bluuebunny/crossref_metadata_2025 huggingface dataset:
Exhaled Breath Reflects Prolonged Exercise and Statin Use during a Field Campaign
Authors: Henderson Ben , Lopes Batista Guilherme , Bertinetto Carlo G. , Meurs Joris , Materić Dušan , Bongers Coen C. W. G. , Allard Neeltje A. E. , Eijsvogels Thijs M. H. , Holzinger Rupert , Harren Frans J. M. , Jansen Jeroen J. , Hopman Maria T. E. , Cristescu Simona M.
Published: March 2021

Volatile organic compounds (VOCs) in exhaled breath provide insights into various metabolic processes and can be used to monitor physiological response to exercise and medication. We integrated and validated in situ a sampling and analysis protocol using proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS) for exhaled breath research. The approach was demonstrated on a participant cohort comprising users of the cholesterol-lowering drug statins and non-statin users during a field campaign of three days of prolonged and repeated exercise, with no restrictions on food or drink consumption. The effect of prolonged exercise was reflected in the exhaled breath of participants, and relevant VOCs were identified. Most of the VOCs, such as acetone, showed an increase in concentration after the first day of walking and subsequent decrease towards baseline levels prior to walking on the second day. A cluster of short-chain fatty acids including acetic acid, butanoic acid, and propionic acid were identified in exhaled breath as potential indicators of gut microbiota activity relating to exercise and drug use. We have provided novel information regarding the use of breathomics for non-invasive monitoring of changes in human metabolism and especially for the gut microbiome activity in relation to exercise and the use of medication, such as statins.
Interfacial Interactions during Demolding in Nanoimprint Lithography
Authors: Li Mingjie , Chen Yulong , Luo Wenxin , Cheng Xing
Published: March 2021

Nanoimprint lithography (NIL) is a useful technique for the fabrication of nano/micro-structured materials. This article reviews NIL in the field of demolding processes and is divided into four parts. The first part introduces the NIL technologies for pattern replication with polymer resists (e.g., thermal and UV-NIL). The second part reviews the process simulation during resist filling and demolding. The third and fourth parts discuss in detail the difficulties in demolding, particularly interfacial forces between mold (template) and resist, during NIL which limit its capability for practical commercial applications. The origins of large demolding forces (adhesion and friction forces), such as differences in the thermal expansion coefficients (CTEs) between the template and the imprinted resist, or volumetric shrinkage of the UV-curable polymer during curing, are also illustrated accordingly. The plausible solutions for easing interfacial interactions and optimizing demolding procedures, including exploring new resist materials, employing imprint mold surface modifications (e.g., ALD-assisted conformal layer covering imprint mold), and finetuning NIL process conditions, are presented. These approaches effectively reduce the interfacial demolding forces and thus lead to a lower defect rate of pattern transfer. The objective of this review is to provide insights to alleviate difficulties in demolding and to meet the stringent requirements regarding defect control for industrial manufacturing while at the same time maximizing the throughput of the nanoimprint technique.
Associations of Dietary Patterns and Nutrients with Glycated Hemoglobin in Participants with and without Type 1 Diabetes
Authors: Basu Arpita , Alman Amy C. , Snell-Bergeon Janet K.
Published: March 2021

Background: Diet has been associated with poor glycemic control in diabetes. Few studies have examined this association in people with type 1 diabetes (T1D), who are at a higher risk for cardiovascular disease than people without diabetes. Methods: We report data from cross-sectional and longitudinal analyses from a coronary artery calcification in type 1 diabetes (CACTI) study (n = 1257; T1D: n = 568; non-diabetic controls: n = 689) collected between the years 2000 and 2002. Participants completed a validated food frequency questionnaire, a physical examination, and biochemical analyses. Dietary patterns based on variations in food group intake were created with principal components analysis. Linear regression was used to examine the associations of dietary patterns, macronutrients, and food groups with HbA1c in a model adjusted for relevant covariates and stratified by diabetes status. Results: Three dietary patterns were identified: “fruits, veggies, meats, cereal”, “baked desserts” and “convenience foods and alcohol” patterns. At baseline, a higher intake of the “baked dessert” pattern was significantly associated with higher HbA1c in T1D at baseline as well at year 6 of the study when adjusted for age, sex, BMI, total calories, and diabetes duration. No such associations were observed in the case of non-diabetic controls. Dietary saturated fats and animal fats were also positively associated with HbA1c in adults with T1D at baseline and/or at year 6. Conclusions: The habitual intake of a dietary pattern that is characterized by an increased intake of added sugar and saturated fats, such as in baked desserts, may increase risks of poor glycemic control in T1D.
Soluble Fiber Inulin Consumption Limits Alterations of the Gut Microbiota and Hepatic Fatty Acid Metabolism Caused by High-Fat Diet
Authors: Albouery Mayssa , Bretin Alexis , Buteau Bénédicte , Grégoire Stéphane , Martine Lucy , Gambert Ségolène , Bron Alain M. , Acar Niyazi , Chassaing Benoit , Bringer Marie-Agnès
Published: March 2021

Diet shapes the gut microbiota which impacts hepatic lipid metabolism. Modifications in liver fat content are associated with metabolic disorders. We investigated the extent of dietary fat and fiber-induced alterations in the composition of gut microbiota and hepatic fatty acids (FAs). Mice were fed a purified low-fat diet (LFD) or high-fat diet (HFD) containing non-soluble fiber cellulose or soluble fiber inulin. HFD induced hepatic decreases in the amounts of C14:0, C16:1n-7, C18:1n-7 and increases in the amounts of C17:0, C20:0, C16:1n-9, C22:5n-3, C20:2n-6, C20:3n-6, and C22:4n-6. When incorporated in a LFD, inulin poorly affected the profile of FAs. However, when incorporated in a HFD, it (i) specifically led to an increase in the amounts of hepatic C18:0, C22:0, total polyunsaturated FAs (PUFAs), total n-6 PUFAs, C18:3n-3, and C18:2n-6, (ii) exacerbated the HFD-induced increase in the amount of C17:0, and (iii) prevented the HFD-induced increases in C16:1n-9 and C20:3n-6. Importantly, the expression/activity of some elongases and desaturases, as well as the gut microbiota composition, were impacted by the dietary fat and fiber content. To conclude, inulin modulated gut microbiota and hepatic fatty acid composition, and further investigations will determine whether a causal relationship exists between these two parameters.
The Influence of Oxidative Stress on Serum Albumin Structure as a Carrier of Selected Diazaphenothiazine with Potential Anticancer Activity
Authors: Maciążek-Jurczyk Małgorzata , Morak-Młodawska Beata , Jeleń Małgorzata , Kopeć Wiktoria , Szkudlarek Agnieszka , Owczarzy Aleksandra , Kulig Karolina , Rogóż Wojciech , Pożycka Jadwiga
Published: March 2021

Albumin is one of the most important proteins in human blood. Among its multiple functions, drug binding is crucial in terms of drug distribution in human body. This protein undergoes many modifications that are certain to influence protein activity and affect its structure. One such reaction is albumin oxidation. Chloramine T is a strong oxidant. Solutions of human serum albumin, both non-modified and modified by chloramine T, were examined with the use of fluorescence, absorption and circular dichroism (CD) spectroscopy. 10H-3,6-diazaphenothiazine (DAPT) has anticancer activity and it has been studied for the first time in terms of binding with human serum albumin—its potential as a transporting protein. Using fluorescence spectroscopy, in the presence of dansylated amino acids, dansyl-l-glutamine (dGlu), dansyl-l-proline (dPro), DAPT binding with two main albumin sites—in subdomain IIA and IIIA—has been evaluated. Based on the conducted data, in order to measure the stability of DAPT complexes with human (HSA) and oxidized (oHSA) serum albumin, association constant (Ka) for ligand-HSA and ligand-oHSA complexes were calculated. It has been presumed that oxidation is not an important issue in terms of 10H-3,6-diazaphenothiazine binding to albumin. It means that the distribution of this substance is similar regardless of changes in albumin structure caused by oxidation, natural occurring in the organism.
Silk Fibroin: An Ancient Material for Repairing the Injured Nervous System
Authors: Yonesi Mahdi , Garcia-Nieto Mario , Guinea Gustavo V. , Panetsos Fivos , Pérez-Rigueiro José , González-Nieto Daniel
Published: March 2021

Silk refers to a family of natural fibers spun by several species of invertebrates such as spiders and silkworms. In particular, silkworm silk, the silk spun by Bombyx mori larvae, has been primarily used in the textile industry and in clinical settings as a main component of sutures for tissue repairing and wound ligation. The biocompatibility, remarkable mechanical performance, controllable degradation, and the possibility of producing silk-based materials in several formats, have laid the basic principles that have triggered and extended the use of this material in regenerative medicine. The field of neural soft tissue engineering is not an exception, as it has taken advantage of the properties of silk to promote neuronal growth and nerve guidance. In addition, silk has notable intrinsic properties and the by-products derived from its degradation show anti-inflammatory and antioxidant properties. Finally, this material can be employed for the controlled release of factors and drugs, as well as for the encapsulation and implantation of exogenous stem and progenitor cells with therapeutic capacity. In this article, we review the state of the art on manufacturing methodologies and properties of fiber-based and non-fiber-based formats, as well as the application of silk-based biomaterials to neuroprotect and regenerate the damaged nervous system. We review previous studies that strategically have used silk to enhance therapeutics dealing with highly prevalent central and peripheral disorders such as stroke, Alzheimer’s disease, Parkinson’s disease, and peripheral trauma. Finally, we discuss previous research focused on the modification of this biomaterial, through biofunctionalization techniques and/or the creation of novel composite formulations, that aim to transform silk, beyond its natural performance, into more efficient silk-based-polymers towards the clinical arena of neuroprotection and regeneration in nervous system diseases.
Inhalationally Administered Semifluorinated Alkanes (SFAs) as Drug Carriers in an Experimental Model of Acute Respiratory Distress Syndrome
Authors: Otto Matthias , Krebs Jörg , Welker Peter , Holm René , Thiel Manfred , Gattinoni Luciano , Quintel Michael , Tsagogiorgas Charalambos
Published: March 2021

Aerosol therapy in patients suffering from acute respiratory distress syndrome (ARDS) has so far failed in improving patients’ outcomes. This might be because dependent lung areas cannot be reached by conventional aerosols. Due to their physicochemical properties, semifluorinated alkanes (SFAs) could address this problem. After induction of ARDS, 26 pigs were randomized into three groups: (1) control (Sham), (2) perfluorohexyloctane (F6H8), and (3) F6H8-ibuprofen. Using a nebulization catheter, (2) received 1 mL/kg F6H8 while (3) received 1 mL/kg F6H8 with 6 mg/mL ibuprofen. Ibuprofen plasma and lung tissue concentration, bronchoalveolar lavage (BAL) fluid concentration of TNF-α, IL-8, and IL-6, and lung mechanics were measured. The ibuprofen concentration was equally distributed to the dependent parts of the right lungs. Pharmacokinetic data demonstrated systemic absorption of ibuprofen proofing a transport across the alveolo-capillary membrane. A significantly lower TNF-α concentration was observed in (2) and (3) when compared to the control group (1). There were no significant differences in IL-8 and IL-6 concentrations and lung mechanics. F6H8 aerosol seemed to be a suitable carrier for pulmonary drug delivery to dependent ARDS lung regions without having negative effects on lung mechanics.
An Intelligent Fire-Protection Coating Based on Ammonium Polyphosphate/Epoxy Composites and Laser-Induced Graphene
Authors: Yang Weiwei , Liu Ying , Wei Jie , Li Xueli , Li Nianhua , Liu Jiping
Published: March 2021

Fire-protection coatings with a self-monitoring ability play a critical role in safety and security. An intelligent fire-protection coating can protect humans from personal and property damage. In this work, we report the fabrication of a low-cost and facile intelligent fire coating based on a composite of ammonium polyphosphate and epoxy (APP/EP). The composite was processed using laser scribing, which led to a laser-induced graphene (LIG) layer on the APP/EP surface via a photothermal effect. The C–O, C=O, P–O, and N−C bonds in the flame-retardant APP/EP composite were broken during the laser scribing, while the remaining carbon atoms recombined to generate the graphene layer. A proof-of-concept was achieved by demonstrating the use of LIG in supercapacitors, as a temperature sensor, and as a hazard detection device based on the shape memory effect of the APP/EP composite. The intelligent flame protection coating had a high flame retardancy, which increased the time to ignition (TTI) from 21 s to 57 s, and the limiting oxygen index (LOI) value increased to 37%. The total amount of heat and smoke released during combustion was effectively suppressed by ≈ 71.1% and ≈ 74.1%, respectively. The maximum mass-specific supercapacitance could reach 245.6 F·g−1. The additional LIG layer enables applications of the device as a LIG-APP/EP temperature sensor and allows for monitoring of the deformation according to its shape memory effect. The direct laser scribing of graphene from APP/EP in an air atmosphere provides a convenient and practical approach for the fabrication of flame-retardant electronics.
Composite P(3HB-3HV)-CS Spheres for Enhanced Antibiotic Efficiency
Authors: Gherasim Oana , Grumezescu Alexandru Mihai , Ficai Anton , Grumezescu Valentina , Holban Alina Maria , Gălățeanu Bianca , Hudiță Ariana
Published: March 2021

Natural-derived biopolymers are suitable candidates for developing specific and selective performance-enhanced antimicrobial formulations. Composite polymeric particles based on poly(3-hydroxybutyrate-co-3-hydroxyvalerate) and chitosan, P(3HB-3HV)-CS, are herein proposed as biocompatible and biodegradable delivery systems for bioproduced antibiotics: bacitracin (Bac), neomycin (Neo) and kanamycin (Kan). The stimuli-responsive spheres proved efficient platforms for boosting the antibiotic efficiency and antibacterial susceptibility, as evidenced against Gram-positive and Gram-negative strains. Absent or reduced proinflammatory effects were evidenced on macrophages in the case of Bac-/Neo- and Kan-loaded spheres, respectively. Moreover, these systems showed superior ability to sustain and promote the proliferation of dermal fibroblasts, as well as to preserve their ultrastructure (membrane and cytoskeleton integrity) and to exhibit anti-oxidant activity. The antibiotic-loaded P(3HB-3HV)-CS spheres proved efficient alternatives for antibacterial strategies.
Proteome Discoverer—A Community Enhanced Data Processing Suite for Protein Informatics
Authors: Orsburn Benjamin C.
Published: March 2021

Proteomics researchers today face an interesting challenge: how to choose among the dozens of data processing and analysis pipelines available for converting tandem mass spectrometry files to protein identifications. Due to the dominance of Orbitrap technology in proteomics in recent history, many researchers have defaulted to the vendor software Proteome Discoverer. Over the fourteen years since the initial release of the software, it has evolved in parallel with the increasingly complex demands faced by proteomics researchers. Today, Proteome Discoverer exists in two distinct forms with both powerful commercial versions and fully functional free versions in use in many labs today. Throughout the 11 main versions released to date, a central theme of the software has always been the ability to easily view and verify the spectra from which identifications are made. This ability is, even today, a key differentiator from other data analysis solutions. In this review I will attempt to summarize the history and evolution of Proteome Discoverer from its first launch to the versions in use today.
The Estimation of Magnetite Prospective Resources Based on Aeromagnetic Data: A Case Study of Qihe Area, Shandong Province, China
Authors: Gao Xiuhe , Xiong Shengqing , Yu Changchun , Zhang Dishuo , Wu Chengping
Published: March 2021

In the Qihe area, the magnetic anomalies caused by deep and concealed magnetite are weak and compared with ground surveys, airborne surveys further weaken the signals. Moreover, the magnetite in the Qihe area belongs to a contact-metasomatic deposit, and the magnetic anomalies caused by the magnetite and its mother rock overlap and interweave. Therefore, it is difficult to directly delineate the target areas of magnetite according to the measured aeromagnetic maps in Qihe or similar areas, let alone estimate prospective magnetite resources. This study tried to extract magnetite-caused anomalies from aeromagnetic data by using high-pass filtering. Then, a preliminary estimation of magnetite prospective resources was realized by the 3D inversion of the extracted anomalies. In order to improve the resolution and accuracy of the inversion results, a combined model-weighting function was proposed for the inversion. Meanwhile, the upper and lower bounds and positive and negative constraints were imposed on the model parameters to further improve the rationality of the inversion results. A theoretical model with deep and concealed magnetite was established. It demonstrated the feasibility of magnetite-caused anomaly extraction and magnetite prospective resource estimation. Finally, the magnetite-caused anomalies were extracted from the measured aeromagnetic data and were consistent with known drilling information. The distribution of underground magnetic bodies was obtained by the 3D inversion of extracted anomalies, and the existing drilling data were used to delineate the volume of magnetite. In this way, the prospective resources of magnetite in Qihe area were estimated.
A Surging Glacier Recognized by Remote Sensing on the Zangser Kangri Ice Field, Central Tibetan Plateau
Authors: Jia Bowen , Hou Shugui , Wang Yetang
Published: March 2021

A glacier surge, which is quasi-periodic and involves rapid flow, is an abnormal glacier motion. Although some glaciers have been found to be surging, little is known about surging glaciers on the Tibetan Plateau (TP), especially the Central and Northern TP. Here, we found a surging glacier (GLIMS ID: G085885E34389N) on the Zangser Kangri ice field (ZK), Central TP, by means of the digital elevation models (DEMs) from the Shuttle Radar Topography Mission (SRTM), TanDEM-X 90 m, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEMs, and High Mountain Asia 8-m DEM (HMA), combined with Landsat images and the Global Land Ice Velocity Extraction from Landsat 8 (GoLIVE) dataset. This surge event was confirmed by the crevasses, shear margin, and visible advancing snout shown in the Landsat images produced since 2014 and the HMA. The inter-comparison of these DEMs and the surface velocity changes showed that the surge event started between October 2012 and January 2014. The glacier may have also surged in the 1970s, based on a comparison between the topographical map and Landsat images. The glacier mass balance here has been slightly positive from 1999 onward (+0.03 ± 0.06 m w.e.a−1 from 1999 to 2015, +0.02 ± 0.07 m w.e.a−1 from 1999 to December 2011), which may indicate that the ZK is located on the southern edge of the mass balance anomaly on the TP. Combining with other surging glaciers on the Central and Northern TP, the relatively balanced mass condition, large size, and shallow slope can be associated with glacier surges on the Central and Northern TP.
Land Use and Land Cover Mapping Using RapidEye Imagery Based on a Novel Band Attention Deep Learning Method in the Three Gorges Reservoir Area
Authors: Zhang Xin , Du Ling , Tan Shen , Wu Fangming , Zhu Liang , Zeng Yuan , Wu Bingfang
Published: March 2021

Land use/land cover (LULC) change has been recognized as one of the most important indicators to study ecological and environmental changes. Remote sensing provides an effective way to map and monitor LULC change in real time and for large areas. However, with the increasing spatial resolution of remote sensing imagery, traditional classification approaches cannot fully represent the spectral and spatial information from objects and thus have limitations in classification results, such as the “salt and pepper” effect. Nowadays, the deep semantic segmentation methods have shown great potential to solve this challenge. In this study, we developed an adaptive band attention (BA) deep learning model based on U-Net to classify the LULC in the Three Gorges Reservoir Area (TGRA) combining RapidEye imagery and topographic information. The BA module adaptively weighted input bands in convolution layers to address the different importance of the bands. By comparing the performance of our model with two typical traditional pixel-based methods including classification and regression tree (CART) and random forest (RF), we found a higher overall accuracy (OA) and a higher Intersection over Union (IoU) for all classification categories using our model. The OA and mean IoU of our model were 0.77 and 0.60, respectively, with the BA module and were 0.75 and 0.58, respectively, without the BA module. The OA and mean IoU of CART and RF were both below 0.51 and 0.30, respectively, although RF slightly outperformed CART. Our model also showed a reasonable classification accuracy in independent areas well outside the training area, which indicates the strong model generalizability in the spatial domain. This study demonstrates the novelty of our proposed model for large-scale LULC mapping using high-resolution remote sensing data, which well overcomes the limitations of traditional classification approaches and suggests the consideration of band weighting in convolution layers.
A Deep Learning Framework for Recognizing Both Static and Dynamic Gestures
Authors: Mazhar Osama , Ramdani Sofiane , Cherubini Andrea
Published: March 2021

Intuitive user interfaces are indispensable to interact with the human centric smart environments. In this paper, we propose a unified framework that recognizes both static and dynamic gestures, using simple RGB vision (without depth sensing). This feature makes it suitable for inexpensive human-robot interaction in social or industrial settings. We employ a pose-driven spatial attention strategy, which guides our proposed Static and Dynamic gestures Network—StaDNet. From the image of the human upper body, we estimate his/her depth, along with the region-of-interest around his/her hands. The Convolutional Neural Network (CNN) in StaDNet is fine-tuned on a background-substituted hand gestures dataset. It is utilized to detect 10 static gestures for each hand as well as to obtain the hand image-embeddings. These are subsequently fused with the augmented pose vector and then passed to the stacked Long Short-Term Memory blocks. Thus, human-centred frame-wise information from the augmented pose vector and from the left/right hands image-embeddings are aggregated in time to predict the dynamic gestures of the performing person. In a number of experiments, we show that the proposed approach surpasses the state-of-the-art results on the large-scale Chalearn 2016 dataset. Moreover, we transfer the knowledge learned through the proposed methodology to the Praxis gestures dataset, and the obtained results also outscore the state-of-the-art on this dataset.
Intelligent Transportation Related Complex Systems and Sensors
Authors: Kyamakya Kyandoghere , Chedjou Jean Chamberlain , Al-Machot Fadi , Haj Mosa Ahmad , Bagula Antoine
Published: March 2021

Building around innovative services related to different modes of transport and traffic management, intelligent transport systems (ITSs) are being widely adopted worldwide to improve the efficiency and safety of the transportation system [...]
IoT Data Qualification for a Logistic Chain Traceability Smart Contract
Authors: Ahmed Mohamed , Taconet Chantal , Ould Mohamed , Chabridon Sophie , Bouzeghoub Amel
Published: March 2021

In the logistic chain domain, the traceability of shipments in their entire delivery process from the shipper to the consignee involves many stakeholders. From the traceability data, contractual decisions may be taken such as incident detection, validation of the delivery or billing. The stakeholders require transparency in the whole process. The combination of the Internet of Things (IoT) and the blockchain paradigms helps in the development of automated and trusted systems. In this context, ensuring the quality of the IoT data is an absolute requirement for the adoption of those technologies. In this article, we propose an approach to assess the data quality (DQ) of IoT data sources using a logistic traceability smart contract developed on top of a blockchain. We select the quality dimensions relevant to our context, namely accuracy, completeness, consistency and currentness, with a proposition of their corresponding measurement methods. We also propose a data quality model specific to the logistic chain domain and a distributed traceability architecture. The evaluation of the proposal shows the capacity of the proposed method to assess the IoT data quality and ensure the user agreement on the data qualification rules. The proposed solution opens new opportunities in the development of automated logistic traceability systems.
Self-Difference Convolutional Neural Network for Facial Expression Recognition
Authors: Liu Leyuan , Jiang Rubin , Huo Jiao , Chen Jingying
Published: March 2021

Facial expression recognition (FER) is a challenging problem due to the intra-class variation caused by subject identities. In this paper, a self-difference convolutional network (SD-CNN) is proposed to address the intra-class variation issue in FER. First, the SD-CNN uses a conditional generative adversarial network to generate the six typical facial expressions for the same subject in the testing image. Second, six compact and light-weighted difference-based CNNs, called DiffNets, are designed for classifying facial expressions. Each DiffNet extracts a pair of deep features from the testing image and one of the six synthesized expression images, and compares the difference between the deep feature pair. In this way, any potential facial expression in the testing image has an opportunity to be compared with the synthesized “Self”—an image of the same subject with the same facial expression as the testing image. As most of the self-difference features of the images with the same facial expression gather tightly in the feature space, the intra-class variation issue is significantly alleviated. The proposed SD-CNN is extensively evaluated on two widely-used facial expression datasets: CK+ and Oulu-CASIA. Experimental results demonstrate that the SD-CNN achieves state-of-the-art performance with accuracies of 99.7% on CK+ and 91.3% on Oulu-CASIA, respectively. Moreover, the model size of the online processing part of the SD-CNN is only 9.54 MB (1.59 MB ×6), which enables the SD-CNN to run on low-cost hardware.
Evidence of Negative Capacitance and Capacitance Modulation by Light and Mechanical Stimuli in Pt/ZnO/Pt Schottky Junctions
Authors: Joly Raoul , Girod Stéphanie , Adjeroud Noureddine , Grysan Patrick , Polesel-Maris Jérôme
Published: March 2021

We report on the evidence of negative capacitance values in a system consisting of metal-semiconductor-metal (MSM) structures, with Schottky junctions made of zinc oxide thin films deposited by Atomic Layer Deposition (ALD) on top of platinum interdigitated electrodes (IDE). The MSM structures were studied over a wide frequency range, between 20 Hz and 1 MHz. Light and mechanical strain applied to the device modulate positive or negative capacitance and conductance characteristics by tuning the flow of electrons involved in the conduction mechanisms. A complete study was carried out by measuring the capacitance and conductance characteristics under the influence of both dark and light conditions, over an extended range of applied bias voltage and frequency. An impact-loss process linked to the injection of hot electrons at the interface trap states of the metal-semiconductor junction is proposed to be at the origin of the apparition of the negative capacitance values. These negative values are preceded by a local increase of the capacitance associated with the accumulation of trapped electrons at the interface trap states. Thus, we propose a simple device where the capacitance values can be modulated over a wide frequency range via the action of light and strain, while using cleanroom-compatible materials for fabrication. These results open up new perspectives and applications for the miniaturization of highly sensitive and low power consumption environmental sensors, as well as for broadband impedance matching in radio frequency applications.
Theoretical Comparison of the Effects of Different Traffic Conditions on Urban Road Environmental External Costs
Authors: Zefreh Mohammad Maghrour , Torok Adam
Published: March 2021

External costs that are associated with air pollution, climate change linked to greenhouse gas emissions (GHG), and noise are among the most important environmental externalities that are generated by road transport, which have been well monetized. This paper theoretically investigates the effects of different traffic conditions on the environmental external costs of urban roads where traffic flow is more complicated than un-interrupted traffic flows. A Monte Carlo method is used to theoretically simulate traffic speed in different traffic conditions. Subsequently, the emitted carbon dioxide (CO2), nitrogen oxides (NOx), carbon monoxide (CO), particulate matter (PM), sulfur dioxide (SO2), and noise were estimated in each of the theoretically simulated traffic conditions. Finally, the environmental external costs in each traffic condition were calculated taking the EU average costs values into account. The results showed that, when compared to free-flow condition, the total air pollutant and GHG external costs (€2010) have been increased by 6%, 31%, 44%, 50%, and 93% in under-saturated flow, accelerated flow, decelerated flow, congestion, and over-saturated congestion, respectively. Furthermore, the total noise cost (€2010/year/person exposed), as compared to free-flow condition, has been decreased by 2%, 11%, 12%, 36%, and 69% in accelerated flow, under-saturated flow, congestion, over-saturated congestion, and decelerated flow, respectively.
Extending Multilevel Statistical Entropy Analysis towards Plastic Recyclability Prediction
Authors: Nimmegeers Philippe , Parchomenko Alexej , De Meulenaere Paul , D’hooge Dagmar R. , Van Steenberge Paul H. M. , Rechberger Helmut , Billen Pieter
Published: March 2021

Multilevel statistical entropy analysis (SEA) is a method that has been recently proposed to evaluate circular economy strategies on the material, component and product levels to identify critical stages of resource and functionality losses. However, the comparison of technological alternatives may be difficult, and equal entropies do not necessarily correspond with equal recyclability. A coupling with energy consumption aspects is strongly recommended but largely lacking. The aim of this paper is to improve the multilevel SEA method to reliably assess the recyclability of plastics. Therefore, the multilevel SEA method is first applied to a conceptual case study of a fictitious bag filled with plastics, and the possibilities and limitations of the method are highlighted. Subsequently, it is proposed to extend the method with the computation of the relative decomposition energies of components and products. Finally, two recyclability metrics are proposed. A plastic waste collection bag filled with plastic bottles is used as a case study to illustrate the potential of the developed extended multilevel SEA method. The proposed extension allows us to estimate the recyclability of plastics. In future work, this method will be refined and other potential extensions will be studied together with applications to real-life plastic products and plastic waste streams.
State Ibuism and Women’s Empowerment in Indonesia: Governmentality and Political Subjectification of Chinese Benteng Women
Authors: Hyunanda Vinny Flaviana , Palacios Ramírez José , López-Martínez Gabriel , Meseguer-Sánchez Víctor
Published: March 2021

This paper examines how the patriarchal understanding of “women’s empowerment” in Indonesia instrumentalizes the notion of Ibu, a social construction of womanhood based on a societally determined idea of domestication and productivity. Through the establishment of a saving and lending cooperative, a group of Chinese Benteng women was subjected to a neoliberal development project that operated on the basis of a market-driven society and promoted a “gender mainstreaming” discourse to enhance this participatory project. They were introduced by a women’s NGO as their broker. The notion of “women’s empowerment” inspired a governmental operation aimed at these women, promoting the particular qualities of the dutiful housewife, devoted mother, and socially active member of Indonesian society. These characters were distinguished by their high level of devotion to community volunteering and to the state’s apolitical project, thus depoliticizing and deradicalizing the feminist view of women’s empowerment; this was simultaneously balanced with the promotion of the traditional gender roles of wife and mother. Such a discourse also molds women’s desires to voluntarily subscribe to such a social construction of womanhood and, at the same time, circumvents objections to any form of women’s subordination reproduced by the same rhetoric of “women’s empowerment”. By employing an ethnographic methodology, this article argues that the patriarchal view of “women’s empowerment” emerged as a deceitful doctrine to prompt Chinese Benteng women into internalizing certain qualities according to the gendered conception of womanhood in Indonesia. This article concludes that the patronizing and dominating aspects of State Ibuism have normalized Indonesian society’s expectations and desires with regard to women’s empowerment.
Application of Growth Activators and Plant Growth-Promoting Rhizobacteria as a Method of Introducing a “Farm to Fork” Strategy in Crop Management of Winter Oilseed
Authors: Artyszak Arkadiusz , Gozdowski Dariusz
Published: March 2021

In the European Union, out of concern for the quality of the natural environment, agriculture aims to limit the doses of mineral nitrogen to mitigate nitrogen leaching into the groundwater and N2O emissions into the atmosphere. This requires a search for new crop management for more environmentally friendly production. The aim of the study was to evaluate crop management technologies that would allow farmers to obtain high yields without high doses of nitrogen fertilizers. The study was conducted in Poland in 2016–2017 and 2018–2019 to test the effects of growth activators without an additional product and with a product containing plant growth-promoting rhizobacteria in the production of winter oilseed rape, reducing the nitrogen dose by 30%. The results obtained in the study show a positive effect of the studied treatments on seed yield, which was higher by 9.8 and 7.7%, and fat yield, higher by 11.4 and 9.2%, respectively, compared to those for the control treatment in which the full nitrogen dose was applied. Taking into account the scale of oilseed rape production in Poland, this means savings of 52.8 thousand tonnes of mineral nitrogen per year. Therefore, introducing the researched solutions into agricultural practice would lead to measurable benefits for the natural environment.
On the Role of Perception: Understanding Stakeholders’ Collaboration in Natural Resources Management through the Evolutionary Theory of Innovation
Authors: Rodríguez-Rodríguez Gonzalo , Ballesteros Hugo M. , Martínez-Cabrera Helena , Vilela Raúl , Pennino María Grazia , Bellido José María
Published: March 2021

Natural resources management deals with highly complex socioecological systems. This complexity raises a conundrum, since wide-ranging knowledge from different sources and types is needed, but at the same time none of these types of knowledge is able by itself to provide the basis for a viable productive system, and mismatches between the two of them are common. Therefore, a growing body of literature has examined the integration of different types of knowledge in fisheries management. In this paper, we aim to contribute to this ongoing debate by integrating the evolutionary theory of innovation—and specifically the concept of proximity—and the theory of perception. We set up a theoretical framework that is able to explain not only why the different types of knowledge differ, but also why they should differ and why this divergence is useful to develop fisheries management. This framework is illustrated through a well-known complex scenario, as was the implementation of the Landing Obligation (LO) in Europe. We conclude that diversity (distance) between types of knowledge is essential for interactive learning, innovation, the incorporation of new ideas or to avoid lock-in, etc. At the same time, cognitive, institutional, geographical, etc. proximity is needed for effective communication, participation and dialogue.
Effects of a Battery Energy Storage System on the Operating Schedule of a Renewable Energy-Based Time-of-Use Rate Industrial User under the Demand Bidding Mechanism of Taipower
Authors: Tsai Cheng-Ta , Cheng Yu-Shan , Lin Kuen-Huei , Chen Chun-Lung
Published: March 2021

Due to the increased development of the smart grid, it is becoming crucial to have an efficient energy management system for a time-of-use (TOU) rate industrial user in Taiwan. In this paper, an extension of the direct search method (DSM) is developed to deal with the operating schedule of a TOU rate industrial user under the demand bidding mechanism of Taipower. To maximize the total incentive obtained from the Taiwan Power Company (TPC, namely Taipower), several operational strategies using a battery energy storage system (BESS) are evaluated in the study to perform peak shaving and realize energy conservation. The effectiveness of the proposed DSM algorithm is validated with the TOU rate industrial user of the TPC. Numerical experiments are carried out to provide a favorable indication of whether to invest in a BESS for the renewable energy-based TOU rate industrial user in order to execute the demand bidding program (DBP).
Community Assessment of Flood Risks and Early Warning System in Ratu Watershed, Koshi Basin, Nepal
Authors: Bajracharya Sagar Ratna , Khanal Narendra Raj , Nepal Pashupati , Rai Sundar Kumar , Ghimire Pawan Kumar , Pradhan Neera Shrestha
Published: March 2021

Nepal is highly vulnerable to flood-related disasters which cause considerable loss of lives and property. The vulnerability of communities to flood-related hazards can be reduced by proper planning, preparedness, and responses using various structural and nonstructural measures. The community-based flood early warning system is one such tool that enables local communities to enhance their resilience to flooding risks. This paper highlights the efficacy of the community assessment of flood risks and early warning systems. Using qualitative and quantitative methods, this paper evaluates the progress of a community-based flood early warning system implemented in the Ratu River—a small tributary of the Koshi River. The establishment of a community network in 2015 was instrumental in the dissemination of flood early warning information and in building local capacities to understand the risks and take timely action. The flood early warning resulted in awareness-raising, strengthened upstream–downstream linkages, and resulted in a greater willingness among communities to help each other prepare for flood disasters in the Ratu watershed.
Understanding Customer Responses to Service Failures during the COVID-19 Pandemic for Sustained Restaurant Businesses: Focusing on Guanxi
Authors: Zhang Chenyu , Park Junkyu , Bonn Mark A. , Cho Meehee
Published: March 2021

Due to the COVID-19 pandemic, restaurants worldwide, including China, have been forced to protect public health by following food safety standards and adapting to the necessary social distancing practices. Accordingly, restaurant diners who are concerned about food safety and unsure of whether it is truly safe to dine out, put more importance on the entire stages of service consumption. Restaurants must make their best efforts to minimize service failures in their service provision process and outcomes. Given that customers from different cultures are reported to evaluate service quality differently, this study was designed to investigate what actions Chinese customers who encounter service failures would take under the influence of Guanxi. Guanxi represents Chinese attitudes towards long-term individual and business relationships and ultimately involves moral obligations and mutual favors. Analyzing our structural equation model using 439 responses obtained from Chinese diners, this study determined that Chinese consumers would react differently in the service process failures and outcome failures in terms of negative word-of-mouth, direct complaints, switching intention, and revisit intention. More importantly, this study confirmed the significant moderating effects of Guanxi within the proposed relationships. Based on the study’s findings, useful implications are provided for academics and practitioners regarding sustained restaurant businesses.
Implementation and Evaluation of Physical, Hybrid, and Virtual Testbeds for Cybersecurity Analysis of Industrial Control Systems
Authors: Robles-Durazno Andres , Moradpoor Naghmeh , McWhinnie James , Russell Gordon , Porcel-Bustamante Jorge
Published: March 2021

Industrial Control Systems are an essential part of our daily lives and can be found in industries such as oil, utilities, and manufacturing. Rapid growth in technology has introduced industrial components with network capabilities that allow them to communicate with traditional computer networks, thus increasing their exposure to cyber-attacks. Current research on Industrial Control Systems suffer from lack of technical information as these systems are part of critical infrastructures. To overcome this, researchers have employed different types of testbeds to develop their mechanisms of cyber-attack detection and prevention. This manuscript describes, implements, and evaluates physical, hybrid, and virtual application of a clean water supply system developed for cybersecurity research. The results show that physical testbeds allow an understanding of the behaviour and dynamics of control components like sensors and actuators, which might be affected by external influences such as noise, vibration, temperature, and non-ideal device behaviour. Although, hybrid testbeds reduce the cost of implementation, they ignore the physical dynamics of the system as explained above. Virtual testbeds are the cheapest option in comparison with physical and hybrid testbeds; however, they provide a limited view of the control system operation that could have negative consequences when developing a detection/prevention system.
Towards a Novel Computer-Aided Optimization of Microreactors: Techno-Economic Evaluation of an Immobilized Enzyme System
Authors: Pietrek Philip , Kraut Manfred , Dittmeyer Roland
Published: March 2021

Immobilized multi-enzyme cascades are increasingly used in microfluidic devices. In particular, their application in continuous flow reactors shows great potential, utilizing the benefits of reusability and control of the reaction conditions. However, capitalizing on this potential is challenging and requires detailed knowledge of the investigated system. Here, we show the application of computational methods for optimization with multi-level reactor design (MLRD) methodology based on the underlying physical and chemical processes. We optimize a stereoselective reduction of a diketone catalyzed by ketoreductase (Gre2) and Nicotinamidadenindinukleotidphosphat (NADPH) cofactor regeneration with glucose dehydrogenase (GDH). Both enzymes are separately immobilized on magnetic beads forming a packed bed within the microreactor. We derive optimal reactor feed concentrations and enzyme ratios for enhanced performance and a basic economic model in order to maximize the techno-economic performance (TEP) for the first reduction of 5-nitrononane-2,8-dione.
SARS-CoV-2 Infection and Antibody Response in a Symptomatic Cat from Italy with Intestinal B-Cell Lymphoma
Authors: Klaus Julia , Palizzotto Carlo , Zini Eric , Meli Marina L. , Leo Chiara , Egberink Herman , Zhao Shan , Hofmann-Lehmann Regina
Published: March 2021

Since the coronavirus disease (COVID-19) pandemic was first identified in early 2020, rare cases of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection in pet cats have been reported worldwide. Some reports of cats with SARS-CoV-2 showed self-limiting respiratory or gastrointestinal disease after suspected human-to-feline transmission via close contact with humans with SARS-CoV-2. In the present study, we investigated a cat with SARS-CoV-2 that was presented to a private animal clinic in Northern Italy in May 2020 in a weak clinical condition due to an underlying intestinal B-cell lymphoma. The cat developed signs of respiratory tract disease, including a sneeze, a cough and ocular discharge, three days after an oropharyngeal swab tested positive for SARS-CoV-2 viral RNA using two real-time reverse transcriptase polymerase chain reaction (RT-qPCR) assays for the envelope (E) and RNA-dependent RNA polymerase (RdRp) gene. Thus, SARS-CoV-2 viral RNA was detectable prior to the onset of clinical signs. Five and six months after positive molecular results, the serological testing substantiated the presence of a SARS-CoV-2 infection in the cat with the detection of anti-SARS-CoV-2 receptor binding domain (RBD) immunoglobulin (IgG) antibodies and neutralizing activity in a surrogate virus neutralization assay (sVNT). To the best of our knowledge, this extends the known duration of seropositivity of SARS-CoV-2 in a cat. Our study provides further evidence that cats are susceptible to SARS-CoV-2 under natural conditions and strengthens the assumption that comorbidities may play a role in the development of clinical disease.