bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dispersion phenomena in EIS and DIS spectra of porous materials and their representation as transmission line bases ‘diffusion’ elements– part II - a case study of proton conductors
Authors: Ryś Piotr , Kowalczyk Jacek , Mroczkowska-Szerszeń Maja , Kaczkan Marcin , Majewska Karolina , Moszczyński Piotr , Pudełko Wojciech , Siekierski Maciej 
Published: November 2024

Abstract
Porosity of materials, understood as an overall averaged parameter or as the pore-size distribution related data is an important quality of numerous functional materials including proton conductive glasses. While most of the existing techniques applied for its assessment cannot be used to monitor the behaviour of ‘live’ systems in operando conditions, it is possible to use Electrochemical Immittance Spectroscopy (EIS) for this purpose. Nevertheless, analysis of these systems still requires an approximation made using transmission lines based models, which can be equated to specific diffusion elements parameters, which can in turn be related to qualities of the porous material investigated. The changes of these parameters can be correlated with various processes– such as dehydration and phase transitions or to the material’s processing history. In this part of the material we present a case study of highly grinded, mechanochemically processed powder-pressed proton conductors: phosphate-silicate glass and two uranyl based compounds– hydroxy phosphate (HUP) and hydroxy arsenate, delivering proof that the dispersive properties of proton transporting materials can be correlated with their dehydration processes, which were followed by means of FT-IR and terahertz time domain spectroscopies.
Ambulatory management of acute uncomplicated diverticulitis (AmbUDiv study): a multicentre, propensity score matching study
Authors: Mohamedahmed Ali Yasen , Hamid Mohammed , Issa Mohamed , Albendary Mohamed , Sultana Emiko , Zaman Shafquat , Bhandari Santosh , Sarma Diwakar , Ball William , Thomas Pradeep , Husain Najam 
Published: November 2024

Abstract
Introduction
Recent studies have suggested that ambulatory management is feasible for acute uncomplicated diverticulitis (AUD); however, there is still no consensus regarding the most appropriate management settings. This study presents a multi-centre experience of managing patients presenting with AUD, specifically focusing on clinical outcomes and comparing ambulatory treatment with in-patient management.

Methods
A retrospective multi-centre study was conducted across four hospitals in the UK and included all adult patients with computed tomography (CT) confirmed (Hinchey grade 1a) acute diverticulitis over a 12-month period (January – December 2022). Patient medical records were followed up for 1-year post-index episode, and outcomes were compared between those treated through the ambulatory pathway versus inpatient treatment using 1:1 propensity score matching (PSM). All statistical analysis was performed using the R Foundation for Statistical Computing, version 4.4.

Results
A total of 348 patients with Hinchey 1a acute diverticulitis were included (260 in-patients; 88 ambulatory pathway), of which nearly a third (31.3%) had a recurrent disease. Inpatient management was dominant (74.7%), with a median of 3 days of hospital stay. PSM resulted in 172 patients equally divided between the two care settings. Ambulatory management was associated with a lower readmission rate (P = 0.02 before PSM, P = 0.08 after PSM), comparable surgical (P = 0.57 before PSM, 0% in both groups after PSM) and radiological interventions (P = 0.99 before and after PSM) within one year. In both matched and non-matched groups, a strong association between readmissions and inpatient management was noted in univariate analysis (P = 0.03 before PSM, P = 0.04 after PSM) and multivariate analysis (P = 0.02 before PSM, P = 0.03 after PSM).

Conclusion
Our study supports the safety and efficacy of managing patients with AUD through a well-designed ambulatory care pathway. In particular, hospital re-admission rates are lower and other outcomes are non-inferior to in-patient treatment. This has implications for substantial cost-savings and better utilisation of limited healthcare resources.
Delirium after cardiac arrest: incidence, risk factors, and association with neurologic outcome—insights from the Freiburg Delirium Registry
Authors: Staudacher Dawid Leander , Heine Laura , Maier Alexander , Kaier Klaus , Heidenreich Adrian , Rilinger Jonathan , Rottmann Felix Arne , Biever Paul Marc , Supady Alexander , Wengenmayer Tobias , Westermann Dirk , Jäckel Markus 
Published: November 2024

Abstract
Aim
Delirium in patients treated in the intensive care unit (ICU) is linked to adverse outcome, according to previous observations. However, data on patients recovering after cardiac arrest are sparse. The aim of this study was to assess incidence, risk factors, and outcome of patients with delirium after cardiac arrest in the Freiburg Delirium Registry (FDR).

Methods
In this retrospective registry study, all patients after cardiac arrest treated in the Freiburg University Medical Center medical ICU between 08/2016 and 03/2021 were included. Delirium was diagnosed using the Nursing Delirium screening scale (NuDesc), assessed three times daily. Favorable neurological outcome was defined as cerebral performance category (CPC) score at ICU discharge ≤ 2.

Results
Two hundred seventeen patients were included and among them, delirium was detected in one hundred ninety-nine (91.7%) patients. Age was independently associated with the incidence of delirium (p = 0.003), and inversely associated with the number of delirium-free days (p < 0.001). Favorable neurological outcome was present in 145/199 (72.9%) with, and 17/18 (94.4%) patients without delirium (p = 0.048). While the incidence of delirium was not independently associated with a favorable neurologic outcome, the number of delirium-free days strongly predicted the primary endpoint [OR 2.14 (1.73–2.64), p > 0.001].

Conclusion
Delirium complicated the ICU course in almost all patients after cardiac arrest. The number of delirium-free days was associated with favorable outcome while incidence of delirium itself was not.

Graphical abstract
Eruption style and dynamics of the ~ 87 ka Baricha peralkaline rhyolite eruption in Ethiopia
Authors: Tadesse Amdemichael Zafu , Fontijn Karen , Wallace Paul A. , Gurioli Lucia , Laha Priya , Terryn Herman , Ayalew Dereje 
Published: November 2024

AbstractPeralkaline rhyolites are a rare magma type, typically associated with continental rift settings, and characterised by excess alkalis relative to alumina and a moderate-low viscosity compared to calc-alkaline equivalents. Despite their prevalence in extensional rift settings, such as the Main Ethiopian Rift, eruption dynamics of peralkaline magmas are poorly understood and have never been directly observed. To address the knowledge gap, this study investigates the style and dynamics of the ~ 87 ka explosive eruption at Baricha volcano as a case study. This eruption deposited widespread pumice lapilli fall and pyroclastic density currents, which provide valuable information on pre- and syn-eruptive magmatic processes. By examining the physical and textural features of the eruption products at different stratigraphic levels, we reconstruct eruption dynamics over time. Our analysis reveals that the eruption had three distinct phases, each characterised by different types of tephra fall deposits and associated with different plume and vent conditions. Specifically, deposits of phases 1 and 3 were characterised by massive and well-sorted tephra falls indicative of sustained plume behaviour, while phase 2 deposits were bedded, lithic-rich (i.e. non-juvenile fragments) tephra falls, and pyroclastic density current deposit associated with an unsteady plume and vent-widening phase. The pumice (8–16 mm size fraction) from this eruption is microlite-free, with a bulk density of 400–700 kg m−3 and > 60% total vesicularity. The vesicle size distribution is polymodal, with the most frequent size ranging from 0.001 to 2.4 mm and an estimated vesicle number density of 0.07*107 to 1.6*107 mm−3. The textural observations suggest rapid nucleation occurred during the late phases of magma ascent. Calculated decompression rates of the ascending magma were 0.07–5.6 MPa/s and show a variation between the eruption phases. We conclude that the shift in eruption dynamics alternating between steady to unsteady plume behaviour during the eruption was likely driven by changes in conduit geometry, lithic abundance of the eruptive mixture, decompression rate, and fresh magma injection.
Sign language interpretation using machine learning and artificial intelligence
Authors: Najib Fatma M. 
Published: November 2024

Abstract
Sign language is the only way for deaf and mute people to represent their needs and feelings. Most of non-deaf-mute people do not understand sign language, which leads to many difficulties for deaf-mutes' communication in their social life. Sign language interpretation systems and applications get a lot of attention in the recent years. In this paper, we review sign language recognition and interpretation studies based on machine learning, image processing, artificial intelligence, and animation tools. The two reverse processes for sign language interpretation are illustrated. This study discusses the recent research on sign language translation to text and speech with the help of hand gestures, facial expressions interpretation, and lip reading. Also, state of the art in speech to sign language translation is discussed. In addition, some of the popular and highly rated Android and Apple mobile applications that facilitate disabled people communication are presented. This paper clarifies and highlights the recent research and real used applications for deaf-mute people help. This paper tries to provide a link between research proposals and real applications. This link can help covering any gap or non-handled functionalities in the real used applications. Based on our study, we introduce a proposal involves set of functionalities/options that separately introduced and discussed by the recent research studies. These recent research directions should be integrated for achieving more real help. Also, a set of non-addressed research directions are suggested for future focus.
Deep Encodings vs. Linguistic Features in Lexical Complexity Prediction
Authors: Ortiz-Zambrano Jenny A. , Espín-Riofrío César H. , Montejo-Ráez Arturo 
Published: November 2024

Abstract
In this work, we present a novel approach to lexical complexity prediction (LCP) that combines diverse linguistic features with encodings from deep neural networks. We explore the integration of 23 handcrafted linguistic features with embeddings from two well-known language models: BERT and XLM-RoBERTa. Our method concatenates these features before inputting them into various machine learning algorithms, including SVM, Random Forest, and fine-tuned transformer models. We evaluate our approach using two datasets: CompLex for English (a high-resource language) and CLexIS2 for Spanish (a relatively low-resource language in ), allowing us to study performance issues from a cross-lingual perspective. Our experiments involve different combinations of linguistic features with encodings from pretrained deep learning models, testing both token-based and sequence-related encodings. The results demonstrate the effectiveness of our hybrid approach. For the English CompLex corpus, our best model achieved a mean absolute error (MAE) of 0.0683, representing a 29.2% improvement over using linguistic features alone (MAE 0.0965). On the Spanish CLexIS2 corpus, we achieved an MAE of 0.1323, a 19.4. These findings show that handcrafted linguistic features play a fundamental role in achieving higher performance, particularly when combined with deep learning approaches. Our work suggests that hybrid approaches should be considered over full end-to-end solutions for LCP tasks, especially in multilingual contexts.
Zervixkarzinom – Immuntherapie beim lokal fortgeschrittenen und metastasierten Zervixkarzinom: Status quo und neue Therapieoptionen
Authors: Schubert M. , Bauerschlag D. O. , Alkatout I. 
Published: November 2024

Zusammenfassung
Das Zervixkarzinom stellt weiterhin weltweit betrachtet das zweithäufigste gynäkologische Karzinom der Frau dar und ist im Falle einer späten Diagnosestellung mit einer hohen Mortalität verbunden. In den entwickelten Ländern ist der Rückgang der Inzidenz vor allem durch die Früherkennungsuntersuchungen (Papanicolaou-Test (Pap-Test), Humaner Papillomavirus-Test (HPV-Test)) zu erklären, wodurch die Zervixdyplasien und Frühstadien des Zervixkarzinoms rechtzeitig erkannt und erfolgreich behandelt werden können. Einen weiteren Faktor stellt die HPV-Impfung dar, wodurch die Inzidenz- und Mortalitätsraten zukünftig weiter sinken werden. Im frühen Zervixkarzinomstadium steht die operative Therapie im Vordergrund, wohingegen im fortgeschrittenen Stadium die primäre Radiochemotherapie die bevorzugte Therapie darstellt. Die metastasierte Situation wird durch die Chemotherapie in Kombination mit der Immuntherapie dominiert. Immunonkologika haben zunehmend einen essenziellen Stellenwert in der gynäkologischen Onkologie und haben in den letzten Jahren ebenso ihren Einzug in die Therapie des Zervixkarzinoms gefunden, bei der gerade in der metastasierten Situation die Therapieoptionen oftmals sehr limitiert sind. Durch verschiedenste bedeutende klinische Studien konnten hier neue Behandlungsparadigmen für das persistierende, rezidivierende sowie das metastasierende Zervixkarzinom geschaffen werden. Ebenso zeigten sich erstmalig positive Ergebnisse in der Erstlinientherapie des lokal fortgeschrittenen Zervixkarzinoms durch die Kombination des Immuncheckpointinhibitors Pembrolizumab mit der standardisierten Radiochemotherapie.
A systematic review of techniques and clinical evidence to adopt virtual reality in post-stroke upper limb rehabilitation
Authors: Mani Bharathi V. , Manimegalai P. , George S. Thomas , Pamela D. , Mohammed Mazin Abed , Abdulkareem Karrar Hameed , Jaber Mustafa Musa , Damaševičius Robertas 
Published: November 2024

AbstractRecognizing the limitations of traditional therapy can be tedious and demotivating, we explore VR’s dynamic and immersive environment to potentially improve patient engagement and motivation. This approach promises accelerated recovery by integrating real-time feedback and progress monitoring. This study aims to compare various VR training techniques employed for upper limb rehabilitation in stroke survivors. We have followed the PRISMA guidelines for systematic reviews. Articles were filtered with title words such as “virtual reality rehabilitation”, “rehabilitation”, “upper limb”, “lower limb”, “interactive gaming system”, and “VR based games” were searched in databases (LILACS, PUBMED, IEEE, WoS, and Scopus). Articles published between 2005 and 2021 were analyzed. There were 820 articles found, but only the most relevant 96 papers were analyzed. Most of the studies were randomised controlled trials (RCTs) that were submitted in 2014 or beyond. The sample size ranged from 5 to 96 persons with chronic stroke, or adults and seniors. There were no samples analyzed for those under the age of 18. Nintendo Wii® and Microsoft’s Kinect were the most popular video gaming systems. In most of the publications, the intervention took place 2–3 sessions per week, for about 2–12 weeks, with each session lasting 30 to 60 min. The most assessed outcomes were body steadiness, upper extremity motor capabilities, daily tasks, and quality of life. The Fugl–Meyer Assessment was one the commonly used tool for measuring outcomes. After VR therapy, the research found that quality of life, dynamic steadiness, and upper extremity movement function improved. To achieve dynamic equilibrium, VR proved more beneficial than traditional treatments. The most important outcomes, the researchers focused, were day-to-day activity and physical movements of the patients. Some studies investigated the early consequences of VR on daily activities and social involvement.
A Kernel approach for extending nonparametric multivariate analysis of variance in high-dimensional settings
Authors: Gallego Vicente , Oller Ramon 
Published: November 2024

AbstractThe nonparametric multivariate analysis of variance (NPMANOVA) testing procedure has been proven to be a valuable tool for comparing groups. In the present paper, we propose a kernel extension of this technique in order to effectively confront high-dimensionality, a recurrent problem in many fields of science. The new method is called kernel multivariate analysis of variance (KMANOVA). The basic idea is to take advantage of the kernel framework: we propose to project the data from the original data space to a Hilbert space generated by a given kernel function and then perform the NPMANOVA method in the reproducing kernel Hilbert space (RKHS). Dispersion of the embedded points can be measured by the distance induced by the inner product in the RKHS but also by many other distances best suited in high-dimensional settings. For this purpose, we study two promising distances: a Manhattan-type distance and a distance based on an orthogonal projection of the embedded points in the direction of the group centroids. We show that the NPMANOVA method and the KMANOVA method with the induced distance are essentially equivalent. We also show that the KMANOVA method with the other two distances performs considerably better than the NPMANOVA method. We illustrate the advantages of our approach in the context of genetic association studies and demonstrate its usefulness on Alzheimer’s disease data. We also provide a software implementation of the method that is available on GitHub https://github.com/8699vicente/Kmanova.
Genomic insights into climate change-induced forest dieback in Abies alba hotspots of decline
Authors: García-García Isabel , Méndez-Cea Belén , Gallego Francisco Javier , Linares Juan Carlos , Horreo Jose Luis 
Published: November 2024

Abstract
Understanding adaptive genetic responses to climate change is an issue of utmost importance to improve conservation policies and adaptive management. This study deeps on it, focusing on rear-edge silver fir (Abies alba) forests, where decline has been reported and linked to climatic stressors, such as warming and recurrent drought events. Hotspots and coldspots of forest decline and mortality were defined. Different sets of single nucleotide polymorphisms (SNPs), namely genome-wide and adaptive, were used to study their genetic characteristics, aiming to identify differences in genetic diversity between vigor classes (declining and non-declining trees) and age cohorts (adult trees and saplings). Global DNA methylation levels were assessed to investigate a possible role of epigenetic processes in adaptation to stressful environments. Parentage and relatedness analysis were conducted to track the genetic lineage of trees from each site. Our findings indicate that, even though adaptive SNPs seem to provide more insightful information than the genome-wide set, the optimal approach for evolutionary studies is a combination of both. Changes in adaptive genomic diversity and DNA methylation were observed between vigor classes, revealing the existence of a molecular basis behind the ongoing decline events in silver forests. Besides, trees’ relatives display a higher mixture of origins in coldspots, which could provide a temporary refuge for the species’ genetic diversity and adaptive potential. All in all, both genetic and epigenetic characteristics should be considered in order to comprehend how forest trees respond to climate stress to achieve adaptation to climate change.
Helmholtz FEM solutions are locally quasi-optimal modulo low frequencies
Authors: Averseng M. , Galkowski J. , Spence E. A. 
Published: November 2024

AbstractFor h-FEM discretisations of the Helmholtz equation with wavenumber k, we obtain k-explicit analogues of the classic local FEM error bounds of Nitsche and Schatz (Math. Comput. 28(128), 937–958 1974), Wahlbin (1991, §9), Demlow et al.(Math. Comput. 80(273), 1–9 2011), showing that these bounds hold with constants independent of k, provided one works in Sobolev norms weighted with k in the natural way. We prove two main results: (i) a bound on the local $$H^1$$

H
1

error by the best approximation error plus the $$L^2$$

L
2

error, both on a slightly larger set, and (ii) the bound in (i) but now with the $$L^2$$

L
2

error replaced by the error in a negative Sobolev norm. The result (i) is valid for shape-regular triangulations, and is the k-explicit analogue of the main result of Demlow et al. (Math. Comput. 80(273), 1–9 2011). The result (ii) is valid when the mesh is locally quasi-uniform on the scale of the wavelength (i.e., on the scale of $$k^{-1}$$

k

-
1

) and is the k-explicit analogue of the results of Nitsche and Schatz (Math. Comput. 28(128), 937–958 1974), Wahlbin (1991, §9). Since our Sobolev spaces are weighted with k in the natural way, the result (ii) indicates that the Helmholtz FEM solution is locally quasi-optimal modulo low frequencies (i.e., frequencies $$\lesssim k$$

≲
k

). Numerical experiments confirm this property, and also highlight interesting propagation phenomena in the Helmholtz FEM error.
Amelioration of hypoxia and cold stress in Nile tilapia: comparative effect of Chlorella vulgaris and its nanoparticle dietary supplementation on performance, antioxidant, hepatic functions, and meat quality
Authors: Youssuf Hadeer , Soror Eman I. , Shehab Ahmed , El-daim Amira M. , Abo-Gamil Zienab H. , Ahmed-Farid Omar , Hamad Ahmed , Edris Shimaa , Matter Aya F. 
Published: November 2024

Abstract
Nile tilapia, a widely cultivated freshwater fish, faces significant stressors, such as hypoxia and cold temperatures, which can negatively impact its quality and growth. The current study explored the impact of Chlorella vulgaris (CV) powder and its nanoparticles (CVNPs) on the growth performance, antioxidant capacity, liver protection, and meat quality of Nile tilapia to alleviate hypoxia and cold stress. A total of 450 healthy 28-day-old Nile tilapia fingerlings (average weight 5.32 ± 1.1 g, length 3.1 ± 0.5 cm) were divided into five groups: T1 (2.5 g/kg CV), T2 (5 g/kg CV), T3 (2.5 g/kg CVNP), T4 (5 g/kg CVNP), and the control group received a basal diet without additives, each with three subgroups in tri-replicate (10 fish/replicate). After six weeks of feeding, growth metrics and meat quality parameters were assessed, and each group was subjected to hypoxia, cold stress, or optimal conditions. The results revealed that T4 exhibited the highest weight gain (WG) and lowest feed conversion ratio (FCR), whereas T1 showed the highest specific growth rate (SGR) and length gain. Hypoxia and cold stress significantly (p < 0.05) increased cortisol, oxidative markers (MDA, NO, and GSSG), and liver enzymes (ALT and AST) while reducing (p < 0.05) antioxidant markers (SOD and GSH) and total cholesterol (TC). ATP levels significantly (p < 0.05) decreased in hypoxic fish, indicating muscle energy depletion. T1 significantly (p < 0.05) lowered cortisol levels, whereas T2 and T3 significantly (p < 0.05) increased superoxide dismutase (SOD) levels. T2 also significantly (p < 0.05) increased the TC level. ALT levels significantly (p < 0.05) decreased at T1, T2, and T4, with AST levels reduced at T4 only. CV and CVNP supplementation significantly (p < 0.05) reduced the muscle MDA levels under optimal and stressful conditions, notably at T1 and T4. Additionally, meat lightness, yellowness, and chroma significantly (p < 0.05) increased in stressed tilapia, whereas meat redness was improved under optimal conditions. Fatty acid profiles varied with CV and CVNP levels across different conditions. In conclusion, CV, particularly in the nanoparticle form, enhanced the growth, antioxidant activity, and meat quality of tilapia under physical stress.