bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical performance comparison between lithium disilicate and hybrid resin nano-ceramic CAD/CAM onlay restorations: a two-year randomized clinical split-mouth study
Authors: Hassan Amr , Hamdi Kareem , Ali Ashraf I. , Al-Zordk Walid , Mahmoud Salah Hasab 
Published: August 2023

AbstractA total of 20 lithium disilicate glass–ceramics (IPS e.max CAD, Ivoclar Vivadent) and 20 resin nano-ceramic (Voco Grandio Blocks) onlay restorations were performed in 20 patients using a split-mouth design to compare the two-year clinical performance of lithium disilicate and resin nano-ceramic onlay restorations. Both restorations were evaluated at baseline, one-year, and two-year clinical follow-ups based on the modified United States Public Health Service (USPHS) criteria. Chi-square and Fisher’s exact tests showed no statistically significant difference between Voco Grandio and IPS e.max ceramic restorations for all evaluated parameters during the different follow-up periods (p > 0.05). Cochrane’s and MC-Nemar’s tests indicated statistically significant differences regarding color match within the Voco Grandio group. They also indicated statistically significant differences in marginal discoloration, marginal adaptation, surface texture, and postoperative hypersensitivity within both ceramic material groups (p < 0.05). Kaplan–Meier curve indicated that the survival rate of both ceramic materials was 90%. After two years of clinical service, IPS e.max CAD and Voco Grandio onlay restorations exhibited similar clinical performance.
Differences in healthcare service utilization between older adults with and without dementia: a cross-sectional study in Shandong, China
Authors: Gao Yu , Sun Jingjie , Zheng Wengui , Cai Weiqin , Gao Qianqian , Lyu Juncheng , Zheng Xiaomeng , Gao Runguo , Ji Lihong , Jing Qi 
Published: August 2023

Abstract

Aim
Dementia is characterized by a decline in cognitive functioning and is the main cause of disability, mortality, and care dependence among older adults. This study compared healthcare utilization in older adults with and without dementia and explored factors influencing service use in the former.

Subject and methods
A total of 8847 seniors (≥ 60 years) were chosen from the Health Service Survey of Shandong Province conducted in 2018. The chi-square test was used for baseline characteristics and healthcare utilization for older adults with and without dementia. Multivariate logistic regression analysed service utilization factors.

Results
Of the respondents, 261 (3.0%) had dementia. The proportions of respondents who used outpatient care and inpatient care were 40.6% and 76.9%, respectively. The rates of outpatient and inpatient care use among seniors with dementia were slightly higher than those among seniors without dementia (44.8% vs 40.5% and 80.8% vs 76.7%, respectively). Older adults with dementia who were married and had experienced non-communicable diseases within the past 6 months were less likely to use outpatient care. No factors associated with the utilization of inpatient care were found.

Conclusion
Health publicity and a combination of community care and medical assistance targeting older adults with dementia is essential to increase healthcare service utilization.
Machine and deep learning for longitudinal biomedical data: a review of methods and applications
Authors: Cascarano Anna , Mur-Petit Jordi , Hernández-González Jerónimo , Camacho Marina , de Toro Eadie Nina , Gkontra Polyxeni , Chadeau-Hyam Marc , Vitrià Jordi , Lekadir Karim 
Published: August 2023

AbstractExploiting existing longitudinal data cohorts can bring enormous benefits to the medical field, as many diseases have a complex and multi-factorial time-course, and start to develop long before symptoms appear. With the increasing healthcare digitisation, the application of machine learning techniques for longitudinal biomedical data may enable the development of new tools for assisting clinicians in their day-to-day medical practice, such as for early diagnosis, risk prediction, treatment planning and prognosis estimation. However, due to the heterogeneity and complexity of time-varying data sets, the development of suitable machine learning models introduces major challenges for data scientists as well as for clinical researchers. This paper provides a comprehensive and critical review of recent developments and applications in machine learning for longitudinal biomedical data. Although the paper provides a discussion of clustering methods, its primary focus is on the prediction of static outcomes, defined as the value of the event of interest at a given instant in time, using longitudinal features, which has emerged as the most commonly employed approach in healthcare applications. First, the main approaches and algorithms for building longitudinal machine learning models are presented in detail, including their technical implementations, strengths and limitations. Subsequently, most recent biomedical and clinical applications are reviewed and discussed, showing promising results in a wide range of medical specialties. Lastly, we discuss current challenges and consider future directions in the field to enhance the development of machine learning tools from longitudinal biomedical data.
Hydrogen Jet Flame Control by Global Mode
Authors: Wawrzak Agnieszka , Wawrzak Karol , Boguslawski Andrzej , Tyliszczak Artur , Geurts Bernard J. 
Published: August 2023

AbstractIn this study, we employ the potential of the global instability phenomenon to qualitatively alter the dynamics of a turbulent flame. We adopt the large eddy simulation method and an in-house numerical code. For the combustion process we do not include explicit sub-filter modeling. The accuracy of this ‘no combustion model’ approach is verified by comparison against the Eulerian Stochastic Fields method. We include several test cases representing different flow regimes, including convective and absolutely unstable conditions. The focus is on a counter-current configuration, which includes a central jet nozzle supplying hydrogen fuel surrounded by a somewhat larger co-axial nozzle sucking fluid from the surroundings of the central nozzle. The suction generates a counterflow where global instability is found to be triggered if sufficiently strong suction is applied. The critical suction value $$I_{GI}$$

I

GI

is larger if the level of the inlet turbulence intensity $$T_i$$

T
i

is increased. Depending on the suction strength, the flame quickly stabilizes, either as being attached to the nozzle or as a lifted flame hovering at a height of a few fuel nozzle diameters. Additionally, it is shown that increasing $$T_i$$

T
i

can assist an initially lifted flame to attach to the nozzle. Flame lifting is the result of self-induced strong toroidal vortices that lead to leaner combustion conditions of the mixture upstream of the flame base. The toroidal vortices prevent upstream flame propagation and lead to a very intense mixing process that gives rise to the lifted reaction zone. This ensures almost complete fuel combustion at a short distance from the inlet. On the contrary, when the suction strength is below $$I_{GI}$$

I

GI

, the flames are attached and a high temperature near the fuel inlet causes an increase in molecular viscosity. This tends to laminarize the mixing layer between the fuel and oxidizer. The flames appear as if they were laminar and non-premixed over a long distance from the inlet. In such a situation, a significant amount of fuel remains unburned.
Soil nitrous oxide and methane fluxes from a land-use change transition of primary forest to oil palm in an Indonesian peatland
Authors: Swails Erin , Drewer Julia , Hartill Jodie , Comeau Louis-Pierre , Verchot Louis V. , Hergoualc’h Kristell A. 
Published: August 2023

AbstractDespite the documented increase in greenhouse gas (GHG) emissions from Southeast Asian peat swamp forest degradation and conversion to oil palm over recent decades, reliable estimates of emissions of nitrous oxide (N2O) and methane (CH4) are lacking. We measured soil fluxes of N2O and CH4 and their environmental controls along a peatland transition from primary forest (PF) to degraded drained forest (DF) to oil palm plantation (OP) over 18 months in Jambi, Sumatra, Indonesia. Sampling was conducted monthly at all sites and more intensively following two fertilization events in the OP. Mean annual emissions of N2O (kg N ha−1 yr−1) were 1.7 ± 0.2 for the PF, 2.3 ± 0.2 for the DF and for the OP 8.1 ± 0.8 without drainage canals (DC) and 7.7 ± 0.7 including DC. High N2O emissions in the OP were driven by peat decomposition, not by N fertilizer addition. Mean CH4 annual fluxes (kg C ha−1 yr−1) were 8.2 ± 1.9 for the PF, 1.9 ± 0.4 for the DF, and 1.6 ± 0.3 for the OP with DC and 1.1 ± 0.2 without. Considering their 20-year global warming potentials (GWP), the combined non-CO2 GHG emission (Mg CO2-equivalent ha−1 yr−1) was 3.3 ± 0.6 for the PF and 1.6 ± 0.2 for the DF. The emission in the OP (3.8 ± 0.3 with or without DC) was similar to the PF because reductions in CH4 emissions offset N2O increases. However, considering 100-year GWP, the combined non-CO2 GHG emission was larger in the OP (3.4 ± 0.3 with DC and 3.5 ± 0.3 without) compared to both the PF and the DF (1.5 ± 0.2 and 1.2 ± 0.1, respectively). The increase in peat N2O emissions associated with the land-use change transition from primary forest to oil palm plantation at our sites provides further evidence of the urgent need to protect tropical peat swamp forests from drainage and conversion.
Machine learning instructed microfluidic synthesis of curcumin-loaded liposomes
Authors: Di Francesco Valentina , Boso Daniela P. , Moore Thomas L. , Schrefler Bernhard A. , Decuzzi Paolo 
Published: August 2023

AbstractThe association of machine learning (ML) tools with the synthesis of nanoparticles has the potential to streamline the development of more efficient and effective nanomedicines. The continuous-flow synthesis of nanoparticles via microfluidics represents an ideal playground for ML tools, where multiple engineering parameters – flow rates and mixing configurations, type and concentrations of the reagents – contribute in a non-trivial fashion to determine the resultant morphological and pharmacological attributes of nanomedicines. Here we present the application of ML models towards the microfluidic-based synthesis of liposomes loaded with a model hydrophobic therapeutic agent, curcumin. After generating over 200 different liposome configurations by systematically modulating flow rates, lipid concentrations, organic:water mixing volume ratios, support-vector machine models and feed-forward artificial neural networks were trained to predict, respectively, the liposome dispersity/stability and size. This work presents an initial step towards the application and cultivation of ML models to instruct the microfluidic formulation of nanoparticles.
Effect of neighborhood deprivation index on breast cancer survival in the United States
Authors: Roy Arya Mariam , George Anthony , Attwood Kristopher , Alaklabi Sabah , Patel Archit , Omilian Angela R. , Yao Song , Gandhi Shipra 
Published: August 2023

Abstract
Purpose
To analyze the association between the Neighborhood Deprivation Index (NDI) and clinical outcomes of locoregional breast cancer (BC).

Methods
Surveillance, Epidemiology and End Results (SEER) database is queried to evaluate overall survival (OS) and disease-specific survival (DSS) of early- stage BC patients diagnosed between 2010 and 2016. Cox multivariate regression was performed to measure the association between NDI (Quintiles corresponding to most deprivation (Q1), above average deprivation (Q2), average deprivation (Q3), below average deprivation (Q4), least deprivation (Q5)) and OS/DSS.

Results
Of the 88,572 locoregional BC patients, 27.4% (n = 24,307) were in the Q1 quintile, 26.5% (n = 23,447) were in the Q3 quintile, 17% (n = 15,035) were in the Q2 quintile, 13.5% (n = 11,945) were in the Q4 quintile, and 15.6% (n = 13,838) were in the Q5 quintile. There was a predominance of racial minorities in the Q1 and Q2 quintiles with Black women being 13–15% and Hispanic women being 15% compared to only 8% Black women and 6% Hispanic women in the Q5 quintile (p < 0.001). In multivariate analysis, in the overall cohort, those who live in Q2 and Q1 quintile have inferior OS and DSS compared to those who live in Q5 quintile (OS:- Q2: Hazard Ratio (HR) 1.28, Q1: HR 1.2; DSS:- Q2: HR 1.33, Q1: HR 1.25, all p < 0.001).

Conclusion
Locoregional BC patients from areas with worse NDI have poor OS and DSS. Investments to improve the socioeconomic status of areas with high deprivation may help to reduce healthcare disparities and improve breast cancer outcomes.
Surrogate-assisted distributed swarm optimisation for computationally expensive geoscientific models
Authors: Chandra Rohitash , Sharma Yash Vardhan 
Published: August 2023

AbstractEvolutionary algorithms provide gradient-free optimisation which is beneficial for models that have difficulty in obtaining gradients; for instance, geoscientific landscape evolution models. However, such models are at times computationally expensive and even distributed swarm-based optimisation with parallel computing struggle. We can incorporate efficient strategies such as surrogate-assisted optimisation to address the challenges; however, implementing inter-process communication for surrogate-based model training is difficult. In this paper, we implement surrogate-based estimation of fitness evaluation in distributed swarm optimisation over a parallel computing architecture. We first test the framework on a set of benchmark optimisation problems and then apply to a geoscientifc model that features landscape evolution model. Our results demonstrate very promising results for benchmark functions and the Badlands landscape evolution model. We obtain a reduction in computationally time while retaining optimisation solution accuracy through the use of surrogates in a parallel computing environment. The major contribution of the paper is in the application of surrogate-based optimisation for geoscientific models which can in the future help in better understanding of paleoclimate and geomorphology.
Predicting Gun Violence in Stockholm, Sweden, Using Sociodemographics, Crime and Drug Market Locations
Authors: Magnusson Mia-Maria 
Published: August 2023

AbstractThe well-being of neighbourhoods in terms of socioeconomic conditions constitutes an important element in analyses focused on the explanation of crime trends and public safety. Recent developments in Sweden concerning gun violence and open drug scenes are worrying and the police are under a great deal of pressure to resolve the situation in many neighbourhoods, which is in turn affecting Swedish society as a whole. This study focuses on micro areas in terms of sociodemographic factors and the presence of drug markets and gun violence. The aim is to explore the relationship between these factors and what characterises areas that are experiencing the greatest difficulties. The study develops an index for the prediction of gun violence in micro areas, in this study portrayed by vector grids. The findings show an overlap between gun violence and drug markets and that micro areas in that overlap share harsh sociodemographic conditions. The study produces an index indicating the probability that a grid cell would experience gun violence. The index was then validated using recent gun incidents, and was found to have high accuracy. The resulting grids constitute a suitable target for resource allocation by police and other actors. This could facilitate a more accurate and precise focus for measures to prevent areas from becoming—or to disrupt already existing—hot spots for gun violence.
Using AI and BES/MFC to decrease the prediction time of BOD5 measurement
Authors: Medvedev Ivan , Kornaukhova Mariya , Galazis Christoforos , Lóránt Bálint , Tardy Gábor Márk , Losev Alexander , Goryanin Igor 
Published: August 2023

AbstractBiochemical oxygen demand (BOD) is one of the most important water/wastewater quality parameters. BOD5 is the amount of oxygen consumed in 5 days by microorganisms that oxidize biodegradable organic materials in an aerobic biochemical manner. The primary objective of this research is to apply microbial fuel cells (MFCs) to reduce the time requirement of BOD5 measurements. An artificial neural network (ANN) has been created, and the predictions we obtained for BOD5 measurements were carried out within 6–24 h with an average error of 7%. The outcomes demonstrated the viability of our AI MFC/BES BOD5 sensor in real-life scenarios.
Fluid-flow effects in the reactive decontamination of porous materials driven by chemical swelling or contraction
Authors: Geng Y. , Kamilova A. A. , Luckins E. K. 
Published: August 2023

AbstractFollowing the release of a chemical warfare agent, it is crucial for public health that the affected environment is entirely decontaminated. If the agent has seeped into a porous building material, the decontamination is achieved by applying a cleanser solution to the surface of the porous material, and allowing it to react in, neutralising the agent. Typically, the agent and cleanser solution are immiscible fluids and so the reaction occurs at the fluid–fluid interfaces within the pores. Previous studies have shown that the rate of decontamination of the porous material can depend on both the chemical reaction rate and the transport of cleanser to the reacting interface. These studies have all assumed that the two fluids have the same densities, so that diffusion is the only cleanser-transport mechanism. In this paper, we relax this assumption and investigate the effect of a fluid flow—generated by a change in density of the material (a swelling, or contraction) during the chemical reaction—on the decontamination process. This flow of fluid results in advection as well as diffusion of chemicals. Buoyancy effects are neglected. In particular, we show that when the agent is more dense than the reaction product, the decontamination process is slower, due to the adverse advection effect.
Sustainability and specifics of fire water sources in new climatic conditions using the example of the Czech Republic
Authors: Kavan Štěpán , Kročová Šárka 
Published: August 2023

AbstractSufficient fire water for fire protection of an area is of fundamental importance in the ​​security of the state and its infrastructure. Fires cannot be completely prevented, but the consequent damages can be minimized provided that there are enough extinguishing agents to eliminate them. The main and most important current and future extinguishing agent is water. Due to the fact that climate change is ongoing, it can be assumed that many existing natural and multipurpose sources of fire water may not meet the capacity requirements for firefighting, or they will not be available at all. The aim of the scientific approach is to evaluate and specify the availability of fire water in the new climatic conditions using the example of the Czech Republic. Another aim of the article is to characterize the possible shortage of fire water and to propose means by which the maximum effect can be achieved with minimum investment costs, and to ensure the long-term sustainability of natural and multipurpose fire water sources. The analysis of strengths and weaknesses, opportunities and threats was used for the evaluation of the availability of fire water in new climatic conditions. It arises from the results of the article and its broader concept that, despite the current satisfactory situation in fire protection in the Czech Republic regarding fire water, the risks of its shortage are increasing when the climate changes significantly. The lack of fire water will not be nationwide, but most likely only regional.
Genetic variation, correlation, and association mapping of seed yield and its component traits in sesame
Authors: Wang Cuiying , Niu Jiaojiao , Miao Hongmei , Li Chun , Duan Yinghui , Ju Ming , Cao Hengchun , Wei Libin , Wang Huili , Zhang Haiyang 
Published: August 2023

AbstractSesame is an important and specific oilseed crop with high quality. Here, we systematically investigated the relationships between plant seed yield (PSY) and nine related traits in 369 sesame core accessions under five environments. The PSY and related traits had general heritability ranging from 14% for PSY to 72% for height to the first capsule (FCH) and final flowering stage (FFS). Correlation analysis suggested that seven yield-related traits, including capsule number per plant (CNP, r = 0.67), capsule stem length (CSL, 0.56), thousand-seed weight (TSW, 0.26), plant height (PH, 0.24), FFS (0.17), initial flowering stage (IFS, − 0.16) and FCH (− 0.14) were the key factors associated with seed yield in sesame (P < 0.01). For the uniculm and branching groups, CNP, CSL, and TSW were the common key factors. Path analysis showed similar direct effects of these key factors on PSY. Association mapping identified 13 simple sequence repeat (SSR) markers significantly associated with the nine seed yield-related traits (P < 0.001). Among these, three SSR markers were repeatedly detected in two environments. Marker Hs635 was associated with the seed number per capsule (SNC). Hs345 was associated with the CNP. Hs618 was associated with the IFS in uniculm accessions. These results provide insights into the traits that influence PSY and their genetics in sesame.
Therapeutic Competence in Parenting Programs: A Focus Group Study
Authors: Lundström Susanna , Lundström Markus 
Published: August 2023

AbstractWhile research on parenting programs typically focuses on program-specific evaluations, this article considers therapeutic competence as a transversal feature across different programs. It draws empirically on focus group interviews with practitioners of two separate parenting programs in Sweden: Circle of Security (COS-P) and Communication Method (COMET). The qualitative data analysis shows how the practitioners of both programs used their therapeutic competence to tailor the program manuals for each parent group; they combined the techniques of positive reinforcement and intentional self-disclosure with an attuned flexibility that was enabled by mentalization. The article concludes that therapeutic competence is a crucial aspect of parenting programs that needs further attention from scholars and practitioners alike.
Long-Term Disability Outcomes for Migrants (and Non-migrants) 12 Years Post-injury: Results from the Prospective Outcomes of Injury Study in New Zealand
Authors: Anglemyer A. , Wyeth E. H. , Derrett S. 
Published: August 2023

AbstractTo understand, and identify predictors of, long-term post-injury (i.e. 12 years post-injury) disability outcomes for migrants and non-migrants. This 12-year longitudinal study followed participants with entitlement claim injuries registered with New Zealand’s universal no-fault injury insurer between 2007 and 2009. Information was collected about migrant status, other sociodemographic, health and disability characteristics, and injury characteristics. Disability outcome information was collected 12 years later. Of 1543 people interviewed 12 years post-injury, 1497 had disability and migrant status data available; 20% were migrants (n = 301). Migrants reporting inadequate pre-injury household income or those who perceived their injury as a threat to life at the time of injury were more likely to experience disability 12 years post-injury (aRR 2.08; 95% CI 1.09–4.03, aRR 2.93; 95%CI 1.17–6.69, respectively). Hospitalised injured migrants were significantly less likely to have long-term disability (aRR 0.18; 95%CI 0.04–0.55) than those not hospitalised. We found sociodemographic and injury-related characteristics were independently associated with long-term disability among migrants. We highlight that some characteristics, ascertained early in the injury pathway, predict risk of long-term disability. Early post-injury interventions focused on improving disability outcomes for migrants may also have long-term impacts.