bluuebunny/crossref_metadata_2025 huggingface dataset:
West Nile Virus in Brazil
Authors: Costa Érica Azevedo , Giovanetti Marta , Silva Catenacci Lilian , Fonseca Vagner , Aburjaile Flávia Figueira , Chalhoub Flávia L. L. , Xavier Joilson , Campos de Melo Iani Felipe , da Cunha e Silva Vieira Marcelo Adriano , Freitas Henriques Danielle , Medeiros Daniele Barbosa de Almeida , Guedes Maria Isabel Maldonado Coelho , Senra Álvares da Silva Santos Beatriz , Gonçalves Silva Aila Solimar , de Pino Albuquerque Maranhão Renata , da Costa Faria Nieli Rodrigues , Farinelli de Siqueira Renata , de Oliveira Tulio , Ribeiro Leite Jardim Cavalcante Karina , Oliveira de Moura Noely Fabiana , Pecego Martins Romano Alessandro , Campelo de Albuquerque Carlos F. , Soares Feitosa Lauro César , Martins Bayeux José Joffre , Bertoni Cavalcanti Teixeira Raffaella , Lisboa Lobato Osmaikon , da Costa Silva Silvokleio , Bispo de Filippis Ana Maria , Venâncio da Cunha Rivaldo , Lourenço José , Alcantara Luiz Carlos Junior
Published: July 2021

Background: West Nile virus (WNV) was first sequenced in Brazil in 2019, when it was isolated from a horse in the Espírito Santo state. Despite multiple studies reporting serological evidence suggestive of past circulation since 2004, WNV remains a low priority for surveillance and public health, such that much is still unknown about its genomic diversity, evolution, and transmission in the country. Methods: A combination of diagnostic assays, nanopore sequencing, phylogenetic inference, and epidemiological modeling are here used to provide a holistic overview of what is known about WNV in Brazil. Results: We report new genetic evidence of WNV circulation in southern (Minas Gerais, São Paulo) and northeastern (Piauí) states isolated from equine red blood cells. A novel, climate-informed theoretical perspective of the potential transmission of WNV across the country highlights the state of Piauí as particularly relevant for WNV epidemiology in Brazil, although it does not reject possible circulation in other states. Conclusion: Our output demonstrates the scarceness of existing data, and that although there is sufficient evidence for the circulation and persistence of the virus, much is still unknown on its local evolution, epidemiology, and activity. We advocate for a shift to active surveillance, to ensure adequate preparedness for future epidemics with spill-over potential to humans.
Impact of Endocytosis Mechanisms for the Receptors Targeted by the Currently Approved Antibody-Drug Conjugates (ADCs)—A Necessity for Future ADC Research and Development
Authors: Hammood Manar , Craig Andrew , Leyton Jeffrey
Published: July 2021

Biologically-based therapies increasingly rely on the endocytic cycle of internalization and exocytosis of target receptors for cancer therapies. However, receptor trafficking pathways (endosomal sorting (recycling, lysosome localization) and lateral membrane movement) are often dysfunctional in cancer. Antibody-drug conjugates (ADCs) have revitalized the concept of targeted chemotherapy by coupling inhibitory antibodies to cytotoxic payloads. Significant advances in ADC technology and format, and target biology have hastened the FDA approval of nine ADCs (four since 2019). Although the links between aberrant endocytic machinery and cancer are emerging, the impact of dysregulated internalization processes of ADC targets and response rates or resistance have not been well studied. This is despite the reliance on ADC uptake and trafficking to lysosomes for linker cleavage and payload release. In this review, we describe what is known about all the target antigens for the currently approved ADCs. Specifically, internalization efficiency and relevant intracellular sorting activities are described for each receptor under normal processes, and when complexed to an ADC. In addition, we discuss aberrant endocytic processes that have been directly linked to preclinical ADC resistance mechanisms. The implications of endocytosis in regard to therapeutic effectiveness in the clinic are also described. Unexpectedly, information on endocytosis is scarce (absent for two receptors). Moreover, much of what is known about endocytosis is not in the context of receptor-ADC/antibody complexes. This review provides a deeper understanding of the pertinent principles of receptor endocytosis for the currently approved ADCs.
An Adenovirus Vector Expressing FMDV RNA Polymerase Combined with a Chimeric VLP Harboring a Neutralizing Epitope as a Prime Boost Strategy to Induce FMDV-Specific Humoral and Cellular Responses
Authors: Rangel Giselle , Martín Verónica , Bárcena Juan , Blanco Esther , Alejo Alí
Published: July 2021

Foot and mouth disease is a highly contagious disease affecting cattle, sheep, and swine among other cloven-hoofed animals that imposes serious economic burden by its direct effects on farm productivity as well as on commerce of farmed produce. Vaccination using inactivated viral strains of the different serotypes is an effective protective measure, but has several drawbacks including a lack of cross protection and the perils associated with the large-scale growth of infectious virus. We have previously developed chimeric virus-like particles (VLPs) bearing an FMDV epitope which induced strong specific humoral responses in vaccinated pigs but conferred only partial protection against homologous challenge. While this and other FMD vaccines under development mostly rely on the induction of neutralizing responses, it is thought that induction of specific T-cell responses might improve both cross protective efficacy as well as duration of immunity. Therefore, we here describe the development of a recombinant adenovirus expressing the highly conserved nonstructural FMDV 3D protein as well as its capacity to induce specific T-cell responses in a murine model. We further describe the generation of an FMDV serotype C-specific chimeric VLP and analyze the immunogenicity of two different prime-boost strategies combining both elements in mice. This combination can effectively induce both humoral and cellular FMDV-specific responses eliciting high titers of ELISA and neutralizing antibodies anti-FMDV as well as a high frequency of IFNγ-secreting cells. These results provide the basis for further testing of this anti FMD vaccination strategy in cattle or pig, two of the most relevant natural host of this pathogen.
Hacking Pancreatic Cancer: Present and Future of Personalized Medicine
Authors: Di Federico Alessandro , Tateo Valentina , Parisi Claudia , Formica Francesca , Carloni Riccardo , Frega Giorgio , Rizzo Alessandro , Ricci Dalia , Di Marco Mariacristina , Palloni Andrea , Brandi Giovanni
Published: July 2021

Pancreatic cancer (PC) is a recalcitrant disease characterized by high incidence and poor prognosis. The extremely complex genomic landscape of PC has a deep influence on cultivating a tumor microenvironment, resulting in the promotion of tumor growth, drug resistance, and immune escape mechanisms. Despite outstanding progress in personalized medicine achieved for many types of cancer, chemotherapy still represents the mainstay of treatment for PC. Olaparib was the first agent to demonstrate a significant benefit in a biomarker-selected population, opening the doors for a personalized approach. Despite the failure of a large number of studies testing targeted agents or immunotherapy to demonstrate benefits over standard chemotherapy regimens, some interesting agents, alone or in combination with other drugs, have achieved promising results. A wide spectrum of therapeutic strategies, including immune-checkpoint inhibitors tyrosine kinase inhibitors and agents targeting metabolic pathways or the tumor microenvironment, is currently under investigation. In this review, we aim to provide a comprehensive overview of the current landscape and future directions of personalized medicine for patients affected by PC.
Risk of Hospitalization for Adverse Drug Events in Women and Men: A Post Hoc Analysis of an Active Pharmacovigilance Study in Italian Emergency Departments
Authors: Crescioli Giada , Boscia Ennio , Bettiol Alessandra , Pagani Silvia , Spada Giulia , Vighi Giuditta , Bonaiuti Roberto , Venegoni Mauro , Vighi Giuseppe , Vannacci Alfredo , Lombardi Niccolò ,   on behalf of the MEREAFaPS Study Group
Published: July 2021

This post hoc analysis of an Italian active pharmacovigilance study describes pharmacological differences of ADEs leading to emergency department (ED) visits and hospitalization in women and men. During the study period (January 2007–December 2018), 61,855 reports of ADEs leading to ED visits were collected. Overall, 30.6% of ADEs resulted in hospitalization (30% in women and 31% in men). Multivariate logistic regression showed that, among women, drug classes significantly associated with an increased risk of hospitalization were heparins (ROR 1.41, CI 1.13–176), antidepressants (ROR 1.12, CI 1.03–1.23) and antidiabetics (ROR 1.13, CI 1.02–1.24). Among men, only vitamin K antagonists (ROR 1.28, CI 1.09–1.50), opioids (ROR 1.30, CI 1.06–1.60) and digitalis glycosides (ROR 1.32, CI 1.09–1.59) were associated with a higher risk of hospitalization. Overall, older age, multiple suspected drugs and the presence of comorbidities were significantly associated with a higher risk of hospitalization. A significantly reduced risk of hospitalization was observed in both women and men experiencing an adverse event following immunization (ROR 0.36, CI 0.27–0.48 and 0.83, 0.42–0.74, respectively) compared to drugs. Results obtained from this real-world analysis highlight important aspects of drug safety between sexes.
Current and Future Pathotyping Platforms for Plasmodiophora brassicae in Canada
Authors: Tso Heather H. , Galindo-González Leonardo , Strelkov Stephen E.
Published: July 2021

Clubroot, caused by Plasmodiophora brassicae, is one of the most detrimental threats to crucifers worldwide and has emerged as an important disease of canola (Brassica napus) in Canada. At present, pathotypes are distinguished phenotypically by their virulence patterns on host differential sets, including the systems of Williams, Somé et al., the European Clubroot Differential set, and most recently the Canadian Clubroot Differential set and the Sinitic Clubroot Differential set. Although these are frequently used because of their simplicity of application, they are time-consuming, labor-intensive, and can lack sensitivity. Early, preventative pathotype detection is imperative to maximize productivity and promote sustainable crop production. The decreased turnaround time and increased sensitivity and specificity of genotypic pathotyping will be valuable for the development of integrated clubroot management plans, and interest in molecular techniques to complement phenotypic methods is increasing. This review provides a synopsis of current and future molecular pathotyping platforms for P. brassicae and aims to provide information on techniques that may be most suitable for the development of rapid, reliable, and cost-effective pathotyping assays.
Protein Carbonylation: Emerging Roles in Plant Redox Biology and Future Prospects
Authors: Tola Adesola J. , Jaballi Amal , Missihoun Tagnon D.
Published: July 2021

Plants are sessile in nature and they perceive and react to environmental stresses such as abiotic and biotic factors. These induce a change in the cellular homeostasis of reactive oxygen species (ROS). ROS are known to react with cellular components, including DNA, lipids, and proteins, and to interfere with hormone signaling via several post-translational modifications (PTMs). Protein carbonylation (PC) is a non-enzymatic and irreversible PTM induced by ROS. The non-enzymatic feature of the carbonylation reaction has slowed the efforts to identify functions regulated by PC in plants. Yet, in prokaryotic and animal cells, studies have shown the relevance of protein carbonylation as a signal transduction mechanism in physiological processes including hydrogen peroxide sensing, cell proliferation and survival, ferroptosis, and antioxidant response. In this review, we provide a detailed update on the most recent findings pertaining to the role of PC and its implications in various physiological processes in plants. By leveraging the progress made in bacteria and animals, we highlight the main challenges in studying the impacts of carbonylation on protein functions in vivo and the knowledge gap in plants. Inspired by the success stories in animal sciences, we then suggest a few approaches that could be undertaken to overcome these challenges in plant research. Overall, this review describes the state of protein carbonylation research in plants and proposes new research avenues on the link between protein carbonylation and plant redox biology.
In Silico Characterization of the Interaction between the PBP2a “Decoy” Protein of Resistant Staphylococcus aureus and the Monomeric Units of Eudragit E-100 and Poly(Maleic Acid-alt-Octadecene) Polymers
Authors: Liscano Yamil , Amú Ana , González Astrid , Oñate-Garzón Jose , Salamanca Constain H.
Published: July 2021

Antimicrobial treatment alternatives for methicillin-resistant Staphylococcus aureus (MRSA) are increasingly limited. MRSA strains are resistant to methicillin due to the formation of β-lactamase enzymes, as well as the acquisition of the mecA gene, which encodes the penicillin-binding protein (PBP2a) that reduces the affinity for β-lactam drugs. Previous studies have shown that the use of ampicillin-loaded nanoparticles can improve antimicrobial activity on resistant S. aureus strains. However, the biological mechanism of this effect has not yet been properly elucidated. Therefore, this short communication focused on characterizing the in silico interactions of the PBP2a membrane receptor protein from S. aureus against the monomeric units of two polymeric materials previously used in the development of different nanoparticles loaded with ampicillin. Such polymers correspond to Eudragit E-100 chloride (EuCl) and the sodium salt of poly(maleic acid-alt-octadecene) (PAM-18Na). For this, molecular coupling studies were carried out in the active site of the PBP2a protein with the monomeric units of both polymers in neutral and ionized form, as well as with ampicillin antibiotic (model β-lactam drug). The results showed that ampicillin, as well as the monomeric units of EuCl and PAM18Na, described a slight binding free energy to the PBPa2 protein. In addition, it was found that the amino acids of the active site of the PBPa2 protein have interactions of different types and intensities, suggesting, in turn, different forms of protein–substrate coupling.
The Role of Ionic Liquids on Biomass Liquefaction—A Short Review of the Recent Advances
Authors: Cristino Ana , Logan Declan , Bordado João , Galhano dos Santos Rui
Published: July 2021

Biomass is recognised as one of the most attractive feedstocks among the alternative resources, having a high potential for the sustainable production of valuable chemicals and biofuels. Due to its abundance, convenience, carbon neutrality and eco-friendliness, biomass is believed to positively impact the current environmental crisis caused by the extensive use of petroleum resources. For this reason, the search for processes that can convert this feedstock, resolving some inherent drawbacks, is needed. Biomass liquefaction using ionic liquids (ILs) as catalysts has received appreciable attention in renewable fuels and chemicals production. With the potential for a substantial number of anion and cation pairings, ILs can be an attractive medium towards reusability and sustainability for these processes due to the unique and tunable combinations of their functional groups-and, therefore, their properties. In this review, several studies using ILs in biomass liquefaction are compared and discussed. With a particular emphasis on the last five years, advantages and disadvantages will be discussed using this class of liquids addressing essential issues such as yields, reusability and conversion, among others.
Effects of Cowl-Induced Expansion on the Wave Complex Induced by Oblique Detonation Wave Reflection
Authors: Wang Aifeng , Shang Jiahao , Wang Qiu , Wang Kuanliang
Published: July 2021

Oblique detonation wave (ODW) reflection on the upper wall leads to a sophisticated wave complex, whose stability is critical to the application of oblique detonation engines. The unstable wave complex characterized with a continuous moving Mach stem has been observed, but the corresponding re-stability adjusting method is still unclear so far. In this study, the cowl-induced expansion wave based on the model with an upper-side expansion wall is introduced, and the ODW dynamics have been analyzed using the reactive Euler equations with a two-step induction–reaction kinetic model. With the addition of a cowl-induced expansion wave, the re-stabilized Mach stem has been distinguished. This re-stability is determined by the weakened secondary reflection wave of lower wall, while the final location of Mach stem is not sensitive to the position of the expansion corner. The re-stabilized ODW structure is also basically irrelevant to the expansion angle, while it may shift to unstable due to the merging of subsonic zones. Transient phenomena for the unstable state have been also discussed, clarifying fine wave structures further.
Study of the Microstructural and First Hydrogenation Properties of TiFe Alloy with Zr, Mn and V as Additives
Authors: Patel Abhishek , Duguay Alexandre , Tougas Bernard , Neumann Bettina , Schade Chris , Sharma Pratibha , Huot Jacques
Published: July 2021

In this paper, we report the effect of adding Zr + V or Zr + V + Mn to TiFe alloy on microstructure and hydrogen storage properties. The addition of only V was not enough to produce a minimum amount of secondary phase and, therefore, the first hydrogenation at room temperature under a hydrogen pressure of 20 bars was impossible. When 2 wt.% Zr + 2 wt.% V or 2 wt.% Zr + 2 wt.% V + 2 wt.% Mn is added to TiFe, the alloy shows a finely distributed Ti2Fe-like secondary phase. These alloys presented a fast first hydrogenation and a high capacity. The rate-limiting step was found to be 3D growth, diffusion controlled with decreasing interface velocity. This is consistent with the hypothesis that the fast reaction is likely to be the presence of Ti2Fe-like secondary phases that act as a gateway for hydrogen.
The Effect of Topology on Phase Behavior under Confinement
Authors: Boelens Arnout M. P. , Tchelepi Hamdi A.
Published: July 2021

This work studies how morphology (i.e., the shape of a structure) and topology (i.e., how different structures are connected) influence wall adsorption and capillary condensation under tight confinement. Numerical simulations based on classical density functional theory (cDFT) are run for a wide variety of geometries using both hard-sphere and Lennard-Jones fluids. These cDFT computations are compared to results obtained using the Minkowski functionals. It is found that the Minkowski functionals can provide a good description of the behavior of Lennard-Jones fluids down to small system sizes. In addition, through decomposition of the free energy, the Minkowski functionals provide a good framework to better understand what are the dominant contributions to the phase behavior of a system. Lastly, while studying the phase envelope shift as a function of the Minkowski functionals it is found that topology has a different effect depending on whether the phase transition under consideration is a continuous or a discrete (first-order) transition.
Application of Deep, Vacuum, and Air Frying Methods to Fry Chub Mackerel (Scomber japonicus)
Authors: Negara Bertoka Fajar Surya Perwira , Lee Mi-Jeong , Tirtawijaya Gabriel , Cho Woo-Hee , Sohn Jae-Hak , Kim Jin-Soo , Choi Jae-Suk
Published: July 2021

Frying is an old method of processing food, especially fish. Mackerel is one of the most consumed fish worldwide because of its high nutritional value. Previously, only a study on the effects of deep frying of fried mackerel has been performed. However, no study has been conducted on the effects of different frying methods on the physiochemical and nutritional properties of chub mackerel. Therefore, in this study, we evaluated the physiochemical and nutritional characteristics of deep fried, vacuum fried, and air fried chub mackerel. Thawing methods were compared and the best method was selected. High frequency defrosting (HFD) was used to thaw frozen fillet mackerel before frying. Response surface methodology (RSM) was used to optimize the temperature and frying time of the three frying methods. The physiochemical and nutritional characteristics, including volatile basic nitrogen (VBN), thiobarbituric acid-reactive substances (TBARS), pH, overall acceptance, proximate, fatty acid, and amino acids of fried mackerel were investigated. The HFD exhibited the lowest number of drips with a short thawing time. The RSM showed that the optimum temperature and frying time for deep, vacuum, and air frying were 165 °C for 3 min, 95 °C for 7 min, and 160 °C for 15 min, respectively. Vacuum frying showed the lowest increase in VBN, TBARS, and pH, and significantly (p < 0.05) differed from the others. It also resulted in increased amino acid and preserved fatty acid content. These findings suggest that vacuum frying is the best frying method which has little oxidation and can maintain nutrition. The results of this study could be applied in the fisheries industry to produce the best fried mackerel and preserve its high nutritive value.
Modeling the Spectral Properties of Obtrusive Light Incident on a Window: Application to Montréal, Canada
Authors: Aubé Martin , Houle Julien-Pierre , Desmarais Justine , Veilleux Nikki , Bordeleau Émie
Published: July 2021

This paper describes the use of a new obtrusive light module of the Illumina v2 model to estimate the light that may enter bedroom windows. We used the following as input to the model: (1) the sources’ flux and spectrum derived from the color images taken by astronauts from the International Space Station (ISS), (2) an association between source spectrum and angular emission, and (3) a per zone inventory of obstacles properties and lamp height. The model calculates the spectral irradiance incident to buildings’ windows taking into account the orientation of the street. By using the color information from an ISS image, we can classify pixels as a function of their spectra. With the same image, it is also possible to determine the upward photopic radiance for each pixel. Both serve as inputs to the model to calculate the spectral irradiance on any window. By having the spectral irradiance, it is possible to determine the Melatonin Suppression Index and the photopic irradiance on the window. Such information can later be used to perform epidemiological studies. The new methodology is applied to the city of Montréal in Canada for a set of houses’ locations. The computations are made for 2013 (pre-LED era).
Improvement of Region-Merging Image Segmentation Accuracy Using Multiple Merging Criteria
Authors: Wang Haoyu , Shen Zhanfeng , Zhang Zihan , Xu Zeyu , Li Shuo , Jiao Shuhui , Lei Yating
Published: July 2021

Image segmentation plays a significant role in remote sensing image processing. Among numerous segmentation algorithms, the region-merging segmentation algorithm is widely used due to its well-organized structure and outstanding results. Many merging criteria (MC) were designed to improve the accuracy of region-merging segmentation, but each MC has its own shortcomings, which can cause segmentation errors. Segmentation accuracy can be improved by referring to the segmentation results. To achieve this, an approach for detecting and correcting region-merging image segmentation errors is proposed, and then an iterative optimization model is established. The main contributions of this paper are as follows: (1) The conflict types of matching segment pairs are divided into scale-expression conflict (SEC) and region-ownership conflict (ROC), and ROC is more suitable for optimization. (2) An equal-scale local evaluation method was designed to quantify the optimization potential of ROC. (3) A regional anchoring strategy is proposed to preserve the results of the previous iteration optimization. Three QuickBird satellite images of different land-cover types were used for validating the proposed approach. Both unsupervised and supervised evaluation results prove that the proposed approach can effectively improve segmentation accuracy. All explicit and implicit optimization modes are concluded, which further illustrate the stability of the proposed approach.
Analysis of Noise and Velocity in GNSS EPN-Repro 2 Time Series
Authors: Nistor Sorin , Suba Norbert-Szabolcs , Maciuk Kamil , Kudrys Jacek , Nastase Eduard Ilie , Muntean Alexandra
Published: July 2021

This study evaluates the EUREF Permanent Network (EPN) station position time series of approximately 200 GNSS stations subject to the Repro 2 reprocessing campaign in order to characterize the dominant types of noise and amplitude and their impact on estimated velocity values and associated uncertainties. The visual inspection on how different noise model represents the analysed data was done using the power spectral density of the residuals and the estimated noise model and it is coherent with the calculated Allan deviation (ADEV)-white and flicker noise. The velocities resulted from the dominant noise model are compared to the velocity obtained by using the Median Interannual Difference Adjusted for Skewness (MIDAS). The results show that only 3 stations present a dominant random walk noise model compared to flicker and powerlaw noise model for the horizontal and vertical components. We concluded that the velocities for the horizontal and vertical component show similar values in the case of MIDAS and maximum likelihood estimation (MLE), but we also found that the associated uncertainties from MIDAS are higher compared to the uncertainties from MLE. Additionally, we concluded that there is a spatial correlation in noise amplitude, and also regarding the differences in velocity uncertainties for the Up component.
Deep Residual Dual-Attention Network for Super-Resolution Reconstruction of Remote Sensing Images
Authors: Huang Bo , He Boyong , Wu Liaoni , Guo Zhiming
Published: July 2021

A super-resolution (SR) reconstruction of remote sensing images is becoming a highly active area of research. With increasing upscaling factors, richer and more abundant details can progressively be obtained. However, in comparison with natural images, the complex spatial distribution of remote sensing data increases the difficulty in its reconstruction. Furthermore, most SR reconstruction methods suffer from low feature information utilization and equal processing of all spatial regions of an image. To improve the performance of SR reconstruction of remote sensing images, this paper proposes a deep convolutional neural network (DCNN)-based approach, named the deep residual dual-attention network (DRDAN), which achieves the fusion of global and local information. Specifically, we have developed a residual dual-attention block (RDAB) as a building block in DRDAN. In the RDAB, we firstly use the local multi-level fusion module to fully extract and deeply fuse the features of the different convolution layers. This module can facilitate the flow of information in the network. After this, a dual-attention mechanism (DAM), which includes both a channel attention mechanism and a spatial attention mechanism, enables the network to adaptively allocate more attention to regions carrying high-frequency information. Extensive experiments indicate that the DRDAN outperforms other comparable DCNN-based approaches in both objective evaluation indexes and subjective visual quality.
CPISNet: Delving into Consistent Proposals of Instance Segmentation Network for High-Resolution Aerial Images
Authors: Zeng Xiangfeng , Wei Shunjun , Wei Jinshan , Zhou Zichen , Shi Jun , Zhang Xiaoling , Fan Fan
Published: July 2021

Instance segmentation of high-resolution aerial images is challenging when compared to object detection and semantic segmentation in remote sensing applications. It adopts boundary-aware mask predictions, instead of traditional bounding boxes, to locate the objects-of-interest in pixel-wise. Meanwhile, instance segmentation can distinguish the densely distributed objects within a certain category by a different color, which is unavailable in semantic segmentation. Despite the distinct advantages, there are rare methods which are dedicated to the high-quality instance segmentation for high-resolution aerial images. In this paper, a novel instance segmentation method, termed consistent proposals of instance segmentation network (CPISNet), for high-resolution aerial images is proposed. Following top-down instance segmentation formula, it adopts the adaptive feature extraction network (AFEN) to extract the multi-level bottom-up augmented feature maps in design space level. Then, elaborated RoI extractor (ERoIE) is designed to extract the mask RoIs via the refined bounding boxes from proposal consistent cascaded (PCC) architecture and multi-level features from AFEN. Finally, the convolution block with shortcut connection is responsible for generating the binary mask for instance segmentation. Experimental conclusions can be drawn on the iSAID and NWPU VHR-10 instance segmentation dataset: (1) Each individual module in CPISNet acts on the whole instance segmentation utility; (2) CPISNet* exceeds vanilla Mask R-CNN 3.4%/3.8% AP on iSAID validation/test set and 9.2% AP on NWPU VHR-10 instance segmentation dataset; (3) The aliasing masks, missing segmentations, false alarms, and poorly segmented masks can be avoided to some extent for CPISNet; (4) CPISNet receives high precision of instance segmentation for aerial images and interprets the objects with fitting boundary.
Methods and Experiments for Sensing Variations in Solar Activity and Defining Their Impact on Heart Variability
Authors: Hanzelka Michael , Dan Jiří , Szabó Zoltán , Roubal Zdeněk , Dohnal Přemysl , Kadlec Radim
Published: July 2021

This paper evaluates variations in solar activity and their impact on the human nervous system, including the manner in which human behavior and decision-making reflect such effects in the context of (symmetrical) social interactions. The relevant research showed that solar activity, manifesting itself through the exposure of the Earth to charged particles from the Sun, affects heart variability. The evaluation methods focused on examining the relationships between selected psychophysiological data and solar activity, which generally causes major alterations in the low-level electromagnetic field. The investigation within this paper revealed that low-level EMF changes are among the factors affecting heart rate variability and, thus, also variations at the spectral level of the rate, in the VLF, (f = 0.01–0.04 Hz), LF (f = 0.04–0.15 Hz), and HF (f = 0.15 až 0.40 Hz) bands. The results of the presented experiments can also be interpreted as an indirect explanation of sudden deaths and heart failures.
Feature-Selection and Mutual-Clustering Approaches to Improve DoS Detection and Maintain WSNs’ Lifetime
Authors: Ahmad Rami , Wazirali Raniyah , Bsoul Qusay , Abu-Ain Tarik , Abu-Ain Waleed
Published: July 2021

Wireless Sensor Networks (WSNs) continue to face two major challenges: energy and security. As a consequence, one of the WSN-related security tasks is to protect them from Denial of Service (DoS) and Distributed DoS (DDoS) attacks. Machine learning-based systems are the only viable option for these types of attacks, as traditional packet deep scan systems depend on open field inspection in transport layer security packets and the open field encryption trend. Moreover, network data traffic will become more complex due to increases in the amount of data transmitted between WSN nodes as a result of increasing usage in the future. Therefore, there is a need to use feature selection techniques with machine learning in order to determine which data in the DoS detection process are most important. This paper examined techniques for improving DoS anomalies detection along with power reservation in WSNs to balance them. A new clustering technique was introduced, called the CH_Rotations algorithm, to improve anomaly detection efficiency over a WSN’s lifetime. Furthermore, the use of feature selection techniques with machine learning algorithms in examining WSN node traffic and the effect of these techniques on the lifetime of WSNs was evaluated. The evaluation results showed that the Water Cycle (WC) feature selection displayed the best average performance accuracy of 2%, 5%, 3%, and 3% greater than Particle Swarm Optimization (PSO), Simulated Annealing (SA), Harmony Search (HS), and Genetic Algorithm (GA), respectively. Moreover, the WC with Decision Tree (DT) classifier showed 100% accuracy with only one feature. In addition, the CH_Rotations algorithm improved network lifetime by 30% compared to the standard LEACH protocol. Network lifetime using the WC + DT technique was reduced by 5% compared to other WC + DT-free scenarios.
An IMU/ODM/UWB Joint Localization System Based on Modified Cubature Kalman Filtering
Authors: Tang Chao , He Chengyang , Dou Lihua
Published: July 2021

In this article, a multisensor joint localization system is proposed based on modified cubature Kalman filtering, which aims to improve the accuracy of state estimation under a moderate computational burden in the presence of high process noise. Specifically, first, the covariance of process noise is matched based on adaptive filtering. The inertial measurement unit (IMU), odometer (ODM), and ultra-wideband (UWB) information acquired by the associated sensors is then employed to augment the system state and are fused to lower the influence of process noise. In the presented localization setting, all sensors (IMU/ODM/UWB) are set to work in parallel under the federated Kalman filter (FKF) framework, which can correct the cumulative error of the internal sensor and and can improve the computational efficiency. Two sets of numerical simulations were performed to show that the proposed method can obtain accurate state estimation with a slightly increased computational burden.
Janus Hydrogel Microbeads for Glucose Sensing with pH Calibration
Authors: Ando Maru , Tsuchiya Mio , Itai Shun , Murayama Tomomi , Kurashina Yuta , Heo Yun Jung , Onoe Hiroaki
Published: July 2021

We present fluorescent Janus hydrogel microbeads for continuous glucose sensing with pH calibration. The Janus hydrogel microbeads, that consist of fluorescent glucose and pH sensors, were fabricated with a UV-assisted centrifugal microfluidic device. The microbead can calibrate the pH values of its surroundings and enables accurate measurements of glucose within various pH conditions. As a proof of concept, we succeeded in obtaining the accurate value of glucose concentration in a body-fluid-like sample solution. We believe that our fluorescent microbeads, with pH calibration capability, could be applied to fully implantable sensors for continuous glucose monitoring.
A Dual-Sensor-Based Screening System for In Vitro Selection of TDP1 Inhibitors
Authors: Jakobsen Ann-Katrine , Keller Josephine Geertsen , Gonzalez María , Martin-Encinas Endika , Palacios Francisco , Alonso Concepcion , Knudsen Birgitta Ruth , Stougaard Magnus
Published: July 2021

DNA sensors can be used as robust tools for high-throughput drug screening of small molecules with the potential to inhibit specific enzymes. As enzymes work in complex biological pathways, it is important to screen for both desired and undesired inhibitory effects. We here report a screening system utilizing specific sensors for tyrosyl-DNA phosphodiesterase 1 (TDP1) and topoisomerase 1 (TOP1) activity to screen in vitro for drugs inhibiting TDP1 without affecting TOP1. As the main function of TDP1 is repair of TOP1 cleavage-induced DNA damage, inhibition of TOP1 cleavage could thus reduce the biological effect of the TDP1 drugs. We identified three new drug candidates of the 1,5-naphthyridine and 1,2,3,4-tetrahydroquinolinylphosphine sulfide families. All three TDP1 inhibitors had no effect on TOP1 activity and acted synergistically with the TOP1 poison SN-38 to increase the amount of TOP1 cleavage-induced DNA damage. Further, they promoted cell death even with low dose SN-38, thereby establishing two new classes of TDP1 inhibitors with clinical potential. Thus, we here report a dual-sensor screening approach for in vitro selection of TDP1 drugs and three new TDP1 drug candidates that act synergistically with TOP1 poisons.
Using IoT in Supply Chain Risk Management, to Enable Collaboration between Business, Community, and Government
Authors: Meng Li
Published: July 2021

The internet of things (IoT) and social media provide information related to disasters that could help businesses to strategically mitigate risks and optimize their supply chain during difficult times. This paper proposes a framework to show how business or supply chain enterprisers can collaborate with community and government in disaster supply chain risk management. Businesses must have an established risk mitigation plan, update it periodically and implement promptly. Community collaboration can build a resilient society, and government should play an important role in leading both financial and non-financial support during natural disasters and pandemic management. The IoT and social media are new mechanisms as a vocal point to enable government, ensuring trustworthiness of information, to provide the community with a means to express needs and feedback, and to assist business services to meet the changeable preferences under risk threats. Social media can be a collaborative effort between all the parties and helps make value added decisions efficiently in supply chain risk management.
The Distribution and Consequences of Sexual Misconduct Perpetrated by Peacekeepers in Haiti: An Exploratory Cross-Sectional Analysis
Authors: Vahedi Luissa , Stuart Heather , Etienne Stéphanie , Lee Sabine , Bartels Susan A
Published: July 2021

During the United Nations Stabilization Mission in Haiti (MINUSTAH), reports of sexual abuse and exploitation and children fathered by peacekeepers were brought forward to the UN. In 2017, a cross-sectional mixed-methods survey was administered by Haitian research assistants using SenseMaker® (Cognitive Edge, Singapore), a rapid data collection tool that allows participants to share a narrative on a topic of interest. In total, 2541 self-interpreted narratives in relation to the experiences of Haitian women and girls vis-à-vis peacekeepers were collected from a convenience sample of Haitian males and females across Haiti. This exploratory secondary data analysis analyzes whether narratives about sexual misconduct perpetrated by MINUSTAH peacekeepers were associated with rural, semi-urban, or urban locations and investigates the relationship between sharing narratives about sexual misconduct and the desire to engage with the UN/MINUSTAH. After adjustment, narratives addressing sexual misconduct were more likely to be shared in rural locations, compared to urban locations (RRrural: 1.19; 95% CI: 1.03, 1.38). Personal experiences of sexual misconduct were more likely (RRsex: 4.52; 95% CI: 3.34, 6.12) to be associated with rejection of the UN/MINUSTAH, compared to personal narratives of positive/neutral experiences. This research is an empirical steppingstone to understanding the distribution and consequences of peacekeeper-perpetrated sexual abuse and exploitation in Haiti.
An Overview of Bioplastic Research on Its Relation to National Policies
Authors: Garrido Ricard , Cabeza Luisa F. , Falguera Victor
Published: July 2021

There is an increasing concern about fossil energy and products derived from it. The plastic industry depends on oil, and produced plastics cannot degrade naturally. An alternative to plastics from oil is the use of bioplastics, which can be degradable. The bibliometric study of the publications related to bioplastics carried out in this paper shows that research on this topic is growing both in developed (USA, European Union, and Canada) and in developing countries (China, India, Thailand, and Malaysia), mostly following the implementation of bioeconomy standards and labels by their governments. The main authors and the collaborations they have worldwide are also presented here. The research carried out in this paper is not only devoted to technological aspects but also to economic aspects and inhabitant ratios. Trends in publications, by country and authors, are analyzed. Finally, this paper also studies the countries governmental policies and how they impact the bioplastic field.
A Multicriteria Evaluation of Sustainable Riparian Revegetation with Local Fruit Trees around a Reservoir of a Hydroelectric Power Plant in Central Brazil
Authors: Ribas José Roberto , Ribas Jorge Santos , García Andrés Suárez , Fariña Elena Arce , Peña David González , Rodríguez Ana García
Published: July 2021

The construction of hydropower plants often requires the flooding of large land areas, causing considerable alterations in the natural environment. In the region surrounding the reservoir of the Corumbá IV hydroelectric plant, located in the Cerrado region of Central Brazil, two types of soil predominate, classified as Dystroferric Red Latosol and Dystroferric Haplic Cambisol. The plant owners have to restore the degraded biome after the flooding of the margins caused by the filling of the reservoir. An experiment was carried out with fifteen native species, selected for having ideal phytosociological properties. Nine of them showed a survivability considered satisfactory in a planting situation, with a view to large-scale planting. Assuming that the planting of native fruit trees can be a quick solution to the attraction and preservation of wildlife, it would therefore provide sustainable riparian revegetation around the reservoir. We adopted the SIMOS technique to rank the criteria based on four morphological features and a Fuzzy AHP model to rank the contributions of the nine fruit tree species to the sustainable restoration of part of the riparian vegetation cover around the reservoir. In practical terms, we concluded that the soil types did not have any influence on tree survival after two years of growth, but the native trees’ morphological features varied among the species. These findings simplify the large-scale planting of seedlings that must be carried out by the operator in the riparian forest around the reservoir.
Construction Cost and Carbon Emission Assessment of a Highway Construction—A Case towards Sustainable Transportation
Authors: Luo Wenkai , Sandanayake Malindu , Zhang Guomin , Tan Yongtao
Published: July 2021

Due to its dynamic nature in construction, benchmarking environmental emissions of road construction projects can be a daunting task. Often stakeholders will have to prioritize the economic and environmental indicators based on the project objectives. The study presents a methodological framework to compare economic and environmental impacts to benchmark sustainable transport construction projects. Through findings, the study aims to inform focus areas and key stages of infrastructure projects to benchmark sustainable performance. Process-based emission and cost estimation models are presented with an AHP based weighting factor that enables prioritization of emissions and costs based on project scopes and objectives. Using a case study, results are represented to validate the framework and methodology. Concrete and steel are identified as the main materials that contribute to total carbon emissions, while soil and gravel are responsible for the highest costs. Electricity consumption is discovered as the major fuel type contributing to carbon emissions. Concrete and dump trucks are discovered as the top two sources of emissions and costs, respectively. Scenario analyses revealed that the choice of equipment significantly affects the project’s emissions and costs. The application of sustainable materials can significantly reduce emissions and cost. The use of the case study approach results in a lack of generalizability. However, the same methodology and process can be adopted for the sustainable benchmarking of different projects. Researchers are encouraged to investigate processes to automate sustainable benchmarking of transport infrastructure construction projects. The study is one of the first attempts to compare cost and environmental impacts using a systematic methodology of transportation infrastructure construction projects.
Knowledge Transfer with Citizen Science: Luft-Leipzig Case Study
Authors: Tõnisson Liina , Voigtländer Jens , Weger Michael , Assmann Denise , Käthner Ralf , Heinold Bernd , Macke Andreas
Published: July 2021

Community-based participatory research initiatives such as “hackAir”, “luftdaten.info”, “senseBox”, “CAPTOR”, “CurieuzeNeuzen Vlaanderen”, “communityAQ”, and “Healthy Air, Healthier Children” campaign among many others for mitigating short-lived climate pollutants (SLCPs) and improving air quality have reported progressive knowledge transfer results. These research initiatives provide the research community with the practical four-element state-of-the-art method for citizen science. For the preparation-, measurements-, data analysis-, and scientific support-elements that collectively present the novel knowledge transfer method, the Luft-Leipzig project results are presented. This research contributes to science by formulating a novel method for SLCP mitigation projects that employ citizen scientists. The Luft-Leipzig project results are presented to validate the four-element state-of-the-art method. The method is recommended for knowledge transfer purposes beyond the scope of mitigating short-lived climate pollutants (SLCPs) and improving air quality.
Eco-Acoustic Assessment of an Urban Park by Statistical Analysis
Authors: Benocci Roberto , Roman H. Eduardo , Bisceglie Alessandro , Angelini Fabio , Brambilla Giovanni , Zambon Giovanni
Published: July 2021

We investigated the statistical properties of the sounds recorded at a site located in the Parco Nord of Milan, Italy, characterized by wooded land rich in biodiversity and exposed to different sources and types of anthropogenic disturbances with the aim of deriving information on its environmental quality in terms of biophonic presence and athropic disturbance. A time series of eco-acosutic indices were determined for 616 audio files recorded from 30 April 2019 (5:00 p.m.) to 3 May 2019 (5:00 a.m.) with a 1-min duration followed by a 5-min pause (10 recordings per hour). In the present study, the following indices were computed: the Acoustic Complexity Index (ACI), Acoustic Diversity Index (ADI), Acoustic Evenness Index (AEI), Bio-acoustic Index (BI), Acoustic Entropy Index (H), Normalized Difference Soundscape Index (NSDI) and Dynamic Spectral Centroid (DSC). Cluster analysis performed on the corresponding time series yielded a dimensional reduction from seven down to three. The results show a clear separation of the eco-acoustic indices into two clusters, reflecting the different dynamics and diversity behaviour throughout the recordings. A post-processing aural survey was also performed, aiming at determining biophonic activities (mainly avian vocalization and other animals), the characteristics of technophonies sources (mainly road traffic noise and airplane fly-overs), human presence (voices and steps) and geophonies (rain and wind). The statistical analysis proved to be a robust tool due to the good matching obtained with the aural survey outcomes. The overall quality of the Parco Nord phonic activity was found to be low. Notwithstanding the presence of avian species, highlighted by the characteristic dawn chorus, both clusters revealed low “scores” of NDSI and DSC indices heavily influenced by road traffic sources. This study represents the first step toward the realization of maps of eco-acoustic indices for the long-term monitoring of fragile habitats.