bluuebunny/crossref_metadata_2025 huggingface dataset:
Quantification of Biologically Fixed Nitrogen by White Lupin (Lupins albus L.) and Its Subsequent Uptake by Winter Wheat Using the 15N Isotope Dilution Method
Authors: Kalembasa Stanisław , Szukała Jerzy , Faligowska Agnieszka , Kalembasa Dorota , Symanowicz Barbara , Becher Marcin , Gebus-Czupyt Beata
Published: September 2020

A field experiment was carried out in 2016–2018 in a white lupin (Lupinus albus L.)-winter wheat (Triticum aestivum cv. ‘Bogatka’) crop rotation. The aim of this study was to determine the amount of nitrogen (N) that was biologically fixed by the white lupin crop in the first year of the rotation and to estimate how much of this N was then taken up from the lupin residues by winter wheat in the second and third years of the rotation. Biologically fixed N was determined by the isotope-dilution method (ID15N) by applying 30 kg N ha−1 of 15N-labeled fertilizer (15NH4)2SO4 (containing 20.1 at.% 15N) to the white lupin and the reference plant spring wheat. The yields of white lupin seeds and crop residues were 3.92 t ha−1 and 4.30 t ha−1, respectively. The total amount of N in the white lupin biomass was 243.2 kg ha−1, which included 209.3 kg ha−1 in the seeds and 33.9 kg ha−1 in the residues. The 15N-labeled residue of white lupin was cut and ploughed into soil. Our results indicate that 111.2 kg N ha−1 was fixed from the atmosphere by the lupin plants, with 93.7 kg ha−1 found in the seeds and 17.5 kg ha−1 in the residues. In the second and third years of the rotation when winter wheat was cultivated, the plots were divided into two groups of subplots (1) without N-fertilization (control) and (2) with an application of 100 kg N ha−1. In the first year of winter wheat cultivation, 20.0% and 21.0% of N from the crop residues was taken up by the control and N-fertilization plots, respectively, while in the second year, uptake was lower at 7.12% and 9.27% in the control and N-fertilized plots, respectively.
Nitrogen Fertilizer Equivalence of Black Soldier Fly Frass Fertilizer and Synchrony of Nitrogen Mineralization for Maize Production
Authors: Beesigamukama Dennis , Mochoge Benson , Korir Nicholas , Musyoka Martha W. , Fiaboe Komi K. M. , Nakimbugwe Dorothy , Khamis Fathiya M. , Subramanian Sevgan , Dubois Thomas , Ekesi Sunday , Tanga Chrysantus M.
Published: September 2020

The use of black soldier fly frass fertilizer (BSFFF) is being promoted globally. However, information on nitrogen (N) fertilizer equivalence (NFE) value and synchrony of N mineralization for crop production remains largely unknown. Comparative studies between BSFFF and commercial organic fertilizer (SAFI) were undertaken under field conditions to determine synchrony of N release for maize uptake. The BSFFF, SAFI, and urea fertilizers were applied at the rates of 0, 30, 60, and 100 kg N ha−1. The yield data from urea treated plots were used to determine the NFE of both organic inputs. Results showed that maize from BSFFF treated plots had higher N uptake than that from SAFI treated plots. High N immobilization was observed throughout the active growth stages of maize grown in soil amended with BSFFF, whereas soil treated with SAFI achieved net N release at the silking stage. Up to three times higher negative N fluxes were observed in SAFI amended soils as compared with BSFFF treated plots at the tasseling stage. The BSFFF applied at 30 and 60 kg N ha−1 achieved significantly higher NFE than all SAFI treatments. Our findings revealed that BSFFF is a promising and sustainable alternative to SAFI or urea for enhanced maize production.
Effect of GH p.L127V Polymorphism and Feeding Systems on Milk Production Traits and Fatty Acid Composition in Modicana Cows
Authors: Bordonaro Salvatore , Tumino Serena , Marletta Donata , De Angelis Anna , Di Paola Fortunato , Avondo Marcella , Valenti Bernardo
Published: September 2020

Growth hormone participates in the regulation of lactation and lipid metabolism. A trial study was conducted to evaluate the effects of genetic polymorphism at GH p.L127V and its interaction with feeding system (extensive, EX; semi-intensive, SI) on milk traits and fatty acids composition in Modicana cows. In the semi-intensive farm (SI) diet consisted of hay, concentrate and 2 h of grazing. In the extensive farm (EX) feeding consisted in 8 h of grazing and hay. The frequencies of LL, LV and VV genotypes were, respectively: 0.64, 0.34, 0.02. GH polymorphism and its interaction with feeding system did not influence milk yield and composition. Cows carrying LL genotype produced milk with lower 6:0 and 8:0 and higher 16:1 c9 and 18:1 c9, total UFA and total MUFA. Feeding significantly affected fatty acids: in EX cows lower SFA and higher PUFA and UFA were found, compared to SI cows. The lower, more favorable atherogenic index of milk from EX system was coherent with the improved healthy characteristics of milk from animals fed almost exclusively on pasture. A significant interaction genotype x feeding system was evident for 18:1, higher in the LL cows only in the EX system, but not in the SI system.
Evaluating the Suitability of Hazelnut Skin as a Feed Ingredient in the Diet of Dairy Cows
Authors: Renna Manuela , Lussiana Carola , Malfatto Vanda , Gerbelle Mathieu , Turille Germano , Medana Claudio , Ghirardello Daniela , Mimosi Antonio , Cornale Paolo
Published: September 2020

Hazelnut skin (HS) was evaluated as a source of nutrients for dairy cows. In total, 26 Aosta Red Pied cows were divided into two balanced groups. All cows were fed hay ad libitum. The control group was also given 6 kg of concentrate, while the hazelnut skin group (HAZ) was given 1 kg of the same concentrate that was substituted by 1 kg of HS. The dry matter intake of the cows was reduced by the dietary inclusion of HS (p ≤ 0.001). The milk yield and main constituents were unaffected by treatment. Milk from HAZ cows showed decreased concentrations of de novo saturated fatty acids (FAs), odd- and branched-chain FA, α-linolenic acid, and long-chain n-3 FAs, as well as increased concentrations of stearic acid, oleic acid, linoleic acid, total monounsaturated FAs, trans biohydrogenation intermediates, and α–tocopherol. Replacing the concentrate with HS increased the human-inedible feed quota in the diet and improved the sustainability of milk production in terms of the food-feed competition. Our results suggest that it is possible to add economic value to organic waste from the hazelnut industry using HS as a feed ingredient for dairy cows, enhancing the feed efficiency and milk antioxidant activity and having expected impacts on the nutraceutical quality of milk fat.
Egyptian Shabtis Identification by Means of Deep Neural Networks and Semantic Integration with Europeana
Authors: Duque Domingo Jaime , Gómez-García-Bermejo Jaime , Zalama Eduardo
Published: September 2020

Ancient Egyptians had a complex religion, which was active for longer than the time that has passed since Cleopatra until our days. One amazing belief was to be buried with funerary statuettes to help the deceased carry out his/her tasks in the underworld. These funerary statuettes, mainly known as shabtis, were produced in different materials and were usually inscribed in hieroglyphs with formulas including the name of the deceased. Shabtis are important archaeological objects which can help to identify the owners, their jobs, ranks or their families. They are also used for tomb dating because, depending on different elements: color, formula, tools, wig, hand positions, etc., it is possible to associate them to a concrete type or period of time. Shabtis are spread all over the world, in excavations, museums or private collections, and many of them have not been studied and identified because this process requires a deep study and reading of the hieroglyphs. Our system is able to solve this problem using two different YOLO v3 networks for detecting the figure itself and the hieroglyphic names, which provide identification and cataloguing. Until now, there has been no other work on the detection and identification of shabtis. In addition, a semantic approach has been followed, creating an ontology to connect our system with the semantic metadata aggregator, Europeana, linking our results with known shabtis in different museums. A complete dataset has been created, a comparison with previous technologies for similar problems has been provided, such as SIFT in the ancient coin classification, and the results of identification and cataloguing are shown. These results are over similar problems and have led us to create a web application that shows our system and is available on line.
A Comparative Study of MCDM Methods Integrated with Rapid Visual Seismic Vulnerability Assessment of Existing RC Structures
Authors: Harirchian Ehsan , Jadhav Kirti , Mohammad Kifaytullah , Aghakouchaki Hosseini Seyed Ehsan , Lahmer Tom
Published: September 2020

Recently, the demand for residence and usage of urban infrastructure has been increased, thereby resulting in the elevation of risk levels of human lives over natural calamities. The occupancy demand has rapidly increased the construction rate, whereas the inadequate design of structures prone to more vulnerability. Buildings constructed before the development of seismic codes have an additional susceptibility to earthquake vibrations. The structural collapse causes an economic loss as well as setbacks for human lives. An application of different theoretical methods to analyze the structural behavior is expensive and time-consuming. Therefore, introducing a rapid vulnerability assessment method to check structural performances is necessary for future developments. The process, as mentioned earlier, is known as Rapid Visual Screening (RVS). This technique has been generated to identify, inventory, and screen structures that are potentially hazardous. Sometimes, poor construction quality does not provide some of the required parameters; in this case, the RVS process turns into a tedious scenario. Hence, to tackle such a situation, multiple-criteria decision-making (MCDM) methods for the seismic vulnerability assessment opens a new gateway. The different parameters required by RVS can be taken in MCDM. MCDM evaluates multiple conflicting criteria in decision making in several fields. This paper has aimed to bridge the gap between RVS and MCDM. Furthermore, to define the correlation between these techniques, implementation of the methodologies from Indian, Turkish, and Federal Emergency Management Agency (FEMA) codes has been done. The effects of seismic vulnerability of structures have been observed and compared.
Disentangled Autoencoder for Cross-Stain Feature Extraction in Pathology Image Analysis
Authors: Hecht Helge , Sarhan Mhd Hasan , Popovici Vlad
Published: September 2020

A novel deep autoencoder architecture is proposed for the analysis of histopathology images. Its purpose is to produce a disentangled latent representation in which the structure and colour information are confined to different subspaces so that stain-independent models may be learned. For this, we introduce two constraints on the representation which are implemented as a classifier and an adversarial discriminator. We show how they can be used for learning a latent representation across haematoxylin-eosin and a number of immune stains. Finally, we demonstrate the utility of the proposed representation in the context of matching image patches for registration applications and for learning a bag of visual words for whole slide image summarization.
DeNERT-KG: Named Entity and Relation Extraction Model Using DQN, Knowledge Graph, and BERT
Authors: Yang SungMin , Yoo SoYeop , Jeong OkRan
Published: September 2020

Along with studies on artificial intelligence technology, research is also being carried out actively in the field of natural language processing to understand and process people’s language, in other words, natural language. For computers to learn on their own, the skill of understanding natural language is very important. There are a wide variety of tasks involved in the field of natural language processing, but we would like to focus on the named entity registration and relation extraction task, which is considered to be the most important in understanding sentences. We propose DeNERT-KG, a model that can extract subject, object, and relationships, to grasp the meaning inherent in a sentence. Based on the BERT language model and Deep Q-Network, the named entity recognition (NER) model for extracting subject and object is established, and a knowledge graph is applied for relation extraction. Using the DeNERT-KG model, it is possible to extract the subject, type of subject, object, type of object, and relationship from a sentence, and verify this model through experiments.
An Assessment of Observed and Simulated Temperature Variability in Sierra de Guadarrama
Authors: Vegas-Cañas Cristina , González-Rouco J. Fidel , Navarro-Montesinos Jorge , García-Bustamante Elena , Lucio-Eceiza Etor E. , García-Pereira Félix , Rodríguez-Camino Ernesto , Chazarra-Bernabé Andrés , Álvarez-Arévalo Inés
Published: September 2020

This work provides a first assessment of temperature variability at interannual and decadal timescales in Sierra de Guadarrama, a high mountain protected area of the Central System in the Iberian Peninsula. Observational data from stations located in the area and simulated data from a high-resolution simulation (1 km) with the Weather Research and Forecasting (WRF) model, fed from ERA Interim reanalysis, are used in order to analyse the temperature variability in the period 2000–2018. Comparison among all datasets allows evaluation of the realism of the model simulations. The results show that the model tends to underestimate the observational mean temperatures and anomalies at high-altitude stations. A linear mean temperature vertical gradient of −5.81 °C/km is observed, but it is overestimated by the model (−6.56 °C/km). The variability of the daily temperature anomalies for both observations and, to a lesser extent, simulations increases with height. The added value that the WRF offers against the use of the ERA Interim is evaluated. The results show that the WRF provides a better performance than the reanalysis, as it shows smaller biases with respect to observational temperature anomalies. Finally, the study of temperature trends over the Sierra de Guadarrama and its surroundings for the period 2000–2018 shows a warming in the area, significantly pronounced in autumn. When extended to the last decades, observations show that this warming has been happening since the first half of the 20th century, especially during the period 1970–2018, but not as much as during 2000–2018.
Linking Hydraulic Modeling with a Machine Learning Approach for Extreme Flood Prediction and Response
Authors: Kim Hyun Il , Han Kun Yeun
Published: September 2020

An emergency action plan (EAP) for reservoirs and urban areas downstream of dams can alleviate damage caused by extreme flooding. An EAP is a disaster action plan that can designate evacuation paths for vulnerable districts. Generally, calculation of dam-break discharge in accordance with dam inflow conditions, calculation of maximum water surface elevation as per hydraulic channel routing, and flood map generation using topographical data are prepared for the purposes of creating an EAP. However, rainfall and flood patterns exhibited in the context of climate change can be extremely diverse. In order to prepare an efficient flood response, techniques should be considered that are capable of generating flood maps promptly while taking dam inflow conditions into account. Therefore, this study aims to propose methodology that is capable of generating flood maps rapidly for any dam inflow conditions. The proposed methodology was performed by linking a dynamic numerical analysis model (DAMBRK) with a random forest regression technique. The previous standard method of drawing flood maps often requires a significant amount of time depending on accuracy and personnel availability; however, the technique proposed here is capable of generating a flood map within one minute. Through use of this methodology, the time taken to prepare flood maps in large-scale water-disaster situations can be reduced. Moreover, methodology for estimating flood risk via use of flood mapping has been proposed. This study would provide assistance in establishing disaster countermeasures that take various flood scenarios into account by promptly providing flood inundation information to disaster-related agencies.
Exploring Beliefs about Aging and Faith: Development of the Judeo-Christian Religious Beliefs and Aging Scale
Authors: Ewen Heidi H. , Nikzad-Terhune Katherina , Dassel Kara B.
Published: September 2020

This paper reports on the development of a novel 10-item scale that measures beliefs about aging as well as religious-based beliefs about aging. The Religious Beliefs and Aging Scale (RBAS) shows acceptable internal consistency (α = 0.74) and is bolstered by a strong correlation (r = 0.70) with the Brief Multidimensional Measure of Religiousness/Spirituality. Exploratory factor analysis elucidated two belief subscales: Afterlife (i.e., how age is experienced in the afterlife; α = 0.897) and Punishment (i.e., aging and dementia as a punishment for sin; α = 0.868). This scale can be used in research regarding end-of-life planning, ageism, and self-care practices.
Catalysis by Metals on Perovskite-Type Oxides
Authors: Ferri Davide
Published: September 2020

Perovskites are currently on everyone’s lips and have made it in high-impact scientific journals because of the revolutionary hybrid organic–inorganic lead halide perovskite materials for solar cells [...]
Treatment of Grade 3 and 4 Osteoarthritis with Intraoperatively Separated Adipose Tissue-Derived Stromal Vascular Fraction: A Comparative Case Series
Authors: Simunec Denis , Salari Honey , Meyer Juliane
Published: September 2020

Osteoarthritis (OA) is the most common form of arthritis of the joints. The stromal vascular fraction (SVF) is a regenerative cell population that can be isolated from adipose tissue. It is the immunomodulatory properties of the stromal vascular fraction that make it a promising candidate for the regenerative treatment of OA. Patients with grade 3 and 4 osteoarthritis were treated with the stromal vascular fraction with and without platelet-rich plasma (PRP) and followed up on their Knee Injury and Osteoarthritis Outcome Score (KOOS) score for 12 months, with MRI and subjective evaluation of the procedure. Magnetic resonance imaging (MRI) revealed a widening of the joint space, a restructuring of the cartilage, and an alleviation of effusions in the treated joints. In three of the four treatment groups, a substantial improvement of the KOOS scores was documented at the 12-month follow-up time point. According to the subjective evaluation, 67% of the patients were satisfied or very satisfied with the procedure and would recommend it to others. No serious adverse events or unwanted side effects related to the SVF treatment were observed or reported. Prior to an invasive artificial joint replacement, the treatment of arthritic knee joints with the intraarticular injection of autologous adipose tissue-derived SVF should be considered a regenerative treatment option.
Identification and Comparison of Hyperglycemia-Induced Extracellular Vesicle Transcriptome in Different Mouse Stem Cells
Authors: Huang Grace , Garikipati Venkata Naga Srikanth , Zhou Yan , Benedict Cynthia , Houser Steven R. , Koch Walter J. , Kishore Raj
Published: September 2020

Extracellular vesicles (EVs) derived from stem /progenitor cells harbor immense potential to promote cardiomyocyte survival and neovascularization, and to mitigate ischemic injury. However, EVs’ parental stem/progenitor cells showed modest benefits in clinical trials, suggesting autologous stem cell/EV quality might have been altered by stimuli associated with the co-morbidities such as hyperglycemia associated with diabetes. Hyperglycemia is a characteristic of diabetes and a major driving factor in cardiovascular disease. The functional role of stem/progenitor cell-derived EVs and the molecular signature of their secreted EV cargo under hyperglycemic conditions remain elusive. Therefore, we hypothesized that hyperglycemic stress causes transcriptome changes in stem/progenitor cell-derived EVs that may compromise their reparative function. In this study, we performed an unbiased analysis of EV transcriptome signatures from 3 different stem/progenitor cell types by RNA sequencing. The analysis revealed differential expression of a variety of RNA species in EVs. Specifically, we identified 241 common-dysregulated mRNAs, 21 ncRNAs, and 16 miRNAs in three stem cell-derived EVs. Gene Ontology revealed that potential function of common mRNAs mostly involved in metabolism and transcriptional regulation. This study provides potential candidates for preventing the adverse effects of hyperglycemia-induced stem/progenitor cell-derived EV dysfunction, and reference data for future biological studies and application of stem/progenitor cell-derived EVs.
HNSCC: Tumour Antigens and Their Targeting by Immunotherapy
Authors: von Witzleben Adrian , Wang Chuan , Laban Simon , Savelyeva Natalia , Ottensmeier Christian H.
Published: September 2020

Head and neck squamous cell carcinomas (HNSCC) are a heterogeneous group of malignant tumours typically caused by alcohol and tobacco consumption, although an increasing number of HNSCC arise due to persistent infection with high-risk human papilloma virus (HPV). The treatment of HNSCC remains challenging, and the first-line setting is focused on surgery and chemoradiotherapy. A substantial proportion of HNSCC patients die from their disease, especially those with recurrent and metastatic disease. Among factors linked with good outcome, immune cell infiltration appears to have a major role. HPV-driven HNSCC are often T-cell rich, reflecting the presence of HPV antigens that are immunogenic. Tumour-associated antigens that are shared between patients or that are unique to an individual person may also induce varying degrees of immune response; studying these is important for the understanding of the interaction between the host immune system and the cancer. The resulting knowledge is critical for the design of better immunotherapies. Key questions are: Which antigens lead to an adaptive immune response in the tumour? Which of these are exploitable for immunotherapy? Here, we review the current thinking regarding tumour antigens in HNSCC and what has been learned from early phase clinical trials.
Convective Transport of Fluid–Solid Interaction: A Study between Non-Newtonian Casson Model with Dust Particles
Authors: Mohd Kasim Abdul Rahman , Arifin Nur Syamilah , Mohd Zokri Syazwani , Salleh Mohd Zuki , Mohammad Nurul Farahain , Chuan Ching Dennis Ling , Shafie Sharidan , Ariffin Noor Amalina Nisa
Published: September 2020

The Casson model is a fascinating model, which is genuinely recommended for use with fluids of a non-Newtonian type. The conventional model is not capable to represent the Casson model with the suspension of foreign bodies (dust particles). Due to this, the two-phase model for the mixture of Casson model fluid and dust particles is formulated. This study examines the emerging role of dust particles in changing the behavior of Casson model. In particular, two-phase flow of dusty Casson model with modified magnetic field and buoyancy effect under Newtonian heating boundary condition along a vertically stretching sheet is considered. The equations that govern under Casson model, together with dust particles, are reduced to a system of nonlinear ordinary differential equations by employing the suitable similarity variables. These transformed equations are then solved numerically by implementing the Runge–Kutta–Fehlberg (RKF45) method. The numerical results of skin friction coefficient plus Nusselt number are displayed graphically. The results revealed the fluid’s velocity tends to deteriorate due to the existence of dust particles, whilst its temperature is increased. The two-phase flow is one of the mathematical modeling techniques for multiphase flow, where the relationship between the fluid and solid is examined more closely. It is expected that the present findings can contribute to the understanding of the theory of two-phase flow mathematically, which will continue to produce significant research in this field.
Effects of Highly Crystalized Nano C-S-H Particles on Performances of Portland Cement Paste and Its Mechanism
Authors: Wang Yuli , Lu Huijuan , Wang Junjie , He Hang
Published: September 2020

In order to improve the early age strength of ordinary Portland cement-based materials, many early strength agents were applied in different conditions. Different from previous research, the nano calcium silicate hydrate (C-S-H) particles used in this study were synthesized through the chemical reaction of CaO, SiO2, and H2O under 120 °C using the hydrothermal method, and the prepared nano C-S-H particles were highly crystalized. The influences of different amounts of nano C-S-H particles (0%, 0.5%, 1%, 2% and 3% by weight of cement) on the setting time, compressive strength, and hydration heat of cement paste were studied. The hydration products and microstructure of the cement paste with different additions of nano C-S-H particles were investigated through thermogravimetry-differential thermal analysis (TG-DTA), X-ray powder diffraction (XRD), and scanning electron microscope (SEM) tests. The results show that the nano C-S-H particles could be used as an early strength agent, and the early strength of cement paste can be increased by up to 43% through accelerating the hydration of tricalcium silicate (C3S). However, the addition of more than 2% nano C-S-H particles was unfavorable to the later strength development due to more space being left during the initial accelerated hydration process. It is suggested that the suitable content of the nano C-S-H particles is 0.5%−1% by weight of cement.
Using Minidrones to Teach Geospatial Technology Fundamentals
Authors: Joyce Karen E. , Meiklejohn Natalie , Mead Paul C.H.
Published: September 2020

With an increased level of interest in promoting science, technology, engineering, and maths (STEM) careers, there are many ways in which drone and geospatial technology can be brought into the education system to train the future workforce. Indeed, state-level government policies are even stipulating that they should be integrated into curriculum. However, in some cases, drones may be seen as the latest toy advertised to achieve an education outcome. Some educators find it difficult to incorporate the technology in a meaningful way into their classrooms. Further, educators can often struggle to maintain currency on rapidly developing technology, particularly when it is outside of their primary area of expertise as is frequently the case in schools. Here, we present a structured approach to using drones to teach fundamental geospatial technology concepts within a STEM framework across primary/elementary, middle, secondary, and tertiary education. After successfully working with more than 6000 participants around the world, we encourage other scientists and those in industry using drones as part of their research or operations to similarly reach out to their local community to help build a diverse and strong STEM workforce of the future.
IoVT: Internet of Vulnerable Things? Threat Architecture, Attack Surfaces, and Vulnerabilities in Internet of Things and Its Applications towards Smart Grids
Authors: Anand Pooja , Singh Yashwant , Selwal Arvind , Singh Pradeep Kumar , Felseghi Raluca Andreea , Raboaca Maria Simona
Published: September 2020

In recent years, people have witnessed numerous Internet of Things (IoT)-based attacks with the exponential increase in the number of IoT devices. Alongside this, the means to secure IoT-based applications are maturing slower than our budding dependence on them. Moreover, the vulnerabilities in an IoT system are exploited in chains to penetrate deep into the network and yield more adverse aftereffects. To mitigate these issues, this paper gives unique insights for handling the growing vulnerabilities in common IoT devices and proposes a threat architecture for IoT, addressing threats in the context of a three-layer IoT reference architecture. Furthermore, the vulnerabilities exploited at the several IoT attack surfaces and the challenges they exert are explored. Thereafter, the challenges in quantifying the IoT vulnerabilities with the existing framework are also analyzed. The study also covers a case study on the Intelligent Transportation System, covering road transport and traffic control specifically in terms of threats and vulnerabilities. Another case study on secure energy management in the Smart Grid is also presented. This case study covers the applications of Internet of Vulnerable Things (IoVT) in Smart energy Grid solutions, as there will be tremendous use of IoT in future Smart Grids to save energy and improve overall distribution. The analysis shows that the integration of the proposed architecture in existing applications alarms the developers about the embedded threats in the system.
Shared Solar and Battery Storage Configuration Effectiveness for Reducing the Grid Reliance of Apartment Complexes
Authors: Syed Moiz Masood , Morrison Gregory M. , Darbyshire James
Published: September 2020

More than 2 million houses in Australia have installed solar photovoltaic (PV) systems; however, apartment buildings have adopted a low percentage of solar PV and battery storage installations. Given that grid usage reduction through PV and battery storage is a primary objective in most residential buildings, apartments have not yet fully benefited from installations of such systems. This research presents shared microgrid configurations for three apartment buildings with PV and battery storage and evaluates the reduction in grid electricity usage by analyzing self-sufficiency. The results reveal that the three studied sites at White Gum Valley achieved an overall self-sufficiency of more than 60%. Owing to the infancy of the shared solar and battery storage market for apartment complexes and lack of available data, this study fills the research gap by presenting preliminary quantitative findings from implementation in apartment buildings.
Review of Steady-State Electric Power Distribution System Datasets
Authors: Meinecke Steffen , Thurner Leon , Braun Martin
Published: September 2020

Publicly available grid datasets with electric steady-state equivalent circuit models are crucial for the development and comparison of a variety of power system simulation tools and algorithms. Such algorithms are essential to analyze and improve the integration of distributed energy resources (DERs) in electrical power systems. Increased penetration of DERs, new technologies, and changing regulatory frameworks require the continuous development of the grid infrastructure. As a result, the number and versatility of grid datasets, which are required in power system research, increases. Furthermore, the used grids are created by different methods and intentions. This paper gives orientation within these developments: First, a concise overview of well-known, publicly available grid datasets is provided. Second, background information on the compilation of the grid datasets, including different methods, intentions and data origins, is reviewed and characterized. Third, common terms to describe electric steady-state distribution grids, such as representative grid or benchmark grid, are assembled and reviewed. Recommendations for the use of these grid terms are made.
Annotation of Human Exome Gene Variants with Consensus Pathogenicity
Authors: Jaravine Victor , Balmford James , Metzger Patrick , Boerries Melanie , Binder Harald , Boeker Martin
Published: September 2020

A novel approach is developed to address the challenge of annotating with phenotypic effects those exome variants for which relevant empirical data are lacking or minimal. The predictive annotation method is implemented as a stacked ensemble of supervised base-learners, including distributed random forest and gradient boosting machines. Ensemble models were trained and cross-validated on evidence-based categorical variant effect annotations from the ClinVar database, and were applied to 84 million non-synonymous single nucleotide variants (SNVs). The consensus model combined 39 functional mutation impacts, cross-species conservation score, and gene indispensability score. The indispensability score, accounting for differences in variant pathogenicities including in essential and mutation-tolerant genes, considerably improved the predictions. The consensus combination is consistent with as many input scores as possible while minimizing false predictions. The input scores are ranked based on their ability to predict effects. The score rankings and categorical phenotypic variant effect predictions are aimed for direct use in clinical and biological applications to prioritize human exome variants and mutations.
Social Media Goes Green—The Impact of Social Media on Green Cosmetics Purchase Motivation and Intention
Authors: Pop Rebeka-Anna , Săplăcan Zsuzsa , Alt Mónika-Anetta
Published: September 2020

In the 21st century, green consumption has risen into a global trend, which inclines cosmetic companies to be more environmental-friendly and to have a larger green product portfolio to satisfy these new consumers’ needs. Social media contributed to this trend, shaping consumers’ attitudes into more environmentally conscious behavior. The present study applied the Theory of Planned Behavior (TPB) to explain the impact of Social Media on consumers’ purchase intention and motivation (altruism and egoism). Based on empirical investigation, an online survey was developed to measure the proposed conceptual model. The reliability and validity of the reflective constructs were tested using partial least squares (PLS) modeling technique. The results indicate the importance of social media on consumers’ attitudes, subjective norms, altruistic and egoistic motivations, and the impact of these variables as the antecedents of green cosmetics purchase intention. These results have important theoretical implications. They revealed that external factors such as social media as an information source, have an important role in consumer motivation formation and green cosmetic purchasing intentions. The findings are relevant for marketers to implement better communication strategies on social media to increase consumers’ motivations and purchase intention toward green cosmetics.
Evaluation of Insertion Energy as Novel Parameter for Dental Implant Stability
Authors: Grobecker-Karl Tanja , Dickinson Anthony , Heckmann Siegfried , Karl Matthias , Steiner Constanze
Published: September 2020

Insertion energy has been advocated as a novel measure for primary implant stability, but the effect of implant length, diameter, or surgical protocol remains unclear. Twenty implants from one specific bone level implant system were placed in layered polyurethane foam measuring maximum insertion torque, torque–time curves, and primary stability using resonance frequency analysis (RFA). Insertion energy was calculated as area under torque–time curve applying the trapezoidal formula. Statistical analysis was based on analysis of variance, Tukey honest differences tests and Pearson’s product moment correlation tests (α = 0.05). Implant stability (p = 0.01) and insertion energy (p < 0.01) differed significantly among groups, while maximum insertion torque did not (p = 0.17). Short implants showed a significant decrease in implant stability (p = 0.01), while reducing implant diameter did not cause any significant effect. Applying the drilling protocol for dense bone resulted in significantly increased insertion energy (p = 0.02) but a significant decrease in implant stability (p = 0.04). Insertion energy was not found to be a more reliable parameter for evaluating primary implant stability when compared to maximum insertion torque and resonance frequency analysis.
Increased Antioxidant Capacity and Pro-Homeostatic Lipid Mediators in Ocular Hypertension—A Human Experimental Model
Authors: Langbøl Mia , Saruhanian Sarkis , Baskaran Thisayini , Tiedemann Daniel , Mouhammad Zaynab , Toft-Kehler Anne , Jun Bokkyoo , Vohra Rupali , Bazan Nicolas , Kolko Miriam
Published: September 2020

The main risk factor for primary open-angle glaucoma (POAG) is increased intraocular pressure (IOP). It is of interest that about half of the patients have an IOP within the normal range (normal-tension glaucoma, NTG). Additionally, there is a group of patients with a high IOP but no glaucomatous neurodegeneration (ocular hypertension, OHT). Therefore, risk factors other than IOP are involved in the pathogenesis of glaucoma. Since the retina has a very high oxygen-demand, decreased autoregulation and a fluctuating oxygen supply to the retina have been linked to glaucomatous neurodegeneration. To assess the significance of these mechanisms, we have utilized a human experimental model, in which we stress participants with a fluctuating oxygen supply. Levels of oxidative stress molecules, antioxidants, and lipid mediators were measured in the plasma. Patients with NTG, OHT, and control subjects were found to have similar levels of oxidative stress markers. In contrast, patients with OHT had a higher level of total antioxidant capacity (TAC) and pro-homeostatic lipid mediators. Thus, we suggest that OHT patients manage fluctuating oxygen levels more efficiently and, thus, are less susceptible to glaucomatous neurodegenerations, due to enhanced systemic antioxidant protection.
Comparative Analysis of the Impact of Additively Manufactured Polymer Tools on the Fiber Configuration of Injection Molded Long-Fiber-Reinforced Thermoplastics
Authors: Knorr Lukas , Setter Robert , Rietzel Dominik , Wudy Katrin , Osswald Tim
Published: September 2020

Additive tooling (AT) utilizes the advantages of rapid tooling development while minimizing geometrical limitations of conventional tool manufacturing such as complex design of cooling channels. This investigation presents a comparative experimental analysis of long-fiber-reinforced thermoplastic parts (LFTs), which are produced through additively manufactured injection molding polymer tools. After giving a review on the state of the art of AT and LFTs, additive manufacturing (AM) plastic tools are compared to conventionally manufactured steel and aluminum tools toward their qualification for spare part and small series production as well as functional validation. The assessment of the polymer tools focuses on three quality criteria concerning the LFT parts: geometrical accuracy, mechanical properties, and fiber configuration. The analysis of the fiber configuration includes fiber length, fiber concentration, and fiber orientation. The results show that polymer tools are fully capable of manufacturing LFTs with a cycle number within hundreds before showing critical signs of deterioration or tool failure. The produced LFTs moldings provide sufficient quality in geometrical accuracy, mechanical properties, and fiber configuration. Further, specific anomalies of the fiber configuration can be detected for all tool types, which include the occurrence of characteristic zones dependent on the nominal fiber content and melt flow distance. Conclusions toward the improvement of additively manufactured polymer tool life cycles are drawn based on the detected deteriorations and failure modes.
XGBoost Improves Classification of MGMT Promoter Methylation Status in IDH1 Wildtype Glioblastoma
Authors: Le Nguyen Quoc Khanh , Do Duyen Thi , Chiu Fang-Ying , Yapp Edward Kien Yee , Yeh Hui-Yuan , Chen Cheng-Yu
Published: September 2020

Approximately 96% of patients with glioblastomas (GBM) have IDH1 wildtype GBMs, characterized by extremely poor prognosis, partly due to resistance to standard temozolomide treatment. O6-Methylguanine-DNA methyltransferase (MGMT) promoter methylation status is a crucial prognostic biomarker for alkylating chemotherapy resistance in patients with GBM. However, MGMT methylation status identification methods, where the tumor tissue is often undersampled, are time consuming and expensive. Currently, presurgical noninvasive imaging methods are used to identify biomarkers to predict MGMT methylation status. We evaluated a novel radiomics-based eXtreme Gradient Boosting (XGBoost) model to identify MGMT promoter methylation status in patients with IDH1 wildtype GBM. This retrospective study enrolled 53 patients with pathologically proven GBM and tested MGMT methylation and IDH1 status. Radiomics features were extracted from multimodality MRI and tested by F-score analysis to identify important features to improve our model. We identified nine radiomics features that reached an area under the curve of 0.896, which outperformed other classifiers reported previously. These features could be important biomarkers for identifying MGMT methylation status in IDH1 wildtype GBM. The combination of radiomics feature extraction and F-core feature selection significantly improved the performance of the XGBoost model, which may have implications for patient stratification and therapeutic strategy in GBM.
Learning Mathematics with Emerging Methodologies—The Escape Room as a Case Study
Authors: Fuentes-Cabrera Arturo , Parra-González María Elena , López-Belmonte Jesús , Segura-Robles Adrián
Published: September 2020

Nowadays, different methodologies are booming in the field of education, and active gamification-based methodologies such as the Escape Room are an example of these methodologies, which is the base of this research. The purpose of this research is to analyze the effectiveness of the use of an Escape Room as an active methodology to learn mathematics. A quantitative research method was performed through an experimental design. Two study groups were set up. With the control group, a traditional training methodology was used, and with the experimental group, an innovative one was used through an Escape room experience. A total of 62 students of the 3rd level of Secondary Education from an educational center in Ceuta (Spain) participated. Results show how the experience developed through the escape room improved achievement, motivation and autonomy in a significant way. It has also reduced learning anxiety significantly. It is concluded that the use of the Escape room in Mathematics improves learning achievement, anxiety, motivation and autonomy, with gender being a variable to be taken into account, especially in motivation and autonomy. Therefore, the escape room has a greater potential than a traditional methodology in Mathematics.
Scale Formation on HSLA Steel during Continuous Casting Part I: The Effect of Temperature–Time on Oxidation Kinetics
Authors: Pineda Huitron Rosa Maria , Ramírez López Pavel Ernesto , Vuorinen Esa , Nazen Jalali Pooria , Pelcastre Leonardo , Kärkkäinen Maija
Published: September 2020

The findings in this work enhance the understanding of oxidation mechanisms and scale growth at high temperatures of a high strength low alloy (HSLA) steel for improving surface quality during continuous casting. The oxidation phenomenon was investigated under dry air and water vapor atmospheres by heating specimens at 1000, 1100, and 1200 °C at different holding times. Temperature and time had great effects on the kinetics, where faster (i.e., parabolic) oxidation rates were present under water vapor when compared with the dry air condition. Temperature strongly influenced the number of defects, such as pores, voids, gaps and micro-cracks, formed in the oxide scale. A phase analysis confirmed the presence of FeO as the first phase formed at the steel surface, Fe3O4 as the middle and thicker phase, and Fe2O3 as the last phase formed in the oxide/air interface. The micromechanics of the oxides demonstrated that a combination of phases with high (wüstite) and low plasticity (magnetite and hematite) could also have been the reason for the uneven cooling during Continuous Casting (CC) that resulted in the undesired surface quality of the steel slabs. This work gives a good look at the oxide scale effect on the surface quality of steel slabs through an understanding the kinetics during oxidation.
Suitability of a Cellulose-Based Nanomaterial for the Remediation of Heavy Metal Contaminated Freshwaters: A Case-Study Showing the Recovery of Cadmium Induced DNA Integrity Loss, Cell Proliferation Increase, Nuclear Morphology and Chromosomal Alterations on Dreissena polymorpha
Authors: Guidi Patrizia , Bernardeschi Margherita , Palumbo Mara , Genovese Massimo , Scarcelli Vittoria , Fiorati Andrea , Riva Laura , Punta Carlo , Corsi Ilaria , Frenzilli Giada
Published: September 2020

The contamination of freshwaters by heavy metals represents a great problem, posing a threat for human and environmental health. Cadmium is classified as carcinogen to humans and its mechanism of carcinogenicity includes genotoxic events. In this study a recently developed eco-friendly cellulose-based nanosponge (CNS) was investigated as a candidate in freshwater nano-remediation process. For this purpose, CdCl2 (0.05 mg L−1) contaminated artificial freshwater (AFW) was treated with CNS (1.25 g L−1 for 2 h), and cellular responses were analyzed before and after CNS treatment in Dreissena polymorpha hemocytes. A control group (AFW) and a negative control group (CNS in AFW) were also tested. DNA primary damage was evaluated by Comet assay while chromosomal damage and cell proliferation were assessed by Cytome assay. AFW exposed to CNS did not cause any genotoxic effect in zebra mussel hemocytes. Moreover, DNA damage and cell proliferation induced by Cd(II) turned down to control level after 2 days when CNS were used. A reduction of Cd(II)-induced micronuclei and nuclear abnormalities was also observed. CNS was thus found to be a safe and effective candidate in cadmium remediation process being efficient in metal sequestering, restoring cellular damage exerted by Cd(II) exposure, without altering cellular physiological activity.
Protonation-Induced Enhanced Optical-Light Photochromic Properties of an Inorganic-Organic Phosphomolybdic Acid/Polyaniline Hybrid Thin Film
Authors: Zeng Qingrui , Guo Suyue , Sun Yuanbo , Li Zhuojuan , Feng Wei
Published: September 2020

A phosphomolybdic acid/polyaniline (PMoA/PANI) optical-light photochromic inorganic/organic hybrid thin film was successfully synthesized by protonation between the the multiprotonic acid phosphomolybdic acid (H3PO4·12MoO3) and the conductive polymer polyaniline. The stable Keggin-type structure of PMoA was maintained throughout the process. Protonation and proton transfer successfully transformed the quinone structure of eigenstate PANI into the benzene structure of single-polarized PANI in the PMoA/PANI hybridized thin film, and proton transfer transformed the benzene structure of single-polarized PANI back to the quinone structure of eigenstate PANI in the PMoA/PANI hybrid thin film, as verified by Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS). The average distribution of PMoA/PANI was observed by atom force microscopy (AFM). Interestingly, protonation of PMoA caused PANI to trigger transformation of the quinone structure into the single-polarized benzene structure, which enhanced the electron delocalization ability and vastly enhanced the maximum light absorption of the PMoA/PANI hybrid thin film as confirmed by density functional theory (DFT), electrochemistry, and ultraviolet-visible spectroscopy (UV-Vis) studies. Under optical-light illumination, the pale-yellow PMoA/PANI hybrid thin film gradually turned deep blue, thus demonstrating a photochromic response, and reversible photochromism was also observed in the presence of hydrogen peroxide (H2O2) or oxygen (O2). After 40 min of optical-light illumination, 36% of the Mo5+ species in PMoA was photoreduced via a protonation-induced proton transfer mechanism, and this proton transfer resulted in a structural change of PANI, as observed by XPS, generating a dominant structure with high maximum light absorption of 3.46, when compared with the literature reports.