bluuebunny/crossref_metadata_2025 huggingface dataset:
Selective feeding and linkages to the microbial food web by the doliolidDolioletta gegenbauri
Authors: Frischer Marc E. , Lamboley Lauren M. , Walters Tina L. , Brandes Jay A. , Arneson Erin , Lacy Lulu E. , López‐Figueroa Natalia B. , Rodríguez‐Santiago Áurea E. , Gibson Deidre M.
Published: April 2021

Gelatinous zooplankton play a crucial role in pelagic marine food webs, however, due to methodological challenges and persistent misconceptions of their importance, the trophic role of gelatinous zooplankton remains poorly investigated. This is particularly true for small gelatinous zooplankton including the marine pelagic tunicate,Dolioletta gegenbauri.D. gegenbauriand other doliolid species occur persistently on wide subtropical shelves where they often produce massive blooms in association with shelf upwelling conditions. As efficient filter feeders and prodigious producers of relatively low‐density organic‐rich aggregates, doliolids are understood to contribute significantly to shelf production, pelagic ecology, and pelagic–benthic coupling. Utilizing molecular gut content analysis and stable isotope analysis approaches, the trophic interactions of doliolids were explored during bloom and non‐bloom conditions on the South Atlantic Bight continental shelf in the Western North Atlantic. Based on molecular gut content analysis, relative ingestion selectivity varied withD. gegenbaurilife stage. At all life stages, doliolids ingested a wide range of prey types and sizes, but exhibited selectivity for larger prey types including diatoms, ciliates, and metazoans. Experimental growth studies confirmed that metazoan prey were ingested, but indicated that they were not digested and assimilated. Stable isotopic composition (δ13C and δ15N) of wild‐caught doliolids, during bloom and non‐bloom conditions, were most consistent with a detrital‐supplemented diet. These observations suggest that the feeding ecology ofD. gegenbauriis more complex than previously reported, and have strong and unusual linkages to the microbial food web.
Stock liquidity and corporate debt maturity structure: Evidences from Indian firms
Authors: Ahangar Nufazil Altaf
Published: April 2021

The study examines the relationship between stock liquidity and the firms' use of short‐term debt. In addition, this study examines the impact of agency costs on this relationship and also documents whether large shareholding acts as a transmission channel through which stock liquidity may influence the use of short‐term debt. The study is based on secondary financial data of non‐financial Indian companies obtained from Center for Monitoring of Indian Economy Prowess database, pertaining to a period of 18 years (2000–2018). This study employs two‐step generalized method of moments (GMM) techniques to arrive at results. Results of the study confirm that firms' use of short‐term debt is negatively associated with stock liquidity. Additionally, we found that this relation is more pronounced for firms subjected to severe agency problems. We also find that large shareholding acts as a transmission channel through which stock market liquidity may influence the use of short‐term debt.
Corneal Confocal Microscopy Identifies Parkinson's Disease with More Rapid Motor Progression
Authors: Lim Sze Hway , Ferdousi Maryam , Kalteniece Alise , Mahfoud Ziyad R. , Petropoulos Ioannis N. , Malik Rayaz A. , Kobylecki Christopher , Silverdale Monty
Published: April 2021

Background

Corneal confocal microscopy (CCM) is a noninvasive, reproducible ophthalmic technique to quantify corneal small nerve fiber degeneration. CCM demonstrates small nerve fiber damage in Parkinson's disease (PD), but its role as a longitudinal biomarker of PD progression has not been explored.

Objective

The aim of this study was to assess corneal nerve morphology using CCM in relation to disease progression in PD.

Methods

Sixty‐four participants with PD were assessed at baseline and at 12‐month follow‐up. Participants underwent CCM with automated corneal nerve quantification and assessment of Movement Disorder Society Unified Parkinson's Disease Rating Scale, Hoehn and Yahr stage, and Montreal Cognitive Assessment.

Results

Corneal nerve fiber density (CNFD), corneal nerve branch density, corneal nerve fiber length, corneal total branch density, and corneal nerve fiber area were significantly lower in participants with PD compared with healthy control subjects. Worsening of Movement Disorder Society Unified Parkinson's Disease Rating Scale part III score over 12 months was significantly greater in participants with a CNFD in the lowest compared with the highest quartile at baseline (mean difference: 6.0; 95% CI: 1.0–10.9; P = 0.019). There were no significant changes in CNFD, corneal nerve branch density, corneal nerve fiber length, corneal total branch density, corneal nerve fiber area, or corneal nerve fiber width between baseline and 12‐month follow‐up.

Conclusions

CCM identifies neurodegeneration in patients with PD, especially those who show the greatest progression in neurological disability. CCM may be a useful tool to help enrich clinical trials with those likely to exhibit more rapid progression and reduce required sample size and cost of studies. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society
A new method of solving equations of elasticity in inhomogeneous quasicrystals by means of symmetric hyperbolic systems
Authors: Yakhno Valery
Published: April 2021

Hooke's law and dynamic equations of motion in inhomogeneous 3‐D quaicrystals (QCs) were reduced to a symmetric hyperbolic system of the first‐order partial differential equations. This symmetric hyperbolic system describes a new mathematical model of wave propagation in inhomogeneous 3‐D QCs. Applying the theory and methods of symmetric hyperbolic systems, we have proved that this model satisfies the Hadamard's correctness requirements: solvability, uniqueness, and stability with respect to perturbation of data. Moreover, a new analytical method of solving the initial value problem for the obtained symmetric hyperbolic system which models wave propagation in vertical inhomogeneous quasicrystals was developed.
Invariant analytical solutions for the motion of an elastic string with electric current in a static magnetic field
Authors: Kurmyshev Evgeny , Piñuelas Castro Luis M. , Yakhno Alexander , Yakhno Liliya
Published: April 2021

In this work, the Lie symmetry theory is used to study the propagation of waves in an elastic string with electric currents in a static magnetic field. Both linear and nonlinear cases of the governing equations of string motion are analyzed. The classification problem of finding the principal admitted Lie groups of symmetries is solved. Some invariant analytical solutions are constructed. The physics of invariant solutions is interpreted when it is possible.
Recognition of honeycomb lung in CT images based on improved MobileNet model
Authors: Gang Li , Haixuan Zhang , Linning E , Ling Zhang , Yu Li , Juming Zhao
Published: April 2021

Purpose

The research is to improve the efficiency and accuracy of recognition of honeycomb lung in CT images.

Methods

Deep learning methods are used to achieve automatic recognition of honeycomb lung in CT images, however, are time consuming and less accurate due to the large amount of structural parameters. In this paper, a novel recognition method based on MobileNetV1 network, multiscale feature fusion method (MSFF), and dilated convolution is explored to deal with honeycomb lung in CT image classification. Firstly, the dilated convolution with different dilated rate is used to extract features to obtain receptive fields of different sizes, and then fuse the features of different scales at multiscale feature fusion block is used to solve the problem of feature loss and incomplete feature extraction. After that, by using linear activation functions (Sigmoid) instead of nonlinear activation functions (ReLu) in the improved deep separable convolution blocks to retain the feature information of each channel. Finally, by reducing the number of improved deep separable blocks to reduce the computation and resource consumption of the model.

Results

The experimental results show that improved MobileNet model has the best performance and the potential for recognition of honeycomb lung image datasets, which includes 6318 images. By comparing with 4 traditional models (SVM, RF, decision tree, and KNN) and 11 deep learning models (LeNet‐5, AlexNet, VGG‐16, GoogleNet, ResNet18, DenseNet121, SENet18, InceptionV3, InceptionV4, Xception, and MobileNetV1), our model achieved the performance with an accuracy of 99.52%, a sensitivity of 99.35%, and a specificity of 99.89%.

Conclusion

Improved MobileNet model is designed for the automatic recognition and classification of honeycomb lung in CT images. Through experiments comparative analysis of other models of machine learning and deep learning, it is proved that the proposed improved MobileNet method has the best recognition accuracy with fewer the model parameters and less the calculation time.
Water‐suppression cycling 3‐T cardiac 1H‐MRS detects altered creatine and choline in patients with aortic or mitral stenosis
Authors: Ding Belinda , Peterzan Mark , Mózes Ferenc E. , Rider Oliver J. , Valkovič Ladislav , Rodgers Christopher T.
Published: April 2021

Cardiac proton spectroscopy (1H‐MRS) is widely used to quantify lipids. Other metabolites (e.g. creatine and choline) are clinically relevant but more challenging to quantify because of their low concentrations (approximately 10 mmol/L) and because of cardiac motion. To quantify cardiac creatine and choline, we added water‐suppression cycling (WSC) to two single‐voxel spectroscopy sequences (STEAM and PRESS). WSC introduces controlled residual water signals that alternate between positive and negative phases from transient to transient, enabling robust phase and frequency correction. Moreover, a particular weighted sum of transients eliminates residual water signals without baseline distortion. We compared WSC and the vendor's standard ‘WET’ water suppression in phantoms. Next, we tested repeatability in 10 volunteers (seven males, three females; age 29.3 ± 4.0 years; body mass index [BMI] 23.7 ± 4.1 kg/m2). Fat fraction, creatine concentration and choline concentration when quantified by STEAM‐WET were 0.30% ± 0.11%, 29.6 ± 7.0 μmol/g and 7.9 ± 6.7 μmol/g, respectively; and when quantified by PRESS‐WSC they were 0.30% ± 0.15%, 31.5 ± 3.1 μmol/g and 8.3 ± 4.4 μmol/g, respectively. Compared with STEAM‐WET, PRESS‐WSC gave spectra whose fitting quality expressed by Cramér‐Rao lower bounds improved by 26% for creatine and 32% for choline. Repeatability of metabolite concentration measurements improved by 72% for creatine and 40% for choline. We also compared STEAM‐WET and PRESS‐WSC in 13 patients with severe symptomatic aortic or mitral stenosis indicated for valve replacement surgery (10 males, three females; age 75.9 ± 6.3 years; BMI 27.4 ± 4.3 kg/m2). Spectra were of analysable quality in eight patients for STEAM‐WET, and in nine for PRESS‐WSC. We observed comparable lipid concentrations with those in healthy volunteers, significantly reduced creatine concentrations, and a trend towards decreased choline concentrations. We conclude that PRESS‐WSC offers improved performance and reproducibility for the quantification of cardiac lipids, creatine and choline concentrations in healthy volunteers at 3 T. It also offers improved performance compared with STEAM‐WET for detecting altered creatine and choline concentrations in patients with valve disease.
Coupling of non‐ordinary state‐based peridynamics and finite element method with reduced boundary effect
Authors: Jin Suyeong , Hwang Young Kwang , Hong Jung‐Wuk
Published: April 2021

In this study, we propose a new numerical technique to couple non‐ordinary state‐based peridynamics (NOSB‐PD) and the finite element method (FEM), and improve the scheme by implementing an effective boundary imposition method and a stabilization method. This coupling scheme takes the mutual advantages of peridynamics and the FEM to solve fracture problems without the imposition of additional criteria, yielding enhanced computational efficiency. In addition, the coupling model brings the reduction of the boundary effect using the boundary imposition method. To combine the peridynamics and FEM, the model is partitioned into the peridynamic subregion and finite element subregion. Subsequently, the two subregions are bridged by interface elements, where peridynamic nodes are embedded. Two types of coupling schemes are developed and the boundary effect of the peridynamic subregion is analyzed in each coupling approach. Moreover, stabilization of the coupling method is implemented to control the zero‐energy mode inherent in NOSB‐PD to simulate fracture problems. The proposed methodology is verified by solving several quasi‐static problems in the one‐ and two‐dimensional domains, and fracture problems are solved. The crack paths predicted by the proposed coupling method are in good agreement with the results of the exact solution and the experiments.
Pain management nursing practice assessment in older adults with dementia
Authors: Minaya‐Freire Alícia , Subirana‐Casacuberta Mireia , Puigoriol‐Juvanteny Emma , Ramon‐Aribau Anna
Published: April 2021

Aim

To assess pain management nursing practice in older adults with dementia through electronic health records (EHR).

Design

Retrospective study.

Methods

Data were collected from EHR related to pain management in older adults with dementia treated at the Acute Geriatrics Unit (AGU) of a university hospital in early 2018.

Results

EHR related to the pain of 111 patients were reviewed. Pain intensity was assessed at admission in 88% of patients and a median of 1.9 times per day of stay. A disproportionate number of the assessments (39%) occurred during the late shift. A median of 1 drug per day was administered. Pain was recorded in 28% of patients’ care plans, and non‐pharmacological interventions were recorded in 12%.

In conclusion, exist variability in pain management nursing practice in older adults with dementia. Admission diagnosis correlated with the analgesic administration schedule, the number of drugs administered and the number of pain nursing annotations.
Prevalence of corona‐associated anxiety and mental health disorder among dentists during the COVID‐19 pandemic
Authors: Salehiniya Hamid , Abbaszadeh Hamid
Published: April 2021

Aim

The 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.

Methods

A 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.

Results

A 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.

Conclusion

The 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.
What Is a Small System?
Authors: Oxenford Jeff , Landes Laura
Published: April 2021

In the water sector, small systems represent a large number of utilities with widely different characteristics. Understanding this range of systems is essential in defining the challenges such systems face and the support they need.
Career Pathway Programs Can Fight Racial Inequality and End Labor Shortfalls
Authors: Hawkins Channing
Published: April 2021

It's no secret that the United States faces a growing shortage of skilled workers. In 2019, according to the Department of Labor, there were nearly 1 million more open positions than there were Americans to fill them, leaving the US economy unable to operate at full capacity with good‐paying middle‐class jobs left on the table. This skilled worker shortage has been felt even more acutely in the water sector, where, according to a 2018 Brookings Institution report, an expected “silver tide” of retirements is often resulting in staffing vacancies as high as 50%, a frequency and rate that are expected to increase in the coming decades.
Focus on Resilience in the Face of Emerging Contaminants
Authors: Flis Kevin
Published: April 2021

New treatment, testing, and remediation approaches are available to help water utilities handle emerging contaminants such as 1,4‐dioxane and PFAS.
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

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

Introduction

The 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 methods

Clinical 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.

Results

Between 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.

Conclusion

The 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

Pleuropulmonary 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

BACKGROUND

Rice 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.

RESULTS

Results 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).

CONCLUSION

In 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.
Geraniol exerts its antiproliferative action by modulating molecular targets in lung and skin carcinoma cells
Authors: Fatima Kaneez , Wani Zahoor Ahmad , Meena Abha , Luqman Suaib
Published: April 2021

Geraniol, an acyclic monoterpene present in several plant species' essential oils, is utilized as a food additive. It possesses potent antiproliferative and antitumor effects ascribed to its antiinflammatory, and antioxidant properties. The study aimed to understand geraniol's mechanism in human lung and skin cancer cells by employing molecular and cell target‐based assays. SRB, NRU, MTT assays, qRT‐PCR, molecular docking, and EAC model were used. Geraniol inhibits the proliferation of PC‐3, A431, and A549 cells (~50%) and suppresses the activity of ornithine decarboxylase (15.42 ± 0.61 μM) and hyaluronidase (57.61 ± 8.53 μM) in A549 cells; LOX‐5 (25.44 ± 3.50 μM) and hyaluronidase (90.71 ± 2.38 μM) in A431 cells. The qRT‐expression analysis of the targeted gene depicts non‐significant change at the transcriptional level of LOX‐5 in A431 cells. A robust binding interaction of geraniol with molecular targets was observed in the molecular docking studies. In Ehrlich Ascites Carcinoma model, geraniol inhibit tumor growth by 50.08% at 75 mg/kg bw and was found to be safe up to 1,000 mg/kg bw in a toxicity study. Geraniol has two prenyl units allied head‐to‐tail and functionalized with one hydroxyl group at its tail end could be responsible for the antiproliferative activity. These observations provide evidence for geraniol to be used as a new prototype to develop a novel anticancer agent.
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

Disasters 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

This 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

In 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

This 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

Hydrogels 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

Threshold 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

Zeolitic 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

Ovarian 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

Placing 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

Tourism 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

Artificial 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
Green Technology Approaches to Solid Waste Management in the Developing Economies
Authors: Hammed T. B. , Sridhar M. K. C.
Published: April 2021

The severity of extreme weather and climate change impacts around the world has been a public health concern in the last few decades. Apart from greenhouse gas generation, poor waste management exacerbates consequences of global warming such as flooding, lower crop yields, and the epidemic of diseases which can escalate into disastrous situations. The general public in developing economies sees wastes as valueless materials and disposes them through open burning, stream dumping, or as conveniently as possible. Also, the cutting of trees for firewood leads to deforestation and desertification that increase people’s vulnerability to climate change impact. Against this backdrop, there is a need for a paradigm shift toward developing indigenous technologies that convert solid waste to cheap and clean energy. Various innovations use the “green technology approach” in putting trash back into the value chain. Furthermore, the green technology approach has a great potential to enhance adaptation and resilience among climate change-displaced populations where they can set up microenterprise on useful end products. In this chapter, unique features of these technologies at the Renewable Resources Centre of the University of Ibadan, practice-oriented researches, and a case study at Kube-Atenda community Ibadan, Nigeria, are presented. This chapter is therefore set out to showcase examples of waste management initiatives and strategies that have been successfully implemented elsewhere by the authors. It also focuses on how some countries in the continent, with developing economies, may foster their resilience and their capacity to adapt to climate change.
Self-interacting multistate boson stars
Authors: Li Hong-Bo , Zeng Yan-Bo , Song Yan , Wang Yong-Qiang
Published: April 2021

Abstract

In this paper, we consider rotating multistate boson stars with quartic self-interactions. In contrast to the nodeless quartic-boson stars in [1], the self-interacting multistate boson stars (SIMBSs) have two types of nodes, including the 1S2S and 1S2P states. We show the mass M of SIMBSs as a function of the synchronized frequency ω, and the nonsynchronized frequency ω2 for three different cases. Moreover, for the case of two coexisting states with self-interacting potential, we study the mass M of SIMBSs versus the angular momentum J for the synchronized frequency ω and the nonsynchronized frequency ω2. Furthermore, for three different cases, we analyze the coexisting phase with both the ground and first excited states for SIMBSs. We also calculate the maximum value of coupling parameter Λ, and find the coupling parameter Λ exists the finite range.
Weak gravity versus de Sitter
Authors: Cribiori N. , Dall’Agata G. , Farakos F.
Published: April 2021

Abstract

We show that one can uncover a Dine-Seiberg problem for de Sitter critical points in supergravity theories by utilizing the magnetic weak gravity conjecture. We present a large variety of N=2 gauged supergravity models that include vector multiplets and in all cases we find that the weak gravity conjecture threatens de Sitter. A common feature in all such examples is a degenerate mass matrix for the gravitini, which we therefore deem a swampland criterion for de Sitter critical points.
On a class of stochastic partial differential equations with multiple invariant measures
Authors: Farkas Bálint , Friesen Martin , Rüdiger Barbara , Schroers Dennis
Published: April 2021

In this work we investigate the long-time behavior for Markov processes obtained as the unique mild solution to stochastic partial differential equations in a Hilbert space. We analyze the existence and characterization of invariant measures as well as convergence of transition probabilities. While in the existing literature typically uniqueness of invariant measures is studied, we focus on the case where the uniqueness of invariant measures fails to hold. Namely, introducing a generalized dissipativity condition combined with a decomposition of the Hilbert space, we prove the existence of multiple limiting distributions in dependence of the initial state of the process and study the convergence of transition probabilities in the Wasserstein 2-distance. Finally, we apply our results to Lévy driven Ornstein–Uhlenbeck processes, the Heath–Jarrow–Morton–Musiela equation as well as to stochastic partial differential equations with delay.
Prognostic ability of mid-term worsening renal function after percutaneous coronary intervention: findings from the SHINANO registry
Authors: Okina Yoshiteru , Miura Takashi , Senda Keisuke , Taki Minami , Kobayashi Masanori , Kanai Masafumi , Okuma Yukari , Yanagisawa Takashi , Hashizume Naoto , Otagiri Kyuhachi , Shoin Kyoko , Watanabe Noboru , Ebisawa Soichiro , Karube Kenichi , Nakajima Hiroyuki , Saigusa Tatsuya , Miyashita Yusuke , Kashiwagi Daisuke , Machida Keisuke , Abe Naoyuki , Tachibana Takahiro , Kanzaki Yusuke , Maruyama Takuya , Nomi Hidetomo , Sakai Takahiro , Yui Hisanori , Mochidome Tomoaki , Kobayashi Takahiro , Kasai Toshio , Ikeda Uichi , Kuwahara Koichiro
Published: April 2021

Chronic kidney disease is a prognostic factor for cardiovascular disease. Worsening renal function (WRF), specifically, is an important predictor of mortality in patients with acute myocardial infarction undergoing primary percutaneous coronary intervention (PCI). We evaluate the prognostic impact of mid-term WRF after PCI on future cardiovascular events. We examined the renal function data of 1086 patients in the first year after PCI using the SHINANO 5-year registry. Patients were divided into two groups, mid-term WRF and non-mid-term WRF, and primary outcomes were major adverse cardiovascular events (MACE) and death. Mid-term WRF was defined as an increase in creatinine (≥ 0.3 mg/dL) in the first year after PCI. Mid-term WRF was found in 101 patients (9.3%), and compared to non-mid-term WRF, it significantly increased the incidence of MACE (p < 0.001), and all-cause death (p < 0.001), myocardial infarction (p = 0.001). Furthermore, mid-term WRF patients had higher incidence of future heart failure (p < 0.001) and new-onset atrial fibrillation (p = 0.01). Patients with both mid-term WRF and chronic kidney disease had increased MACE compared to patients with either condition alone (p < 0.001). Similarly, patients with mid-term WRF and acute kidney injury had increased MACE compared to patients with either condition alone (p < 0.001). Multivariate Cox regression analysis revealed mid-term WRF as a strong predictor of MACE (hazard ratio: 2.50, 95% confidence interval 1.57–3.98, p < 0.001). Mid-term WRF after PCI negatively affects MACE, as well as future admission due to heart failure and new-onset atrial fibrillation, chronic kidney disease, and acute kidney injury.