bluuebunny/crossref_metadata_2025_split huggingface dataset:
Exploring the experience of a cognitive rehabilitation intervention for cancer-related cognitive change in people living with cancer: An interpretative phenomenological analysis
Authors: Joyce Andrea , Burns Lindsey , McAloney-Kocaman Kareena 
Published: August 2023

AbstractObjectivesSome cancer patients experience cancer-related cognitive change (CRCC). Cognitive rehabilitation interventions (CRIs) have recently been developed to help mitigate the impact of CRCC, which, untreated, can impact resumption of daily life post-cancer treatment. The experience of participants is important to understand but largely absent within research literature. This study aimed to explore how those with CRCC experience the phenomenon following completion of a CRI.MethodsThis study comprised a qualitative phenomenological approach. This involved conducting in-depth, semi-structured interviews with 6 self-referred participants from one CRI. Participants were invited to discuss their experience of CRCC and what the CRI therefore meant to them. Interviews were analyzed using interpretative phenomenological analysis.ResultsAnalysis of the findings revealed 4 key themes. (1) “Experiencing and addressing isolation” comprises reflections on posttreatment perceived abandonment and consequent feelings of belonging through CRI participation. (2) “Identity” explores participants’ reflections around perceived loss-of-self and feelings of empowerment from the intervention. (3) “Cognitive and physical balance” comprises the planning and choices participants make, supported by both their own and CRI coping strategies as they seek acceptance of cognitive change. (4) “Course reflections” explore reflections on intervention structure, format, and delivery, focusing on 2 subthemes of accessibility, flexibility and inclusivity, and communication. All participants reflected positively on their experience.Significance of resultsResults support further dissemination among health professionals and implementation of this CRI to better support self-reported CRCC concerns within this population. Future qualitative research should explore the long-term impact of CRI interventions.
PIC Simulations of Overstretched Ion‐Scale Current Sheets in the Magnetotail
Authors: Arnold H. , Sitnov M. I. 
Published: August 2023

AbstractOnset of reconnection in the tail requires the current sheet thickness to be of the order of the ion thermal gyroradius or smaller. However, existing isotropic plasma models cannot explain the formation of such thin sheets at distances where the X‐lines are typically observed. Here we reproduce such thin and long sheets in particle‐in‐cell simulations using a new model of their equilibria with weakly anisotropic ion species assuming quasi‐adiabatic ion dynamics, which substantially modifies the current density. It is found that anisotropy/agyrotropy contributions to the force balance in such equilibria are comparable to the pressure gradient in spite of weak ion anisotropy. New equilibria whose current distributions are substantially overstretched compared to the magnetic field lines are found to be stable in spite of the fact that they are substantially longer than isotropic sheets with similar thickness.
Prediction of childhood overweight and obesity at age 10–11: findings from the Studying Lifecourse Obesity PrEdictors and the Born in Bradford cohorts
Authors: Ziauddeen Nida , Roderick Paul J. , Santorelli Gillian , Alwan Nisreen A. 
Published: August 2023

Abstract
Background
In England, 41% of children aged 10–11 years live with overweight or obesity. Identifying children at risk of developing overweight or obesity may help target early prevention interventions. We aimed to develop and externally validate prediction models of childhood overweight and obesity at age 10–11 years using routinely collected weight and height measurements at age 4–5 years and maternal and early-life health data.

Methods
We used an anonymised linked cohort of maternal pregnancy and birth health records in Hampshire, UK between 2003 and 2008 and child health records. Childhood body mass index (BMI), adjusted for age and sex, at 10–11 years was used to define the outcome of overweight and obesity (BMI ≥ 91st centile) in the models. Logistic regression models and multivariable fractional polynomials were used to select model predictors and to identify transformations of continuous predictors that best predict the outcome. Models were externally validated using data from the Born in Bradford birth cohort. Model performance was assessed using discrimination and calibration.

Results
Childhood BMI was available for 6566 children at 4–5 (14.6% overweight) and 10–11 years (26.1% overweight) with 10.8% overweight at both timepoints. The area under the curve (AUC) was 0.82 at development and 0.83 on external validation for the model only incorporating two predictors: BMI at 4–5 years and child sex. AUC increased to 0.84 on development and 0.85 on external validation on additionally incorporating maternal predictors in early pregnancy (BMI, smoking, age, educational attainment, ethnicity, parity, employment status). Models were well calibrated.

Conclusions
This prediction modelling can be applied at 4–5 years to identify the risk for childhood overweight at 10–11 years, with slightly improved prediction with the inclusion of maternal data. These prediction models demonstrate that routinely collected data can be used to target early preventive interventions to reduce the prevalence of childhood obesity.
Subcortical volumetric alterations in four major psychiatric disorders: a mega-analysis study of 5604 subjects and a volumetric data-driven approach for classification
Authors: Okada Naohiro , Fukunaga Masaki , Miura Kenichiro , Nemoto Kiyotaka , Matsumoto Junya , Hashimoto Naoki , Kiyota Masahiro , Morita Kentaro , Koshiyama Daisuke , Ohi Kazutaka , Takahashi Tsutomu , Koeda Michihiko , Yamamori Hidenaga , Fujimoto Michiko , Yasuda Yuka , Hasegawa Naomi , Narita Hisashi , Yokoyama Satoshi , Mishima Ryo , Kawashima Takahiko , Kobayashi Yuko , Sasabayashi Daiki , Harada Kenichiro , Yamamoto Maeri , Hirano Yoji , Itahashi Takashi , Nakataki Masahito , Hashimoto Ryu-ichiro , Tha Khin K. , Koike Shinsuke , Matsubara Toshio , Okada Go , van Erp Theo G. M. , Jahanshad Neda , Yoshimura Reiji , Abe Osamu , Onitsuka Toshiaki , Watanabe Yoshiyuki , Matsuo Koji , Yamasue Hidenori , Okamoto Yasumasa , Suzuki Michio , Turner Jessica A. , Thompson Paul M. , Ozaki Norio , Kasai Kiyoto , Hashimoto Ryota 
Published: August 2023

AbstractDifferential diagnosis is sometimes difficult in practical psychiatric settings, in terms of using the current diagnostic system based on presenting symptoms and signs. The creation of a novel diagnostic system using objective biomarkers is expected to take place. Neuroimaging studies and others reported that subcortical brain structures are the hubs for various psycho-behavioral functions, while there are so far no neuroimaging data-driven clinical criteria overcoming limitations of the current diagnostic system, which would reflect cognitive/social functioning. Prior to the main analysis, we conducted a large-scale multisite study of subcortical volumetric and lateralization alterations in schizophrenia, bipolar disorder, major depressive disorder, and autism spectrum disorder using T1-weighted images of 5604 subjects (3078 controls and 2526 patients). We demonstrated larger lateral ventricles volume in schizophrenia, bipolar disorder, and major depressive disorder, smaller hippocampus volume in schizophrenia and bipolar disorder, and schizophrenia-specific smaller amygdala, thalamus, and accumbens volumes and larger caudate, putamen, and pallidum volumes. In addition, we observed a leftward alteration of lateralization for pallidum volume specifically in schizophrenia. Moreover, as our main objective, we clustered the 5,604 subjects based on subcortical volumes, and explored whether data-driven clustering results can explain cognitive/social functioning in the subcohorts. We showed a four-biotype classification, namely extremely (Brain Biotype [BB] 1) and moderately smaller limbic regions (BB2), larger basal ganglia (BB3), and normal volumes (BB4), being associated with cognitive/social functioning. Specifically, BB1 and BB2–3 were associated with severe and mild cognitive/social impairment, respectively, while BB4 was characterized by normal cognitive/social functioning. Our results may lead to the future creation of novel biological data-driven psychiatric diagnostic criteria, which may be expected to be useful for prediction or therapeutic selection.
Regional and temporal variability of Indian summer monsoon rainfall in relation to El Niño southern oscillation
Authors: Athira K. S. , Roxy M. K. , Dasgupta Panini , Saranya J. S. , Singh Vineet Kumar , Attada Raju 
Published: August 2023

AbstractThe Indian summer monsoon rainfall (ISMR) exhibits significant variability, affecting the food and water security of the densely populated Indian subcontinent. The two dominant spatial modes of ISMR variability are associated with the El Niño Southern Oscillation (ENSO) and the strength of the semi-permanent monsoon trough along with related variability in monsoon depressions, respectively. Although the robust teleconnection between ENSO and ISMR has been well established for several decades, the major drivers leading to the time-varying relationship between ENSO and ISMR patterns across different regions of the country are not well understood. Our analysis shows a consistent increase from a moderate to substantially strong teleconnection strength between ENSO and ISMR from 1901 to 1940. This strengthened relationship remained stable and strong between 1941 and 1980. However, in the recent period from 1981 to 2018 the teleconnection decreased consistently again to a moderate strength. We find that the ENSO–ISMR relationship exhibits distinct regional variability with time-varying relationship over the north, central, and south India. Specifically, the teleconnection displays an increasing relationship for north India, a decreasing relationship for central India and a consistent relationship for south India. Warm SST anomalies over the eastern Pacific Ocean correspond to an overall decrease in the ISMR, while warm SST anomalies over the Indian Ocean corresponds to a decrease in rainfall over the north and increase over the south of India. ﻿The central Indian region experienced the most substantial variation in the ENSO–ISMR relationship. This variation corresponds to the variability of the monsoon trough and depressions, strongly influenced by the Pacific Decadal Oscillation and North Atlantic Oscillation, which regulate the relative dominance of the two spatial modes of ISMR. By applying the PCA-Biplot technique, our study highlights the significant impacts of various climate drivers on the two dominant spatial modes of ISMR which account for the evolving nature of the ENSO–ISMR relationship.
Training certified detectives to track down the intrinsic shortcuts in COVID-19 chest x-ray data sets
Authors: Zhang Ran , Griner Dalton , Garrett John W. , Qi Zhihua , Chen Guang-Hong 
Published: August 2023

AbstractDeep learning faces a significant challenge wherein the trained models often underperform when used with external test data sets. This issue has been attributed to spurious correlations between irrelevant features in the input data and corresponding labels. This study uses the classification of COVID-19 from chest x-ray radiographs as an example to demonstrate that the image contrast and sharpness, which are characteristics of a chest radiograph dependent on data acquisition systems and imaging parameters, can be intrinsic shortcuts that impair the model’s generalizability. The study proposes training certified shortcut detective models that meet a set of qualification criteria which can then identify these intrinsic shortcuts in a curated data set.
Güte der Glukosemessung in niedergelassenen diabetologischen Praxen basierend auf einer Strukturbefragung
Authors: Schwarz Toralf , Scheper Nikolaus , Freckmann Guido , Pleus Stefan , Nauck Matthias , Landgraf Rüdiger , Heinemann Lutz 
Published: August 2023

ZusammenfassungZiel der Befragung niedergelassener Diabetologen war es, Informationen zur Güte der Glukosemessung in deren Praxen zu erhalten. 71 Praxen haben einen Online-Fragebogen dazu ausgefüllt. 63 (89%) dieser Praxen verfügen über ein eigenes Praxislabor, die anderen entnehmen Blut und versenden die Proben an ein externes Labor. In 61 (86%) Praxen ist mindestens eine Methode zur Glukosebestimmung vor Ort vorhanden. Zur Messung werden drei Messsysteme eingesetzt (Auflistung nach Häufigkeit): HemoCue Glucose 201 (31 (48%)), Super-GL/Senso-Star GL30 (19 (30%)), Biosen S/C (11 (17%)). 53 (75%) der Praxen geben an, regelmäßig an Ringversuchen für Glukose teilzunehmen. Interne Qualitätskontrollen werden täglich (42 (68%)) bzw. wöchentlich (17 (27%)) durchgeführt. Darauf verzichtet wird in 2 (3%) von 61 Praxen. Obwohl 53 (75%) der Praxen angeben, an Ringversuchen teilzunehmen, nehmen an externen Qualitätskontrollen nur 48 (79%) von 61 Praxen teil. Anscheinend ist nicht in allen Praxen bekannt, dass der Begriff externe Qualitätskontrolle Ringversuch-Beteiligung bedeutet. Ein Qualitätsmanagement haben 62 (97%) von 64 Praxen, dies ist nur bei 24 (40%) der Praxen zertifiziert. Ein spezielles QM-Handbuch ist bei 41 (67%) der 61 Praxen vorhanden. 14 (24%) der Praxen gaben an, nur venöses Blut zu verwenden, die übrigen messen zusätzlich in Kapillarblut. Die Standzeit von Blutproben bis zur Verarbeitung wird von 10% der Praxen, die hierzu eine Angabe gemacht haben, mit >30 min angegeben. Diese Befragung weist auf einen erheblichen Fortbildungsbedarf hin. Es gibt Defizite bei den Kenntnissen zu einer qualitätsgesicherten Labordiagnostik, einem entsprechenden Qualitätsmanagement und bei der Umsetzung der Richtlinien der Bundesärztekammer.
Bedarfs- und Zufriedenheitsanalyse von Patienten und Zuweisenden eines ambulanten Kataraktangebots
Authors: Zander Daniel Bernhard , Mähner Philipp M. , Reinhard Thomas , Tscheulin Dieter K. , Wacker Katrin 
Published: August 2023

Zusammenfassung
Hintergrund Zur Sicherstellung eines effizienten Ressourceneinsatzes im Rahmen ambulanter Versorgungsangebote ist die Planung und Gewährleistung eines konstanten Patientenstroms
durch eine optimale Ausgestaltung des Angebots an den Wünschen und Bedürfnissen relevanter Anspruchsgruppen von elementarer Bedeutung.
Material und Methoden Die vorliegende Studie untersucht, wie die Bedürfnisse sowie die Zufriedenheit von Patienten und zuweisenden niedergelassenen Fachärzten im Rahmen eines
ambulanten Kataraktangebots ermittelt werden und welche Schlüsse für die Ausgestaltung des Leistungsangebots gezogen werden können. Zur Ermittlung der Bedürfnisse und Zufriedenheit wurden
ein Patienten-Fragebogen und ein Zuweisenden-Fragebogen entwickelt. Promotoren und Detraktoren der Wahl bzw. Zuweisung wurden in Anlehnung an das Konzept des Net-Promoter-Scores, einem
Marktforschungsinstrument, identifiziert.
Ergebnisse 339 (38%) Patienten und 26 (45%) Zuweisende der Hauptzuweisendengruppe füllten im Befragungszeitraum die ausgehändigten Fragebogen aus. Die wichtigsten Eigenschaften für
die Einweisungsempfehlung der Zuweisenden waren die Behandlungsqualität, die Patientenzufriedenheit sowie die Kommunikation bei Rückfragen und die Schnelligkeit der Übersendung des
Arztbriefes. Die Patienten priorisierten vor allem den fachlichen Ruf, die bisherigen Erfahrungen mit der Klinik sowie die Empfehlung ihres Augenarztes und die wunschgerechte Terminvergabe
als wichtigste Eigenschaften für deren Auswahlentscheidung eines Kataraktzentrums.
Schlussfolgerung Beide Gruppen beeinflussen sich in ihrer Empfehlungs- bzw. Wahlabsicht. Eine simultane Evaluation beider Anspruchsgruppen zur Gewährleistung eines konstanten
Patientenstroms ist folglich unumgänglich. In der durchgeführten Studie weisen die Patienten und Zuweisenden eine hohe Gesamtzufriedenheit mit dem Kataraktangebot des Universitätsklinikums
auf, jedoch konnten auch verschiedene Verbesserungspotenziale entdeckt werden. Insgesamt liefert die vorgestellte Vorgehensweise einen umfassenden Ansatz zur Durchführung von Bedarfs- bzw.
Zufriedenheitsanalysen von Patienten und Zuweisenden im Rahmen eines ambulanten Versorgungsangebots, um die Patientenversorgung nachhaltig zu verbessern.
Eugene Nicholas Myers' Lecture on Head and Neck Cancer, 2020: The Surgeon as a Prognostic Factor in Head and Neck Cancer Patients Undergoing Surgery*
Authors: Kowalski Luiz P. 
Published: August 2023

AbstractThis paper is a transcript of the 29th Eugene N. Myers, MD International Lecture on Head and Neck Cancer presented at the American Academy of Otolaryngology-Head and Neck Surgery (AAO-HNS) in 2020. By the end of the 19th century, the survival rate in treated patients was 10%. With the improvements in surgical techniques, currently, about two thirds of patients survive for > 5 years. Teamwork and progress in surgical reconstruction have led to advancements in ablative surgery; the associated adjuvant treatments have further improved the prognosis in the last 30 years. However, prospective trials are lacking; most of the accumulated knowledge is based on retrospective series and some real-world data analyses. Current knowledge on prognostic factors plays a central role in an efficient treatment decision-making process. Although the influence of most tumor- and patient-related prognostic factors in head and neck cancer cannot be changed by medical interventions, some environmental factors—including treatment, decision-making, and quality—can be modified. Ideally, treatment strategy decisions should be taken in dedicated multidisciplinary team meetings. However, evidence suggests that surgeons and hospital volume and specialization play major roles in patient survival after initial or salvage head and neck cancer treatment. The metrics of surgical quality assurance (surgical margins and nodal yield) in neck dissection have a significant impact on survival in head and neck cancer patients and can be influenced by the surgeon's expertise. Strategies proposed to improve surgical quality include continuous performance measurement, feedback, and dissemination of best practice measures.
Time-resolved electron paramagnetic resonance spectrometer based on ultrawide single-sideband phase-sensitive detection
Authors: Zhang Shixue , Zhou Shengqi , Qi Jianqing , Jiao Lei , Guo Xingwei 
Published: August 2023

A time-resolved electron paramagnetic resonance (TREPR) method with 40 ns time resolution and a high sensitivity suitable for the detection of short-lived radicals under thermal equilibrium is developed. The key is the introduction of a new detection technique named ultrawide single sideband phase sensitive detection (U-PSD) to the conventional continuous-wave EPR, which remarkably enhanced the sensitivity for the detection of broadband transient signals compared with the direct detection protocol. By repeatedly triggering a transient kinetic event f(t) (e.g., by laser flash photolysis) under a 100 kHz magnetic field modulation with precise phase control, this technique can build an ultrawide single sideband modulated signal. After single sideband demodulation, the flicker noise-suppressed signal f(t) with wide bandwidth is recovered. A U-PSD TREPR spectrometer prototype has been built, which integrated timing sequence control, laser flash excitation, data acquisition systems, and the U-PSD algorithm with a conventional continuous-wave EPR. It exhibited excellent performance in monitoring a model transient radical system, laser flash photolysis of benzophenone in isopropanol. Both the intense chemically induced dynamic electron polarization signals and the much weaker thermal equilibrium EPR signals of the generated acetone ketyl radical and benzophenone ketyl radical were clearly observed within a wide timescale ranging from sub-microsecond to milliseconds. This prototype validated the feasibility of the U-PSD technique and demonstrated its superior performance in studying complex photochemical systems containing various transient radicals, which complements the established TREPR techniques and provides a powerful tool for deep mechanistic understandings, such as in photoredox catalysis and artificial photosynthesis.
Detailed formation mechanism of sharp plasmonic lattice modes on Au hemi-ellipsoid arrays in inhomogeneous environment
Authors: Yang Hua , Lou Chaogang , Huang Xiaodan , Yu Xiaojian , Yang Zhihao 
Published: August 2023

Abstract
Plasmonic lattice modes (PLM) on the periodic arrays of Au hemi-ellipsoids on quartz substrates (inhomogeneous environment) is demonstrated experimentally. It is found that formation of PLM results from the coupling between the resonance of Au hemi-ellipsoids and the diffracted waves inside the substrates. The quality factor of PLM can be attributed to three factors: the weakening of zero-order diffracted waves, the strengthening of hemi-ellipsoid’s resonance and the match between the period of the arrays and nanoparticles’ resonance wavelength. The simulated results show that the structural parameters, such as the radius of Au hemi-ellipsoid and the environmental refractive index, have effects on the quality factor of PLM. In addition, experimental results also indicate that the backward incidence results in a sharper transmission valley than the forward incidence.
Vibration amplitude normalization enhanced fault diagnosis under conditions of variable speed and extremely limited samples
Authors: Zhang Yan , Qin Xiaoyan , Han Yan , Huang Qingqing 
Published: August 2023

Abstract
Intelligent fault diagnosis of rotating equipment is increasingly reliant on algorithms that are driven by big data. By contrast, signal processing was once widely utilized for fault diagnosis in machinery as a classical tool for signal analysis due to its capability to investigate the fault-related mechanism and almost no demand on the number of data samples. This investigation was motivated by the notion that signal processing and data-driven algorithms are combined to exploit their respective characteristics and strengths. Furthermore, in engineering practice, numerous complex factors such as time-variable operating conditions of equipment, non-stationary properties of signals, and extremely limited samples available for model training, can make it difficult to learn discriminative features from input data, thereby diminishing the diagnostic accuracy. In this paper, a novel framework of vibration amplitude normalization (VAN) enhanced fault diagnosis is proposed. Firstly, after dissects deeply the effects of the time-varying speed conditions on vibration signal and its characteristics, VAN technique is proposed for non-stationary signal processing to obtain the approximate stationary signal, so as to facilitate the subsequent state characteristics mining from the vibration signal. Then, two VAN enhanced fault diagnosis methods—i.e. signal amplitude normalization integrated with shallow learning by cascade and VAN integrated with deep learning by embedding—are developed to capture discriminative features from approximate stationary signal for fault diagnosis under conditions of variable speed and extremely limited samples. Finally, the feasibility and effectiveness of the proposed methods are verified using actual vibration datasets measured on test rig and in-site wind turbines. The number of samples required to achieve the same diagnostic accuracy is reduced by an average of 60%, demonstrating the superiority.