bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comprehensive technical analysis of post-combustion carbon capture and storage based on monoethanolamine absorption for petrochemical industry in Indonesia
Authors: Asyrofi Muh , Muthia Rahma , Indianto Mohammad Akita 
Published: October 2024

Abstract
The implementation of carbon capture and storage in the petrochemical industry is one of the means of decarbonization. This research focuses on a comprehensive technical analysis of the deployment of post-combustion carbon capture and storage based on monoethanolamine absorption in the petrochemical industry. The olefin complex petrochemical industry in Tuban, Indonesia, is the basis for the analysis, which includes a steam cracker, polyethylene, polypropylene, and raw pyrolysis gasoline hydrotreating units, with capacities of 1000, 940, 600, and 570 kilotons/year, respectively. The total energy consumption is about 16 024.53 GJ/h, and the CO2 emissions are about 1.6 megatons/year. Based on these plant systems, comprehensive technical analyses of the implementation of carbon capture and storage in that industry were performed using Aspen HYSYS® simulation software. Sensitivity analysis was carried out to determine the total CO2 captured, energy intensity, monoethanolamine consumption, and net CO2 captured in various scenarios based on the number of absorber column stages, absorption pressure, and desorption temperature. The CO2 storage site is about 100 km away and is transported by an onshore pipeline with a supercritical phase of CO2. The optimal net CO2 capture value is achieved by setting up a 50-stage absorber column with a pressure of 1 barg and a temperature of 110°C at the top of the desorber column, resulting in a CO2 capture yield of 86.4% and an energy intensity of 12.6 GJ/ton CO2. Under these conditions, the net CO2 captured in the scenario based on gas power plants’ electricity is 0.225 megatons/year, while in the scenario based on gas power plants incorporating 30% biomass electricity, it is 0.544 megatons/year. With increased use of renewable energy in carbon capture and storage facilities, more net CO2 is captured. This study can be applied to various cases of post-combustion carbon capture and storage implementation in the industrial sector, especially in the petrochemical industry.
Exploring Nigeria’s waste-to-energy potential: a sustainable solution for electricity generation
Authors: Umar Yusuf , Yakubu Rahimat Oyiza , Abdulazeez Abdulazeez Alhaji , Ijeoma Muzan Williams 
Published: October 2024

Abstract
This research explored the potential of waste-to-energy (WtE) technology as a sustainable solution to Nigeria’s energy deficit and waste management challenges. Various WtE technologies were reviewed, including incineration, anaerobic digestion, gasification, and pyrolysis, highlighting their applicability and benefits for Nigeria. The potential energy yield from different waste streams, combined with economic viability, environmental benefits, and social impacts, demonstrates the importance of WtE technology for the country. The lower heating value of municipal solid waste and agricultural residue significantly affects energy yield. The incineration of 27.36 million tons of organic waste annually while using relevant technology with energy recovery could generate between 14.52 and 23.08 TWh of electricity per annum. The inclusion of paper and textiles increases the potential yield to 18.69 and 29.71 TWh per year. The potential power generation from agricultural residues is estimated at 80.3 GW. However, Nigeria must address technical, economic, and policy challenges to realize this potential. This can be achieved by developing a robust regulatory framework, fostering public–private partnerships, enhancing local capacity, engaging communities, and investing in research and development. The implementation of WtE projects will facilitate sustainable waste management, improve energy security, create jobs, and promote environmental stewardship.
Epidemiological and Clinical Features of a Large Blastomycosis Outbreak at a Paper Mill in Michigan
Authors: Hennessee Ian , Palmer Sara , Reik Rebecca , Miles-Jay Arianna , Nawaz Muhammad Yasir , Blankenship Heather M , Kramer Rebecca , Hughes Adam , Snyder Michael , Yin Robert L , Litvintseva Anastasia P , Parnell Lindsay A , Gade Lalitha , Chiller Tom , de Perio Marie A , Stobierski Mary Grace , McFadden Jevon , Toda Mitsuru ,   Michigan Blastomycosis Outbreak Investigation Team, Millerick-May Melissa , Tiffany Henderson A , Scott Schreiber A , Shannon Johnson A , Collins Jim , McCullor Kimberly , Schooley Angie , Heyer Tonya , Hirt Brandon , Soehnlen Marty K , Gold Jeremy A W , Smith Dallas J , Rodríguez Stewart Roxana M , Williams Samantha L , Lockhart Shawn R , O'Connor Allyson W , Callaway Perri C , Stanton Marcia L , Bailey Rachel L , Reid Harvey R , LeBouf Ryan F , Park Ju-Hyeong , Weissman David N , Cox-Ganser Jean , Hines Stella E , Shi Dallas 
Published: October 2024

Abstract

Background
Blastomycosis is an environmentally acquired fungal infection that can result in severe pulmonary illness and high hospitalization rates. In 2023, a blastomycosis outbreak was detected among workers at a paper mill in Delta County, Michigan.

Methods
We included patients with clinical and laboratory evidence of blastomycosis who had spent ≥40 hours in Delta County since 1 September 2022 and had illness onset 1 December 2022–1 July 2023. We assessed epidemiological and clinical features of patients and evaluated factors associated with hospitalization. We performed whole-genome sequencing to characterize genetic relatedness of clinical isolates from 8 patients.

Results
In total, 131 patients were identified; all had worked at or visited the mill. Sixteen patients (12%) were hospitalized; 1 died. Compared with nonhospitalized patients, more hospitalized patients had diabetes (P = .03) and urine antigen titers above the lower limit of quantification (P &lt; .001). Hospitalized patients were also more likely to have had ≥1 healthcare visits before receiving a blastomycosis diagnostic test (P = .02) and to have been treated with antibiotics prior to antifungal prescription (P = .001). All sequenced isolates were identified as Blastomyces gilchristii and clustered into a distinct outbreak cluster.

Conclusions
This was the largest documented blastomycosis outbreak in the United States. Epidemiologic evidence indicated exposures occurred at or near the mill, and genomic findings suggested a common exposure source. Patients with diabetes may have increased risk of hospitalization, and elevated urine antigen titers could indicate greater disease severity. Early suspicion of blastomycosis may prompt earlier diagnosis and treatment, potentially reducing unnecessary antibiotic prescriptions and improving patient outcomes.
Cardiac involvement in a female patient with Beçhet’s disease: newer diagnostic and therapeutic approaches—a case report
Authors: Kouremeti Maria , Kordalis Athanasios , Dimitroglou Yannis , Tsioufis Konstantinos , Aggeli Constantina 
Published: October 2024

Abstract

Background
Behçet’s disease (BD) is a multisystemic chronic inflammatory disorder. Cardiac manifestations in BD are extremely rare. There have been no reports of cardiac involvement of BD and especially endomyocardial fibrosis in the left ventricle (LV).

Case summary
A 50-year-old woman presented at the emergency department experiencing palpitations and fatigue, accompanied by elevated levels of B-type natriuretic peptide. Her medical history included mucocutaneous involvement of BD. Vital signs were within normal ranges, and electrocardiography showed a normal sinus rhythm. Physical examination did not reveal any pathological findings. The 24 h ambulatory electrocardiogram monitoring indicated sinus rhythm with premature ventricular contractions. Transthoracic echocardiography demonstrated a reduced LV ejection fraction. Further investigation with cardiac magnetic resonance imaging reported diffused areas of subendocardial enhancement, indicative of fibrosis likely due to vasculitis probably associated with BD. The patient was administered tartrate metoprolol, eplerenone, and dapagliflozin in addition to the ongoing medical treatment for BD, which included methylprednisolone, colchicine, and apremilast. This treatment approach resulted in an improvement in the patient’s clinical condition.

Discussion
This case highlights that diffuse subendocardial fibrosis of the LV may be associated with the underlying BD.
Same trait, different genes: pelvic spine loss in three brook stickleback populations in Alberta, Canada
Authors: Mee Jonathan A , Ly Carolyn , Pigott Grace C 
Published: October 2024

Abstract
The genetic basis of phenotypic or adaptive parallelism can reveal much about constraints on evolution. This study investigated the genetic basis of a canonically parallel trait: pelvic spine reduction in sticklebacks. Pelvic reduction has a highly parallel genetic basis in threespine stickleback in populations around the world, always involving a deletion of the pel1 enhancer of Pitx1. We conducted a genome-wide association study to investigate the genetic basis of pelvic spine reduction in 3 populations of brook stickleback in Alberta, Canada. Pelvic reduction did not involve Pitx1 in any of the 3 populations. Instead, pelvic reduction in 1 population involved a mutation in an exon of Tbx4, and it involved a mutation in an intron of Lmbr1 in the other two populations. Hence, the parallel phenotypic evolution of pelvic spine reduction across stickleback genera, and among brook stickleback populations, has a nonparallel genetic basis. This suggests that there may be redundancy in the genetic basis of this adaptive polymorphism, but it is not clear whether a lack of parallelism indicates a lack of constraint on the evolution of this adaptive trait. Whether different pleiotropic effects of different mutations have different fitness consequences or whether certain pelvic reduction mutations confer specific benefits in certain environments remains to be determined.
Tempo and mode of winter diapause evolution in butterflies
Authors: Halali Sridhar , Yapar Etka , Wheat Christopher W , Wahlberg Niklas , Gotthard Karl , Chazot Nicolas , Nylin Sören , Lehmann Philipp 
Published: October 2024

Abstract
Quantifying the tempo and mode via modern phylogenetic comparative methods can provide key insights into how selection and constraints shape trait evolution on a macroevolutionary time scale. Here, we elucidate the evolution of hibernation (winter) diapause, a complex and defining life-history trait that allows temporal escape from harsh winters in temperate regions for many insects, including our model system, butterflies. Butterflies can diapause in all major life stages, and the availability of global-scale phylogenies makes them an ideal model system for studying diapause evolution. First, using a thorough literature survey, we scored the developmental stage of hibernation diapause (egg, larva, pupa, adult) vs. absence of diapause. We find that larval diapause is most common, while pupal, egg, and adult diapause are relatively rare. Next, we determined that the loss of diapause occurred at a much higher rate and that gains primarily occurred from the non-diapause state. While ancestral state estimation at deeper nodes remained uncertain, we found consistent patterns for some families and strong evidence for extensive convergence in diapause evolution. Contrary to expectations, we find no support for increased gain of diapause during the Eocene–Oligocene glaciation (~35 million years ago). Overall, the evolution of diapause in butterflies has a complex history, has evolved convergently, and has likely predated the major glaciation event consistent with the deep history of diapause evolution in insects. This study advances our understanding of the evolution of a complex and important life-history trait and establishes a macroevolutionary foundation for future studies on the ultimate and proximate basis of diapause evolution.
Life-Course Multidisciplinary Psychosocial Predictors of Dementia Among Older Adults: Results From the Health and Retirement Study
Authors: Kuwayama Sayaka , Tarraf Wassim , González Kevin A , Márquez Freddie , González Hector M 
Published: October 2024

Abstract

Background and Objectives
Identifying predictors of dementia may help improve risk assessments, increase awareness for risk reduction, and identify potential targets for interventions. We use a life-course psychosocial multidisciplinary modeling framework to examine leading predictors of dementia incidence.

Research Design and Methods
We use data from the Health and Retirement Study to measure 57 psychosocial factors across 7 different domains: (i) demographics, (ii) childhood experiences, (iii) socioeconomic conditions, (iv) health behaviors, (v) social connections, (vi) psychological characteristics, and (vii) adverse adulthood experiences. Our outcome is dementia incidence (over 8 years) operationalized using Langa–Weir classification for adults aged 65+ years who meet criteria for normal cognition at the baseline when all psychosocial factors are measured (N = 1 784 in training set and N = 1 611 in testing set). We compare the standard statistical method (Logistic regression) with machine learning (ML) method (Random Forest) in identifying predictors across the disciplines of interest.

Results
Standard and ML methods identified predictors that spanned multiple disciplines. The standard statistical methods identified lower education and childhood financial duress as among the leading predictors of dementia incidence. The ML method differed in their identification of predictors.

Discussion and Implications
The findings emphasize the importance of upstream risk and protective factors and the long-reaching impact of childhood experiences on cognitive health. The ML approach highlights the importance of life-course multidisciplinary frameworks for improving evidence-based interventions for dementia. Further investigations are needed to identify how complex interactions of life-course factors can be addressed through interventions.
The ensemble kalman filter for dynamic inverse problems
Authors: Weissmann Simon , Chada Neil K , Tong Xin T 
Published: October 2024

Abstract
In inverse problems, the goal is to estimate unknown model parameters from noisy observational data. Traditionally, inverse problems are solved under the assumption of a fixed forward operator describing the observation model. In this article, we consider the extension of this approach to situations where we have a dynamic forward model, motivated by applications in scientific computation and engineering. We specifically consider this extension for a derivative-free optimizer, the ensemble Kalman inversion (EKI). We introduce and justify a new methodology called dynamic-EKI (DEKI), which is a particle-based method with a changing forward operator. We analyze our new method, presenting results related to the control of our particle system through its covariance structure. This analysis includes moment bounds and an ensemble collapse, which are essential for demonstrating a convergence result. We establish convergence in expectation and validate our theoretical findings through experiments with DEKI applied to a 2D Darcy flow partial differential equation.
Pollen foraging mediates exposure to dichotomous stressor syndromes in honey bees
Authors: Wizenberg Sydney B , French Sarah K , Newburn Laura R , Pepinelli Mateus , Conflitti Ida M , Moubony Mashaba , Ritchie Caroline , Jamieson Aidan , Richardson Rodney T , Travas Anthea , Imrit Mohammed Arshad , Chihata Matthew , Higo Heather , Common Julia , Walsh Elizabeth M , Bixby Miriam , Guarna M Marta , Pernal Stephen F , Hoover Shelley E , Currie Robert W , Giovenazzo Pierre , Guzman-Novoa Ernesto , Borges Daniel , Foster Leonard J , Zayed Amro 
Published: October 2024

Abstract
Recent declines in the health of honey bee colonies used for crop pollination pose a considerable threat to global food security. Foraging by honey bee workers represents the primary route of exposure to a plethora of toxins and pathogens known to affect bee health, but it remains unclear how foraging preferences impact colony-level patterns of stressor exposure. Resolving this knowledge gap is crucial for enhancing the health of honey bees and the agricultural systems that rely on them for pollination. To address this, we carried out a national-scale experiment encompassing 456 Canadian honey bee colonies to first characterize pollen foraging preferences in relation to major crops and then explore how foraging behavior influences patterns of stressor exposure. We used a metagenetic approach to quantify honey bee dietary breadth and found that bees display distinct foraging preferences that vary substantially relative to crop type and proximity, and the breadth of foraging interactions can be used to predict the abundance and diversity of stressors a colony is exposed to. Foraging on diverse plant communities was associated with increased exposure to pathogens, while the opposite was associated with increased exposure to xenobiotics. Our work provides the first large-scale empirical evidence that pollen foraging behavior plays an influential role in determining exposure to dichotomous stressor syndromes in honey bees.
Dandelion-shaped strontium-gallium microparticles for the hierarchical stimulation and comprehensive regulation of wound healing
Authors: Ji Minrui , Yuan Zaixin , Ma Hongdong , Feng Xian , Ye Cong , Shi Lei , Chen Xiaodong , Han Fei , Zhao Caichou 
Published: October 2024

Abstract
The management of full-thickness skin injuries continues to pose significant challenges. Currently, there is a dearth of comprehensive dressings capable of integrating all stages of wound healing to spatiotemporally regulate biological processes following full-thickness skin injuries. In this study, we report the synthesis of a dandelion-shaped mesoporous strontium-gallium microparticle (GE@SrTPP) achieved through dopamine-mediated strontium ion biomineralization and self-assembly, followed by functionalization with gallium metal polyphenol networks. As a multifunctional wound dressing, GE@SrTPP can release bioactive ions in a spatiotemporal manner akin to dandelion seeds. During the early stages of wound healing, GE@SrTPP demonstrates rapid and effective hemostatic performance while also exhibiting antibacterial properties. In the inflammatory phase, GE@SrTPP promotes M2 polarization of macrophages, suppresses the expression of pro-inflammatory factors, and decreases oxidative stress in wounds. Subsequently, during the stages of proliferation and tissue remodeling, GE@SrTPP facilitates angiogenesis through the activation of the Hypoxia-inducible factor-1α/vascular endothelial growth factor (HIF-1α/VEGF) pathway. Analogous to the dispersion and rooting of dandelion seeds, the root-like new blood vessels supply essential nutrients for wound healing. Ultimately, in a rat chronic wound model, GE@SrTPP achieved successful full-thickness wound repair. In summary, these dandelion-shaped GE@SrTPP microparticles demonstrate comprehensive regulatory effects in managing full-thickness wounds, making them highly promising materials for clinical applications.
Moving psychedelic-assisted therapies from promising research into routine clinical practice: Lessons from the field of implementation science
Authors: Adams Danielle R , Allen Heidi , Nicol Ginger E , Cabassa Leopoldo J 
Published: October 2024

Abstract
Psychedelics (e.g., 3,4-Methylenedioxymethamphetamine [MDMA], lysergic acid diethylamide [LSD], psilocybin) are molecules that have the potential to produce rapid therapeutic effects when paired with psychotherapy. Randomized clinical trials of psychedelic-assisted psychotherapy (PAT) have shown promising results for post-traumatic stress disorder (PTSD), depression, and substance use disorders. The U.S. Food and Drug Administration has acknowledged the promise of PAT, signaling potential approval of psilocybin-assisted therapy for depression by 2026. Given this timeline, implementation scientists must engage with PAT researchers, policymakers, and practitioners to think critically about bringing these promising new treatments into routine practice settings while maintaining quality and safety. This commentary aims to initiate a dialogue between implementation scientists and PAT researchers and practitioners on addressing these questions with a lens toward equity. Specifically, we discuss how the field of implementation science can support PAT stakeholders to accelerate the translational process from research into practice, focusing specifically on safety-net settings (i.e., Federally Qualified Health Centers and Veterans Affairs health systems) that serve historically marginalized populations. We use the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) Framework to illustrate five critical areas where implementation science can help move PAT from research into real-world practice. For each RE-AIM dimension, we highlight ways the field of implementation science can contribute tools (e.g., implementation strategies), methodologies (e.g., pragmatic hybrid implementation-effectiveness trials), and approaches (community-based participatory research) for establishing the safety, effectiveness, and accessibility of PAT for historically underserved communities.
Travel and mind: a bidirectional analysis of travel participation and cognitive functioning among Americans over 50
Authors: Hua Chenggang , Peng Siyun , Cole Shu 
Published: October 2024

Abstract
The causal relationship between travel participation and cognitive function is complex and unclear in the literature. While some suggest travel protects cognitive health (social causation), others believe cognitive decline restricts travel ability (social withdrawal). This study aims to uncover which hypothesis prevails in this association. Utilizing data from 475 Americans in the Health and Retirement Study (HRS) over a 6-year period from 2006 to 2012, we conducted Cross-Lagged Panel Modeling (CLPM) to examine the reciprocal relationships between travel participation and cognitive function while adjusting for instrumental activities of daily living (IADL), education, race, gender, and age. Our results show a significant positive link between travel in 2006 and cognitive function in 2012 (β = 0.091, p &lt; .05), and a positive predictive effect of cognitive function in 2006 on travel in 2012 (β = 0.116, p &lt; .05). Additionally, factors like education, race, and age significantly affected both cognitive function and travel participation. The study provides initial evidence for the therapeutic potential of travel as a cognitive health intervention, suggesting that engaging in travel may slow cognitive decline 6 years later. Furthermore, lower cognitive function appears to limit travel participation 6 years later. The implications of this study are significant for public health policy, gerontology, and elder care, advocating for the integration of travel into cognitive health programs and highlighting the need for tailored approaches that consider sociodemographic factors, ultimately contributing to the enhancement of quality of life among the U.S. aging population.