bluuebunny/crossref_metadata_2025 huggingface dataset:
Light Reflected from Different Plant Canopies Affected Beta vulgaris L. Growth and Development
Authors: Adjesiwor Albert T. , Kniss Andrew R.
Published: November 2020

Studies on crop response to light quality (red (R) to far-red (FR) light ratio) often recommend early weed removal to reduce the effects of shade avoidance responses on crop yield. However, it is unclear whether crops are able to distinguish reflected light quality of kin from that of nonkin. We evaluated the response of sugar beet (Beta vulgaris L.) to reflected FR light from sugar beet, common lambsquarters (Chenopodium album L.), Kentucky bluegrass (Poa pratensis L.), alfalfa (Medicago sativa L.), and bare soil (control) under outdoor conditions in 2016 and 2017. Treatments were completely randomized with 10 replications per treatment. The study methods ensured there was no direct resource competition. The reflected R:FR of plant species ranged from 0.06 (common lambsquarters) to 0.24 (sugar beet) compared to 0.7 for the bare soil. In 2016 and 2017, there were 2 to 4 more leaves in the sugar beet surrounded by soil compared to sugar beet surrounded by neighboring species. There was up to 47, 57, 43, and 23% reduction in sugar beet leaf area, shoot dry weight, root diameter, and root dry weight, respectively, due to reflected R:FR light from neighboring species. Sugar beet did not respond differently to reflected light quality of kin compared to nonkin.
Animal Cruelty and Neighborhood Conditions
Authors: Reese Laura A. , Vertalka Joshua J. , Richard Cassie
Published: November 2020

Background: Animal cruelty appears to be widespread. Competing theories have been posed regarding the causes of animal cruelty leading to conflicting findings and little direction for public policies to combat it. Objective: To assess the applicability of extant theories of the causes of animal cruelty: domestic violence; deviance; perpetrator traits; and social disorganization. Methods: Data are drawn from police department reports of animal cruelty in the City of Detroit from 2007 to 2015; 302 incidences of animal cruelty were reported. Multiple regression is used to determine the theory which best appears to account for animal cruelty. Results: Common types of animal cruelty in Detroit are shooting; blunt force trauma; neglect; and dogfighting. While most incidents involve unknown persons; cruelty by owners; neighbors; and domestic partners is also common. Neighborhood conditions in terms of economic stress; vacancy and blight; and crime appear to have the greatest impact on animal cruelty. Conclusions: The findings from Detroit support deviance and social disorganization theories of animal cruelty. Neighborhood conditions in terms of economic stress, vacancy and blight, and crime appear to have the greatest impact on animal cruelty in this urban area.
Laser-Induced Forward Transfer with Optical Stamp of a Protein-Immobilized Calcium Phosphate Film Prepared by Biomimetic Process to a Human Dentin
Authors: Narazaki Aiko , Oyane Ayako , Miyaji Hirofumi
Published: November 2020

The rapid and area-specific printing of calcium phosphate with superior biocompatibility and osteoconductivity is a useful technique for the surface functionalization of biomedical devices. We recently demonstrated the laser-induced forward transfer (LIFT) of a brittle calcium phosphate film onto a soft and shock-absorbing polydimethylsiloxane (PDMS) substrate. In this work, a new LIFT using an optically transparent PDMS-coated stamp, which we hereafter call LIFT with optical stamp (LIFTOP), was introduced to achieve the transfer of brittle films to harder substrates. Cell adhesion protein fibronectin-immobilized calcium phosphate films (Fn-CaP) were prepared on the optical stamp through a biomimetic process. Then, the irradiation of a single laser pulse transferred the Fn-CaP film from the optical stamp onto relatively hard substrates, polyethylene terephthalate and human dentin. As a result of this LIFTOP process, Fn-CaP microchips with a shape corresponding to the laser beam spot were printed on the substrates. Cross-sectional observation of the interface between the Fn-CaP microchip and the dentin substrate revealed good attachment between them without obvious gaps for the most part.
Accelerating Emergence of Aerial Swarm
Authors: Jia Yongnan , Li Qing , Zhang Zhaolong
Published: November 2020

Herein, we present a methodology and framework for exploiting certain interdisciplinary studies that can particularly benefit from integration. In this paper, rigorous derivation of control theory and statistical analysis of simulation results are organically unified for testifying and optimizing the emergence of order in aerial swarming scenarios under free boundary conditions. Each Unmanned Aerial Vehicle (UAV) is regulated by a simplified mathematical model, based on which a distributed flocking protocol is proposed as a feasible solution for aerial swarms. On condition that the initial interaction network is connected, the LaSalle–Krasovskii invariance principle is implemented to verify the effectiveness of the above algorithm. However, most existing results on flocking are far from being engineering applications. A basic challenge is how to present a low-cost energy and time saving solution on account of the limited flight capability of these UAVs and real-time operational requirements. As is well known, energy consumption can be reduced if unnecessary interactions among individuals are eliminated. Therefore, another contribution of this paper is to propose a precise optimization of an existing flocking algorithm for UAVs with respect to interaction requirements. Energy and time measurements, as well as scalability effects, are assessed in terms of statistical significance and strength. The results indicate that the flocking control protocol adopting the minimal interaction is the most promising swarm.
Comparison of Two-Dimensional and Three- Dimensional Responses for Vortex-Induced Vibrations of a Rectangular Prism
Authors: Zhou Shuai , Zou Yunfeng , Hua Xugang , Liu Zhipeng
Published: November 2020

The accurate prediction of the amplitudes of vortex-induced vibrations (VIV) is important in wind-resistant design. Wind tunnel tests of scaled section models have been commonly used. However, the amplitude prediction processes were usually inaccurate because of insufficient evaluations of three-dimensional (3D) effects. This study presents experimental measurements of VIV responses in a prototype rectangular prism and its 1:1 two-dimensional section model in smooth flow. The results show that the section model vibrates with the same Reynolds number, equivalent mass, frequency, and damping ratio as those of the prototype prism without scale effects. The VIV amplitudes can be qualitatively and quantitatively measured and analyzed. The measured VIV lock-ins of these two models agree with each other. However, the prototype prism produces a 20% higher maximum amplitude than the section model. Several classical VIV mathematical models are used to validate the wind tunnel test results. This confirms that the 3D coupling effects of the modal shape and the imperfect correlations of excitation forces positively contribute to the maximum amplitude. Based on the section model outcomes, the amplified factor of 1.2 is found to be appropriate for the amplitude prediction of VIV for the present prism, and it can also provide a reference for other structures.
Air Pollution and Emergency Hospital Admissions—Evidences from Lisbon Metropolitan Area, Portugal
Authors: Franco Pedro , Gordo Cristina , Marques da Costa Eduarda , Lopes António
Published: November 2020

The relevance of air pollution in the public health agenda has recently been reinforced—it is known that exposure to it has negative effects in the health of individuals, especially in big cities and metropolitan areas. In this article we observed the evolution of air pollutants (CO, NO, NO2, O3, PM10) emissions and we confront them with health vulnerabilities related to respiratory and circulatory diseases (all circulatory diseases, cardiac diseases, cerebrovascular disease, ischemic heart disease, all respiratory diseases, chronic lower respiratory diseases, acute upper respiratory infections). The study is supported in two databases, one of air pollutants and the other of emergency hospital admissions, in the 2005–2015 period, applied to the Lisbon Metropolitan Area. The analysis was conducted through Ordinary Least Squares (OLS) regression, while also using semi-elasticity to quantify associations. Results showed positive associations between air pollutants and admissions, tendentially higher in respiratory diseases, with CO and O3 having the highest number of associations, and the senior age group being the most impacted. We concluded that O3 is a good predictor for the under-15 age group and PM10 for the over-64 age group; also, there seems to exist a distinction between the urban city core and its suburban areas in air pollution and its relation to emergency hospital admissions.
Schlieren Images of Negative Streamer and Leader Formations in CO2 and a CF3I-CO2 Electronegative Gas Mixture
Authors: Widger Phillip , Hills Meirion , Mitchard Daniel
Published: November 2020

In electrical networks, SF6 gas is currently used to insulate high-voltage equipment, however, due to its high environmental impact, new alternatives such as CO2 and electronegative gas mixtures such as CF3I-CO2 are being trialled to replace SF6 and create a sustainable energy system. A high-voltage lightning impulse (1.2 μs/50 μs) was used to approximate the disturbance in a high-voltage electrical network caused by a lightning strike and helped to identify the likely streamer and leader formations in different gases insulating a piece of gas insulated switchgear. In this paper, the theoretical and practical aspects of electrical streamer and leader formations in pure CO2 and an electronegative gas mixture of CF3I-CO2 are examined using schlieren videography in small length rod-plane gas gaps between 20 and 50 mm in length. Schlieren allows the examination of gas density in streamer formations and for the differences in weakly attaching gases, such as CO2, and electronegative gas mixtures, such as CF3I-CO2, to be studied. The gas pressure is varied in order to examine the differences in streamer and leader formation as the gas density is varied and hence the probability of electron collision is varied.
Automated Multiple Concrete Damage Detection Using Instance Segmentation Deep Learning Model
Authors: Kim Byunghyun , Cho Soojin
Published: November 2020

In many developed countries with a long history of urbanization, there is an increasing need for automated computer vision (CV)-based inspection to replace conventional labor-intensive visual inspection. This paper proposes a technique for the automated detection of multiple concrete damage based on a state-of-the-art deep learning framework, Mask R-CNN, developed for instance segmentation. The structure of Mask R-CNN, which consists of three stages (region proposal, classification, and segmentation) is optimized for multiple concrete damage detection. The optimized Mask R-CNN is trained with 765 concrete images including cracks, efflorescence, rebar exposure, and spalling. The performance of the trained Mask R-CNN is evaluated with 25 actual test images containing damage as well as environmental objects. Two types of metrics are proposed to measure localization and segmentation performance. On average, 90.41% precision and 90.81% recall are achieved for localization and 87.24% precision and 87.58% recall for segmentation, which indicates the excellent field applicability of the trained Mask R-CNN. This paper also qualitatively discusses the test results by explaining that the architecture of Mask R-CNN that is optimized for general object detection purposes, can be modified to detect long and slender shapes of cracks, rebar exposure, and efflorescence in further research.
Modeling the Ecosystem Services Related to Phytoextraction: Carbon Sequestration Potential Using Willow and Poplar
Authors: Riccioli Francesco , Guidi Nissim Werther , Masi Matteo , Palm Emily , Mancuso Stefano , Azzarello Elisa
Published: November 2020

Poplar and willow demonstrate great potential for the phytoextraction of trace elements (TEs) from soils. In most cases, these species are managed as short-rotation coppice, producing high woody biomass yields, which could provide a valuable contribution toward reducing greenhouse gas emissions in the atmosphere. In the current study, we compared the TE extraction and CO2 sequestration rates in a four-year field trial in Southern Italy of two arboreal species (willow and poplar). The results show that, once established in the study area, willow extracted more Cd and Cu and less Pb than poplar. The two species demonstrated the same average Ni and Zn extraction rates. Greater biomass yields in poplar suggest that this species was able to fix greater amounts of CO2 (28.7 Mg ha−1 yr−1) than willow (24.9 Mg ha−1 yr−1). We argue that the choice of the species to be used in phytoextraction should first be made considering the TE-specific affinity and phytoextraction rates. For TEs whose extraction rates were the same (i.e., Ni and Zn), poplar is to be preferred because of its ability to fix greater amounts of CO2 than willow.
Application of Corrected Methods for High-Resolution XRF Core Scanning Elements in Lake Sediments
Authors: Zhang Xiaonan , Zhang Hucai , Chang Fengqin , Ashraf Umar , Peng Wei , Wu Han , Liu Qi , Liu Fengwen , Zhang Yun , Duan Lizeng
Published: November 2020

Contemporary studies emphasize theoretical and analytical aspects of monitoring water quality within lacustrine settings. The X-ray fluorescence (XRF) core scanner provides the most rapid, non-destructive high-resolution elemental measurements for unprocessed sediments. However, the analytical precision of measured elemental composition may be offset due to water content and inhomogeneities in the physical properties of the sediment. A range of calibration approaches developed specifically for converting XRF scanning intensities to element fractions has been made available. Here, two lake sediment-cores retrieved from southwest China were used to evaluate the performance of various calibration methods. In particular, the influence of sediment properties on XRF scanning intensities was assessed by redundancy analyses (RDA) and the generalized additive model (GAM). The results demonstrate that for fine-grained sediments, the impact of grain size results in only minor deviations in the XRF scanning intensities. Water content of the lake sediment was shown to be the most important factor influencing the XRF scanning intensities, especially for light elements (e.g., Al to Fe). Significant decreases in XRF scanning intensities may occur when sediment water content is greater than 47%. We recommend testing the element fractions obtained via conventional techniques throughout the core and applying the multivariate log-ratio calibration for high-resolution XRF scanning elements within lake sediments.
Performance Evaluation of Offline Motion Preparation Approaches on the Example of a Non-Linear Kinematics
Authors: Holowenko Olaf , Drowatzky Lucas , Ihlenfeldt Steffen
Published: November 2020

In motion control, the generation of motion profiles for non-linear kinematics is usually computationally complex. In order to minimize the workload on the machine’s control system, the approach pursued is outsourcing complex calculation tasks to the offline area. In this offline motion preparation, predefined criteria have to be taken into account to guarantee process stability on the real machine. During the motion preparation, a high performance is desired, characterized by less data generated and at the same time little computing effort. The evaluation will use the example of a motion specification, which is characterized by a large amount of data compared to conventional motion specifications. Thus, the demands on performance become even higher. This paper examines the performance of different motion preparation approaches known from literature. On the one hand, selected spline-based algorithms are discussed and compared. A recursive algorithm based on monomial splines is recommended for use in the example. On the other hand, a very simple approach based on the linearization of the non-linear workspace of the mechanism is presented and applied on the algorithms. With this, the performance increased significantly again.
Silver Nanowire Micro-Ring Formation Using Immiscible Emulsion Droplets for Surface-Enhanced Raman Spectroscopy
Authors: Lee Hyungdong , Ye Woojun , Lee Jaehyun , Kim Hyunggun , Byun Doyoung
Published: November 2020

Precise and rapid detection of biomolecules is a fast-growing research theme in the field of biomedical engineering. Based on the surface-enhanced Raman scattering, micro/nano-scale structures composed of noble metals (e.g., gold and silver) play a critical role in plasmonics. However, it is still limited to structuring nanomaterials in a specific manner. Here, we investigated a novel surface-enhanced Raman spectroscopy (SERS) application using one-dimensional nanomaterials and micro-encapsulation methods. With the immiscible nature of fluids, the nanomaterials were properly captured inside a number of droplets for encapsulation, deforming to micro-ring nanostructures. To yield uniform sizes of the silver micro-ring structures, a microchannel system was designed to characterize particle sizes via microscopic approaches. We were able to obtain printable silver nanowire micro-ring ink, and investigated the SERS substrate effect of the silver micro-ring structure. This fabrication method can be used in many other SERS-based biomedical engineering applications in the near future.
Agricultural Residues of Lignocellulosic Materials in Cement Composites
Authors: Ferraz Patrícia Ferreira Ponciano , Mendes Rafael Farinassi , Marin Diego Bedin , Paes Juliana Lobo , Cecchin Daiane , Barbari Matteo
Published: November 2020

Lignocellulosic material residues in cement composites are a favourable option for new fibre cement formulations in building materials, because they combine good mechanical properties with low density. This study aimed to evaluate the chemical, physical, anatomical, and mechanical properties of five cement panels reinforced with the following lignocellulosic materials: eucalyptus, sugarcane bagasse, coconut shell, coffee husk, and banana pseudostem. Lignocellulosic cement panels were produced with each lignocellulosic material residue, and three replicates of each type of lignocellulosic material were examined (15 panels in total). The lignin, extractives, ash, and holocellulose were examined. After 28 days of composite curing, the following physical properties of the panels were evaluated: density, porosity, water absorption after immersion for 2 and 24 h, and thickness swelling after immersion for 2 and 24 h. Mechanical tests (compression strength, internal bonding, modulus of rupture, and modulus of elasticity) were performed before and after the accelerated ageing test with a universal testing machine. Scanning electron microscopy and supervised image classification were performed to investigate the morphologies of the different materials and the filler/matrix interfaces. Eucalyptus and sugarcane panels had the best results in terms of the evaluated properties and thus, could potentially be used as non-structural walls. However, banana pseudostem, coconut shell, and coffee husk panels had the worst results and therefore, under these conditions, should not be used in building.
Development of Alfa Fiber-Based Mortar with Improved Thermo-Mechanical Properties
Authors: Sakami Siham , Boukhattem Lahcen , Boumhaout Mustapha , Benhamou Brahim
Published: November 2020

This work deals with the development of a new composite based on mortar reinforced with optimally sized alfa fiber (AF). Experimental investigations of physical and thermo-mechanical properties of the new AF mortar composite are performed for AF weight fraction varying from 0% to 5%. This simple material preparation process is described and scanning electron microscopy (SEM) is undertaken to analyze the morphology of this composite. It shows a random dispersion of the AF into the mortar matrix. Physical properties such as open porosity, water absorption, and bulk density fluctuations with AF mass content are measured. Measured thermal conductivity is compared to the values generated by different prediction models. Good agreement, within 9.6%, is obtained with data predicted by Woodside–Messmer’s method. It is demonstrated that this simple blending of AF into mortar improves significantly the thermo-mechanical behavior of the new composite. An addition of 5% of AF weight content makes composite material lighter by about 15%, enhances its insulating thermal capabilities by about 57% and increases its heat diffusion damping rate by about 49%. Moreover, the composite mechanical (flexural and compressive) strength increases by up to 10% for an AF weight content of 1%.
Novel Thermal Management Strategy for Improved Inverter Reliability in Electric Vehicles
Authors: Trancho Elena , Ibarra Edorta , Prieto Pablo , Arias Antoni , Lis Adrian , Pai Ajay Poonjal
Published: November 2020

Requirements for electric vehicle (EV) propulsion systems—i.e., power density, switching frequency and cost—are becoming more stringent, while high reliability also needs to be ensured to maximize a vehicle’s life-cycle. Thus, the incorporation of a thermal management strategy is convenient, as most power inverter failure mechanisms are related to excessive semiconductor junction temperatures. This paper proposes a novel thermal management strategy which smartly varies the switching frequency to keep the semiconductors’ junction temperatures low enough and consequently extend the EV life-cycle. Thanks to the proposal, the drivetrain can operate safely at maximum attainable performance limits. The proposal is validated through simulation in an advanced digital platform, considering a 75-kW in-wheel Interior Permanent Magnet Synchronous Machine (IPMSM) drive fed by an automotive Silicon Carbide (SiC) power converter.
Droop Control Strategy of Utility-Scale Photovoltaic Systems Using Adaptive Dead Band
Authors: Kim Woosung , Song Sungyoon , Jang Gilsoo
Published: November 2020

This paper proposes a novel droop control strategy for addressing the voltage problem against disturbance in a transmission system connected with a utility-scale photovoltaic. Typically, a voltage control at the renewable energy sources (RESs) connected to the transmission grid uses a reactive power–voltage control scheme with a fixed dead band. However, this may cause some problems; thus, this paper proposes a method for setting a dead band value that varies with time. Here, a method for calculating an appropriate dead band that satisfies the voltage maintenance standard for two disturbances is described using voltage sensitivity analysis and the equation of existing droop control. Simulation studies are conducted using the PSS® E program to analyze the short term voltage stability and display the results for various dead bands. The proposed modeling and operational strategy are validated in simulation using a modified IEEE 39 bus system. The results provide useful information, indicating that the control scheme through an adaptive dead band enables more stable system operation than that through a fixed dead band.
Towards a Better Understanding of the Removal of Carbamazepine by Ankistrodesmus braunii: Investigation of Some Key Parameters
Authors: Yehya Tania , Favier Lidia , Audonnet Fabrice , Fayad Nidal , Bahry Hajar , Bahrim Gabriela Elena , Vial Christophe
Published: November 2020

Nowadays, water pollution by pharmaceuticals is a major issue that needs an urgent solution, as these compounds, even when found at trace or ultra-trace levels, could have harmful effects on organisms. Carbamazepine (CBZ) is a pharmaceutical product that is detected as a micropollutant in many water resources. Different treatment methods were lately employed for the removal of CBZ, which are often cheap but inefficient or efficient but expensive. Yet, there are limited available studies on the elimination of this molecule by algae despite their well-known highly adaptive abilities. In this study, the biological treatment of CBZ was carried out using the green microalgae, Ankistrodesmus braunii (A. braunii), which has been reported to be particularly resistant to CBZ toxicity in the literature. The respective effects of the culture medium, the initial inoculum, and CBZ concentrations were studied on CBZ removal. Lastly, the mechanism of CBZ elimination by A. braunii was investigated. The presented data clearly demonstrates that the presence of this molecule did not completely repress A. braunii growth or the ability of these algae to remove CBZ; after 60 days of incubation, the highest percentage of CBZ elimination achieved was 87.6%. Elimination was more successful in Bold’s basal medium than in proteose peptone medium. Finally, the removal mechanism was also investigated to provide a better understanding of the transformation mechanism of this molecule. It was shown that the main removal mechanism was the bioaccumulation of CBZ by A. braunii cells, but the biotransformation of the initial CBZ into metabolites was also observed.
Combining Post Sentiments and User Participation for Extracting Public Stances from Twitter
Authors: Wang Jenq-Haur , Liu Ting-Wei , Luo Xiong
Published: November 2020

With the wide popularity of social media, it’s becoming more convenient for people to express their opinions online. To better understand what the public think about a topic, sentiment classification techniques have been widely used to estimate the overall orientation of opinions in post contents. However, users might have various degrees of influence depending on their participation in discussions on different topics. In this paper, we address the issues of combining sentiment classification and link analysis techniques for extracting stances of the public from social media. Since social media posts are usually very short, word embedding models are first used to learn different word usages in various contexts. Then, deep learning methods such as Long Short-Term Memory (LSTM) are used to learn the long-distance context dependency among words for better estimation of sentiments. Third, we consider the major user participation in popular social media by adjusting the users weights to reflect their relative influence in user-post interaction graphs. Finally, we combine post sentiments and user influences into a total opinion score for extracting public stances. In the experiments, we evaluated the performance of our proposed approach for tweets about the 2016 U.S. Presidential Election. The best performance of sentiment classification can be observed with an F-measure of 72.97% for LSTM classifiers. This shows the effectiveness of deep learning methods in learning word usage in social media contexts. The experimental results on stance extraction showed the best performance of 0.68% Mean Absolute Error (MAE) in aggregating public stances on election candidates. This shows the potential of combining tweet sentiments and user participation structures for extracting the aggregate stances of the public on popular topics. Further investigation is needed to verify the performance in different social media sources.
Mapping the Inorganic and Proteomic Differences among Different Types of Human Teeth: A Preliminary Compositional Insight
Authors: Sharma Vaibhav , Rastogi Simran , Kumar Bhati Kaushal , Srinivasan Alagiri , Roychoudhury Ajoy , Nikolajeff Fredrik , Kumar Saroj
Published: November 2020

In recent years, studies on mineralized tissues are becoming increasingly popular not only due to the diverse mechanophysical properties of such materials but also because of the growing need to understand the intricate mechanism involved in their assembly and formation. The biochemical mechanism that results in the formation of such hierarchical structures through a well-coordinated accumulation of inorganic and organic components is termed biomineralization. Some prime examples of such tissues in the human body are teeth and bones. Our current study is an attempt to dissect the compositional details of the inorganic and organic components in four major types of human teeth using mass spectrometry-based approaches. We quantified inorganic materials using inductively coupled plasma resonance mass spectrometry (ICP-MS). Differential level of ten different elements, Iron (Fe), Cadmium (Cd), Potassium (K), Sulphur (S), Cobalt (Co), Magnesium (Mg), Manganese (Mn), Zinc (Zn), Aluminum (Al), and Copper (Cu) were quantified across different teeth types. The qualitative and quantitative details of their respective proteomic milieu revealed compositional differences. We found 152 proteins in total tooth protein extract. Differential abundance of proteins in different teeth types were also noted. Further, we were able to find out some significant protein-protein interaction (PPI) backbone through the STRING database. Since this is the first study analyzing the differential details of inorganic and organic counterparts within teeth, this report will pave new directions to the compositional understanding and development of novel in-vitro repair strategies for such biological materials.
Fluctuations in Intracellular CheY-P Concentration Coordinate Reversals of Flagellar Motors in E. coli
Authors: Che Yong-Suk , Sagawa Takashi , Inoue Yuichi , Takahashi Hiroto , Hamamoto Tatsuki , Ishijima Akihiko , Fukuoka Hajime
Published: November 2020

Signal transduction utilizing membrane-spanning receptors and cytoplasmic regulator proteins is a fundamental process for all living organisms, but quantitative studies of the behavior of signaling proteins, such as their diffusion within a cell, are limited. In this study, we show that fluctuations in the concentration of the signaling molecule, phosphorylated CheY, constitute the basis of chemotaxis signaling. To analyze the propagation of the CheY-P signal quantitatively, we measured the coordination of directional switching between flagellar motors on the same cell. We analyzed the time lags of the switching of two motors in both CCW-to-CW and CW-to-CCW switching (∆τCCW-CW and ∆τCW-CCW). In wild-type cells, both time lags increased as a function of the relative distance of two motors from the polar receptor array. The apparent diffusion coefficient estimated for ∆τ values was ~9 µm2/s. The distance-dependency of ∆τCW-CCW disappeared upon loss of polar localization of the CheY-P phosphatase, CheZ. The distance-dependency of the response time for an instantaneously applied serine attractant signal also disappeared with the loss of polar localization of CheZ. These results were modeled by calculating the diffusion of CheY and CheY-P in cells in which phosphorylation and dephosphorylation occur in different subcellular regions. We conclude that diffusion of signaling molecules and their production and destruction through spontaneous activity of the receptor array generates fluctuations in CheY-P concentration over timescales of several hundred milliseconds. Signal fluctuation coordinates rotation among flagella and regulates steady-state run-and-tumble swimming of cells to facilitate efficient responses to environmental chemical signals.
Alendronate/cRGD-Decorated Ultrafine Hyaluronate Dot Targeting Bone Metastasis
Authors: Lee Eunsol , Park Jaeduk , Youn Yu Seok , Oh Kyung Taek , Kim Dongin , Lee Eun Seong
Published: November 2020

In this study, we report the hyaluronate dot (dHA) with multiligand targeting ability and a photosensitizing antitumor model drug for treating metastatic bone tumors. Here, the dHA was chemically conjugated with alendronate (ALN, as a specific ligand to bone), cyclic arginine-glycine-aspartic acid (cRGD, as a specific ligand to tumor integrin αvβ3), and photosensitizing chlorin e6 (Ce6, for photodynamic tumor therapy), denoted as (ALN/cRGD)@dHA-Ce6. These dots thus prepared (≈10 nm in diameter) enabled extensive cellular interactions such as hyaluronate (HA)-mediated CD44 receptor binding, ALN-mediated bone targeting, and cRGD-mediated tumor integrin αvβ3 binding, thus improving their tumor targeting efficiency, especially for metastasized MDA-MB-231 tumors. As a result, these dots improved the tumor targeting efficiency and tumor cell permeability in a metastatic in vivo tumor model. Indeed, we demonstrated that (ALN/cRGD)@dHA-Ce6 considerably increased photodynamic tumor ablation, the extent of which is superior to that of the tumor ablation of dot systems with single or double ligands. These results indicate that dHA with multiligand can provide an effective treatment strategy for metastatic bone tumors.
Gas Crosstalk between PFPE–PEG–PFPE Triblock Copolymer Surfactant-Based Microdroplets and Monitoring Bacterial Gas Metabolism with Droplet-Based Microfluidics
Authors: Ki Sunghyun , Kang Dong-Ku
Published: November 2020

The PFPE–PEG–PFPE (Perfluoropolyether-polyethylene glycol-perfluoropolyether) surfactant has been used in droplet-based microfluidics and is known to provide high droplet stability and biocompatibility. Since this surfactant ensures the stability of droplets, droplet-based microfluidic systems have been widely used to encapsulate and analyze various biological components at the single-molecule scale, including viruses, bacteria, nucleic acids and proteins. In this study, we experimentally confirmed that gas crosstalk occurred between droplets formed by fluorinated oil and the PFPE–PEG–PFPE surfactant. E. coli K-12 bacterial cells were encapsulated with Luria–Bertani broth within droplets for the cultivation, and gas crosstalk was identified with neighboring droplets that contain phenol red. Since bacteria produce ammonia gas during its metabolism, penetration of ammonia gas initiates a color change of phenol red-containing droplets. Ammonia gas exchange was also confirmed by reacting ammonium chloride and sodium hydroxide within droplets that encapsulated. Herein, we demonstrate the gas crosstalk issue between droplets when it is formed using the PFPE–PEG–PFPE surfactant and also confirm that the density of droplet barrier has effects on gas crosstalk. Our results also suggest that droplet-based microfluidics can be used for the monitoring of living bacteria by the determination of bacterial metabolites during cultivation.
Real-Time Optical Monitoring of Endotracheal Tube Displacement
Authors: Ullah Ramzan , Doerfer Karl , Khampang Pawjai , Fathi Faraneh , Hong Wenzhou , Kerschner Joseph E. , Yu Bing
Published: November 2020

Proper ventilation of a patient with an endotracheal tube (ETT) requires proper placement of the ETT. We present a sensitive, noninvasive, operator-free, and cost-effective optical sensor, called Opt-ETT, for the real-time assessment of ETT placement and alerting of the clinical care team should the ETT become displaced. The Opt-ETT uses a side-firing optical fiber, a near-infrared light-emitting diode, two photodetectors with an integrated amplifier, an Arduino board, and a computer loaded with a custom LabVIEW program to monitor the position of the endotracheal tube inside the windpipe. The Opt-ETT generates a visual and audible warning if the tube moves over a distance set by the operator. Displacement prediction is made using a second-order polynomial fit to the voltages measured from each detector. The system is tested on ex vivo porcine tissues, and the accuracy is determined to be better than 1.0 mm. In vivo experiments with a pig are conducted to test the performance and usability of the system.
Is the Regular Intake of Anticoagulative Agents an Independent Risk Factor for the Severity of Traumatic Brain Injuries in Geriatric Patients? A Retrospective Analysis of 10,559 Patients from the TraumaRegister DGU®
Authors: Eibinger Nicolas , Halvachizadeh Sascha , Hallmann Barbara , Seibert Franz Josef , Puchwein Paul , Berk Till , Lefering Rolf , Sprengel Kai , Pape Hans Christoph , Jensen Kai Oliver ,   The TraumaRegister DGU
Published: November 2020

The purpose of this study was to assess anticoagulant medication as an independent factor influencing the occurrence of a severe traumatic brain injury in geriatric patients. Data were collected from the TraumaRegister DGU® between January 2015 and December 2018. We included patients with an age of ≥65 years with a blunt TBI; an AISHead ≥2 but no other relevant injuries. Patients were divided into five subgroups: no anticoagulant medication, anti-platelet drugs, vitamin K antagonists, direct-oral-anticoagulants, and heparinoids. Separation between moderate TBI (AISHead 2–3) and severe TBI (AISHead ≥ 4) and multivariable regression analysis were performed. The average age of 10,559 included patients was 78.8 years with a mean ISS of 16.8 points and a mortality of 22.9%. The most common cause of injury was a low fall of <3 m with 72.8%. With increasing age, the number of patients without any anticoagulant therapy decreased from 65.9% to 29.9%. The intake of coagulation medication increased mortality significantly. Severe TBI was observed in 51% of patients without medication and ranged from 61 to 67% with anticoagulant drugs. After adjusting for confounding variables, the intake of VKA or DOACs was significantly associated with an increased risk of severe TBI. The use of anticoagulant medication is an independent factor and is associated with an increased severity of TBI depending on the type of medication used.
Neuroimaging of Basal Ganglia in Neurometabolic Diseases in Children
Authors: Paprocka Justyna , Machnikowska-Sokołowska Magdalena , Gruszczyńska Katarzyna , Emich-Widera Ewa
Published: November 2020

Diseases primarily affecting the basal ganglia in children result in characteristic disturbances of movement and muscle tone. Both experimental and clinical evidence indicates that the basal ganglia also play a role in higher mental states. The basal ganglia can be affected by neurometabolic, degenerative diseases or other conditions from which they must be differentiated. Neuroradiological findings in basal ganglia diseases are also known. However, they may be similar in different diseases. Their assessment in children may require repeated MRI examinations depending on the stage of brain development (mainly the level of myelination). A large spectrum of pathological changes in the basal ganglia in many diseases is caused by their vulnerability to metabolic abnormalities and chemical or ischemic trauma. The diagnosis is usually established by correlation of clinical and radiological findings. Neuroimaging of basal ganglia in neurometabolic diseases is helpful in early diagnosis and monitoring of changes for optimal therapy. This review focuses on neuroimaging of basal ganglia and its role in the differential diagnosis of inborn errors of metabolism.
Functional and Structural Connectome Features for Machine Learning Chemo-Brain Prediction in Women Treated for Breast Cancer with Chemotherapy
Authors: Chen Vincent Chin-Hung , Lin Tung-Yeh , Yeh Dah-Cherng , Chai Jyh-Wen , Weng Jun-Cheng
Published: November 2020

Breast cancer is the leading cancer among women worldwide, and a high number of breast cancer patients are struggling with psychological and cognitive disorders. In this study, we aim to use machine learning models to discriminate between chemo-brain participants and healthy controls (HCs) using connectomes (connectivity matrices) and topological coefficients. Nineteen female post-chemotherapy breast cancer (BC) survivors and 20 female HCs were recruited for this study. Participants in both groups received resting-state functional magnetic resonance imaging (rs-fMRI) and generalized q-sampling imaging (GQI). Logistic regression (LR), decision tree classifier (CART), and xgboost (XGB) were the models we adopted for classification. In connectome analysis, LR achieved an accuracy of 79.49% with the functional connectomes and an accuracy of 71.05% with the structural connectomes. In the topological coefficient analysis, accuracies of 87.18%, 82.05%, and 83.78% were obtained by the functional global efficiency with CART, the functional global efficiency with XGB, and the structural transitivity with CART, respectively. The areas under the curves (AUCs) were 0.93, 0.94, 0.87, 0.88, and 0.84, respectively. Our study showed the discriminating ability of functional connectomes, structural connectomes, and global efficiency. We hope our findings can contribute to an understanding of the chemo brain and the establishment of a clinical system for tracking chemo brain.
Tissue-Resident Memory T Cells in the Liver—Unique Characteristics of Local Specialists
Authors: Bartsch Lea M. , Damasio Marcos P. S. , Subudhi Sonu , Drescher Hannah K.
Published: November 2020

T cells play an important role to build up an effective immune response and are essential in the eradication of pathogens. To establish a long-lasting protection even after a re-challenge with the same pathogen, some T cells differentiate into memory T cells. Recently, a certain subpopulation of memory T cells at different tissue-sites of infection was detected—tissue-resident memory T cells (TRM cells). These cells can patrol in the tissue in order to encounter their cognate antigen to establish an effective protection against secondary infection. The liver as an immunogenic organ is exposed to a variety of pathogens entering the liver through the systemic blood circulation or via the portal vein from the gut. It could be shown that intrahepatic TRM cells can reside within the liver tissue for several years. Interestingly, hepatic TRM cell differentiation requires a distinct cytokine milieu. In addition, TRM cells express specific surface markers and transcription factors, which allow their identification delimited from their circulating counterparts. It could be demonstrated that liver TRM cells play a particular role in many liver diseases such as hepatitis B and C infection, non-alcoholic fatty liver disease and even play a role in the development of hepatocellular carcinoma and in building long-lasting immune responses after vaccination. A better understanding of intrahepatic TRM cells is critical to understand the pathophysiology of many liver diseases and to identify new potential drug targets for the development of novel treatment strategies.
Significance of Simple Steatosis: An Update on the Clinical and Molecular Evidence
Authors: Mazzolini Guillermo , Sowa Jan-Peter , Atorrasagasti Catalina , Kücükoglu Özlem , Syn Wing-Kin , Canbay Ali
Published: November 2020

Non-alcoholic fatty liver disease (NAFLD) is defined clinicopathologically by the accumulation of lipids in >5% of hepatocytes and the exclusion of secondary causes of fat accumulation. NAFLD encompasses a wide spectrum of liver damage, extending from simple steatosis or non-alcoholic fatty liver (NAFL) to non-alcoholic steatohepatitis (NASH)—the latter is characterized by inflammation and hepatocyte ballooning degeneration, in addition to the steatosis, with or without fibrosis. NAFLD is now the most common cause of chronic liver disease in Western countries and affects around one quarter of the general population. It is a multisystem disorder, which is associated with an increased risk of type 2 diabetes mellitus as well as liver- and cardiovascular-related mortality. Although earlier studies had suggested that NAFL is benign (i.e., non-progressive), cumulative evidence challenges this dogma, and recent data suggest that nearly 25% of those with NAFL may develop fibrosis. Importantly, NAFLD patients are more susceptible to the toxic effects of alcohol, drugs, and other insults to the liver. This is likely due to the functional impairment of steatotic hepatocytes, which is virtually undetectable by current clinical tests. This review provides an overview of the current evidence on the clinical significance of NAFL and discusses the molecular basis for NAFL development and progression.
Integrated Single-Cell RNA-Sequencing Analysis of Aquaporin 5-Expressing Mouse Lung Epithelial Cells Identifies GPRC5A as a Novel Validated Type I Cell Surface Marker
Authors: Horie Masafumi , Castaldi Alessandra , Sunohara Mitsuhiro , Wang Hongjun , Ji Yanbin , Liu Yixin , Li Fan , Wilkinson Thomas A. , Hung Long , Shen Hua , Kage Hidenori , Offringa Ite A. , Marconett Crystal N. , Flodby Per , Zhou Beiyun , Borok Zea
Published: November 2020

Molecular and functional characterization of alveolar epithelial type I (AT1) cells has been challenging due to difficulty in isolating sufficient numbers of viable cells. Here we performed single-cell RNA-sequencing (scRNA-seq) of tdTomato+ cells from lungs of AT1 cell-specific Aqp5-Cre-IRES-DsRed (ACID);R26tdTomato reporter mice. Following enzymatic digestion, CD31-CD45-E-cadherin+tdTomato+ cells were subjected to fluorescence-activated cell sorting (FACS) followed by scRNA-seq. Cell identity was confirmed by immunofluorescence using cell type-specific antibodies. After quality control, 92 cells were analyzed. Most cells expressed ‘conventional’ AT1 cell markers (Aqp5, Pdpn, Hopx, Ager), with heterogeneous expression within this population. The remaining cells expressed AT2, club, basal or ciliated cell markers. Integration with public datasets identified three robust AT1 cell- and lung-enriched genes, Ager, Rtkn2 and Gprc5a, that were conserved across species. GPRC5A co-localized with HOPX and was not expressed in AT2 or airway cells in mouse, rat and human lung. GPRC5A co-localized with AQP5 but not pro-SPC or CC10 in mouse lung epithelial cell cytospins. We enriched mouse AT1 cells to perform molecular phenotyping using scRNA-seq. Further characterization of putative AT1 cell-enriched genes revealed GPRC5A as a conserved AT1 cell surface marker that may be useful for AT1 cell isolation.
The Role of Mitigation Options for Achieving a Low-Carbon Economy in the Netherlands in 2050 Using a System Dynamics Modelling Approach
Authors: Linderhof Vincent , Dekkers Kristie , Polman Nico
Published: November 2020

To reach a low-carbon economy in the Netherlands, the level of greenhouse gases (GHG) emissions has to be reduced by 80–95% CO2 emissions compared to 1990 (223.1 MtCO2-equivalents). This study aims to address how investment subsidies combined with carbon levies could be deployed to support technological mitigation options to achieve a low-carbon economy in the Netherlands in 2050. A system dynamic model has been built including demographic-economic, energy and environmental sub-systems of the Netherlands. The model has been validated with earlier projections of the EU for the energy and climate policy in 2050. Next to the business-as-usual scenario, there are four policy scenarios simulated from 2010 to 2050. In all policy scenarios a carbon levy was imposed on non-renewable energy to finance subsidies on mitigation options. Results show that imposing subsidies on the mitigation option renewable energy is most effective in combination with the carbon levy.