bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prevalence of corona‐associated anxiety and mental health disorder among dentists during the COVID‐19 pandemic
Authors: Salehiniya Hamid , Abbaszadeh Hamid 
Published: April 2021

AbstractAimThe aim of this study was to investigate the prevalence and severity of corona‐associated anxiety and mental health disorder among Iranian dentists during the COVID‐19 pandemic.MethodsA study was conducted using online survey from May 2nd to 14th, 2020. The questionnaire consisted of three sections: demographic information, anxiety (18 questions), and general health (GH) (GHQ‐28). Scoring system was based on Likert scale. The questionnaire was registered at Porsline website. Data were analyzed using t test and Pearson's correlation coefficient statistical tests.ResultsA total of 320 dentists from all over the country fully completed questionnaires. 42.5% of dentist had corona‐associated anxiety and 32.5% out of them had mild severity and no severe anxiety was observed. 62.5% of dentists were nonpsychiatric according to GHQ‐28, 35% had mild disorders in GH, and no one had severe GH disorders. There were significant relationships between gender, marital status, and family history of psychiatric disorders with GH status. There was a significant relationship between history of physical illness with corona‐associated anxiety. There was a significant relationship between history of psychiatric disorders with corona‐associated anxiety and GH status.ConclusionThe prevalence of corona‐associated anxiety and mental disorders in dentists was moderate; by holding psychological workshops to maintain and strengthen the morale of dentists during the corona pandemic, along with teaching them the correct way to use personal protective equipment, while maintaining the mental health of dentists, we will help them return to work and provide dental services.
Impacts of the COVID‐19 pandemic on human–nature interactions: Pathways, evidence and implications
Authors: Soga Masashi , Evans Maldwyn J. , Cox Daniel T. C. , Gaston Kevin J. 
Published: April 2021

Abstract

The coronavirus (COVID‐19) pandemic and the global response have dramatically changed people's lifestyles in much of the world. These major changes, as well as the associated changes in impacts on the environment, can alter the dynamics of the direct interactions between humans and nature (hereafter human–nature interactions) far beyond those concerned with animals as sources of novel human coronavirus infections. There may be a variety of consequences for both people and nature.

Here, we suggest a conceptual framework for understanding how the COVID‐19 pandemic might affect the dynamics of human–nature interactions. This highlights three different, but not mutually exclusive, pathways: changes in (a) opportunity, (b) capability and (c) motivation.

Through this framework, we also suggest that there are several feedback loops by which changes in human–nature interactions induced by the COVID‐19 pandemic can lead to further changes in these interactions such that the impacts of the pandemic could persist over the long term, including after it has ended.

The COVID‐19 pandemic, which has had the most tragic consequences, can also be viewed as a ‘global natural experiment’ in human–nature interactions that can provide unprecedented mechanistic insights into the complex processes and dynamics of these interactions and into possible strategies to manage them to best effect.

A free Plain Language Summary can be found within the Supporting Information of this article.
Clinical and molecular characterization of patients with stage 4(M) neuroblastoma aged less than 18 months without MYCN amplification
Authors: Berthold Frank , Rosswog Carolina , Christiansen Holger , Frühwald Michael , Hemstedt Nadine , Klingebiel Thomas , Fröhlich Birgit , Schilling Freimut H. , Schmid Irene , Simon Thorsten , Hero Barbara , Fischer Matthias , Ernst Angela 
Published: April 2021

AbstractIntroductionThe survival of children with stage 4(M) neuroblastoma without MYCN amplification and below the age of 18 months is considered better than the still dismal outcome of older high‐risk neuroblastoma patients. This study analyzes the impact of clinical and molecular characteristics on the long‐term outcome.Patients and methodsClinical presentation, survival, and recurrence patterns of patients enrolled onto trials NB90, NB97, and NB2004 were retrospectively analyzed. Gene expression signatures based on RNA microarrays (TH10) were investigated if tumor material was available.ResultsBetween 1990 and 2015, 177 patients with stage 4(M) MYCN nonamplified neuroblastoma aged less than 18 months at diagnosis were eligible. After a median follow‐up of 9.7 years (IQR 5.0, 13.4), the proportions of 10‐year event‐free survival (EFS) and overall survival (OS) were 73% (95% confidence interval [CI] 67–79%) and 86% (95% CI 80–92%), respectively. Of the 27 neuroblastoma recurrences, 44% occurred in more than one site. Four additional patients presented histologically mature ganglioneuroma at recurrence. Six patients developed a secondary malignancy. The secondary 5‐year EFS and OS of the 27 patients with neuroblastoma recurrence were 44% and 59%, respectively. TH10 gene expression signature was not prognostically predictive in the investigated subcohort.ConclusionThe outcome of patients with stage 4(M) neuroblastoma aged less than 18 months is favorable when treated with high‐risk or otherwise intensive therapy. The development of secondary malignancies and the potential of maturation to ganglioneuroma call for a controlled stepwise reduction of treatment intensity.
Pleuropulmonary blastoma in children and adolescents: The EXPeRT/PARTNER diagnostic and therapeutic recommendations
Authors: Bisogno Gianni , Sarnacki Sabine , Stachowicz‐Stencel Teresa , Minard Colin V. , Ferrari Andrea , Godzinski Jan , Gauthier Villars Marion , Bien Ewa , Hameury Frederic , Helfre Sylvie , Schneider Dominik T. , Reguerre Yves , Lopez Almaraz Ricardo , Janic Dragana , Cesen Maja , Kolenova Alexandra , Rascon Jelena , Martinova Kata , Cosnarovici Rodica , Pourtsidis Apostolos , Ben Ami Tal , Roganovic Jelena , Koscielniak Ewa , Schultz Kris Ann P. , Brecht Ines B. , Orbach Daniel 
Published: April 2021

AbstractPleuropulmonary blastoma (PPB) is a rare cancer occurring mainly during early childhood and often associated with germline DICER1 mutations. It is classified by the macroscopic appearance into three interrelated clinico‐pathologic entities on a developmental continuum. Complete tumor resection is a main prognostic factor and can be performed at diagnosis or after neoadjuvant treatment that includes chemotherapy and in some cases radiotherapy. Optimal modalities of neo‐ or adjuvant treatments can be challenging taking into account potential long‐term toxicities in this young population. This paper presents the recommendations for diagnosis and treatment of children and adolescents with PPB elaborated by the European Cooperative Study Group for Pediatric Rare Tumors (EXPeRT) within the European Union‐funded project PARTNER (Paediatric Rare Tumours Network ‐ European Registry).
Unraveling the polypharmacology of a natural antifungal product, eugenol, against Rhizoctonia solani
Authors: Zhao Yongtian , Wang Qi , Wu Xia , Jiang Mingfang , Jin Hong , Tao Ke , Hou Taiping 
Published: April 2021

AbstractBACKGROUNDRice sheath blight caused by Rhizoctonia solani is a devastating disease of rice in China. However, indiscriminate use of chemical fungicides applied to control the disease raise major environmental and food safety issues. Ecofriendly biocontrol alternatives are urgently needed. Eugenol, one of the main ingredients in Syzygium aromaticum, has attracted much attention owing to its antifungal properties. However, its mode of action is still not clear. Herein, the antifungal activity and mode of action of eugenol against R. solani were investigated.RESULTSResults confirmed that the mycelia of R. solani treated with eugenol shrank and became dehydrated, the cytoplasmic wall separated, and the vacuoles and mitochondria decreased or dissolved. Moreover, we found that eugenol downregulated expression of C‐4 methyl sterol oxidase, inhibited synthesis of ergosterol, increased membrane permeability and impaired the transportation of amino acids and glucose across the cell membrane. In addition, eugenol decreased the mitochondrial membrane potential and initiated an oxidative stress reaction by increasing reactive oxygen species and malondialdehyde, which together with membrane damage contribute to the antifungal activity of eugenol. Meanwhile, eugenol might inhibit R. solani by affecting oxidative phosphorylation and the tricarboxylic acid cycle (TCA cycle).CONCLUSIONIn view of its multitarget properties against R. solani, eugenol provides an alternative approach to chemical control strategies against rice sheath blight. © 2021 Society of Chemical Industry.
A disaster by any other name?: COVID‐19 and support for an All‐Hazards approach
Authors: Penta Samantha , Kendra James , Marlowe Valerie , Gill Kimberly 
Published: April 2021

AbstractDisasters are among the crises that can test the decision making skill of elected and appointed public officials from planning through response and recovery. The COVID‐19 crisis, a public health emergency rather than one with immediate damage to the built environment, has affected many aspects of community life. Experiences in responding to the pandemic will likely stimulate fresh planning initiatives for public health emergencies. How then should emergency planners approach planning and response tasks? The All‐Hazards approach has been a mainstay of both research and policymaking for over 40 years, but it has come under recent criticism. In this paper, we consider if the All‐Hazards approach to disaster management is still viable. Comparing the management needs that emerged in the pandemic with those of disasters from more familiar hazard agents, we conclude that the All‐Hazards approach is valid and can continue to guide policymakers in their hazard and disaster management activities.
Learning model predictive control with long short‐term memory networks
Authors: Terzi Enrico , Bonassi Fabio , Farina Marcello , Scattolini Riccardo 
Published: April 2021

AbstractThis article analyzes the stability‐related properties of long short‐term memory (LSTM) networks and investigates their use as the model of the plant in the design of model predictive controllers (MPC). First, sufficient conditions guaranteeing the Input‐to‐State stability (ISS) and Incremental Input‐to‐State stability (ISS) of LSTM are derived. These properties are then exploited to design an observer with guaranteed convergence of the state estimate to the true one. Such observer is then embedded in a MPC scheme solving the tracking problem. The resulting closed‐loop scheme is proved to be asymptotically stable. The training algorithm and control scheme are tested numerically on the simulator of a pH reactor, and the reported results confirm the effectiveness of the proposed approach.
Robust adaptive radial‐basis function neural network‐based backstepping control of a class of perturbed nonlinear systems with unknown system parameters
Authors: Jin Xiao‐Zheng , Lü Shao‐Yu , Che Wei‐Wei , Deng Chao , Chi Jing 
Published: April 2021

SummaryIn this article, the robust adaptive output tracking control problem is addressed for a class of nonlinear systems with nonlinear dynamics and unknown system parameters. The nonlinear dynamics including internal parameter uncertainties and external disturbances are formulated as time‐varying state/input‐dependent perturbations. Radial‐basis function neural networks (RBFNNs) are developed to approximate the perturbations. A robust adaptive RBFNN‐based output feedback control strategy against the perturbations is developed by using backstepping technique with immeasurable states and without knowing any system parameter. Based on Lyapunov stability theorem, the asymptotic output tracking results of the closed‐loop nonlinear system are obtained in the presence of perturbations, immeasurable states, and unknown system parameters. The efficacy of the proposed adaptive RBFNN‐based output feedback control strategy is validated by simulation in a DC–DC buck converter system.
A descriptor regular form‐based approach to observer‐based integral sliding mode controller design
Authors: Li Jinghao , Zhai Ding 
Published: April 2021

AbstractThis article establishes a descriptor regular form and shows its applications in observer‐based integral sliding mode controllers design of descriptor systems. A reduced‐order linear observer and a full‐order descriptor sliding mode observer are, respectively, designed to estimate the state variables of the descriptor system under consideration. Necessary and sufficient conditions for the existence of the proposed descriptor regular form and observers are derived. With the descriptor regular form, it is revealed that the separation principle holds for the proposed observer‐based integral sliding mode control methods. This means that the proposed observers can be designed independently and when using the estimation of state variables obtained from them to replace the state variables in a stabilizing state‐feedback integral sliding mode controller, the resulting observer‐based integral sliding mode controller can still stabilize the descriptor system. Finally, a constrained mechanical system is numerically simulated to verify the methods proposed.
Development of a Cleavable Biotin‐Drug Conjugate Hydrogelator for the Controlled and Dual Delivery of Anticancer Drugs
Authors: Das Soumi , Kumar Thakur Krishan , Kunnumakkara Ajaikumar B. , Kundu Lal Mohan 
Published: April 2021

AbstractHydrogels based drug delivery has found extensive application recently. In most of the cases, polymers and peptide based hydrogels were used in drug delivery. In this report, we have developed a hydrogelator containing an anti‐tumor agent 5‐Fluorouracil (5‐Fu). The design comprised of a photo‐responsive prodrug of 5‐Fu covalently conjugated to an essential nutrient, biotin (vitamin B7), providing the hydrogelator high biocompatibility. The synthesized molecule formed hydrogel at pH 7. The hydrogel also can effectively entrap another water‐soluble chemotherapeutic agent doxorubicin hydrochloride (DOX). The release of 5‐Fu was observed in a light dependent manner whereas sustained release of DOX was recorded from the hydrogel. The controlled and sustained release of both the drugs were monitored by UV‐Vis, fluorescence spectroscopy and 1H NMR study. Such 5‐Fu‐biotin gel could be useful as a dual drug carrier for effective delivery of two hydrophilic antitumor agents simultaneously.
Planar and Transparent Memristive Devices Based on Titanium Oxide Coated Silver Nanowire Networks with Tunable Switching Voltage
Authors: Resende Joao , Sekkat Abderrahime , Nguyen Viet Huong , Chatin Tomy , Jiménez Carmen , Burriel Mónica , Bellet Daniel , Muñoz‐Rojas David 
Published: April 2021

AbstractThreshold switching devices are fundamental active elements in more than Moore approaches, integrating the new generation of non‐volatile memory devices. Here, the authors report an in‐plane threshold resistive switching device with an on/off ratio above 106, a low resistance state of 10 to 100 kΩ and a high resistance state of 10 to 100 GΩ. Our devices are based on nanocomposites of silver nanowire networks and titanium oxide, where volatile unipolar threshold switching takes place across the gap left by partially spheroidized nanowires. Device reversibility depends on the titanium oxide thickness, while nanowire network density determines the threshold voltage, which can reach as low as 0.16 V. The switching mechanism is explained through percolation between metal–semiconductor islands, in a combined tunneling conduction mechanism, followed by a Schottky emission generated via Joule heating. The devices are prepared by low‐cost, atmospheric pressure, and scalable techniques, enabling their application in printable, flexible, and transparent electronics.
A Versatile Competitive Coordination Strategy for Tailoring Bioactive Zeolitic Imidazolate Framework Composites
Authors: Wu Xiaoling , Xiong Jun , Liu Shuli , Zong Min‐Hua , Lou Wen‐Yong 
Published: April 2021

AbstractZeolitic imidazolate frameworks (ZIFs) serving as platforms for bioactive guest encapsulation have attracted growing attention, yet the tailoring of its architectures and bioactivity remains a major challenge. Herein, a versatile competitive coordination strategy is proposed by using amorphous zinc nucleotide gel as template for step‐by‐step growth of ZIFs, which enables the tailoring of bioactive ZIF composites under facile conditions. Mechanism investigation reveals that introduced nucleotide determines the hierarchical pore structure and hydrophilicity, leading to customized activity retention and stability of the resultant bioactive ZIF composites. Furthermore, nucleoside monophosphate enhances the acidic tolerance of ZIFs. To the authors’ knowledge, this is the first example showing the dynamic evolution of amorphous gels to crystalline ZIFs for in situ encapsulation of enzymes with tailored catalytic performance. This study provides insights for rational design of ZIF‐based biocomposites and broadens the application of bioactive metal–organic frameworks.
Therapeutic Gene Silencing Using Targeted Lipid Nanoparticles in Metastatic Ovarian Cancer
Authors: Singh Manu Smriti , Ramishetti Srinivas , Landesman‐Milo Dalit , Goldsmith Meir , Chatterjee Sushmita , Palakuri Ramesh , Peer Dan 
Published: April 2021

AbstractOvarian cancer is an aggressive tumor owing to its ability to metastasize from stage II onward. Herein, lipid nanoparticles (LNPs) that encapsulate combination of small interfering RNAs (siRNAs), polo‐like kinase‐1 (PLK1), and eukaryotic translation‐initiation factor 3c (eIF3c), to target different cellular pathways essential for ovarian cancer progression are generated. The LNPs are further modified with hyaluronan (tNPs) to target cluster of differentiation 44 (CD44) expressing cells. Interestingly, hyaluronan‐coated LNPs (tNPs) prolong functional activity and reduce growth kinetics of spheroids in in vitro assay as compared to uncoated LNPs (uNPs) due to ≈1500‐fold higher expression of CD44. Treatment of 2D and 3D cultured ovarian cancer cells with LNPs encapsulating both siRNAs result in 85% cell death and robust target gene silencing. In advanced orthotopic ovarian cancer model, intraperitoneal administration of LNPs demonstrates CD44 specific tumor targeting of tNPs compared to uNPs and robust gene silencing in tissues involved in ovarian cancer pathophysiology. At very low siRNA dose, enhanced overall survival of 60% for tNPs treated mice is observed compared to 10% and 20% for single siRNA‐, eIF3c‐tNP, and PLK1‐tNP treatment groups, respectively. Overall, LNPs represent promising platform in the treatment of advanced ovarian cancer by improving median‐ and overall‐survival.
Interdisciplinarity: A complexity approach towards academic research
Authors: Zaiț Adriana , Bratianu Constantin , Vătămănescu Elena‐Mădălina , Andrei Andreia Gabriela , Horodnic Ioana Alexandra 
Published: April 2021

AbstractPlacing the issue of interdisciplinarity within a complexity framework, the current paper aims to explore different facets of interdisciplinary research (IDR). The theoretical and empirical analysis revolves around the main factors influencing IDR abilities and achievements, that is, the propelling context, attitude and further awareness of thinking and acting across boundaries in order to reach viable solutions to complex problems. On purpose to test the inferred relationships, the study relies on a questionnaire‐based survey conducted with 214 early‐career researchers from interdisciplinary departments or enrolled in interdisciplinary projects. The findings revealed that both attitude and context are important for rising researchers' awareness, in forming their abilities and reporting interdisciplinary achievements, the structural model explaining 51.9% in the variation of interdisciplinary research abilities and 17.1% in the variation of the researchers' interdisciplinary outcomes.
Automated content analysis: The review of the big data systemic discourse in tourism and hospitality
Authors: Peterlin Judita , Meško Maja , Dimovski Vlado , Roblek Vasja 
Published: April 2021

AbstractTourism is one of the economic activities that has changed most since large‐scale multidimensional data set, so‐called big data, was provided. The scientific literature on big data and tourism with the hospitality industry has been growing exponentially, which is, for this reason, hard to comprehend and synthesise manually. Our research question is how to familiarise oneself with the current knowledge of the relationship between the big data and the complex changes in the tourism and hospitality industry. An automated content analysis procedure was used to identify key topics and concepts of interest to the researchers. A careful review of the abstracts and full texts was carried out, resulting in a final list of 308 papers published in 154 journals. We used the Leximancer software 5.0 to create an automated content analysis. Seven topics (tourism, data, search, model, industry, online and travel) from papers published between 2011 and 5/2020 were found. We propose future development trends of big data in sustainable tourism.
The impact of automation and artificial intelligence on digital forensics
Authors: Jarrett Aaron , Choo Kim‐Kwang Raymond 
Published: April 2021

AbstractArtificial intelligence (AI; broadly defined to include Machine Learning and Deep Learning) and automation are two current and reciprocal computing disciplines. As such, AI‐powered software, programs, operating systems, and devices are developed on a massive scale to automate a wide variety of processes and operations. The principal aims of integrating AI and automation include efficiency, accuracy, and cost‐reduction. While there is still an on‐going cost associated with automation, the cost is typically many magnitudes smaller than the on‐going costs incurred to get the job done manually, which increases the likelihood of generating a high return on investment. One emerging application of AI and automation is digital forensics. For example, US Federal and State Law Enforcement Agencies have started exploring the utility of AI‐powered technology to make the job of digital forensics more impactful. This trend can maximize the accuracy of digital forensic investigations, enabling the resolution of more digital investigations.This article is categorized under:
Digital and Multimedia Science > Cyber Threat Intelligence
Digital and Multimedia Science > Artificial Intelligence
Digital and Multimedia Science > Cybercrime Investigation