bluuebunny/crossref_metadata_2025_split huggingface dataset:
Anxiety and depression in Alzheimer’s disease: a systematic review of pathogenetic mechanisms and relation to cognitive decline
Authors: Botto Rossana , Callai Nicoletta , Cermelli Aurora , Causarano Lorenzo , Rainero Innocenzo 
Published: April 2022

Abstract

Objectives
To explore the pathogenetic hypothesis provided to explain the comorbidity of anxious and depressive symptomatology and AD and to assess the association between anxious and depressive symptoms and the AD-related cognitive impairment.

Methods
In October 2020 and March 2021, PsycINFO, Embase, Ovid, and CINAHL were searched for peer-reviewed original articles investigating anxiety and/or depression in AD.

Results
A total of 14,760 studies were identified and 34 papers on AD patients were included in the review. Suggested biological causes of depression and anxiety in AD include higher strychnine-sensitive glycine receptor (GlyRS) functioning and selective reduction of N-methyl-d-aspartate (NMDA) receptor NR2A density, cortical and limbic atrophy, lower resting cortical metabolism, lower CSF Aβ42 and higher t-tau and p-tau levels, and neuritic plaques. At the same time, dysthymia arises in the early stages of AD as an emotional reaction to the progressive cognitive decline and can cause it; anxiety can appear as an initial compensating behaviour; and depression might be related to AD awareness and loss of functional abilities. Affective symptoms and the expression of the depressive symptoms tend to reduce as AD progresses.

Conclusion
The neurodegeneration of areas and circuits dealing with emotions can elicit anxiety and depression in AD. In the early stages of the disease, anxiety and depression could arise as a psychological reaction to AD and due to coping difficulties. In late AD stages, the cognitive impairment reduces the emotional responses and their expression. Anxiety and depression are more intense in early-onset AD, due to the major impact of AD on the individual.
Epidemiologie der Epilepsie im höheren Lebensalter
Authors: Lang Johannes D. , Hamer Hajo M. 
Published: April 2022

Zusammenfassung
Hintergrund
Epilepsie ist eine häufige neurologische Erkrankung, die alle Altersgruppen betreffen kann. Symptomatische Epilepsien, u. a. auf dem Boden zerebrovaskulärer und neurodegenerativer Erkrankungen, nehmen mit dem Alter zu. Die Kenntnis über die Epidemiologie der Epilepsien des höheren Lebensalters ermöglicht, ein umfassenderes Bild der Erkrankungen und der therapeutischen und sozialmedizinischen Herausforderungen für den einzelnen Betroffenen und die Gesellschaft zu erhalten.

Fragestellung
Welche Erkenntnisse liegen aktuell zur Epidemiologie der Epilepsien des höheren Lebensalters vor und wie sind sie einzuordnen?

Material und Methoden
Eine MEDLINE-Recherche auf PubMed mit den Begriffen „epilepsy“, „elderly“ und „incidence“ oder „prevalence“ oder „epidemiology“ wurde durchgeführt, und relevante Arbeiten wurden diesem Artikel zugrunde gelegt.

Ergebnisse
Die Punktprävalenz der Epilepsien des höheren Lebensalters liegt zwischen 0,5 und 0,8 % der Bevölkerung und betrifft in Deutschland somit ca. 500.000 Menschen. Die höchste altersadjustierte Prävalenz besteht jenseits des 75. Lebensjahres. In den vergangenen Jahrzehnten stieg die Prävalenz insbesondere bei den über 75-Jährigen weiter an auf das Doppelte der erwachsenen erwerbstätigen Bevölkerung. Die Inzidenz zeigt einen deutlichen Anstieg bei den über 65-Jährigen mit einem Maximum bei ca. 80 bis 85 Jahren und etwas häufiger bei Männern.

Diskussion
Gründe für die hohe Inzidenz und Prävalenz der Epilepsien des höheren Lebensalters sind die altersabhängige Inzidenz potenziell epilepsieassoziierter Erkrankungen bei einem gleichzeitig längeren Langzeitüberleben für diese Erkrankungen aufgrund einer besseren medizinischen Versorgung und ein Anstieg der Lebenserwartung. Die Veränderung der Alterspyramide mit einem höheren (und in den kommenden Jahrzehnten weiter zunehmenden) Anteil älterer Menschen wird die Zunahme der Altersepilepsie weiter verstärken.
Antibacterial and wound healing properties of cellulose acetate electrospun nanofibers loaded with bioactive glass nanoparticles; in-vivo study
Authors: Sharaf Samar S. , El-Shafei Amira M. , Refaie Rakia , Gibriel Abdullah A. , Abdel-Sattar Raghda 
Published: April 2022

AbstractBioactive glasses (BGs) have gained great attention owing to their versatile biological properties. Combining BG nanoparticles (BGNPs) with polymeric nanofibers produced nanocomposites of great performance in various biomedical applications especially in regenerative medicine. In this study, a novel nanocomposite nanofibrous system was developed and optimized from cellulose acetate (CA) electrospun nanofibers containing different concentrations of BGNPs. Morphology, IR and elemental analysis of the prepared electrospun nanofibers were determined using SEM, FT-IR and EDX respectively. Electrical conductivity and viscosity were also studied. Antibacterial properties were then investigated using agar well diffusion method. Moreover, biological wound healing capabilities for the prepared nanofiber dressing were assessed using in-vivo diabetic rat model with induced wounds. The fully characterized CA electrospun uniform nanofiber (100–200 nm) with incorporated BGNPs exhibited broad range of antimicrobial activity against gram negative and positive bacteria. The BGNP loaded CA nanofiber accelerated wound closure efficiently by the 10th day. The remaining wound areas for treated rats were 95.7 ± 1.8, 36.4 ± 3.2, 6.3 ± 1.5 and 0.8 ± 0.9 on 1st, 5th, 10th and 15th days respectively. Therefore, the newly prepared BGNP CA nanocomposite nanofiber could be used as a promising antibacterial and wound healing dressing for rapid and efficient recovery.
Model method drawing acts as a double-edged sword for solving inconsistent word problems
Authors: de Koning Björn B. , Boonen Anton J. H. , Jongerling Joran , van Wesel Floryt , van der Schoot Menno 
Published: April 2022

Abstract
Drawing bar diagrams has been shown to improve performance on mathematical word problems wherein the relational keyword is consistent with the required arithmetic operation. This study extends this by testing the effectiveness of bar diagram drawing for word problems with an inconsistent keyword-arithmetic operation mapping. Seventy-five fifth graders solved consistent and inconsistent word problems while encouraged to draw bar diagrams. For each word problem, we assessed problem type (consistent/inconsistent), performance (correct/incorrect), and bar diagrams (accurate/inaccurate/no drawing). Overall, bar diagram drawing was associated with increased performance on both consistent and inconsistent word problems, but the strongest benefits of drawing were found for inconsistent word problems. For inconsistent word problems, bar diagram accuracy was more clearly related to performance (accurate bar diagrams related to correct answers, but inaccurate ones to incorrect answers) than for consistent word problems. We conclude that bar diagram drawing provides an effective graphical support for solving inconsistent word problems.
Attention-based hybrid CNN-LSTM and spectral data augmentation for COVID-19 diagnosis from cough sound
Authors: Hamdi Skander , Oussalah Mourad , Moussaoui Abdelouahab , Saidi Mohamed 
Published: April 2022

AbstractCOVID-19 pandemic has fueled the interest in artificial intelligence tools for quick diagnosis to limit virus spreading. Over 60% of people who are infected complain of a dry cough. Cough and other respiratory sounds were used to build diagnosis models in much recent research. We propose in this work, an augmentation pipeline which is applied on the pre-filtered data and uses i) pitch-shifting technique to augment the raw signal and, ii) spectral data augmentation technique SpecAugment to augment the computed mel-spectrograms. A deep learning based architecture that hybridizes convolution neural networks and long-short term memory with an attention mechanism is proposed for building the classification model. The feasibility of the proposed is demonstrated through a set of testing scenarios using the large-scale COUGHVID cough dataset and through a comparison with three baselines models. We have shown that our classification model achieved 91.13% of testing accuracy, 90.93% of sensitivity and an area under the curve of receiver operating characteristic of 91.13%.
Sol-Gel ceramic glazes with photocatalytic activity
Authors: Monrós G. , Llusar M. , Badenes J. , Galindo R. 
Published: April 2022

AbstractA frit is a glassy ceramic composition that has been fused, quenched, and granulated. A single frit or a mixture of frits and ceramic materials forms a ceramic glaze. The purpose of this pre-fusion is to render any soluble and/or toxic components insoluble by rendering it inert in a glassy composition with silica and other added oxides. The ceramic glaze dispersed in water (ceramic slip) is deposited on a ceramic body and fired for waterproofing and aesthetic purposes. Multicomponent frits (zinc-potassium borosilicate system) with similar behavior to conventional ceramic frits for single-firing ceramic glazes (“monoporosa” glazes fired at 1080 °C) were prepared by Sol-Gel methods (monophasic and polyphasic gels) avoiding the pre-fusion and characterized as photocatalytic agents (showing high degradation activity on Orange II). The effect of doping with bandgap modifiers (V2O5, Sb2O5 and SnO2) and also with devitrification agents (ZrO2 to crystallize zircon, Al2O3 to anorthite, Mo2O3 to powellite and ZnO to gahnite ZnAl2O4) were analyzed.
Thermochemistry of substituted benzenes: acetophenones with methyl, ethyl, cyano and acetoxy substituents
Authors: Andreeva Irina V. , Verevkin Sergey P. 
Published: April 2022

AbstractThe enthalpies of vaporization/sublimation of 2-, 3- and 4-methyl-acetophenones and 2-, 3-, 4-cyano-acetophenones were derived from the vapor pressure temperature dependence measured with help of the gas saturation method. Enthalpies of fusion of 4-methyl-acetophenone and 2-, 3- and 4-cyano-acetophenone were measured by using DSC. The literature thermochemical data for methyl-, ethyl, cyano- and acetoxy-substituted acetophenones and new results were evaluated using structure–property correlations. The G* quantum chemical methods were validated for reliable estimation of the enthalpies of formation of substituted acetophenones in the gaseous state. The evaluated thermodynamic data were used to design the “centerpiece” method for the assessment of enthalpies of formation and enthalpies of vaporization of substituted benzenes.
Graphical abstract
On the cracking patterns of brittle rings with elastic radial support under hydrostatic pressure
Authors: Michel Sébastien , Sipos András A. 
Published: April 2022

AbstractThe evolution of the cracking pattern of an internally pressurized, circular, brittle ring supported with radial elastic springs is investigated. The ill-posed Griffith-type energy functional is regularized via a sequence of boundary value problems (BVPs). We show, that internal bending in the fragments plays an essential role in the position of the new crack. We also find that the pattern formation is driven by a co-dimension one bifurcation, which leads to the conclusion that in the beginning of the cracking process the new crack emerges in the vicinity of the existing cracks. In the second phase of the evolution the cracking process obeys a halving rule. The critical value of the fragment-length is derived. The results obtained are readily applicable to describe the crack evolution of hemispherical domes.
Gene expression programming and data mining methods for bushfire susceptibility mapping in New South Wales, Australia
Authors: Hosseini Maryamsadat , Lim Samsung 
Published: April 2022

AbstractAustralia is one of the most bushfire-prone countries. Prediction and management of bushfires in bushfire-susceptible areas can reduce the negative impacts of bushfires. The generation of bushfire susceptibility maps can help improve the prediction of bushfires. The main aim of this study was to use single gene expression programming (GEP) and ensemble of GEP with well-known data mining to generate bushfire susceptibility maps for New South Wales, Australia, as a case study. We used eight methods for bushfire susceptibility mapping: GEP, random forest (RF), support vector machine (SVM), frequency ratio (FR), ensemble techniques of GEP and FR (GEPFR), RF and FR (RFFR), SVM and FR (SVMFR), and logistic regression (LR) and FR (LRFR). Areas under the curve (AUCs) of the receiver operating characteristic were used to evaluate the proposed methods. GEPFR exhibited the best performance for bushfire susceptibility mapping based on the AUC (0.892 for training, 0.890 for testing), while RFFR had the highest accuracy (95.29% for training, 94.70% for testing) among the proposed methods. GEPFR is an ensemble method that uses features from the evolutionary algorithm and the statistical FR method, which results in a better AUC for the bushfire susceptibility maps. Single GEP showed AUC of 0.884 for training and 0.882 for testing. RF also showed AUC of 0.902 and 0.876 for training and testing, respectively. SVM had 0.868 for training and 0.781 for testing for bushfire susceptibility mapping. The ensemble methods had better performances than those of the single methods.
Efficient energy balancing across multiple harmonics of nonlinear normal modes
Authors: Hong Dongxiao , Hill Thomas L. , Neild Simon A. 
Published: April 2022

AbstractPredicting the forced responses of nonlinear systems is a topic that attracts extensive studies. The energy balancing method considers the net energy transfer in and out of the system over one period and establishes connections between forced responses and nonlinear normal modes (NNMs). In this paper, we consider the energy balancing across multiple harmonics of NNMs for predicting forced resonances. This technique is constructed by combining the energy balancing mechanism with restrictions (established via excitation scenarios) on external forcing and harmonic phase-shifts; a semi-analytical framework is derived to achieve both accurate/robust results and efficient computations. With known inputs from NNM solutions, the required forcing amplitudes to reach NNMs at resonances, along with their discrepancy, i.e. the harmonic phase-shifts, are computed via a one-step scheme. Several examples are presented for different excitation scenarios to demonstrate the applicability of this method and to show its capability in accurately predicting the existence of an isola where multiple harmonics play a significant part in the response.
Dose Finding in Oncology: What is Impeding Coming of Age?
Authors: Mayawala Kapil , de Alwis Dinesh 
Published: April 2022

AbstractAfter a drug molecule enters clinical trials, there are primarily three levers to enhance probability of success: patient selection, dose selection and choice of combination agents. Of these, dose selection remains an under-appreciated aspect in oncology drug development despite numerous peer-reviewed publications. Here, we share practical challenges faced by the biopharmaceutical industry that reduce the willingness to invest in dose finding for oncology drugs. First, randomized dose finding admittedly slows down clinical development. To reduce the size of dose finding study, trend in exposure vs. tumor-size analysis can be assessed, instead of a statistical test for non-inferiority between multiple doses. Second, investment in testing a lower dose when benefit-risk at the higher dose is sufficient for regulatory approval (i.e., efficacy at the higher dose is better than standard of care and safety is acceptable) is perceived as low priority. Changing regulatory landscape must be considered to optimize dose in pre-marketing setting as post-marketing changes in dose can be commercially costly. Third, the risk of exposing patients to subtherapeutic exposures with a lower dose should be assessed scientifically instead of assuming a monotonic relationship between dose and efficacy. Only the doses which are expected to be at the plateau of dose/exposure–response curve should be investigated in Phase 1b/2. Overall, changing the perceptions that have been impeding investment in dose finding in oncology requires pragmatic discourse among biopharmaceutical industry, regulatory agencies and academia. These perceptions should also not deter dose finding for recently emerging modalities, including BITEs and CART cell therapies.
A higher-order model of community resilience potential: development and assessment through confirmatory composite analysis based on partial least squares
Authors: Pasca Paola , De Simone Evelyn , Ciavolino Enrico , Rochira Alessia , Mannarini Terri 
Published: April 2022

AbstractThe topic of community resilience attracts as much academic research as it does social media. Understanding the drivers of change and community adaptation in the face of critical events is a key clue to governance actions and local measures. However, both academia and the media often provide partial definitions of community resilience. Beginning with an integration of theory-driven and data-driven knowledge, the study aims to uncover and operationalize the building blocks of community resilience potential within a measurement tool. An assessment study, conducted on 1278 participants from diverse communities statistically supported a broad, inclusive model: Community Resilience Potential is composed of four main constituents (social capital, community competence, structural-functional potential, socio-economic potential). The Confirmatory Composite Analysis formalized for Partial Least-Squares Structural Equation Modeling revealed its good psychometric properties and measurement invariance. Although the study has limitations, it provides researchers with a valuable, theoretically grounded, widely-applicable tool for the investigation of the community resilience potential.
Eco-friendly adsorbents based on abietic acid, boswellic acid, and chitosan/magnetite for removing waste oil from the surface of the water
Authors: Fekry Mohamed , Elmesallamy Salwa M. , El-Rahman Nasser R. Abd , Bekhit Mahmoud , Elsaied Hend Alaidy 
Published: April 2022

AbstractPetroleum oil leakage and industrial oily waste on the water surface are sustainable pollutions. The removal process by eco-friendly adsorbents is a critical challenge. It also requires sustainable treatment. The natural hydrophobic material such as abietic acid, boswellic acid, and chitosan was added to magnetite nanoparticles with different concentrations of 10, 15, and 20% on its surface. The magnetite acquires partially hydrophobic properties. The prepared natural adsorbents were analyzed by employing wide-angle X-ray diffraction (WAXD), vibrating sample magnetometer (VSM), Fourier transform infrared spectroscopy (FTIR), scanning electron microscope (SEM), particle size and zeta potential, and contact angle measurements. Chitosan adsorbs at the outer surface of magnetite nanoparticles while boswellic and abietic absorb in bulk. All prepared adsorbents are effective in adsorbing waste oil from the water surface. The contact angle of MB20 (magnetite/20 percent boswellic) is greater than that of MA20 and MC20 (magnetite/20% abietic or chitosan, respectively), indicating that it has more hydrophobic characteristics. The oil removal efficiency and adsorption capacity of MB20 are the highest values 57.6%, and 24 g/g, respectively. All eco-friendly adsorbents are nontoxic with low-cost production and are used many times.
Prevalence and Risk Factors of Psychiatric Symptoms Among Older People in England During the COVID-19 Pandemic: a Latent Class Analysis
Authors: Curran Emma , Rosato Michael , Ferry Finola , Leavey Gerard 
Published: April 2022

Abstract
The COVID-19 pandemic has affected mental health and social connections. Older people may be disproportionately affected, placing them at increased risk for complex mental ill-health outcomes and quality of life undermined by anxiety and depression. Understanding gender differences in the determinants of anxiety and depression symptoms is crucial to policy and practice. This study aims to examine gender-specific symptom subtypes (and subthreshold symptoms) in an older English population sampled during the COVID period, in relation to their socio-demographic, social, and health circumstances. The sample comprises all individuals aged 50 years or older and included in the English Longitudinal Study of Ageing COVID-19 sub-study conducted during June–July 2020. Latent class analysis (LCA) defined indicative sample subgroups of clinically relevant anxiety and depression. Multinomial logistic regression assessed associations between socio-demographic characteristics, health and social care indicators, loneliness, and pre-pandemic mental ill-health. LCA derived three classes of self-reported depression and anxiety: for females (1) comorbid depression and anxiety (19.9% of the sample), (2) depression and subthreshold anxiety (31.6%), and (3) no or low symptoms of depression and anxiety (48.5%), and for males (1) comorbid depression and anxiety (12.8%), (2) subthreshold anxiety and depression (29.6%), and (3) no or low depression and anxiety (57.6%). Multinomial logistic regression analyses indicate that compared to those with low/no mental health symptoms, severity of pandemic-era mental ill-health was positively associated with pre-pandemic mental health levels, worry over finances, having access to essentials, loneliness, and access to health and social care services. Findings support the persistence of comorbidity of both depression and anxiety in the pandemic period. Results may inform government health strategy on interventions to prevent social isolation and mitigate the effects of the pandemic on deteriorating mental health in older people who may be more susceptible.
Assessing the potential for restoring Mediterranean coastal dunes under pressure from tourism
Authors: Pinna Maria Silvia , Cogoni Donatella , Bacchetta Gianluigi , Fenu Giuseppe 
Published: April 2022

Abstract
Mediterranean dune systems have undergone a large reduction in the last decades. The main factors involved in this process are urbanisation promoting an alteration of dune morphology and changes in plant communities. The most representative coastal dune systems of Sardinia have been selected as a study case and analysed to evaluate their environmental status, vulnerability, and the potential for dune restoration. Thirty coastal-dune systems, ranging from high natural sites to urbanised areas were analysed. A matrix of 35 variables × 30 sites was built to calculate the relationship among dune development (StaDun) and other indices related to the coastal dunes potential to host dunes (BeaPot), the conservation actions and management of coastal-dune systems (CoMan), and the anthropogenic pressure and the transgression capacity of the sand (SurLan). The values obtained for StaDun and Dune restoration potential index (DPR) were clustered. The results highlighted the relationship among StaDun, BeaPot and CoMan indices. The geomorphological and ecological characteristics determine the main factors that influence the presence, typology, and development of dunes in each site. Conversely, StaDun was weakly correlated to SurLan index. The DPR index allowed to discriminate the coastal dunes that required management actions. The first group included well-developed dune systems for which conservation and management actions were not necessary. The second one consisted of sites for which these previous actions and restoration measures were necessary. DPR index provides a tool useful to assess and classify coastal dune areas based on their potential for restoration, and to plan appropriate management actions.
Graphical Abstract