bluuebunny/crossref_metadata_2025_split huggingface dataset:
Home Care Patient's Experiences and Medication Burden Related to High‐Risk Medication Use: A Cross‐Sectional Study
Authors: Dumitrescu Irina , Casteels Minne , De Vliegher Kristel , Hubens Charlotte , Dilles Tinne 
Published: December 2024

ABSTRACTBackgroundAge, polypharmacy and comorbidity are examples of known factors that increase the risk of adverse drug reactions in patients. The use of high‐risk medication also entails a heightened risk of harm. There is currently no information available on the home care patients' experiences and medication burden experienced due to their high‐risk medication use and how they manage their medication. Further investigation with regard to this combination is necessary. The patient's experiences and medication burden related to high‐risk medication use can be taken into account when drawing up guidelines and standards of care for healthcare professionals.ObjectivesTo describe home care patients' experiences and medication burden related to high‐risk medication use, more specifically how patients manage their high‐risk medication use, which professional support they receive and which potential adverse drug reactions they experience.DesignA cross‐sectional study of home care patients in Belgium, aged 65 years and older who took at least one high‐risk medication.ResultsIn our population of 106 home care patients, a median use of 8 medications per patient is reported, of which 2 can be considered high‐risk medication. Metformin, insulin and lormetazepam are the most frequently used high‐risk medications. Home care patients believe their medication is important to them, are able to manage the intake and seem to have a high level of therapy adherence. Most patients do not believe their medication intake implies a certain risk. Most patients are supported by a home care nurse for the preparation of their medication. A mean number of 5 symptoms/potential adverse drug reactions is reported out of the 21 potential adverse drug reactions questioned. The potential adverse drug reaction most frequently attributed to medication use was bleeding.ConclusionsPractice guidelines with detailed medicine‐specific protocols are needed to enhance (high‐risk) medication‐related care in an overall high‐risk medication policy. Understanding the patient's risk experiences and communicating with the patient is important to ensure safe medication care but also to identify patients at risk for nonadherence and adverse reactions. The patient's experiences with their medication intake provide rich information for healthcare providers and should therefore be included in patient observations. Home care nurses should closely follow up on the home care patient's medication therapy with respect for the patient's autonomy.
On Global and Decay Solution of Viscous Compressible MHD Equations
Authors: Benabidallah Rachid , Ebobisse François , Azouz Mohamed 
Published: December 2024

ABSTRACTWe consider in an infinite horizontal layer, the equations of the viscous compressible magnetohydrodynamic flows subject to the gravitational force. On the upper and lower planes of the layer, we consider homogeneous Dirichlet conditions on the velocity while a large constant vector field is prescribed on the magnetic field. The existence of the global strong solution with small initial data and its asymptotic behavior as time goes to infinity are established.
Predictors of recent mental health service utilization among firearm‐owning US service members with high levels of psychological distress
Authors: Rodriguez Taylor R. , Bandel Shelby L. , Bond Allison E. , Anestis Michael D. , Anestis Joye C. 
Published: December 2024

AbstractIntroductionService members with mental health difficulties and access to a firearm are at an increased risk for suicide. Mental healthcare providers are well‐positioned to discuss firearms and create safety plans; however, many service members do not seek treatment. This study aims to identify potential sociodemographic predictors of recent mental healthcare utilization among firearm‐owning service members who report past month distress.MethodsThe sample included 268 US military service members. Participants reported whether they attended at least one behavioral health visit in the 3 months prior to participation.ResultsFemales, individuals of a racial background other than Black or White, older individuals, and those who have never been active‐duty were more likely to have attended a session. Additionally, the likelihood of utilization was higher among those who reported past week wish to die and suicidal behaviors in the past year.ConclusionWhile certain service members are less likely to have utilized mental healthcare, findings suggest that those with suicidal ideation and access to a firearm are likely to engage in at least one appointment. As such, providing mental healthcare providers with training and resources for promoting secure firearm storage is an important avenue for suicide prevention.
Information Costs and the Non‐Take‐Up of Social Benefits: A Detailed Exploration of Belgian Social Assistance
Authors: Bolland Manon , Janssens Julie , Goedemé Tim 
Published: December 2024

ABSTRACTIn many European countries, about half of those eligible for means‐tested social benefits, do not receive the benefits to which they are entitled. In the literature, a wide range of factors have been identified that potentially contribute to the non‐take‐up of social benefits. Particular attention has been paid to factors that relate to the claimants themselves, including the experienced or perceived costs associated with claiming benefits and negative attitudes towards claiming benefits. However, the theory on the conditions under which claiming costs matter is still underdeveloped, while the evidence on the relative importance of claiming costs is to a large extent indirect and based on proxy variables. In this paper, we measure individual and household (dis)incentives for taking up social assistance benefits more directly, and evaluate to what extent they are associated with non‐take‐up of social assistance for people at active age in Belgium. To do so, we use a combination of register data and data from the TAKE survey, a new representative survey tailored for studying the determinants of non‐take‐up in Belgium. Combining both sources of information and detailed simulations of eligibility, we show that information costs are much better at predicting non‐receipt of social assistance than process costs and stigma. While attitudes towards the receipt of benefits are of little consequence, optimism about the future seems to matter more, as does the level of material deprivation experienced by the household. We also explore under what conditions information costs matter most. While findings are not very robust, our data suggest that the importance of information costs is mediated by the level optimism about the future and changes in household composition that act as trigger events.
Identification, characterization, and design of plant genome sequences using deep learning
Authors: Wang Zhenye , Yuan Hao , Yan Jianbing , Liu Jianxiao 
Published: December 2024

SUMMARYDue to its excellent performance in processing large amounts of data and capturing complex non‐linear relationships, deep learning has been widely applied in many fields of plant biology. Here we first review the application of deep learning in analyzing genome sequences to predict gene expression, chromatin interactions, and epigenetic features (open chromatin, transcription factor binding sites, and methylation sites) in plants. Then, current motif mining and functional component design and synthesis based on generative adversarial networks, large models, and attention mechanisms are elaborated in detail. The progress of protein structure and function prediction, genomic prediction, and large model applications based on deep learning is also discussed. Finally, this work provides prospects for the future development of deep learning in plants with regard to multiple omics data, algorithm optimization, large language models, sequence design, and intelligent breeding.
A favorable natural variation in CCD7 from orchardgrass confers enhanced tiller number
Authors: Xu Xiaoheng , Liang Yueyang , Feng Guangyan , Li Shunfeng , Yang Zhongfu , Nie Gang , Huang Linkai , Zhang Xinquan 
Published: December 2024

SUMMARYTiller number is a crucial determinant that significantly influences the productivity and reproductive capacity of forage. The regeneration potential, biomass production, and seed yield of perennial forage species are highly reliant on the development of tillering. Strigolactones (SLs) are recently discovered carotenoid‐derived phytohormones that play a crucial role in the regulation of tillering in annual crops. However, the modulation of tiller growth in perennial forage by SLs remains insufficiently investigated. In this study, we identified two alleles of the SLs biosynthesis gene, DgCCD7A and DgCCD7D, which encode CAROTENOID CLEAVAGE DIOXYGENASE 7 (CCD7), from two distinct subspecies of orchardgrass (Dactylis glomerata) exhibiting contrasting tillering phenotype and SLs content. The functionality of the DgCCD7A allele derived from high‐tillering phenotypic orchardgrass was found to be diminished compared to that of DgCCD7D from the low‐tillering type in rescuing the increased branching phenotype of CCD7‐defective mutants in Arabidopsis and rice (Oryza sativa). Notably, the introduction of DgCCD7A in rice resulted in an increase in tiller number without significantly compromising grain yield. Moreover, we demonstrated that the L309P variation in DgCCD7A is a rare natural variant exclusively found in orchardgrass. Our findings revealed that DgCCD7A, a rare favorable natural variation of CCD7 in orchardgrass, holds significant potential for breeding application in improving the plant architecture of perennial forage and crops.
Development of a Highly Conductive Nano-Engineered Geopolymer for Geothermal Applications
Authors: Afridi Muhammad Ali , Wu Yuxing , Khattak Mohammad J. , Karbalaeisaleh Fatemeh 
Published: December 2024

Abstract
Geothermal energy presents a promising opportunity for sustainable and efficient energy production. To maximize the efficiency of geothermal systems, developing advanced materials capable of effectively transferring and withstanding thermal loads is crucial. This study focuses on demonstrating highly conductive nano-engineered geopolymer cement tailored for geothermal applications using prototype laboratory samples. The study included an evaluation of thermal conductivity, shear bond strength, and compressive strength of newly designed geopolymer mixtures as well as the thermal conductivity of large-scale geopolymer samples, with a specific emphasis on their performance in the handling fluid flow for enhanced geothermal systems. The results showed that, compared to the control geopolymer, the developed geopolymer formulations had a lower thermal conductivity performance due to higher air voids in the system. In general, the addition of carbon nanotubes and graphite in geopolymer mixtures reduces the strength and elastic modulus. The thermal conductivity of the large prototype sample cured for 7 days at 49 °C showed better thermal conductivity for the control geopolymer. Conversely, the water flow data reflected better performance for the modified mixtures. Additionally, numerical simulations were developed and validated by the experimental observations for further studies on the effect of geopolymer properties on the performance of geothermal systems.
Data-Driven Depiction of Aging Related Physiological Volume Shrinkage in Brain White Matter: An Image Processing Based Three-Dimensional Micromechanical Model
Authors: Agarwal Mohit , Georgiadis John , Pelegri Assimina A. 
Published: December 2024

Abstract
Aging in the human brain, both in healthy and pathological conditions, leads to significant microstructural alterations, resulting in cognitive decline, with cerebral atrophy being a major contributing factor. This atrophy, characterized by the loss of neurons and glial cells, plays a crucial role in the reduction of brain function. While magnetic resonance imaging (MRI) and magnetic resonance elastography (MRE) provide noninvasive tools to measure brain morphology (volume changes) and regional mechanical properties (tissue stiffness) at the millimeter scale, they are unable to capture cellular-level or micron-scale changes in brain tissue. The challenge is in correlating the mechanical property changes observed at the millimeter scale with the underlying cellular-level micro-architectural alterations. To address this limitation, an ensemble of three-dimensional micromechanical finite element (FE) models was developed, utilizing MRI/MRE data to compute the mechanics of the aging brain with a higher level of detail. Using image processing techniques in Python's NIBABEL library, a mathematical model was constructed to quantify volume fraction (VF) shrinkage in brain white matter (BWM). These models incorporate uniaxial tensile loading and simulate the interactions between axons, myelin, and the glial matrix. Among the three finite element models compared, model type III, which includes both volume fraction changes and shear modulus degeneration, showed a high-order age-related atrophy and brain softening. This approach emphasizes the significant role of computational mechanics in linking macroscopic MRI measurements to cellular-scale changes, enhancing our understanding of brain tissue degeneration.
Ultra-Short-Term Mooring Forces Forecasting for Floating Wind Turbines With Response-Frequency-Informed Deep Learning and On-Site Data
Authors: Kang Yirou , Cheng Zhengshun , Chen Peng , Yang Longzhi , Erfort Gareth , Liu Lei , Hu Zhiqiang 
Published: December 2024

Abstract
Accurate dynamic response forecasting is crucial for the operational monitoring, maintenance, and dynamic control of floating wind turbines (FWT). In this study, an ultra-short-term forecasting model of mooring line tension for a full-size FWT is developed by combining a long short-term memory (LSTM) encoder–decoder network with frequency decomposition (FD), i.e., the LSTM-FD method. After presenting the principles of the LSTM-FD-based ultra-short-term forecasting model, full-scaled measurement data from the Hywind Scotland wind farm are used to validate and demonstrate the accuracy of the proposed model. The result shows that the LSTM-FD method has good consistency between different datasets, and higher accuracy than the LSTM without frequency decomposition. For instance, achieving a 10% enhancement in the accuracy of maximum forecasting for line 1 bridle 1 over a 60-s horizon. More importantly, compared to traditional methods, LSTM-FD improves accuracy by using frequency decomposition to better capture changes in mooring forces of FWT across different frequency ranges. In summary, the proposed method can facilitate more precise and timely maintenance scheduling, reduce operational costs, and enhance the overall safety of FWT operations by mitigating the risk of mooring line failures.
Effect of Blending Ammonia With Natural Gas Hydrocarbons on the Performance of a Heavy-Duty Spark Ignition Engine
Authors: Alvarez Luis F. , Askari Omid , Dumitrescu Cosmin E. 
Published: December 2024

Abstract
Ammonia (NH3) is a promising carbon-free fuel candidate to replace conventional petroleum-based fuels. However, NH3 has low flame speed, low calorific value, narrow flammability limits, and requires high ignition energy. As a result, the use of NH3 in power applications such as internal combustion (IC) engines may require a secondary fuel to promote and sustain the flame as well as hardware engine modifications such as a higher compression ratio (CR) and a high-energy ignition coil. This work investigated the use of a dual-fuel approach involving NH3 and natural gas (NG) components (i.e., methane, propane, and ethane) in a single-cylinder four-stroke heavy-duty compression ignition (CI) engine converted to spark ignition (SI), at an engine speed of 1000 rpm, equivalence ratio of 0.8, and an energy substitution ratio (ESR) of the hydrocarbon fuel up to 0.4. Results showed no penalty on efficiency, as the overall combustion phasing was more optimal as ESR increased. In addition, since all the indicated mean effective pressure (IMEP) values were close to each other for different spark timing (ST), it suggests no need for changing the engine control strategy. COVIMEP showed an increase with ESR, suggesting that the addition of NH3 led to more cycle-to-cycle variations, with propane having the highest COVIMEP. This higher cycle-to-cycle variation for propane–ammonia mixtures was probably coming from a competition between its higher reactivity when compared to the other two hydrocarbons and the effect of different fuel properties on the in-cylinder gas motion.
Haptic Interaction Methods for Freehand Contour Generation on a Refreshable Pin Display
Authors: Harnett MacKenzie , Lacy Amanda K. , Yu Pijuan , Friesen Rebecca F. 
Published: December 2024

Abstract
Emerging surface haptic display technology holds promise for enhancing manual interactions such as contour drawing, a task that requires simultaneous generation and sensing for accurate control of the emerging shape. Existing haptic technology enabling tactile drawing is primarily restricted to niche and expensive products for blind accessibility, and the advantages and optimal strategies of engaging with tactile feedback remain unclear. This study compares three tactile interaction methods for contour drawing using a refreshable pin array: input directly on the pin surface with a finger, input on the surface using a stylus, and input on a peripheral screen while the tactile feedback is felt on the pin surface with one’s other hand. A user study investigating contour generation performance using these three different methods found that individual contour properties had greater impacts on drawing accuracy than interaction methods and that accuracy does not always correlate with user perception of performance across methods. Experimental observations highlight several strategies and hand postures users adopted to leverage each interaction method. These results can serve as a guide to developing robust feedback systems for contour drawing on future iterations of surface haptic interface technology.
Repurposing Supply Chains and Process Planning Across Products Using a Similarity Model Based on Supernetworks
Authors: Nwodu Arriana , Jiang Zhengqian , Dulebenets Maxim , Guo Weihong , Wang Hui 
Published: December 2024

Abstract
Manufacturers should repurpose their supply chain quickly in response to a new demand, which reflects a surge in market needs over a certain period of time. The ability to meet this demand depends on the reconfigurability of manufacturing supply chains across products; however, many industries do not have the quantitative tools for evaluating the reconfigurability. Repurposing manufacturing supply chains across industries (e.g., manufacturers from the auto and health industries) poses a unique challenge since existing suppliers should be reutilized to meet the new demand. This paper establishes a methodology that addresses the supply chain repurposing problem by identifying a new supply chain composed of pieces of existing ones to meet the new demand where cross-product reconfiguration is required. First, the supernetwork framework is used to represent the joint information in the manufacturing supply chain, including assembly task planning and manufacturer–supplier assignment. Next, a supernetwork similarity metric is proposed to assess the reconfigurability of existing supply chains across industries when detailed reconfiguration cost data are unavailable. Guided by the similarity metric, a nonlinear integer programming model is developed for joint decision-making in selecting assembly plans and supply chains to create a product in demand, leveraging existing supply chains of other products. The problem is solved by an evolutionary algorithm customized for the supply chain repurposing problem studied herein. The paper concludes with a case study demonstrating how five manufacturing supply chains that produce different products can be repurposed to generate an intubation ventilator system.
Stage-specific pharmacodynamic chloroquine and pyronaridine action on artemisinin ring-stage resistant Kelch C580Y mutation
Plasmodium falciparum
correlates to hemozoin inhibition process
Authors: Sayeed Abeer , Atkinson Revie , Vekilov Peter G. , Rimer Jeffrey D. , Sullivan David J. 
Published: December 2024

ABSTRACT

The antimalarial quinolines pyronaridine and chloroquine both inhibit hemozoin crystallization, predominately produced by
Plasmodium falciparum
intra-erythrocytic trophozoite stage parasites. Pyronaridine extends activity to ring-stage chloroquine-sensitive parasites, in contrast to chloroquine. Here, we investigated chloroquine and pyronaridine hemozoin inhibition type correlated to stage-specific activity on chloroquine-resistant ring-stage artemisinin sensitive and resistant
P. falciparum
CamWT and CamWT-C580Y parasites. Pyronaridine (2.8 μM) is tenfold more potent at beta-hematin nucleation than chloroquine (40 μM). Both pyronaridine and chloroquine (0.2 and 0.7 μM, respectively) had similar sub-μM inhibition of beta-hematin extension.
P. falciparum
CamWT-C580Y parasites produce smaller width hemozoin crystals which extend less than isogenic CamWT hemozoin. Stage-specific pulse dose pyronaridine and chloroquine on CamWT-C580Y or CamWT isogenic parasites observed 3- to 4-fold higher pyronaridine IC
50
s compared to 10- to 15-fold higher chloroquine on most CamWT-C580Y to CamWT stages. These findings collectively show that hemozoin nucleation inhibition widens stage-specific pyronaridine activity on
P. falciparum
drug-resistant parasites.
A conserved cysteine in the DNA-binding domain of MmuPV1 E2 is required for replication
in vivo
Authors: Gonzalez Jessica , Stoll Kennedy , DeSmet Marsha , Androphy Elliot J. 
Published: December 2024

ABSTRACT

The papillomavirus (PV) E2 protein is highly conserved, consisting of an N-terminal transactivation domain linked to a C-terminal DNA binding and dimerization domain (DBD) by a flexible hinge region. The E2 DBD exhibits a helix-turn-helix structure that dimerizes into a beta barrel prior to binding DNA; the first helix, α1, is responsible for recognition of the palindromic E2 binding site. The DNA recognition helix consists of a tract of basic amino acids with a highly conserved central cysteine residue. Previous mutational analysis studies on this conserved cysteine have found that it is not required for viral replication or DNA binding. To investigate the function of this conserved cysteine
in vitro
and
in vivo
, we generated point mutations in MmuPV1 E2 at cysteine 307. We report here that this cysteine in the DNA recognition helix is required for transient viral replication and transactivation of proximal promoters, but C307 point mutants are still capable of enhancing the activation of distant upstream promoters
in vitro
. MmuPV1 genomes with the C307 mutation failed to produce warts when injected into mice, suggesting that the DNA recognition cysteine is required for viral replication
in vivo
.

IMPORTANCE

Papillomaviruses are the etiological agents of cancers of the oropharynx and anogenital tract. Understanding the mechanisms underlying PV pathogenesis is complicated by the strict species tropism displayed by the virus. The research presented here is significant because it links
in vitro
and
in vivo
models investigating the role of a conserved cysteine in the MmuPV1 E2 protein. This work elucidates the molecular mechanisms that regulate PV transcription and DNA replication and how these contribute to disease progression.