bluuebunny/crossref_metadata_2025 huggingface dataset:
Testing PtCu Nanoparticles Supported on Highly Ordered Mesoporous Carbons CMK3 and CMK8 as Catalysts for Low-Temperature Fuel Cells
Authors: Garcia-Cardona Julia , Alcaide Francisco , Brillas Enric , Sirés Ignasi , Cabot Pere L.
Published: June 2021

Pt(Cu) nanoparticles supported on CMK3 and CMK8 ordered mesoporous carbons (OMCs) have been synthesized by electroless deposition of Cu followed by galvanic exchange with Pt. The structural characterization by high-resolution transmission electron microscopy and X-ray diffraction showed the formation of Pt(Cu) nanoparticles of 4–5 nm, in which PtCu alloys with contracted fcc Pt lattice and 70–80 at.% Pt was identified. The X-ray photoelectron spectroscopy analyses indicated that the Pt(Cu) nanoparticles were mainly composed of a PtCu alloy core covered by a Pt-rich shell, in agreement with the steady cyclic voltammograms, which did not show any Cu oxidation peaks. Electroactive surface areas up to about 70 m2 gPt−1 were obtained. The onset potentials for CO oxidation and the oxygen reduction reaction were more negative and positive, respectively, as compared to Pt/C, thus indicating higher activity of these Pt(Cu) catalysts with respect to the latter. Based on the corresponding binding energies, these better activities were attributed to the favorable geometric and ligand effects of Cu on Pt, which were able to reduce the adsorption energy of the intermediates on Pt. Pt(Cu)/CMK3 showed competitive mass and specific activities, as well as better stability than Pt/C.
Incorporation of 5-Bromo-2′-deoxyuridine into DNA and Proliferative Behavior of Cerebellar Neuroblasts: All That Glitters Is Not Gold
Authors: Martí-Clúa Joaquín
Published: June 2021

The synthetic halogenated pyrimidine analog, 5-bromo-2′-deoxyuridine (BrdU), is a marker of DNA synthesis. This exogenous nucleoside has generated important insights into the cellular mechanisms of the central nervous system development in a variety of animals including insects, birds, and mammals. Despite this, the detrimental effects of the incorporation of BrdU into DNA on proliferation and viability of different types of cells has been frequently neglected. This review will summarize and present the effects of a pulse of BrdU, at doses ranging from 25 to 300 µg/g, or repeated injections. The latter, following the method of the progressively delayed labeling comprehensive procedure. The prenatal and perinatal development of the cerebellum are studied. These current data have implications for the interpretation of the results obtained by this marker as an index of the generation, migration, and settled pattern of neurons in the developing central nervous system. Caution should be exercised when interpreting the results obtained using BrdU. This is particularly important when high or repeated doses of this agent are injected. I hope that this review sheds light on the effects of this toxic maker. It may be used as a reference for toxicologists and neurobiologists given the broad use of 5-bromo-2′-deoxyuridine to label dividing cells.
Molecular and Cellular Mechanisms of Glioblastoma
Authors: Castresana Javier S. , Meléndez Bárbara
Published: June 2021

Glioblastoma is the most malignant primary brain tumor [...]
New Perspectives on the Biogenesis of Viral Inclusion Bodies in Negative-Sense RNA Virus Infections
Authors: Dolnik Olga , Gerresheim Gesche K. , Biedenkopf Nadine
Published: June 2021

Infections by negative strand RNA viruses (NSVs) induce the formation of viral inclusion bodies (IBs) in the host cell that segregate viral as well as cellular proteins to enable efficient viral replication. The induction of those membrane-less viral compartments leads inevitably to structural remodeling of the cellular architecture. Recent studies suggested that viral IBs have properties of biomolecular condensates (or liquid organelles), as have previously been shown for other membrane-less cellular compartments like stress granules or P-bodies. Biomolecular condensates are highly dynamic structures formed by liquid-liquid phase separation (LLPS). Key drivers for LLPS in cells are multivalent protein:protein and protein:RNA interactions leading to specialized areas in the cell that recruit molecules with similar properties, while other non-similar molecules are excluded. These typical features of cellular biomolecular condensates are also a common characteristic in the biogenesis of viral inclusion bodies. Viral IBs are predominantly induced by the expression of the viral nucleoprotein (N, NP) and phosphoprotein (P); both are characterized by a special protein architecture containing multiple disordered regions and RNA-binding domains that contribute to different protein functions. P keeps N soluble after expression to allow a concerted binding of N to the viral RNA. This results in the encapsidation of the viral genome by N, while P acts additionally as a cofactor for the viral polymerase, enabling viral transcription and replication. Here, we will review the formation and function of those viral inclusion bodies upon infection with NSVs with respect to their nature as biomolecular condensates.
Single-Cell RNA-Seq Reveals Transcriptomic Heterogeneity and Post-Traumatic Osteoarthritis-Associated Early Molecular Changes in Mouse Articular Chondrocytes
Authors: Sebastian Aimy , McCool Jillian L. , Hum Nicholas R. , Murugesh Deepa K. , Wilson Stephen P. , Christiansen Blaine A. , Loots Gabriela G.
Published: June 2021

Articular cartilage is a connective tissue lining the surfaces of synovial joints. When the cartilage severely wears down, it leads to osteoarthritis (OA), a debilitating disease that affects millions of people globally. The articular cartilage is composed of a dense extracellular matrix (ECM) with a sparse distribution of chondrocytes with varying morphology and potentially different functions. Elucidating the molecular and functional profiles of various chondrocyte subtypes and understanding the interplay between these chondrocyte subtypes and other cell types in the joint will greatly expand our understanding of joint biology and OA pathology. Although recent advances in high-throughput OMICS technologies have enabled molecular-level characterization of tissues and organs at an unprecedented resolution, thorough molecular profiling of articular chondrocytes has not yet been undertaken, which may be in part due to the technical difficulties in isolating chondrocytes from dense cartilage ECM. In this study, we profiled articular cartilage from healthy and injured mouse knee joints at a single-cell resolution and identified nine chondrocyte subtypes with distinct molecular profiles and injury-induced early molecular changes in these chondrocytes. We also compared mouse chondrocyte subpopulations to human chondrocytes and evaluated the extent of molecular similarity between mice and humans. This work expands our view of chondrocyte heterogeneity and rapid molecular changes in chondrocyte populations in response to joint trauma and highlights potential mechanisms that trigger cartilage degeneration.
An Institutional-Based Governance Framework for Energy Efficiency Promotion in Small Island Developing States
Authors: Shah Kalim U. , Raghoo Pravesh , Surroop Dinesh
Published: June 2021

Energy efficiency and conservation policy continues to take the proverbial “backseat” to energy access and renewable energy policy discourses in small island developing states (SIDS). In this study, we intend to motivate the energy efficiency policy agenda to encourage more action. To do so, we review the current energy challenges in SIDS and the role of energy efficiency in addressing those challenges, discuss the trends in the rate of improvement in energy efficiency in SIDS, exhibit an updated list of energy efficiency programs and initiatives being implemented in SIDS, consider barriers to energy efficiency implementation and set forth a policy-focused plan to accelerate action. Barriers for the adoption of energy efficiency policies continue to be institutional and policy- and governance-oriented; economic and financial; informational; and technical. A four-pronged policy advancement approach tackling initiation, incentivization, information and investment is recommended to tap the potential gains from energy efficiency. We attempt here, based on our findings, to offer a more practically executable plan of action, focusing squarely on combining institutional arrangements, policy requirements and current energy efficiency affairs in SIDS.
Special Issue “1D, 2D, and 3D ZnO: Synthesis, Characterization, and Applications”
Authors: Sánchez Olga , Hernández-Vélez Manuel
Published: June 2021

Zinc Oxide (ZnO) is a well-known II–VI semiconductor with a direct bandgap around 3 [...]
Effects of Oxygen Content on Operational Characteristics and Stability of High-Mobility IGTO Thin-Film Transistors during Channel Layer Deposition
Authors: Jeong Hwan-Seok , Cha Hyun-Seok , Hwang Seong-Hyun , Lee Dong-Ho , Song Sang-Hun , Kwon Hyuck-In
Published: June 2021

In this study, we investigated the effects of oxygen content on the transfer characteristics and stability of high-mobility indium-gallium-tin oxide (IGTO) thin-film transistors (TFTs) during channel layer deposition. The IGTO thin films were deposited through direct current sputtering at different ambient oxygen percentages of 10%, 20%, 30%, 40%, and 50%. The experimental results indicate that the drain currents were hardly modulated by the gate-to-source voltage in the IGTO TFT prepared at 10% ambient oxygen. However, as the oxygen content increased from 20% to 50%, the transfer curves shifted to the positive direction with a decrease in field-effect mobility (μFE). The IGTO TFTs exhibited deteriorated positive bias stress (PBS) stability as the oxygen content increased. However, the stabilities of the IGTO TFTs under negative bias illumination stress (NBIS) improved with an increase in the ambient oxygen percentage during the channel layer deposition. Furthermore, to understand the mechanism of the observed phenomena, we performed X-ray photoelectron spectroscopy (XPS) analysis of the IGTO thin films prepared at different oxygen percentages. The XPS results demonstrate that the deteriorated PBS stability and enhanced NBIS stability of the IGTO TFTs prepared at higher oxygen percentages were mainly ascribed to the larger amount of oxygen interstitials resulting from the excess oxygen and the smaller number of oxygen vacancies within the IGTO, respectively. The obtained results suggest that the oxygen percentages of 30% in the sputtering ambient is the most suitable oxygen percentage for optimizing the electrical properties (μFE = 24.2 cm2/V·s, subthreshold swing = 0.43 V/dec, and threshold voltage = −2.2 V) and adequate PBS and NBIS stabilities of IGTO TFTs.
On Concept of Hybrid in Colloid Sciences
Authors: La Mesa Camillo , Risuleo Gianfranco
Published: June 2021

The concepts hybrid and hybridization are common in many scientific fields, as in the taxonomic parts of botany and zoology, in modern genetic, and in the quantum–mechanical theory of atomic–molecular orbitals, which are of foremost relevance in most aspects of modern chemistry. Years later, scientists applied the concept hybrid to colloids, if the particles’ domains are endowed with functionalities differing each from the other in nature and/or composition. For such denomination to be fully valid, the domains belonging to a given hybrid must be recognizable each from another in terms of some intrinsic features. Thus, the concept applies to particles where a given domain has its own physical state, functionality, or composition. Literature examples in this regard are many. Different domains that are present in hybrid colloids self-organize, self-sustain, and self-help, according to the constraints dictated by kinetic and/or thermodynamic stability rules. Covalent, or non-covalent, bonds ensure the formation of such entities, retaining the properties of a given family, in addition to those of the other, and, sometimes, new ones. The real meaning of this behavior is the same as in zoology; mules are pertinent examples, since they retain some features of their own parents (i.e., horses and donkeys) but also exhibit completely new ones, such as the loss of fertility. In colloid sciences, the concept hybrid refers to composites with cores of a given chemical type and surfaces covered by moieties differing in nature, or physical state. This is the result of a mimicry resembling the ones met in a lot of biological systems and foods, too. Many combinations may occur. Silica nanoparticles on which polymers/biopolymers are surface-bound (irrespective of whether binding is covalent or not) are pertinent examples. Here, efforts are made to render clear the concept, which is at the basis of many applications in the biomedical field, and not only. After a historical background and on some features of the species taking part to the formation of hybrids, we report on selected cases met in modern formulations of mixed, and sometimes multifunctional, colloid entities.
Experimental Study on the Effect of Compound Activator on the Mechanical Properties of Steel Slag Cement Mortar
Authors: Guan Junfeng , Zhang Yulong , Yao Xianhua , Li Lielie , Zhang Lei , Yi Jinhua
Published: June 2021

In this study, activator, metakaolin, and silica fume were used as a compound activator to improve the activity of steel slag powder. The influence of activator, steel slag powder, metakaolin, and silica fume on the resulting strength of steel slag cement mortar was investigated by orthogonal experiments. For four weight fractions of steel slag powder (10%, 20%, 30%, 40%), the experimental results indicate that the compressive strength of mortar can reach up to more than 85% of the control group while the flexural strength can reach up to more than 90% of the flexural strength of the control group. Through orthogonal analysis, it is determined that the activator is the primary factor influencing the mortar strength. According to the result of orthogonal analysis, the optimal dosages of activator, steel slag powder, metakaolin, and silica fume are suggested. The GM (0, N) prediction model of compressive strength and flexural strength was established, and the compressive strength and flexural strength of mortar with the optimal dosage combinations were predicted. The prediction results show that by using the optimal dosage combination, the mortar strength can reach the level of P·O·42.5 cement. Considering the different strength and cost requirements of cementitious materials in practical engineering, the economic benefits of replacing cement with steel slag powder activated by compound activator in various proportions and equal amounts were presented. The results show that the method proposed in this study can reduce the cost of cementitious materials.
Hugoniot States and Mie–Grüneisen Equation of State of Iron Estimated Using Molecular Dynamics
Authors: Wang Yuntian , Zeng Xiangguo , Chen Huayan , Yang Xin , Wang Fang , Ding Jun
Published: June 2021

The objective of this study was to develop a micromechanical approach for determining the Mie–Grüneisen EOS parameters of iron under the Hugoniot states. The multiscale shock technique (MSST) coupled with molecular dynamics (MD) simulations was employed to describe the shocked Hugoniot relation of single-crystal (SC) and nanocrystalline (NC) iron under high pressures. The Mie–Grüneisen equation of state (EOS) parameters, the cold pressure (Pc), the cold energy (Ec), the Grüneisen coefficient (γ), and the melting temperature (Tm) are discussed. The error between SC and NC iron results was found to be less than 1.5%. Interestingly, the differences in Hugoniot state (PH) and the internal energy between SC and NC iron were insignificant, which shows that the effect of grain size (GS) under high pressures was not significant. The Pc and Ec of SC and NC iron calculated based on the Morse potential were almost the same with those calculated based on the Born–Mayer potential; however, those calculated based on the Born–Mayer potential were a little larger at high pressures. In addition, several empirical and theoretical models were compared for the calculation of γ and Tm. The Mie–Grüneisen EOSs were shown on the 3D contour space; the pressure obtained with the Hugoniot curves as the reference was larger than that obtained with the cold curves as the reference.
Microwave Mediated Fast Synthesis of Silver Nanoparticles and Investigation of Their Antibacterial Activities for Gram-Positive and Gram-Negative Microorganisms
Authors: Ahmed Faheem , AlOmar Suliman Yousef , Albalawi Fadwa , Arshi Nishat , Dwivedi Sourabh , Kumar Shalendra , Shaalan Nagih Mohammed , Ahmad Naushad
Published: June 2021

Herein, a simple one-step microwave irradiation technique has been used to synthesize the silver nanoparticles using silver nitrate (AgNO3) solution and cetyltrimethyl ammonium bromide (CTAB) as a stabilizing agent. The crystals of as-prepared nanoparticles were studied using X-ray diffraction (XRD) and a selected area electron diffraction (SAED) pattern, confirming the single-phase face-centered cubic structure. The optical property measured using UV-Vis spectroscopy shows an absorption maximum at 420 nm, which also confirms the formation of silver nanoparticles. Transmission electron microscopy (TEM) analysis revealed that the silver nanoparticles have a spherical shape with an average diameter of ~6 nm. The antibacterial properties of silver nanoparticles were investigated using both Gram-positive and Gram-negative microorganisms, such as Staphylococcus aureus, Pseudomonas aeruginosa, andEscherichia coli. Klebsiella pneumoniae, and Candida albicans. Results showed a highest zone of inhibition of about 35 mm against P. aeruginosa as compared with E. coli (21 mm), S. aureus (30 mm), K. pneumonia (28 mm), and C. albicans (29 mm). These studies suggested that silver nanoparticles prepared by this fast and effective method might be developed as antibacterial agents against an extensive range of microorganisms to control and stop the spreading and persistence of bacterial infections.
Studies of Hydrogen Bond Vibrations of Hydrogen-Disordered Ice Ic
Authors: Yu Xu-Hao , Qin Xiao-Ling , Dong Xiao-Tong , Cao Jing-Wen , Zhu Xu-Liang , Wang Hao-Cheng , Sun Yan-Ju , Xu Zi-Xun , Zhang Peng
Published: June 2021

The hydrogen-disordered structure of ice, Ic, makes it difficult to analyze the vibrational normal modes in the far-infrared region (i.e., the molecular translation band). To clarify the origin of the energy-splitting of hydrogen bond vibrations in this area, a 64-molecule supercell was constructed and calculated using first-principles density functional theory. The results were in good agreement with inelastic neutron scattering experiments and our previous study of a hydrogen-ordered ice Ic model. Assisted by analytic equations, we concluded that the origin of the two hydrogen bond peaks in real ice Ic is consistent with that of hydrogen-ordered ice Ic: the peaks originate from two kinds of normal mode vibration. We categorize the four peaks in the far-infrared region recorded from inelastic neutron scattering experiments as the acoustic peak, the superposition peak, the two-hydrogen bond peak and the four-hydrogen bond peak. We conclude that the existence of two intrinsic hydrogen bond vibration modes represents a general rule among the ice family, except ice X.
A Review of Inorganic Scintillation Crystals for Extreme Environments
Authors: Kim Chanho , Lee Wonhi , Melis Alima , Elmughrabi Abdallah , Lee Kisung , Park Chansun , Yeom Jung-Yeol
Published: June 2021

In the past, the main research and use of scintillators in extreme environments were mainly limited to high energy physics and the well-logging industry, but their applications are now expanding to reactor monitoring systems, marine and space exploration, nuclear fusion, radiation therapy, etc. In this article, we review and summarize single-crystal inorganic scintillator candidates that can be applied to radiation detection in extreme environments. Crucial scintillation properties to consider for use in extreme environments are temperature dependence and radiation resistance, along with scintillators’ susceptibility to moisture and mechanical shock. Therefore, we report on performance change, with a focus on radiation resistance and temperature dependence, and the availability of inorganic scintillator for extreme environments—high radiation, temperature, humidity and vibration—according to their applications. In addition, theoretical explanations for temperature dependence and radiation resistance are also provided.
Morphological and Crystallographic Effects in the Laser Powder-Bed Fused Stainless Steel Microstructure
Authors: Fischer Tim , Hitzler Leonhard , Werner Ewald
Published: June 2021

One of the key aspects in additive manufacturing of stainless steels is the relationship between process parameters and the resulting microstructure. The selected process parameters typically cause a rapid solidification of the material, which leads to a microstructure that is highly textured both morphologically and crystallographically. While the morphological texture is characterised by a mainly columnar shape of the grains, the crystallographic texture is marked by a preferred grain orientation in the <001> direction (fibre texture). Due to the texture effects, pronounced anisotropic mechanical properties are present in the material. In this report, a series of virtual microstructures with different morphological and crystallographic features are generated to develop a fundamental understanding of the individual texture effects on the mechanical properties. The grain morphology is based on Voronoi tessellations, and the crystallographic texture is captured with crystal plasticity. Furthermore, the numerical predictions are compared with experimental studies. The mechanical properties predicted on the basis of the virtual microstructures show that the crystallographic effect is much more dominant than the morphology of the individual grains. Consistent with the experiments, the highest load-bearing capacity of the material occurs when the macroscopic loading acts under an angle of 45∘ to the preferred orientation of the crystals.
Dynamic Response of Soil Enzymes and Microbial Diversity to Continuous Application of Atrazine in Black Soil of a Cornfield without Rotation in Northeast China
Authors: Yang Fengshan , Yang Siyuan , Xu Jiangli , Wang Yanbo , Gao Mengying , Zhang Manxia , Dai Wenlong , Fu Haiyan , Zeng Weimin , Liu Chunguang
Published: June 2021

Atrazine has been extensively used in China’s agricultural production for a long time and the potential risks to the environment have received widespread attention. The purpose of this study was to examine the effect of the continuous application of atrazine on soil herbicide residues, soil enzyme activity, and microbial community structure, as well as to provide a theoretical reference for the appropriate application of atrazine and the improvement of soil. Previous studies have focused on the effects of atrazine on soil microorganisms, but the experiments used higher doses than recommended. To reveal the actual effects of atrazine on soil microorganisms, the recommended dose of atrazine was used for 0, 1, and 2 years. We studied atrazine residues and enzyme activity in the soil, and phospholipid fatty acids (PLFA) were measured to study the structure of the soil microbiome. The results show that the rate of atrazine degradation occurred rapidly after the initial administration, and with the increase in continuous administration, its half-life decreased from 24.6 d in the first year to 14.1 d in the second year. The application of atrazine significantly affected soil urease activity and cellulase activity, but it had no significant effect on saccharase activity. The continuous application of atrazine had a significant effect on the biomass of cultured bacteria in soil, but not on the biomass of culturable fungi and actinomycetes in the soil. Furthermore, the results of PLFA analysis show that the application of atrazine had a significant effect on the microbial structure of the soil. These results indicate that the significant increase in the degradation rate of atrazine during continuous application is related to the high adaptability of the soil microbiome.
Spatial Dynamics of Two Host-Parasite Relationships on Intertidal Oyster Reefs
Authors: Hanke Marc H. , Posey Martin H. , Alphin Troy D.
Published: June 2021

Intertidal reefs comprised of the eastern oyster (Crassostrea virginica) have long experienced habitat loss, altering habitat patch characteristics of size and distance from edge to interior, potentially influencing spatial dynamics of host-parasite relationships. Using two parasitic relationships, one between eastern oyster host and parasitic oyster pea crab (Zaops ostreum) and the other between a xanthid crab (Eurypanopeus depressus) and a parasitic rhizocephalan barnacle (Loxothylacus panopaei), we examined how host-parasite population characteristics varied on intertidal reefs by season, reef size, and distance from edge to interior. Pea crab prevalence was more related to habitat characteristics rather than host density, as pea crab prevalence was the highest on large reefs and along edges, areas of comparatively lower oyster densities. Reef size did not influence densities of parasitized or non-parasitized xanthid crabs, but densities varied from edge to interior. Non-parasitized xanthids had significantly lower densities along the reef edge compared to more interior reef locations, while parasitized xanthid crabs had no significant edge to interior pattern. Organismal size had a varied relationship based upon habitat characteristics, as pea crab carapace width (CW) varied interactively with season and reef size, whereas CW of parasitized/non-parasitized xanthid crabs varied significantly between edge and interior locations. These results demonstrated that influential habitat characteristics, such as patch size and edge versus interior, are both highly species and host-parasite specific. Therefore, continued habitat alteration and fragmentation of critical marine habitats may further impact spatial dynamics of host-parasite relationships.
Does Chytridiomycosis Affect Tree Frog Attachment?
Authors: Nieuwboer Lisa , van Leeuwen Johan L. , Martel An , Pasmans Frank , Spitzen-van der Sluijs Annemarieke , Langowski Julian K. A.
Published: June 2021

The pandemic disease chytridiomycosis, caused by the fungus Batrachochytrium dendrobatidis (Bd), is a major threat to amphibian biodiversity. For most species, the exact mechanisms of chytridiomycosis that lead to negative population dynamics remain uncertain, though mounting evidence suggests that sublethal effects could be an important driver. In this review, we propose that tree frog attachment is a promising case to study the sublethal effects of a Bd infection on amphibians. A synthesis of the current knowledge on the functional morphology of the adhesive toe pads of tree frogs, on the underlying mechanisms of tree frog attachment, and on the epidermal pathology of chytridiomycosis substantiates the hypothesis that Bd-induced epidermal alterations have the potential to disrupt tree frog attachment. We highlight a series of (biomechanical) experiments to test this hypothesis and to shed some light on the sublethal disease mechanisms of chytridiomycosis. The knowledge generated from such an approach could contribute to future research on Bd epidemiology and ultimately to the conservation of the biodiversity of arboreal anurans.
Measurements of LoRaWAN Technology in Urban Scenarios: A Data Descriptor
Authors: Masek Pavel , Stusek Martin , Svertoka Ekaterina , Pospisil Jan , Burget Radim , Lohan Elena Simona , Marghescu Ion , Hosek Jiri , Ometov Aleksandr
Published: June 2021

This work is a data descriptor paper for measurements related to various operational aspects of LoRaWAN communication technology collected in Brno, Czech Republic. This paper also provides data characterizing the long-term behavior of the LoRaWAN channel collected during the two-month measurement campaign. It covers two measurement locations, one at the university premises, and the second situated near the city center. The dataset’s primary goal is to provide the researchers lacking LoRaWAN devices with an opportunity to compare and analyze the information obtained from 303 different outdoor test locations transmitting to up to 20 gateways operating in the 868 MHz band in a varying metropolitan landscape. To collect the data, we developed a prototype equipped with a Microchip RN2483 Low-Power Wide-Area Network (LPWAN) LoRaWAN technology transceiver module for the field measurements. As an example of data utilization, we showed the Signal-to-noise Ratio (SNR) and Received Signal Strength Indicator (RSSI) in relation to the closest gateway distance.
Usefulness of the Electrocardiogram in a Patient Presenting with Right-Sided Pneumothorax and Presyncope
Authors: Florescu Lavinia Maria , Țentea Călina-Patricia , Eötvös Csilla-Andrea , Lazar Roxana-Daiana , Zehan Iulia-Georgiana , Sabha Wissam , Pop Sorin , Todea Doina Adina , Blendea Dan
Published: June 2021

We present the case of a 71-year-old man with history of smoking, pulmonary emphysema, hypertension, multivessel coronary artery disease and prior coronary artery bypass graft surgery who presented with spontaneous right-sided pneumothorax associated with phasic changes of the QRS amplitude on the electrocardiogram. While several case reports have described QRS amplitude changes associated with left-sided pneumothorax, reports of phasic ECG changes in right-sided pneumothorax are exceedingly rare. Such changes, when present in a patient with sudden onset chest pain and dyspnea, should prompt a diagnostic workup for possible pneumothorax.
Survival Prediction of Lung Cancer Using Small-Size Clinical Data with a Multiple Task Variational Autoencoder
Authors: Vo Thanh-Hung , Lee Guee-Sang , Yang Hyung-Jeong , Oh In-Jae , Kim Soo-Hyung , Kang Sae-Ryung
Published: June 2021

Due to the increase of lung cancer globally, and particularly in Korea, survival analysis for this type of cancer has gained prominence in recent years. For this task, mathematical and traditional machine learning approaches are commonly used by medical doctors. While the deep learning approach has had proven success in computer vision tasks, natural language processing and other AI techniques are also adopted for this task. Due to the privacy issues and management process, data in medicine are difficult to collect, which leads to a paucity of samples. The small number of samples makes it difficult to use deep learning and renders this approach unusable. In this investigation, we propose a network architecture that combines a variational autoencoder (VAE) with the typical DNN architecture to solve the survival analysis task. With a training size of n = 4107, MVAESA achieves a C-index of 0.722 while CoxCC, CoxPH, and CoxTime achieved scores of 0.713, 0.703, and 0.710, respectively. With a small training size of n = 379, MVAESA achieves a C-index of 0.707, compared with 0.689, 0.688 and 0.690 for CoxCC, CoxPH, and CoxTime, respectively. The results show that the combination of a VAE with a target task makes the network more stable and that the network could be trained using a small-sized sample.
Study on the Implementation of a Simple and Effective Memory System for an AI Chip
Authors: Kim Taepyeong , Park Sangun , Cho Yongbeom
Published: June 2021

In this study, a simple and effective memory system required for the implementation of an AI chip is proposed. To implement an AI chip, the use of internal or external memory is an essential factor, because the reading and writing of data in memory occurs a lot. Those memory systems that are currently used are large in design size and complex to implement in order to handle a high speed and a wide bandwidth. Therefore, depending on the AI application, there are cases where the circuit size of the memory system is larger than that of the AI core. In this study, SDRAM, which has a lower performance than the currently used memory system but does not have a problem in operating AI, was used and all circuits were implemented digitally for simple and efficient implementation. In particular, a delay controller was designed to reduce the error due to data skew inside the memory bus to ensure stability in reading and writing data. First of all, it verified the memory system based on the You Only Look Once (YOLO) algorithm in FPGA to confirm that the memory system proposed in AI works efficiently. Based on the proven memory system, we implemented a chip using Samsung Electronics’ 65 nm process and tested it. As a result, we designed a simple and efficient memory system for AI chip implementation and verified it with hardware.
Design and Implementation of a Hydroponic Strawberry Monitoring and Harvesting Timing Information Supporting System Based on Nano AI-Cloud and IoT-Edge
Authors: Park Sun , Kim JongWon
Published: June 2021

The strawberry market in South Korea is actually the largest market among horticultural crops. Strawberry cultivation in South Korea changed from field cultivation to facility cultivation in order to increase production. However, the decrease in production manpower due to aging is increasing the demand for the automation of strawberry cultivation. Predicting the harvest of strawberries is an important research topic, as strawberry production requires the most manpower for harvest. In addition, the growing environment has a great influence on strawberry production as hydroponic cultivation of strawberries is increasing. In this paper, we design and implement an integrated system that monitors strawberry hydroponic environmental data and determines when to harvest with the concept of IoT-Edge-AI-Cloud. The proposed monitoring system collects, stores and visualizes strawberry growing environment data. The proposed harvest decision system classifies the strawberry maturity level in images using a deep learning algorithm. The monitoring and analysis results are visualized in an integrated interface, which provides a variety of basic data for strawberry cultivation. Even if the strawberry cultivation area increases, the proposed system can be easily expanded and flexibly based on a virtualized container with the concept of IoT-Edge-AI-Cloud. The monitoring system was verified by monitoring a hydroponic strawberry environment for 4 months. In addition, the harvest decision system was verified using strawberry pictures acquired from Smart Berry Farm.
CNN-Based Road-Surface Crack Detection Model That Responds to Brightness Changes
Authors: Lee Taehee , Yoon Yeohwan , Chun Chanjun , Ryu Seungki
Published: June 2021

Poor road-surface conditions pose a significant safety risk to vehicle operation, especially in the case of autonomous vehicles. Hence, maintenance of road surfaces will become even more important in the future. With the development of deep learning-based computer image processing technology, artificial intelligence models that evaluate road conditions are being actively researched. However, as the lighting conditions of the road surface vary depending on the weather, the model performance may degrade for an image whose brightness falls outside the range of the learned image, even for the same road. In this study, a semantic segmentation model with an autoencoder structure was developed for detecting road surface along with a CNN-based image preprocessing model. This setup ensures better road-surface crack detection by adjusting the image brightness before it is input into the road-crack detection model. When the preprocessing model was applied, the road-crack segmentation model exhibited consistent performance even under varying brightness values.
Using Improved SPA and ICS-LSSVM for Sustainability Assessment of PV Industry along the Belt and Road
Authors: Liang Yi , Wang Haichao
Published: June 2021

Scientific and timely sustainability evaluation of the photovoltaic industry along the Belt and Road is of great significance. In this paper, a novel hybrid evaluation model is proposed for accurate and real-time assessment that integrates modified set pair analysis with least squares support vector machine that combines improved cuckoo search algorithm. First, the indicator system is set from five principles, namely economy, politics, society, ecological environment and resources. Then, the traditional approach is established through modifying set pair analysis on the basis of variable fuzzy set coupling evaluation theory. A modern intelligent assessment model is designed that integrates improved cuckoo search algorithm and least squares support vector machine where the concept of random weight is introduced in improved cuckoo search algorithm. In the case analysis, the relative errors calculated by the proposed model all fluctuate in the range of [−3%, 3%], indicating that it has the strongest fitting and learning ability. The empirical analysis verifies the scientificity and precision of the method and points out influencing factors. It provides a new idea for rapid and effective assessment of PV industry along the Belt and Road, as well as assistance for the sustainable development of this industry. This paper innovatively proposes the sustainability evaluation index system and evaluation model for the photovoltaic industry in countries along the Belt and Road, thus contributing to the promotion of sustainable development of the photovoltaic industry in countries along the Belt and Road.
Enhancement of Machinery Activity Recognition in a Mining Environment with GPS Data
Authors: Gackowiec Paulina , Brzychczy Edyta , Kęsek Marek
Published: June 2021

Fast-growing methods of automatic data acquisition allow for collecting various types of data from the production process. This entails developing methods that are able to process vast amounts of data, providing generalised knowledge about the analysed process. Appropriate use of this knowledge can be the basis for decision-making, leading to more effective use of the company’s resources. This article presents the approach for data analysis aimed at determining the operating states of a wheel loader and the place where it operates based on the recorded data. For this purpose, we have used several methods, e.g., for clustering and classification, namely: DBSCAN, CART, C5.0. Our approach has allowed for the creation of decision rules that recognise the operating states of the machine. In this study, we have taken into account the GPS signal readings, and thanks to this, we have indicated the differences in machine operation within the designated states in the open pit and at the mine base area. In this paper, we present the characteristics of the selected clusters corresponding to the machine operation states and emphasise the differences in the context of the operation area. The knowledge obtained in this study allows for determining the states based on only a few selected most essential parameters, even without consideration of the coordinates of the machine’s workplace. Our approach enables a significant acceleration of subsequent analyses, e.g., analysis of the machine states structure, which may be helpful in the optimisation of its use.
A Comprehensive Risk Assessment Framework for Synchrophasor Communication Networks in a Smart Grid Cyber Physical System with a Case Study
Authors: Jha Amitkumar V. , Appasani Bhargav , Ghazali Abu Nasar , Bizon Nicu
Published: June 2021

The smart grid (SG), which has revolutionized the power grid, is being further improved by using the burgeoning cyber physical system (CPS) technology. The conceptualization of SG using CPS, which is referred to as the smart grid cyber physical system (SGCPS), has gained a momentum with the synchrophasor measurements. The edifice of the synchrophasor system is its communication network referred to as a synchrophasor communication network (SCN), which is used to communicate the synchrophasor data from the sensors known as phasor measurement units (PMUs) to the control center known as the phasor data concentrator (PDC). However, the SCN is vulnerable to hardware and software failures that introduce risk. Thus, an appropriate risk assessment framework for the SCN is needed to alleviate the risk in the protection and control of the SGCPS. In this direction, a comprehensive risk assessment framework has been proposed in this article for three types of SCNs, namely: dedicated SCN, shared SCN and hybrid SCN in an SGCPS. The proposed framework uses hardware reliability as well as data reliability to evaluate the associated risk. A simplified hardware reliability model has been proposed for each of these networks, based on failure probability to assess risk associated with hardware failures. Furthermore, the packet delivery ratio (PDR) metric is considered for measuring risk associated with data reliability. To mimic practical shared and hybrid SCNs, the risk associated with data reliability is evaluated for different background traffics of 70%, 80% and 95% using 64 Kbps and 300 Kbps PMU data rates. The analytical results are meticulously validated by considering a case study of West Bengal’s (a state in India) power grid. With respect to the case study, different SCNs are designed and simulated using the QualNet network simulator. The simulations are performed for dedicated SCN, shared SCN and hybrid SCN with 64 Kbps and 300 Kbps PMU data rates. The simulation results are comprehensively analyzed for risk hedging of the proposed SCNs with data reliability and hardware reliability. To summarize, the mean risk with data reliability (RwDR) as compared to the mean risk with hardware reliability (RwHR) increases in shared SCN and hybrid SCN by a factor of 17.108 and 23.278, respectively. However, minimum RwDR increases in shared and hybrid SCN by a factor of 16.005 and 17.717, respectively, as compared to the corresponding minimum RwHR. The overall analysis reveals that the RwDR is minimum for dedicated SCN, moderate for shared SCN, and highest for hybrid SCN.
Optimization for Data-Driven Preventive Control Using Model Interpretation and Augmented Dataset
Authors: Ren Junyu , Li Benyu , Zhao Ming , Shi Hengchu , You Hao , Chen Jinfu
Published: June 2021

Transient stability preventive control (TSPC) ensures that power systems have a sufficient stability margin by adjusting power flow before faults occur. The generation of TSPC measures requires accuracy and efficiency. In this paper, a novel model interpretation-based multi-fault coordinated data-driven preventive control optimization strategy is proposed. First, an augmented dataset covering the fault information is constructed, enabling the transient stability assessment (TSA) model to discriminate the system stability under different fault scenarios. Then, the adaptive synthetic sampling (ADASYN) method is implemented to deal with the imbalanced instances of power systems. Next, an instance-based machine model interpretation tool, Shapley additive explanations (SHAP), is embedded to explain the TSA model’s predictions and to find out the most effective control objects, thus narrowing the number of control objects. Finally, differential evolution is deployed to optimize the generation of TSPC measures, taking into account the security and economy of TSPC. The proposed method’s efficiency and robustness are verified on the New England 39-bus system and the IEEE 54-machine 118-bus system.
Consumer Preferences and Willingness to Pay for Potting Mix with Biochar
Authors: Thomas McKenzie , Jensen Kimberly L. , Lambert Dayton M. , English Burton C. , Clark Christopher D. , Walker Forbes R.
Published: June 2021

Biochar is a co-product of advanced biofuels production from feedstocks including food, agricultural, wood wastes, or dedicated energy crops. Markets for soil amendments using biochar are emerging, but little is known about consumer preferences and willingness to pay (WTP) for these products or the depth of the products’ market potential for this product. This research provides WTP estimates for potting mix amended with 25% biochar, conditioned on consumer demographics and attitudes about product information labeling. Data were collected with an online survey of 577 Tennessee home gardeners. WTP was elicited through a referendum contingent valuation. Consumer WTP for an 8.81 L bag of 25% biochar potting mix is $8.52; a premium of $3.53 over conventional potting mix. Demographics and attitudes toward biofuels and the environment influence WTP. Biochar amounts demanded are projected for the study area’s potential market. Optimal prices, profits, and market shares are estimated across different marginal costs of producing biochar potting mix.
Techno-Economic Aspects of Noble Gases as Monitoring Tracers
Authors: Weber Ulrich Wolfgang , Kampman Niko , Sundal Anja
Published: June 2021

A comprehensive monitoring program is an integral part of the safe operation of geological CO2 storage projects. Noble gases can be used as geochemical tracers to detect a CO2 anomaly and identify its origin, since they display unique signatures in the injected CO2 and naturally occurring geological fluids and gases of the storage site complex. In this study, we assess and demonstrate the suitability of noble gases in source identification of CO2 anomalies even when natural variability and analytical uncertainties are considered. Explicitly, injected CO2 becomes distinguishable from shallow fluids (e.g., subsea gas seeps) due to its inheritance of the radiogenic signature (e.g., high He) of deep crustal fluids by equilibration with the formation water. This equilibration also results in the CO2 inheriting a distinct Xe concentration and Xe/noble gas elemental ratios, which enable the CO2 to be differentiated from deep crustal hydrocarbon gases that may be in the vicinity of a storage reservoir. However, the derivation has uncertainties that may make the latter distinction less reliable. These uncertainties would be best and most economically addressed by coinjection of Xe with a distinct isotope ratio into the CO2 stream. However, such a tracer addition would add significant cost to monitoring programs of currently operating storage projects by up to 70% (i.e., from 1 $US/t to 1.7 $US/t).
Modelling Efficiency of Electric Utilities Using Three Stage Virtual Frontier Data Envelopment Analysis with Variable Selection by Loads Method
Authors: Kannan Pavala Malar , Marthandan Govindan , Kannan Rathimala
Published: June 2021

Electric utility regulators and policy makers implement incentive-based regulation to improve electric utilities efficiency or to manage the cost of electricity. However, poorly implemented regulation may produce undesired results such as low reliability or poor quality of service. Moreover, the competition within the electricity sector is likely to be low because of the high barriers to entry, vertically integrated electric utilities, and high capital requirements. Therefore, benchmarking exercises allow policy makers and regulators to gauge the relative efficiency of electric utilities and help them to reward or penalize the electric utilities accordingly. In this study, we examined the variables that significantly influence the efficiency of electric utilities and developed an optimum method to measure the efficiency of the electric utilities. The results of the efficiency measurement were then used to rank the electric utilities. The result of this study indicates that there are 13 variables that significantly affect the efficiency score of electric utilities and three stage virtual frontier data envelopment analysis (3S-VF-DEA) is the optimum method to measure the efficiency of the electric utilities.