bluuebunny/crossref_metadata_2025_split huggingface dataset:
Innovative synthesis technique for high-performance dielectric resonator antennas: laser-induced shockwave sintering of potassium sodium niobate (KNN)
Authors: Zhang Hao , Joo Yun Hwan , Wang Yue , Yi Tongqiang , Sung Tae Hyun 
Published: March 2024

Abstract
This study explored the synthesis and sintering of potassium sodium niobate (KNN) nanoparticles, emphasizing morphology, crystal structure, and sintering methods. The as-synthesized KNN nanoparticles exhibited a spherical morphology below 200 nm. Solid state sintering (SSS) and laser-induced shockwave sintering (LISWS) were compared, with LISWS producing denser microstructures and improved grain growth. Raman spectroscopy and x-ray diffraction confirmed KNN perovskite structure, with LISWS demonstrating higher purity. High-resolution x-ray photoelectron spectroscopy spectra indicated increased binding energies in LISWS, reflecting enhanced density and crystallinity. Dielectric and loss tangent analyses showed temperature-dependent behavior, with LISWS-3 exhibiting superior properties. Antenna performance assessments revealed LISWS-3’s improved directivity and reduced sidelobe radiation compared to SSS, attributed to its denser microstructure. Overall, LISWS proved advantageous for enhancing KNN ceramics, particularly in antenna applications.
Integration of statistical and simulation analyses for ternary hybrid nanofluid over a moving surface with melting heat transfer
Authors: Rehman Aqeel ur , Abbas Zaheer , Hussain Zawar , Hasnain Jafar , Asma Mir 
Published: March 2024

Abstract
In industrial and engineering fields including lamination, melt-spinning, continuous casting, and fiber spinning, the flow caused by a continually moving surface is significant. Therefore, the problem of ternary hybrid nanofluid flow over a moving surface is studied. This study explores the stability and statistical analyses of the magnetohydrodynamics (MHD) forced flow of the ternary hybrid nanofluid with melting heat transfer phenomena. The impacts of viscous dissipation, Joule heating, and thermal radiation are also included in the flow. Different fluids including ternary hybrid nanofluid, hybrid nanofluids, and nanofluids with base fluid ethylene glycol (EG) are examined and compared, where magnetite (Fe3O4) and silica (SiO2) are taken as the magnetic nanomaterials while silver (Ag) is chosen as the nonmagnetic nanomaterial. The skin friction coefficient and the local Nusselt number are estimated through regression analysis. By employing similarity transformations, the governing partial differential equations are converted into non-linear ordinary differential equations. Then, the least square method is applied to solve the equations analytically. Dual solutions are established in a particular range of moving parameter λ. Due to this, a stability test is implemented to find the stable solution by using the bvp4c function in MATLAB software. It is found that the first solution is the stable one while the second is unstable. The use of ternary hybrid nanomaterials improves the heat transport rate. The increasing values of the Eckert number enlarge the heat passage. The fluid velocity and temperature profiles for nonmagnetic nanomaterials are higher than that of magnetic nanomaterials. The uniqueness and originality of this study stems from the fact that, to the best of the authors’ knowledge, it is the first to use this combination technique.
Laser-induced transverse voltage effect in c-axis inclined La
x
Sr1−x
TiO3 thin films prepared by MOCVD
Authors: Xie Tian , Tao Bowan , Zhao Ruipeng , Zhang Tong , Chen Xi , Yang Kai , Li Zhenzhe , Xia Yudong , Tian Hongbo , Ming Guoliang 
Published: March 2024

Abstract
Light and thermal detectors based on the laser-induced transverse voltage (LITV) effect have garnered significant interest for their rapid and broad spectral response. In this study, we prepared the La-doped SrTiO3 (STO) epitaxial thin films on the 12° inclined single crystal LaAlO3 (LAO) (100) substrates using our home-designed metal–organic chemical vapor deposition system. Under the illumination of a 248 nm laser, the LITV signals of La
x
Sr1−x
TiO3 films were observed and showed dependence on the La doping level, which can be explained by the changes in the light absorption coefficient, thermal conductivity, and optical penetration depth. The optimized LITV signal was observed with a peak voltage of 23.25 V and a decay time of 106 ns under the laser power density of 1.0 mJ mm−2. The high peak voltage and fast response time of La
x
Sr1−x
TiO3 show great potential in the field of light and thermal detection.
Circumventing the ammonia-related growth suppression for obtaining regular GaN nanowires by HVPE
Authors: Semlali Elias , Avit Geoffrey , André Yamina , Gil Evelyne , Moskalenko Andriy , Shields Philip , Dubrovskii Vladimir G , Cattoni Andrea , Harmand Jean-Christophe , Trassoudaine Agnès 
Published: March 2024

Abstract
Selective area growth by hydride vapor phase epitaxy of GaN nanostructures with different shapes was investigated versus the deposition conditions including temperature and ammonia flux. Growth experiments were carried out on templates of GaN on sapphire masked with SiN
x
. We discuss two occurrences related to axial and radial growth of GaN nanowires. A growth suppression phenomenon was observed under certain conditions, which was circumvented by applying the cyclic growth mode. A theoretical model involving inhibiting species was developed to understand the growth suppression phenomenon on the masked substrates. Various morphologies of GaN nanocrystals were obtained by controlling the competition between the growth and blocking mechanisms as a function of the temperature and vapor phase composition. The optimal growth conditions were revealed for obtaining regular arrays of ∼5 μm long GaN nanowires.
Nano antenna-assisted quantum dots emission into high-index planar waveguide
Authors: Yu X , Weeber J-C , Markey L , Arocas J , Bouhelier A , Leray A , Colas des Francs G 
Published: March 2024

Abstract
Integrated quantum photonic circuits require the efficient coupling of photon sources to photonic waveguides. Hybrid plasmonic/photonic platforms are a promising approach, taking advantage of both plasmon modal confinement for efficient coupling to a nearby emitter and photonic circuitry for optical data transfer and processing. In this work, we established directional quantum dot (QD) emission coupling to a planar TiO2 waveguide assisted by a Yagi-Uda antenna. Antenna on waveguide is first designed by scaling radio frequency dimensions to nano-optics, taking into account the hybrid plasmonic/photonic platform. Design is then optimized by full numerical simulations. We fabricate the antenna on a TiO2 planar waveguide and deposit a few QDs close to the Yagi-Uda antenna. The optical characterization shows clear directional coupling originating from antenna effect. We estimate the coupling efficiency and directivity of the light emitted into the waveguide.
Activation of polyimide by oxygen plasma for atomic layer deposition of highly compact titanium oxide coating
Authors: Yan Chi , Tong Hua , Liu Cui , Ye Xiaojun , Yuan Xiao , Xu Jiahui , Li Hongbo 
Published: March 2024

Abstract
Titanium oxide (TiO2) coated polyimide has broad application prospects under extreme conditions. In order to obtain a high-quality ultra-thin TiO2 coating on polyimide by atomic layer deposition (ALD), the polyimide was activated by in situ oxygen plasma. It was found that a large number of polar oxygen functional groups, such as carboxyl, were generated on the surface of the activated polyimide, which can significantly promote the preparation of TiO2 coating by ALD. The nucleation and growth of TiO2 were studied by x-ray photoelectron spectroscopy monitoring and scanning electron microscopy observation. On the polyimide activated by oxygen plasma, the size of TiO2 nuclei decreased and the quantity of TiO2 nuclei increased, resulting in the growth of a highly uniform and dense TiO2 coating. This coating exhibited excellent resistance to atomic oxygen. When exposed to 3.5 × 1021 atom cm−2 atomic oxygen flux, the erosion yield of the polyimide coated with 100 ALD cycles of TiO2 was as low as 3.0 × 10−25 cm3/atom, which is one order less than that of the standard POLYIMIDE-ref Kapton® film.
Bark beetle-driven community and biogeochemical impacts in forest ecosystems: a review
Authors: Siegert Courtney , Clay Natalie , Pace Kimberlyn , Vissa Sneha , Hofstetter Richard W , Leverón Oscar , Riggins John J 
Published: March 2024

Abstract
Bark beetles are a principal source of tree mortality in conifer forests, with beetle distribution and beetle-associated tree mortality increasing in frequency and extent. While bark beetles are associated with large-scale outbreaks that affect landscape structure, function, and wood quality, they are also drivers of important ecological processes that modify forest ecosystems. Bark beetle activity may affect biogeochemistry and forest decomposition processes by mediating microbial and detrital communities and by facilitating the turnover of deadwood. The turnover of deadwood in bark beetle-attacked forests has important implications for forest biogeochemical cycling, as dead wood releases CO2 into the atmosphere and carbon, nitrogen, and other nutrients into surrounding soils. However, our understanding of how initial physical, chemical, and biotic changes to bark beetle-attacked trees affect the succession of detrital organisms and decomposition of beetle-generated deadwood remains poor. Furthermore, the relationship between woody decomposition and landscape-level changes in biogeochemical processes in forest ecosystems following bark beetle activity is not well unified. This review article bridges this divide and provides an interdisciplinary perspective on tree mortality, ecological succession, and woody decomposition mediated by bark beetles.
Pain trajectories and their associations with cognition among older adults: a 10-year cohort study from network perspective
Authors: Sun He-Li , Bai Wei , Chen Pan , Zhang Ling , Smith Robert D , Su Zhaohui , Cheung Teris , Ungvari Gabor S , Ng Chee H , Zhang Qinge , Xiang Yu-Tao 
Published: March 2024

Abstract

Background
Few studies have examined the associations between pain trajectories and cognitive function in older adults. This study explored the associations between pain trajectories and different cognitive domains in older adults from a network perspective.

Methods
Data on pain trajectories were derived from the Health and Retirement Study between 2010 and 2020 using latent class growth analyses. Measurements of key cognition domains, including memory, attention, calculation, orientation and language, were included. Linear regression and network analysis were performed to evaluate the associations between different pain trajectories and cognition.

Results
A total of 9,551 older adults were included in this study and three trajectories of pain were identified. After controlling for the covariates, persistent severe pain trajectory was associated with poorer overall cognition, memory and calculation ability when compared to mild or non-persistent pain trajectory. In the pain and cognition network model, memory (expected influence (EI) = 0.62), language (EI = 0.58) and calculation (EI = 0.41) were the most central domains.

Conclusions
Pain trajectories appeared stable over time among older adults in this study. Severity of persistent pain was an important risk factor for poor cognition, especially in relation to memory and calculation domains. Interventions targeting memory, language and calculation domains might be useful in addressing cognitive decline in older adults with persistent pain.
Development and external validation of the eFalls tool: a multivariable prediction model for the risk of ED attendance or hospitalisation with a fall or fracture in older adults
Authors: Archer Lucinda , Relton Samuel D , Akbari Ashley , Best Kate , Bucknall Milica , Conroy Simon , Hattle Miriam , Hollinghurst Joe , Humphrey Sara , Lyons Ronan A , Richards Suzanne , Walters Kate , West Robert , van der Windt Danielle , Riley Richard D , Clegg Andrew ,   The eFI+ investigators
Published: March 2024

Abstract

Background
Falls are common in older adults and can devastate personal independence through injury such as fracture and fear of future falls. Methods to identify people for falls prevention interventions are currently limited, with high risks of bias in published prediction models. We have developed and externally validated the eFalls prediction model using routinely collected primary care electronic health records (EHR) to predict risk of emergency department attendance/hospitalisation with fall or fracture within 1 year.

Methods
Data comprised two independent, retrospective cohorts of adults aged ≥65 years: the population of Wales, from the Secure Anonymised Information Linkage Databank (model development); the population of Bradford and Airedale, England, from Connected Bradford (external validation). Predictors included electronic frailty index components, supplemented with variables informed by literature reviews and clinical expertise. Fall/fracture risk was modelled using multivariable logistic regression with a Least Absolute Shrinkage and Selection Operator penalty. Predictive performance was assessed through calibration, discrimination and clinical utility. Apparent, internal–external cross-validation and external validation performance were assessed across general practices and in clinically relevant subgroups.

Results
The model’s discrimination performance (c-statistic) was 0.72 (95% confidence interval, CI: 0.68 to 0.76) on internal–external cross-validation and 0.82 (95% CI: 0.80 to 0.83) on external validation. Calibration was variable across practices, with some over-prediction in the validation population (calibration-in-the-large, −0.87; 95% CI: −0.96 to −0.78). Clinical utility on external validation was improved after recalibration.

Conclusion
The eFalls prediction model shows good performance and could support proactive stratification for falls prevention services if appropriately embedded into primary care EHR systems.
Altered Trajectories: Considering the Long-Term Impact of Educational Disruption during the COVID-19 Pandemic on Neurodevelopment and a Call to Action for Neuropsychology
Authors: Colvin Mary K , Reesman Jennifer , Glen Tannahill 
Published: March 2024

Abstract

Objective
The COVID-19 pandemic resulted in educational disruption of historic breadth and duration. The impact of school closures and remote learning have been evaluated in recent studies and reflect critical data for neuropsychologists who routinely assess brain development as it relates to diagnosis, recommendations, and informing public policy.

Method
Pre-pandemic and contemporaneous literature was summarized, including data on educational disruption and child and adolescent mental health challenges reported during the pandemic, and research on the impact of stress, social isolation, educational achievement, and other factors on brain development during critical developmental windows.

Results
Studies indicate that prolonged educational disruption has resulted in attenuated learning gains, most remarkably for those already at risk for educational disparities. Studies have shown increased mental health challenges for youth during the pandemic, with higher rates of mood and eating disorders, and suicidal ideation. Given that some skills develop optimally within specific time periods, pandemic-related disruption has likely contributed to altered developmental trajectories.

Conclusion
Trajectory of neuropsychological development of children and adolescents, especially marginalized students, may be affected by effects on learning and mental health due to prolonged educational disruption and psychological stressors. Evaluation and treatment may be delayed due to backlog and increased demand. Clinical neuropsychological practice recommendations are presented with a call to action for the field in moving forward flexibly to increase access to evaluation services.
Compensatory Strategy Intervention: What Older Patients Want and Why
Authors: Goldstein Allyson , Commissariat Persis V , Sullivan Kelli L , Hallowell Emily S , Davis Jennifer D , Margolis Seth A 
Published: March 2024

Abstract

Objective
Compensatory strategies can improve performance of instrumental activities of daily living in people with cognitive impairment. This study investigated patient interest in compensatory strategy interventions and preference for various intervention formats.

Methods
Semi-structured qualitative interviews with 38 older adults with cognitive impairment queried motivation to improve strategy use and interest in intervention formats/delivery methods. Two coders used thematic analysis to determine rates of interest in each intervention type and explore patient-reported barriers and facilitators to motivation and intervention models.

Results
Most of the samples reported motivation to enhance compensatory strategy use. Degree of motivation was driven by current experiences with strategy use, perceived benefit of potential changes, intrinsic desire to improve life and self, and current perceived need. The vast majority were interested in hour-long, multi-session, instructor-led interventions. Just over half of the sample was interested in a self-directed virtual program, and just under half was interested in involving family/friends. Facilitators and barriers to interest in intervention formats and delivery methods varied based on participants’ previous experiences, preferred learning style, content, and time commitment of the intervention, and perceived current need for intervention. One-fifth of the sample expressed no interest in any intervention type, though they expressed openness to assistance in the future as needed.

Conclusions
Older adults with cognitive impairment are generally motivated to enhance their compensatory strategy use. Clinicians/researchers designing compensatory strategy interventions should consider instructor-led formats, present individualized benefits of interventions, and demonstrate the benefits of both preventative and remedial intervention to optimize patient engagement.
Understanding large scale sequencing datasets through changes to protein folding
Authors: Shorthouse David , Lister Harris , Freeman Gemma S , Hall Benjamin A 
Published: March 2024

Abstract
The expansion of high-quality, low-cost sequencing has created an enormous opportunity to understand how genetic variants alter cellular behaviour in disease. The high diversity of mutations observed has however drawn a spotlight onto the need for predictive modelling of mutational effects on phenotype from variants of uncertain significance. This is particularly important in the clinic due to the potential value in guiding clinical diagnosis and patient treatment. Recent computational modelling has highlighted the importance of mutation induced protein misfolding as a common mechanism for loss of protein or domain function, aided by developments in methods that make large computational screens tractable. Here we review recent applications of this approach to different genes, and how they have enabled and supported subsequent studies. We further discuss developments in the approach and the role for the approach in light of increasingly high throughput experimental approaches.
dingo: a Python package for metabolic flux sampling
Authors: Chalkis Apostolos , Fisikopoulos Vissarion , Tsigaridas Elias , Zafeiropoulos Haris 
Published: March 2024

Abstract

We present dingo, a Python package that supports a variety of methods to sample from the flux space of metabolic models, based on state-of-the-art random walks and rounding methods. For uniform sampling, dingo’s sampling methods provide significant speed-ups and outperform existing software. Indicatively, dingo can sample from the flux space of the largest metabolic model up to now (Recon3D) in less than a day using a personal computer, under several statistical guarantees; this computation is out of reach for other similar software. In addition, dingo supports common analysis methods, such as flux balance analysis and flux variability analysis, and visualization components. dingo contributes to the arsenal of tools in metabolic modelling by enabling flux sampling in high dimensions (in the order of thousands).

Availability and implementation
The dingo Python library is available in GitHub at https://github.com/GeomScale/dingo and the data underlying this article are available in https://doi.org/10.5281/zenodo.10423335.
Covariate adjustment in randomized experiments with missing outcomes and covariates
Authors: Zhao Anqi , Ding Peng , Li Fan 
Published: March 2024

Summary
Covariate adjustment can improve precision in analysing randomized experiments. With fully observed data, regression adjustment and propensity score weighting are asymptotically equivalent in improving efficiency over unadjusted analysis. When some outcomes are missing, we consider combining these two adjustment methods with the inverse probability of observation weighting for handling missing outcomes, and show that the equivalence between the two methods breaks down. Regression adjustment no longer ensures efficiency gain over unadjusted analysis unless the true outcome model is linear in covariates or the outcomes are missing completely at random. Propensity score weighting, in contrast, still guarantees efficiency over unadjusted analysis, and including more covariates in adjustment never harms asymptotic efficiency. Moreover, we establish the value of using partially observed covariates to secure additional efficiency by the missingness indicator method, which imputes all missing covariates by zero and uses the union of the completed covariates and corresponding missingness indicators as the new, fully observed covariates. Based on these findings, we recommend using regression adjustment in combination with the missingness indicator method if the linear outcome model or missing-completely-at-random assumption is plausible and using propensity score weighting with the missingness indicator method otherwise.
The gift and the giving: reciprocity in international aid and development in Timor-Leste
Authors: Jones Richard G 
Published: March 2024

Abstract
This paper examines the transactional dynamics of participation in foreign aid and development programs by exploring links between Marcel Mauss’ characteristics of gift-giving and Marshall Sahlins’ typology of reciprocal relationships. Grounded in Mauss’ insights, a modified version of Sahlins’ Negative, Generalized and Balanced categories is applied to recipient experiences of donor activities in Timor-Leste. In this context, I look at how the ‘development gift’ positions and defines those involved, from producing uncomfortable hierarchies of power and prestige to enhancing mutual trust and respect. Analysis of interviews with ‘ordinary’ Timorese indicates that in offering, accepting and repaying the gift, significant difficulties arise from misunderstandings about the social obligations structuring the exchange. Sahlins’ Negative and, in some circumstances, Generalized forms predict a breakdown in relationships, although not necessarily in the project itself. By contrast, the Balanced form typically leads to the type of interactions recipients desire. Responding to interviewee comments, I propose a ‘charitable’ mode of the Generalized form and identify a new category, Familial reciprocity. I conclude by recommending this modified typology as a way of understanding how we might give and receive respect, a word frequently used by recipients to describe successful development relationships with outsiders. Importantly, while grounded specifically in Timorese experiences, there is scope to apply the proposed framework to any activity in which one party identifies as a donor and others are presented as beneficiaries of their ‘free’ development gifts.