bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gaps in transitional care to adulthood for patients with cerebral palsy: a systematic review
Authors: Mitchell Devon L. , Shlobin Nathan A. , Winterhalter Emily , Lam Sandi K , Raskin Jeffrey S 
Published: August 2023

Abstract
Purpose
The transition from pediatric to adult care can be complex and difficult to navigate for adolescents with cerebral palsy (CP). We aimed to assess the current state of transitional care for young persons with CP and delineate guidelines for best practice with opportunities for intervention.

Methods
A systematic review was conducted using PRISMA guidelines to search PubMed, Embase, and Scopus databases. Articles were screened for relevance via title and abstract prior to full-text review.

Results
Of 3151 resultant articles, 27 observational studies were included. Fourteen (52%) studies assessed clinical outcomes of patients with CP during and post-transition. Transition-associated poor outcomes included housing instability, unemployment, difficulty forming relationships, increased hospital admission rates, and decreased use of rehabilitation services. Factors associated with improved outcomes included family participation, promotion of self-efficacy, and meeting the adult team before transition. Nine (33%) studies conducted interviews with transition-age persons with CP. Key themes were a lack of transition preparedness, difficulty navigating the adult system, gaps in seamless care, and limited accessibility to specialists and environments suitable for patients with complex care needs. Four (15%) studies examined features of current transition services. Perceived barriers included poor communication within health service teams, limited adult providers accepting CP patients, and the lack of financial resources for specialized care. There was no standardized transition tool or approach.

Conclusion
These findings underscore the importance of a planned transition process in optimizing long-term medical and psychosocial outcomes for persons with CP. Further research, including translational, team-based, and community-engaged research, are needed.
The effect of erenumab on brain network function in episodic migraine patients: a randomized, placebo-controlled clinical trial (RESET BRAIN)
Authors: Filippi Massimo , Messina Roberta , Bartezaghi Marta , Cetta Ilaria , Colombo Bruno , Grazzi Licia , Martinelli Daniele , Ornello Raffaele , Pichiecchio Anna , Raimondi Debora , Russo Antonio , Sacco Simona , Splendiani Alessandra , Tassorelli Cristina , Turrini Renato , Valsasina Paola , Rocca Maria Assunta ,   RESET BRAIN Study Group, Bruno Federico , Campanella Angela , Caponnetto Valeria , Dall’Occhio Luca , Silvestro Marcello , Vuotto Roberto 
Published: August 2023

Abstract
Background
We aimed to explore whether erenumab, a monoclonal antibody targeting the calcitonin gene-related peptide receptor, could exert a central effect on brain network function in migraine, and investigate the persistence of such an effect following treatment discontinuation.

Methods
This was a randomized, double-blind, placebo-controlled, multicenter trial with a crossover design performed in adult episodic migraine patients with previous treatment failure. Patients were randomized (1:1) to 12 weeks of erenumab 140 mg or placebo, followed by a 12-week crossover. Resting state (RS) functional connectivity (FC) changes of brain networks involved in migraine were investigated using a seed-based correlation approach.

Results
Sixty-one patients were randomized to treatment. In each treatment sequence, 27 patients completed the visit at week 12. Forty-four enrolled patients, 22 in each treatment sequence, completed the study procedures with no major protocol violations. We observed a carry-over effect of erenumab during the placebo treatment and therefore data analysis was performed as a parallel comparison of erenumab vs placebo of the first 12 weeks of treatment. From baseline to week 12, compared to placebo, patients receiving erenumab showed RS FC changes within the cerebellar, thalamic and periaqueductal gray matter networks, significantly associated with clinical improvement. Compared to non-responders, patients achieving a 50% reduction in migraine days had distinct patterns of thalamic and visual network RS FC. Brain RS FC changes reversed when erenumab was stopped. A lower baseline RS FC of the pontine network identified patients responding to erenumab.

Conclusion
Erenumab modulates RS FC of networks involved in migraine pathophysiology. In line with clinical response, erenumab-induced brain RS FC changes tend to reverse when treatment is stopped.
Eight years of AutoML: categorisation, review and trends
Authors: Barbudo Rafael , Ventura Sebastián , Romero José Raúl 
Published: August 2023

AbstractKnowledge extraction through machine learning techniques has been successfully applied in a large number of application domains. However, apart from the required technical knowledge and background in the application domain, it usually involves a number of time-consuming and repetitive steps. Automated machine learning (AutoML) emerged in 2014 as an attempt to mitigate these issues, making machine learning methods more practicable to both data scientists and domain experts. AutoML is a broad area encompassing a wide range of approaches aimed at addressing a diversity of tasks over the different phases of the knowledge discovery process being automated with specific techniques. To provide a big picture of the whole area, we have conducted a systematic literature review based on a proposed taxonomy that permits categorising 447 primary studies selected from a search of 31,048 papers. This review performs an extensive and rigorous analysis of the AutoML field, scrutinising how the primary studies have addressed the dimensions of the taxonomy, and identifying any gaps that remain unexplored as well as potential future trends. The analysis of these studies has yielded some intriguing findings. For instance, we have observed a significant growth in the number of publications since 2018. Additionally, it is noteworthy that the algorithm selection problem has gradually been superseded by the challenge of workflow composition, which automates more than one phase of the knowledge discovery process simultaneously. Of all the tasks in AutoML, the growth of neural architecture search is particularly noticeable.
The agrarian question in dairy farms: An analysis of dairy farms in the European Union countries
Authors: Requena-i-Mora Marina , Barbeta-Viñas Marc 
Published: August 2023

AbstractIn this article, we review the Agrarian Question focusing on dairy farms. We have the dual aim of adding to the debate surrounding the economic profitability of small and large dairy farms and increasing what is known about the decline of dairy farms. The agrarian question at the heart of our research centres on the paradoxical endurance of family farms, despite predictions from both liberal and Marxist perspectives that they would diminish in number over time. By addressing these complex issues, we hope to shed light on the challenges and opportunities facing the dairy industry today. We focus on analysing dairy farms in the European Union countries, using panel regressions from 2008 to 2018 to define the relationship between the average number of cows per farm, profit margins and Farm Net Income. The most important results show that (i) paradoxically, profits were higher on smaller farms; (ii) however, empirical data show that small dairy farms are disappearing; (iii) this is because when including subsidies, farms with a higher number of cows are more profitable than smaller farms.
Optimizing learning return on investment: Identifying learning strategies based on user behavior characteristic in language learning applications
Authors: Li Mengsiying , Wang Tai 
Published: August 2023

AbstractBegan with Computer-Assisted Language Learning (CALL) in the 1960s and extended to the widespread use of various Mobile-Assisted Language Learning (MALL) tools in education, language learning has embraced technology early on, achieved noticeable results, and found extensive practical use. However, due to the challenges in accessing user data from various language learning platforms, the measurement and assessment of language-related variables continue to rely on self-reporting and peer evaluations. This reliance hampers researchers to observe language learning from alternative perspectives, especially when it comes to analyzing raw behavioral data. To explore potential correlations between different learning modes, this study analyzed 2 million samples from Chinese students using an English language learning application. The study quantified the effectiveness of English vocabulary learning using the economic concept of return on investment (ROI) as an evaluation metric and identified four distinct learning strategies. It observed significant differences in learning ROI among learners who adopted different strategies. Based on this analysis, we recommend the following suggestions for improving language learning ROI: when memorizing new vocabulary, investing excessive amounts of time may be counterproductive; a more effective approach is to "eat less but more often," which means arranging review sessions at a reasonable pace and shortening the interval between each review.
Assessing the Impacts of Birmingham’s Clean Air Zone on Air Quality: Estimates from a Machine Learning and Synthetic Control Approach
Authors: Liu Bowen , Bryson John R. , Sevinc Deniz , Cole Matthew A. , Elliott Robert J. R. , Bartington Suzanne E. , Bloss William J. , Shi Zongbo 
Published: August 2023

AbstractWe apply a two-step data driven approach to determine the causal impact of the clean air zone (CAZ) policy on air quality in Birmingham, UK. Levels of NO2, NOx and PM2.5 before and after CAZ implementation were collected from automatic air quality monitoring sites both within and outside the CAZ. We apply a unique combination of two recent methods: (1) a random forest machine learning method to strip out the effects of meteorological conditions on air pollution levels, and then (2) the Augmented Synthetic Control Method (ASCM) on the de-weathered air pollution data to isolate the causal effect of the CAZ. We find that, during the first year following the formal policy implementation, the CAZ led to significant but modest reductions of NO2 and NOX levels measured at the roadside within (up to 3.4% and 5.4% of NO2 and NOX, respectively) and outside (up to 6.6% and 11.9%) the zone, with no detectable changes at the urban background site outside the CAZ. No significant impacts of the CAZ were found on concentrations of fine particulates (PM2.5). Our analysis demonstrates the short-term effectiveness of CAZ in reducing concentrations of NO2 and NOX.
Bibliometric analysis of the Vogt‒Koyanagi‒Harada disease literature
Authors: Li Liangpin , Yuan Liyun , Zhou Xueyan , Hua Xia , Yuan Xiaoyong 
Published: August 2023

Abstract
Purpose
As an autoimmune disease, Vogt‒Koyanagi‒Harada disease (VKHD) is a main type of uveitis in many countries and regions, significantly impacting patient vision. At present, information regarding VKHD is still limited, and further research is needed. We conducted a bibliometric analysis to characterize the overall status, current trends, and current focus of VKHD research.

Method
Literature published from 1975 to 2022 was obtained from the Web of Science core collection and analysed with the R-language packages Bibliometrix, VOSviewer, and CiteSpace software.

Results
A total of 1050 papers on VKHD were retrieved from 261 journals, and 16,084 references were obtained from the papers in the original search. The average annual number of published articles was approximately 21.9, and the number of publications rapidly increased after 2004. The journal Ocular Immunology and Inflammation published the most papers on VKHD, while the American Journal of Ophthalmology has the highest citation frequency. The leading countries were Japan, China (PRC), and the United States of America (USA). Yang PZ from Chongqing Medical University was the most prolific and cited author. The most frequently cited study discussed revision of VKHD diagnostic criteria. An analysis of the highest frequency keywords showed that most research focused on the treatment, diagnosis, and pathogenesis of VKHD and its relationship with other related diseases. At present, the most urgent research direction is in the relationship between COVID-19 or COVID-19 vaccines and VKHD and the corresponding mechanisms underlying it.

Conclusion
Utilizing dynamic and visualization tools, bibliometrics provides a clear depiction of the research history, development trends, and research hotspots in VKHD It serves as a valuable tool for identifying research gaps and areas that necessitate further exploration. Our study revealed potential directions for future VKHD research, including investigating specific molecular mechanisms underlying the disease, exploring the clinical utility of optical coherence tomography angiography and other diagnostic techniques, and conducting clinical research on novel therapeutic drugs.
Sputtered Ag-doped NiO thin films: structural, optical, and electrocatalytic activity toward methanol oxidation
Authors: Abdel-wahab Mohamed Sh. , El Emam Hadeer K. , El Rouby Waleed M. A. 
Published: August 2023

AbstractSignificant research is being performed to find suitable electrocatalysts in alkaline direct methanol fuel cells. Despite tremendous improvements, producing non-Pt catalysts with great activity and high stability is still difficult. Herein, Ag-doped NiO thin films were deposited on fluorine-doped tin oxide (FTO) by the co-sputtering deposition method, utilizing various deposition times (200, 400, 600, and 800) seconds. The film thickness for the deposited films varied from 17, 35, 70, and 100 nm by increasing the deposition time from 200, 400, 600, to 800) seconds. The NiO–Ag-800 recorded the lowest band gap of 3.36 eV, whereas the NiO–Ag-200 recorded the highest band gap of 3.81 eV. The deposited thin films were used as electrocatalysts for methanol oxidation. Its physical properties facilitate the adsorbed reactions, allow for easier penetration of electrolytes, and help in rapid reaction kinetics. Moreover, because Ag–NiO is deposited on an FTO substrate with outstanding adhesion and excellent electric contact, it can be utilized; without adding any binder or conducting agents. The films displayed reduced onset potential for oxidation of the methanol, high current density, and long-term stability. The thickness of the thin film proved that it plays a role in electroactivity. The efficiency of the films increased with increasing thickness, where the Ag–NiO-800 record the lowest onset potential is 0.37 V vs. Ag/AgCl.
Sorption behavior of Sr(II) in granitic rock: the effect of MX-80 bentonite colloids
Authors: Pakkanen Noora , Puhakka Eini , Siitari-Kauppi Marja , Hölttä Pirkko 
Published: August 2023

AbstractMX-80 bentonite colloids’ effect on radionuclide sorption was studied by batch method and transport in flow using a granitic drill core column and Sr(II) as a radionuclide. Batch-type sorption and desorption experiments were conducted to determine Sr(II)’s distribution coefficients on bentonite colloids and metatexitic gneiss. Molecular modeling assessed the radionuclide’s sorption affinity and justified the differences in Sr(II)’s sorption behavior on biotite versus montmorillonite. The distribution coefficients were found to be a hundred times greater for colloids than for granitic rock. Strontium’s breakthrough from the column with bentonite colloids was successful without notable retardation on rock minerals.
Towards integrable perturbation of 2d CFT on de Sitter space
Authors: Jäkel Christian D. , Tanimoto Yoh 
Published: August 2023

AbstractWe describe a procedure to deform the dynamics of a two-dimensional conformal net to possibly obtain a Haag–Kastler net on the de Sitter spacetime. The new dynamics is given by adding a primary field smeared on the time-zero circle to the Lorentz generators of the conformal net. As an example, we take an extension of the chiral $$\hbox {U}(1)$$

U
(
1
)

-current net by a charged field with conformal dimension $$d < \frac{1}{4}$$

d
<

1
4

. We show that the perturbing operators are defined on a dense domain.
Ψnet: a parallel network with deeply coupled spatial and squeezed features for segmentation of medical images
Authors: Elmeslimany Eman M. , Kishk Sherif S. , Altantawy Doaa A. 
Published: August 2023

AbstractThe process of delineating a region of interest or an object in an image is called image segmentation. Efficient medical image segmentation can contribute to the early diagnosis of illnesses, and accordingly, patient survival possibilities can be enhanced. Recently, deep semantic segmentation methods demonstrate state-of-the-art (SOTA) performance. In this paper, we propose a generic novel deep medical segmentation framework, denoted as Ψnet. This model introduces a novel parallel encoder-decoder structure that draws up the power of triple U-Nets. In addition, a multi-stage squeezed-based encoder is employed to raise the network sensitivity to relevant features and suppress the unnecessary ones. Moreover, atrous spatial pyramid pooling (ASPP) is employed in the bottleneck of the network which helps in gathering more effective features during the training process, hence better performance can be achieved in segmentation tasks. We have evaluated the proposed Ψnet on a variety of challengeable segmentation tasks, including colonoscopy, microscopy, and dermoscopy images. The employed datasets include Data Science Bowl (DSB) 2018 challenge as a cell nuclei segmentation from microscopy images, International Skin Imaging Collaboration (ISIC) 2017 and 2018 as skin lesion segmentation from dermoscopy images, Kvasir-SEG, CVC-ClinicDB, ETIS-LaribDB, and CVC-ColonDB as polyp segmentation from colonoscopy images. Despite the variety in the employed datasets, the proposed model, with extensive experiments, demonstrates superior performance to advanced SOTA models, such as U-Net, ResUNet, Recurrent Residual U-Net, ResUNet++, UNet++, BCDU-Net, MultiResUNet, MCGU-Net, FRCU-Net, Attention Deeplabv3p, DDANet, ColonSegNet, and TMD-Unet.
Window-Adjusted Common Spatial Pattern for Detecting Error-Related Potentials in P300 BCI
Authors: Huang Zhihua , Li Minghong , Zheng Wenming , Wu Yingjie , Jiang Kun , Zheng Huiru 
Published: August 2023

AbstractUnder certain task conditions, error-related potential (ErrP) will be elicited, meaning that the subject is perceiving an error, responding to an external error, or engaging in a cognitive process of reinforcement learning. The detection of ErrP on a single trial basis has been studied and applied to improve all kinds of brain–computer interfaces (BCIs). However, the performance of this kind of detection is not currently good enough. In the paper, we proposed a novel method, called window-adjusted common spatial pattern (WACSP), for detecting ErrP in P300 BCI. In this method, the coefficient of determination was introduced to measure the difference of Electroencephalogram (EEG) signals on a channel at a moment and to guide the search of time windows in which EEG differences are significant, and common spatial pattern (CSP) was further used to capture the stable spatial patterns of EEG differences between correct and incorrect responses in each time window. WACSP and the commonly used methods were tested on the data sets that were built using the EEG signals acquired during the P300 BCI experiments with different feedback. The comparisons of accuracy, area under receiver operating characteristics curve (AUC) and F-measure show that WACSP significantly outperforms the commonly used methods. The proposed method can improve ErrP detection based on a single trial.
An Australian convective wind gust climatology using Bayesian hierarchical modelling
Authors: Spassiani Alessio C. , Mason Matthew S. , Cheng Vincent Y. S. 
Published: August 2023

AbstractTo quantify the hazard or risks associated with severe convective wind gusts, it is necessary to have a reliable and spatially complete climatology of these events. The coupling of observational and global reanalysis (ERA-Interim) data over the period 2005–2015 is used here to facilitate the development of a spatially complete convective wind gust climatology for Australia. This is done through the development of Bayesian Hierarchical models that use both weather station-based wind gust observations and seasonally averaged severe weather indices (SWI), calculated using reanalysis data, to estimate seasonal gust frequencies across the country while correcting for observational biases specifically, the sparse observational network to record events. Different SWI combinations were found to explain event counts for different seasons. For example, combinations of Lifted Index and low level wind shear were found to generate the best results for autumn and winter. While for spring and summer, the composite Microburst Index and the combination of most unstable CAPE and 0–1 km wind shear were found to be most successful. Results from these models showed a minimum in event counts during the winter months, with events that do occur mainly doing so along the southwest coast of Western Australia or along the coasts of Tasmania and Victoria. Summer is shown to have the largest event counts across the country, with the largest number of gusts occurring in northern Western Australia extending east into the Northern Territory with another maximum over northeast New South Wales. Similar trends were found with an extended application of the models to the period 1979–2015 when utilizing only reanalysis data as input. This implementation of the models highlights the versatility of the Bayesian hierarchical modelling approach and its ability, when trained, to be used in the absence of observations.
Trivialization of the bottom line and losing relevance of losses
Authors: Srivastava Anup 
Published: August 2023

AbstractThe purpose of this article is to illustrate the growing limitations of the current methods of calculating earnings, particularly when earnings is a negative number. Earnings, presumably the most important output of a financial reporting system, is not a singular metric. It is obtained by subtracting numerous expense line items from revenues, both of which are calculated after applying a diverse, and often inconsistent, set of accounting conventions. Despite this apparent deficiency, earnings could be informative of recurring profits, if revenues are measured correctly and expenses are traced to revenues. However, both principles are increasingly violated for the cohorts of firms listed in the last 30 years, which now constitute over 80% of the set of listed firms. Revenues of recent cohorts do not capture many events that create recurring cash flows. Their operating expenses are dominated by intangible outlays that are unmatched to current revenues. As a result, newer cohorts’ profits and profit margins, especially when negative, offer little to inform future profits. Given that revenue and expense recognition rules are unlikely to change anytime soon, the current developments raise a question: Should the reporting of the summary measure of earnings be voluntary instead of mandatory?