of research and its relevance in applications, such as solid-state hydrogen storage, hydrogen sensors, hydrogen embrittlement, and hydrogen separation membranes, a coherent picture of the intricate interplay between defects, strain and Pd nanoparticle hydrogen sorption properties is missing. Here, we employ a combination of single particle nanocompression, single particle plasmonic nanoimaging and high-resolution cross-sectional single particle TEM imaging to investigate hydrogen absorption kinetics and hydride phase formation pressures in a nanofabricated array of Pd nanoparticles on sapphire substrate with systematically varied levels of plastic deformation – and thus defects and strain. We not only show a clear deformation-level dependent trend of both the kinetics and the hydride formation pressure, but also reveal their complex evolution upon hydrogen cycling. We discuss how these results provide a quantitative view of the impact of plastic deformation on nanoscale metal hydrides, and how they reveal the surface and bulk morphology of Pd nanoparticles upon repeated hydrogen cycling.

Solar-assisted tri-generation system with LCPV‑CPC and small-scale gas turbine for year-round clean energy in hot-dry climates

Cross-market volatility spillovers between China and the United States: A DCC-EGARCH-t-Copula framework with out-of-sample forecasting

This study examines volatility spillovers between Chinese and U.S. equity markets by developing a comprehensive framework that captures asymmetric volatility, extreme co-movements, and dynamic correlations. We propose an integrated methodology combining EGARCH models with Student-t innovations, a Student-t copula, and a Dynamic Conditional Correlation (DCC) structure. Using daily returns of the Hang Seng Index (HSI) and the S&P 500, our analysis reveals three principal findings. First, the EGARCH model effectively captures the pronounced leverage effect and fat-tailed distributions characteristic of both markets. Second, the Student-t copula demonstrates the best fit among competing specifications, indicating significant symmetric tail dependence between the two markets. Third, time-varying correlations exhibit high persistence, rising during crises yet remaining within a moderate range. Crucially, out-of-sample forecasting shows that our unified framework achieves superior predictive accuracy relative to standard benchmarks. These findings provide valuable insights for investors designing hedging strategies, exchanges determining margin requirements, and policymakers monitoring financial contagion. Our approach offers a robust tool for analyzing volatility transmission between developed and emerging markets.

Autophagy acts as a brake on obesity-related fibrosis by controlling purine nucleoside signalling

Abstract A hallmark of obesity is a pathological expansion of white adipose tissue (WAT), accompanied by marked tissue dysfunction and fibrosis. Autophagy promotes adipocyte differentiation and lipid homeostasis, but its role in obese adipocytes and adipose tissue dysfunction remains incompletely understood. Using a mouse model, we demonstrate that autophagy is a key tissue-specific regulator of WAT remodelling in diet-induced obesity. Importantly, loss of adipocyte autophagy substantially exacerbates pericellular fibrosis in visceral WAT. Change in WAT architecture correlates with increased infiltration of macrophages with tissue-reparative, fibrotic features. We uncover that autophagy restrains purine nucleoside metabolism in obese adipocytes. This ultimately leads to a reduced release of the purine catabolites xanthine and hypoxanthine. Purines signal cell-extrinsically for fibrosis by driving macrophage polarisation towards a tissue reparative phenotype. Our findings in mice reveal a role for adipocyte autophagy in regulating tissue purine nucleoside metabolism, thereby limiting obesity-associated fibrosis and maintaining the functional integrity of visceral WAT. Purine signals may serve as a critical balance checkpoint and therapeutic target in fibrotic diseases.

Analyzing the normal and epileptic output of a neural mass model based on cyclic-small gain theorem

Malaria in travelers and local populations: Comprehensive study of incidence patterns and origin-based classification in Saudi Arabia

Background Malaria continues to pose a significant public health threat in the Kingdom of Saudi Arabia (KSA), despite ongoing control efforts. Most malaria cases in the KSA are associated with travelers arriving from malaria-endemic regions. The rationale for studying malaria in the KSA stems from the country’s goal to eliminate the disease and address the increased risk of imported cases, which is heightened by substantial migration and religious tourism. Methods This study aimed to assess the origins of malaria cases, the relative contribution of the different Plasmodium species involved, and the incidence rates across different age groups in the KSA. The Ministry of Health collected data on malaria cases in 13 administrative regions from January 2022 to December 2023. The chi-square test was used to analyze the data and determine the overall parameters and the rate of slide positivity. Results The findings indicated that “imported” malaria cases were the predominant type of disease in the KSA. Out of 1,453,451 febrile cases examined, 0.7% (10,779) were positive across the 13 regions. In 2022, 688,629 cases were examined, with 0.9% (6,460) being positive. In 2023, 764,822 cases were examined, with 0.6% (4,319) being positive. Among these regions, Jazan exhibited the highest incidence rates (59%), followed by Makkah (20%), with a statistically significant difference (P = 0.046) between the regions. Malaria incidence was higher in patients aged ≥15 years. This study found significant variations (P = 0.002) in malaria incidence rates among different Plasmodium species. Plasmodium falciparum exhibited the highest rate at 63.5%, followed by P. vivax - P. ovale at 33%, P. malariae at 0.5%, and mixed infections where more than one species is involved at 3%. Conclusion During the study period, imported malaria was the major type of malaria, especially in the Jazan region and Makkah. The highest incidence was caused by P. falciparum . These findings indicate the need for targeted interventions and public health strategies to mitigate the “imported” malaria burden, particularly among travelers.

Towards annual updating of forced warming to date and constrained climate projections

Abstract In the context of rapid human-caused climate change, regular updates of the state of knowledge of current and future climate are needed. New statistical methods using observational constraints underpinned estimates of present-day human-induced warming and projected future warming in the most recent IPCC report. As time goes by, and new updated observational records become available, how should estimates of the current and projected human-caused climate change be updated? Here, we use a perfect model framework and show that incorporating observations from every new year in observationally constrained projections improves their accuracy, without causing major year-to-year spurious variability on outcomes. The forced warming estimated for the current year also exhibits high enough stability to be considered as a robust indicator of the state of the climate system.

Carrying capacity and strategic planning for sustainable tourism practices in the Char Dham from the Western Himalaya, India

Microbeads and microcapsules for diet delivery to Zelus renardii

Predation on Aphrophoridae and other olive tree pests makes Zelus renardii a candidate for biocontrol actions to limit Xylella fastidiosa infections while mitigating other olive tree pests. The opportunity drives the search for an effective mass rearing method of Z. renardii. Predator rearing on artificial diets greatly benefits from feed-effective formulation, preparation, storage, preservation, and delivery. Given the several oligidic, meridic, and holidic available formulations, we face the challenge of a proper diet processing for delivery. To understand how to obtain a large number of preservable and sterile diet portions while avoiding microbial contamination, we explore prilling/vibration techniques to rear Z. renardii. Prilling or vibrating the diets yields multicore microbeads or monocore microcapsules; water domains exist, whose arrangements are well-documented by the cryo-SEM study and represented in corresponding false-color images. Issues include the density interplay between low- or high-density alginate and the liquid diet formulation during prilling/vibration. Other options relate to alginate stickiness or consistency, which makes it difficult to disperse the diet domains in the microbeads or to obtain a single diet domain per microcapsule because of unpredictable wall thickness and core lateralization. We suggest options to make microbeads and microcapsule portions available for up to one year for predators, stored in cold, pure water.

Observation of a guest-free Si46 clathrate-I framework from Ba8-xSi46 upon in situ vacuum heating

A performance analysis of convolutional autoencoder modified WaveGAN architectures for realistic 12 lead electrocardiogram synthesis

Analysis of spatial heterogeneity in Xi'an's urban heat island effect using multi-source data fusion

In the context of global climate change, this study aims to investigate the spatial heterogeneity and driving mechanisms of the urban heat island (UHI) effect within Xi’an’s second ring road area. We constructed a novel multi-source data fusion framework that integrates high-resolution remote sensing imagery, detailed building spatial data, and semantic indicators from street view imagery. Based on this framework, we extracted seven key environmental features and land surface temperature (LST) data. We employed Multi-scale Geographically Weighted Regression (MGWR) and machine learning models, including Random Forest, XGBoost, and Gradient Boosted Regression, to analyze both nonlinear interactions and spatially localized variations influencing UHI intensity. The results indicate that building density (BD), green view index (GVI), and road density (RD) are the dominant factors affecting LST, showing significant spatial heterogeneity. BD has the highest global importance with a SHAP value of 0.665 in the XGBoost model and shows positive effects on LST, especially in high-density areas. GVI exhibits stable negative correlations with LST, highlighting its cooling potential in medium- to high-density zones. MGWR regression coefficients for BD and GVI range from −0.66 to 1.38 and −0.53 to 0.33, respectively, revealing substantial local variation. Our analysis reveals the necessity of spatially differentiated climate adaptation strategies, and confirms the effectiveness of fine-grained environmental indicators in representing UHI formation mechanisms. The proposed multi-source data fusion and integrated MGWR-machine learning framework offers refined methodological tools and practical insights for enhancing urban thermal resilience and developing targeted microclimate regulation policies.

AQuaRef: machine learning accelerated quantum refinement of protein structures

Abstract Cryo-EM and X-ray crystallography provide crucial experimental data for obtaining atomic-detail models of biomacromolecules. Refining these models relies on library-based stereochemical data, which, in addition to being limited to known chemical entities, do not include meaningful noncovalent interactions. Quantum mechanical (QM) calculations could alleviate these issues but are too expensive for large molecules. Here we present a novel AI-enabled Quantum Refinement (AQuaRef) based on AIMNet2 machine learned interatomic potential (MLIP) mimicking QM at substantially lower computational costs. By refining 41 cryo-EM and 30 X-ray structures, we show that this approach yields atomic models with superior geometric quality compared to standard techniques, while maintaining an equal or better fit to experimental data. Notably, AQuaRef aids in determining proton positions, as illustrated in the challenging case of short hydrogen bonds in the parkinsonism-associated human protein DJ-1 and its bacterial homolog YajL.

Associations between perceived excessive maternal control in childhood, well-being, and dorsal striatum volume in older adults

An investigation of strong edge geodesic number on m-polar fuzzy environment and its application

For crisp graphs, the notion of edge geodesic numbers has been known for a long time. But lately, the focus has shifted to investigating this idea in fuzzy graphs, which has resulted in studies of a number of properties. Determining a strong edge geodesic number in the context of a m -polar fuzzy graph (m PFG), where nodes and edges both have m membership values, poses special difficulties that call for creative solutions. Strong geodesic numbers and strong edge geodesic numbers in m PFGs are defined in this study along with a detailed description. It determines an upper bound for strong edge geodesic numbers in a variety of well-known m PFGs. The metric space on the set of all vertices in a graph is associated with the strong edge geodesic distance. This article also discusses the sufficient and required conditions for robust edge geodesic cover. Additionally, isomorphic properties on strong geodesic distance are examined. Along with its various characteristics, the neighborhood notion on strong geodesic distance is also presented. Interesting characteristics of the latter are explored, and the connections between strong geodesic and strong edge geodesic numbers are analyzed. Additionally, the usefulness of strong edge geodesic numbers in m PFGs is illustrated via a practical application. This work expands the scope of fuzzy graph theory and its applications by defining and analyzing these new notions, which offer deeper insights into the structural and dynamic features of m PFGs.

The cumulenic linear C5 and its coupling-reaction products