Browse Articles

A Hybrid Framework for Air Pollution Forecasting using DSES, DLA, Self-Attention Transformer, and BiGRU with Bayesian Optimization

Abstract This paper presents a novel hybrid forecasting framework, DSES-DLA-Transformers-BiGRU-BO, for accurate and interpretable air pollution prediction by synergistically capturing temporal dynamics and seasonal variations within multivariate time series. To be specific, this study first incorporates Dual Seasonal Exponential Smoothing (DSES) to extract and smooth the underlying trend along with dual seasonal components, inspired by the seasonal nature of environmental signals. Second, the proposed Dual-Level Attention Mechanism (DLA) simultaneously performs feature-level attention to identify influential environmental variables and temporal-level attention to capture critical historical dependencies in air pollution sequences. These enriched representations are then processed using a Bidirectional Gated Recurrent Unit (BiGRU) architecture to learn bidirectional sequence patterns, thereby enabling the model to understand both historical context and future trend. Third, Bayesian Optimization (BO) is employed to adaptively fine-tune the model’s hyperparameters, enhancing predictive robustness and performance across different time scales. Extensive experiments conducted on real-world air pollution dataset confirm the superior forecasting accuracy of the proposed DSES-DLA-Transformers-BiGRU-BO model, outperforming state-of-the-art statistical and deep learning counterparts by notable margins across various metrics, including MAE, MSE, RMSE, MAPE, DA, WLR, and TUS. Additionally, the proposed framework demonstrates computationally feasible hybrid forecasting architecture and generalization capability, offering a scalable and effective solution for environmental monitoring systems.

Kinetic and physicochemical modeling of β-galactosidase from Rhynchophorus palmarum larvae

Palm weevil ( Rhynchophorus palmarum L.) is a significant pest that has been identified as a threat to palm trees in tropical regions. Beyond its agricultural impact, its digestive system represents a promising source of biocatalysts. The present study investigates the catalytic activity of β -galactosidase extracted from the digestive juice of R. palmarum larvae. o -nitrophenyl- β -D-galactopyranoside ( o NPG) was utilized as the substrate in this investigation. The purified enzyme exhibited optimal activity at 330.0 ± 1.2 K and pH = 5.0 ± 0.1, as determined by empirical and mechanistic models. The activation energy (E a ) was estimated at 56.3 ± 9 kJ mol -1 using mechanistic models. Furthermore, the pK values for the enzyme-substrate complex were determined to be 4.0 ± 0.1 for the nucleophile and 6.2 ± 0.2 for the proton donor, which provides insight into the catalytic residues. Kinetic analysis through nonlinear regression yielded a catalytic constant (k cat ) of 4.9 × 10 3 s -1 with V max and K m values of 49 ± 2 U mg -1 and 0.77 ± 0.08 mM, respectively. The results obtained provide novel insights into the physicochemical properties of this enzyme. The findings of this study demonstrated that the insect digestive system is a promising and largely untapped source of robust β -galactosidases with considerable potential for industrial biocatalytic applications.

Effect of different manure application rates on the nutritional composition of yam landraces grown under field conditions in Southern Ethiopia

Associations of egocentric social network characteristics with conversations about the harms of smoking and the benefits of quitting

Background Although conversations initiated by smoking-cessation messages are associated with subsequent quit attempts, limited research has examined how the social network characteristics of people who smoke relate to engagement in these conversations. The current study aimed to assess associations between key social network attributes and conversations about the harms of smoking and the benefits of quitting in the context of exposure to novel cessation messages. Methods Data were collected from a convenience sample of U.S. adults who smoke (n = 366) and who received a 14-day supply of cigarettes in packs that four different labeling types (i.e., novel text-based messages about smoking harms on the side of packs; pictorial health warnings with the same text, but with imagery and printed on 50% of front and back of packs; efficacy-message inserts with text and imagery about smoking cessation benefits and quitting strategies, placed inside the packs; and/or efficacy message inserts with pictorial health warning labels). At baseline, participants reported their egocentric network characteristics, and each night for 14 consecutive days, they completed a survey about their conversations with network members in the prior 24 hours. Bivariate and adjusted mixed-effects logistic regression models, controlling for experimental message study condition and other covariates, assessed relationships between network attributes and conversations. We estimated separate models predicting the likelihood of conversations (1) about the harms of smoking and (2) about the benefits of quitting on any given day. Results In adjusted models, network members’ (i.e., alters’) disapproval of smoking and the prevalence of alters that smoke were positively associated with conversations about both smoking harms and quitting benefits. Network size was negatively associated with, and average closeness to alters was positively associated with, conversations about quitting benefits. Conclusion Social network characteristics can influence conversations about smoking harms and cessation benefits. Leveraging these features in cessation interventions could more effectively reduce smoking. Trial Registration: ClinicalTrials.gov NCT04075682

Estrogenic and androgenic endpoints responses to bisphenols and atrazine in fish primary hepatocytes

Perceived facilitators and barriers against human papillomavirus vaccine among rural parents with eligible daughters in the Alle district, Southern Ethiopia

Introduction Human papillomavirus vaccine acceptance is influenced by the parental perceptions of the vaccine, but there are few related studies in Ethiopia, and most have focused on quantitative approaches. Therefore, this qualitative study intended to explore parental perceptions about the human papillomavirus vaccine acceptance. Objective To explore the perceived facilitators and barriers against human papillomavirus among rural parents with eligible daughters in the Alle district, southern Ethiopia. Methods A qualitative study using focus group discussion and in-depth interviews was conducted from April 25, 2023, to May 25, 2023, among eligible parents of daughters in the Alle district, southern Ethiopia. A convenience sample of 53 parents was recruited for focus group discussions, and 15 parents were purposely sampled for in-depth interviews. The data were collected by a semi-structured focus group discussion guide and in-depth interview questionnaires. The interview data were translated into English after transcription, and thematic analysis was done by Atlas software version 7.1.16. Results Among the total participants, 66.2% were female parents and 60.2% were protestant religious followers. Findings were split between two major themes: perceived facilitators and barriers to human papillomavirus vaccine acceptance. The perceived facilitators identified were preventing cervical cancer, seeing it as an expression of parental role and responsibility, and believing in the recommendation of health professionals as facilitators of human papillomavirus vaccination. The identified perceived barriers to human papillomavirus vaccination included: a lack of awareness, a lack of reliable information sources, a lack of trust in the vaccine, misconceptions, fear of side effects, and cultural and religious factors affecting the acceptance of human papillomavirus vaccination. Conclusion Parents identified various facilitators and barriers to accepting the human papillomavirus vaccine. Therefore, we recommend that the government and concerned institutions work in collaboration to address the identified challenges to improve the acceptance of human papillomavirus vaccination.

Electrical field-responsive micelles based on orthogonal assembly of two homopolymers and its application in drug delivery

COVID-19 vaccine confidence among adults of pima county using the NIMHD minority health and health disparities research framework: A qualitative analysis

Introduction Vaccinations have been established as one of the most effective strategies to prevent the spread of infectious diseases. However, vaccine hesitancy has been a growing issue that needs to be monitored and understood to ensure successful promotion. Historic structural, social, and health disparities have been demonstrated to have significant impact on many health outcomes including vaccination uptake. This study applied the National Institute on Minority Health and Health Disparities Research Framework to examine factors influencing COVID-19 vaccination intention during the COVID-19 pandemic among adults in Pima County, Arizona. Methods Between 22 Aug and 05 Dec 2020, 10 focus group discussions stratified by race/ethnicity, gender and language spoken (FGDs) were conducted virtually among 56 adult residents of Pima County, Arizona. After transcription and translation of FGDs conducted in Spanish, transcripts were organized by demographic characteristics and coded in Dedoose software by four independent coders. The NIMHD Framework’s Domains of Influence were used as a priori codes in the thematic analysis. All participants completed an informed consent process prior to participation. Results Of the 56 participants who took part in the ten focus groups, 27% self-reported being Hispanic or Latinx, 25% were White/non-Hispanic, 9% were Black, and 4% were Asian. The preferred language was most often reported as English. Unique challenges for each demographic group emerged from this analysis, such as language barriers among Hispanic participants, historical mistreatment concerns among Black participants, and conflicting political messages for White participants. Cultural norms, family influences, and attitudes toward autonomy versus community responsibility further shaped vaccine decisions. Effective communication about vaccine safety, clinical trials, and public health messaging were identified as critical to addressing mistrust and vaccine confidence across diverse groups. Conclusion Major themes in this study that predict vaccine intention include health literacy challenges, misinformation, mistrust in healthcare systems, and the desire to protect others. Understanding the behaviors and decisions behind vaccination acceptance and receipt is important for developing effective vaccine communication strategies. Identifying health disparities driving vaccination hesitancy may help guide future strategies and policies to improve vaccination rates, especially among minority groups.

A unified deep learning framework for subseasonal wind forecast post-processing

Profiling the diets of Classic Maya communities living in Southeastern Petén through stable isotope analysis

During the Early and Late Classic periods (250–900 CE), Maya communities in southeastern Petén experienced rapid demographic growth, and organized themselves here not as centralized city states but as a network of complex, small-scale polities. As documented by the Archaeological Atlas of Guatemala (IDAEH), this area encompasses more than 400 registered sites across the northwestern Maya Mountains, several river basins, and humid savannas, and therefore offers a diversified ecological and cultural setting for exploring local subsistence strategies of the era. Excavation and sampling strategies targeted non-elite burials, providing a unique opportunity to reconstruct the diets of commoner populations on a regional scale, especially given that no prior isotopic research has been conducted in this vast area. For this study, we analyzed stable carbon (δ 13 C) and nitrogen (δ 15 N) isotopes from human bone collagen and δ 13 C from dental enamel carbonate to evaluate collective food selection, composition, and variability over time, as well as potential social or environmental influences. We contextualized these with the isotopic profiles in published research that covers the more hierarchically organized urban centers from other parts of the Maya area. Our own results reveal consistent maize-based diets that were likely supplemented by other plant-based foods and terrestrial animal resources, with inter-site differences reflecting local social and ecological contexts. Variation in isotopic values by age and the presence of skeletal modifications suggest that life-history and biocultural factors shaped dietary patterns. Overall, our findings demonstrate an increasing reliance on maize towards the end of the Classic period and even beyond the hegemonial collapse. Taken together, our findings in southeastern Petén’s populations expand our understanding of subsistence diversity and diet among non-elite Classic Maya populations.

A synthetic virus-like assembly unlocks dual-antigen presentation for broad-spectrum anti-SARS-CoV-2 immunity

Abstract In the present study, by building on the previous development of a DC-SIGN-targeting virus-like structure (VLS) vaccine platform and a comprehensive characterization of SARS-CoV-2 structural biology, particularly insights into the role of the nucleocapsid (N) protein in eliciting cytotoxic T lymphocyte (CTL) responses during infection, we designed a SARS-CoV-2 virion-mimetic structural vaccine that encapsulates an mRNA encoding the spike S1 antigen complexed with N protein complexes, with S1 proteins loaded on its surface. This characterized virion-mimetic structural vaccine not only induces the production of high-efficiency antibodies against both the spike and N proteins but also elicits robust S1-specific and N-specific CTL responses in animal models. Furthermore, the generated antibodies exhibit cross-reactive neutralizing activity against multiple SARS-CoV-2 variants and provide protective immunity against challenge with mutant viruses in immunized hosts. This SARS-CoV-2 virion-mimetic structure effectively recapitulates natural infection pathways, comprehensively activating the innate immune system and thereby creating an optimal microenvironment for eliciting potent and broad-spectrum adaptive immune responses.

Expression of Concern: Molecular epidemiology and phylogenetics of camel anaplasmosis

Heterogeneity-aware orthogonal covariance attention for MRI-based multi-class brain tumor differentiation

Investigation of the splitting tensile performance of Rock-Filled Concrete based on mesoscopic modeling: Effects of the interfacial transition zone and rockfill characteristics

Rock-filled concrete (RFC) is a three-phase heterogeneous composite composed of large-size rockfill, self-compacting concrete (SCC), and the interfacial transition zone (ITZ) between them. Its mechanical performance is jointly affected by the rockfill skeleton effect and the properties of the ITZ. Existing studies still provide insufficient understanding of how interfacial properties and rockfill characteristics influence the splitting tensile performance and damage evolution mechanism of RFC. In this study, splitting tensile tests of RFC were conducted based on an actual engineering project, and an engineering-scale three-dimensional mesoscopic finite element model was established based on the experimental results. The effects of ITZ strength, rockfill strength, and rockfill particle size on the splitting tensile mechanical response, damage evolution process, and failure morphology of RFC were investigated. The results show that when σ ITZ ∕ σ scc increased from 0.2 to 1.0, the splitting tensile strength of RFC increased by 36.75%; when σ Rock ∕ σ scc increased from 1.0 to 5.0, the splitting tensile strength increased by 39.65%. The splitting tensile strength of RFC increased with increasing ITZ strength and rockfill strength and gradually approached saturation, with threshold values of σ ITZ ∕ σ scc  = 0.8 and σ Rock ∕ σ scc  = 4.0, respectively. The influence of rockfill particle size on splitting tensile strength showed a trend of first increasing and then decreasing. Compared with a single particle size distribution, a graded particle size distribution improved the rockfill skeleton structure and more effectively enhanced the splitting tensile performance of RFC. Overall, improving ITZ quality and adopting a properly graded rockfill particle size distribution are important approaches for enhancing the splitting tensile performance of RFC, and the findings provide a theoretical basis for RFC material design and engineering applications.

Advanced bis-thiourea polymer resins for efficient gold (III) recovery

Research on the anti-pull performance of a novel small-diameter steel tube-stud grouting connector

To clarify the pull-out performance of steel tube-stud grouting (STG) connectors, this paper designed 18 test specimens, with main research parameters including embedment depth of stud (4d and 8d), steel type of stud, steel tube thickness, stud end diameter, and steel tube backing plate hole diameter. The study investigated the failure mode and deformation capacity of connectors, and strain patterns of the studs and steel tubes in the connectors, through pull-out tests and numerical simulation analysis. The study found a high degree of consistency between experimental and simulated results, and strain and stress in the studs gradually increased from the ends outward. This study fills an existing research gap regarding external-wall connections for steel structures and proposes an innovative, reliable connecting detail for prefabricated steel facade joints. Test results confirm that the proposed connection exhibits favourable pullout behaviour even with low-strength grout and a shallow stud embedment of 4d, which reduces material costs and simplifies field construction. The derived formula for yield load capacity achieves high prediction accuracy (maximum error is 11.3%) and applies to practical engineering calculations, thereby enhancing design efficiency and structural safety. In addition, this work provides theoretical underpinnings and experimental datasets for parametric optimization, engineering popularization, and the development of specifications for STG connectors.

Spatial characterization of interface dermatitis in cutaneous lupus reveals novel chemokine axis-mediated recruitment of leukocytes that drive disease

Deep learning approaches show promise for predicting childhood malnutrition: A comparative study with traditional machine learning methods using survey data

Childhood malnutrition remains a major public health concern in Nepal and other low-resource settings, while conventional case-finding approaches are labor-intensive and frequently unavailable in remote areas. This study provides one of the first applications of machine learning and deep learning to identify child malnutrition in Nepal. We systematically compared 16 algorithms spanning deep learning, gradient boosting, and traditional machine learning families, using data from the Nepal Multiple Indicator Cluster Survey (MICS) 2019. A composite malnutrition indicator was constructed by integrating stunting, wasting, and underweight status, and model performance was evaluated using ten metrics, with emphasis on F1-score and recall to account for substantial class imbalance and the high cost of failing to detect malnourished children. Among all models, TabNet achieved the highest scores among evaluated models, likely attributable to its attention-based architecture. A consensus feature importance analysis identified maternal education, household wealth index, and child age as the primary predictors of malnutrition, followed by geographic characteristics, vaccination status, and meal frequency. Collectively, these results demonstrate a scalable, survey-based screening framework for identifying children at elevated risk of malnutrition and for guiding targeted nutritional interventions. The proposed approach supports Nepal’s progress toward the Sustainable Development Goals and offers a transferable methodological template for similar low-resource settings globally.

Carbon-aware resource allocation and task offloading in EH-assisted edge-cloud systems

Predictors and evolution of post-stroke depression among adults admitted for first stroke at referral hospitals in Dodoma, Tanzania: A protocol for a prospective longitudinal observational study

Background Survivors of strokes are prone to disabilities, especially in underdeveloped countries. Post-stroke depression (PSD) is a common neuropsychiatric condition that exacerbates symptoms and raises the danger of stroke recurrence, disability, and mortality. Nevertheless, little is documented about PSD’s incidence, predictors, and consequences. This study aims to assess predictors and outcomes of post-stroke depression among patients admitted with the first stroke episode at referral hospitals in Dodoma, Tanzania. Methods and analysis The study is a prospective longitudinal observational design; a consecutive sampling technique will be used to attain the estimated sample size of adults aged ≥18 years who have had their first stroke episode, within 14 days. The study will be conducted at referral hospitals in the Dodoma region, Tanzania. At admission, baseline clinical and sociodemographic parameters will be recorded, including relevant medical and psychiatric history. Depressive symptoms will be assessed at 1- and 3-months post-stroke, with the 1-month assessment serving as the baseline for post-stroke depression. The International Neuropsychiatric Interview (M.I.N.I) will be used to diagnose major depressive disorder and to exclude participants with a prior history of depression, while the PHQ-9 will be used to quantify severity and monitor progression of depressive symptoms over time. Data will be summarised using descriptive statistics; continuous data will be reported as mean (SD) or median (IQR), while categorical data will be reported as frequencies and proportions. The PSD predictors will be determined using logistic regression analysis. The study will adhere to data-sharing guidelines and take ethical considerations into account. Ethics and dissemination The University of Dodoma’s institutional Research Review and Ethical Committee has granted permission to conduct the study with reference number MA.84/261/02. The relevant authorities granted approval for the study to be carried out at DRRH and BMH.