bluuebunny/crossref_metadata_2025 huggingface dataset:
Differences in Virulence among PVY Isolates of Different Geographical Origins When Infecting an Experimental Host under Two Growing Environments Are Not Determined by HCPro
Authors: Makki Mongia , del Toro Francisco Javier , Necira Khouloud , Tenllado Francisco , Djilani-Khouadja Fattouma , Canto Tomás
Published: May 2021

The contribution of the HCPro factors expressed by several PVY isolates of different geographical origins (one from Scotland, one from Spain, and several from Tunisia) to differences in their virulence in Nicotiana benthamiana plants was investigated under two growing conditions: standard (st; 26 °C and current ambient levels of CO2), and climate change-associated (cc; 31 °C and elevated levels of CO2). In all cases, relative infection symptoms and viral titers were determined. The viral HCPro cistrons were also sequenced and amino-acid features of the encoded proteins were established, as well as phylogenetic distances. Additionally, the abilities of the HCPros of several isolates to suppress silencing were assessed under either growing condition. Overall, viral titers and infection symptoms decreased under cc vs. st conditions. However, within each growing condition, relative titers and symptoms were found to be isolate-specific, with titers and symptom severities not always correlating. Crucially, isolates expressing identical HCPros displayed different symptoms. In addition, all HCPro variants tested displayed comparable silencing suppression strengths. Therefore, HCPro alone could not be the main determinant of the relative differences in pathogenicity observed among the PVY isolates tested in this host, under the environments considered.
An Update on Crop ABA Receptors
Authors: Ruiz-Partida Rafael , Rosario Sttefany M. , Lozano-Juste Jorge
Published: May 2021

The hormone abscisic acid (ABA) orchestrates the plant stress response and regulates sophisticated metabolic and physiological mechanisms essential for survival in a changing environment. Plant ABA receptors were described more than 10 years ago, and a considerable amount of information is available for the model plant Arabidopsis thaliana. Unfortunately, this knowledge is still very limited in crops that hold the key to feeding a growing population. In this review, we summarize genomic, genetic and structural data obtained in crop ABA receptors. We also provide an update on ABA perception in major food crops, highlighting specific and common features of crop ABA receptors.
Effects of Weed Control Practices on Plant Diversity in a Homogenous Olive-Dominated Landscape (South-East of Italy)
Authors: Terzi Massimo , Barca Emanuele , Cazzato Eugenio , D’Amico Francesco Saverio , Lasorella Cesare , Fracchiolla Mariano
Published: May 2021

Olive groves represent an important economic, agro-ecological, and cultural resource in the Mediterranean Basin. Weed management plays a fundamental role in their sustainable management. The aim of this work was to characterize and assess the plant diversity associated with different weed control practices, in a homogeneous olive-dominated landscape in the South-East of Italy. Sixty-five vegetation plots were sampled in orchards treated with different weed control practices: mowing, tillage, and use of chemical herbicides. The multi-response permutation procedure was used to test the hypothesis of no difference among the treatments. The relationships between plots were visualized by means of non-metric multidimensional scaling ordination. A generalized linear mixed model was used to analyze the relationships between weed control practices and life forms, chorotypes, and diversity indexes. The results showed that the three weed control practices determined slightly different plant communities. Chemically weeded orchards showed an impoverished floristic composition and the lowest diversity, whereas mowing and tillage yielded similar values. These latter two treatments differed for the percentages of hemicryptophytes and therophytes. Moreover, different from other studies, we did not find plant species of particular concern for biodiversity conservation. We hypothesize that this result is due to the monotonous structure of the agro-landscape we investigated, where natural elements are almost lacking. From this point of view, a correct management of agro-districts should consider both the agronomic practices at the level of the individual olive groves and the structure of the agro-landscape.
Elevated Temperature Induced Adaptive Responses of Two Lupine Species at Early Seedling Phase
Authors: Jurkonienė Sigita , Jankauskienė Jurga , Mockevičiūtė Rima , Gavelienė Virgilija , Jankovska-Bortkevič Elžbieta , Sergiev Iskren , Todorova Dessislava , Anisimovienė Nijolė
Published: May 2021

This study aimed to investigate the impact of climate warming on hormonal traits of invasive and non-invasive plants at the early developmental stage. Two different lupine species—invasive Lupinus polyphyllus Lindl. and non-invasive Lupinus luteus L.—were used in this study. Plants were grown in climate chambers under optimal (25 °C) and simulated climate warming conditions (30 °C). The content of phytohormone indole-3-acetic acid (IAA), ethylene production and the adaptive growth of both species were studied in four-day-old seedlings. A higher content of total IAA, especially of IAA-amides and transportable IAA, as well as higher ethylene emission, was determined to be characteristic for invasive lupine both under optimal and simulated warming conditions. It should be noted that IAA-L-alanine was detected entirely in the invasive plants under both growth temperatures. Further, the ethylene emission values increased significantly in invasive lupine hypocotyls under 30 °C. Invasive plants showed plasticity in their response by reducing growth in a timely manner and adapting to the rise in temperature. Based on the data of the current study, it can be suggested that the invasiveness of both species may be altered under climate warming conditions.
Mine Vegetation Identification via Ecological Monitoring and Deep Belief Network
Authors: Gong Bin , Shu Cheng , Han Song , Cheng Sheng-Gao
Published: May 2021

Based on the characteristics of remote sensing images of mine vegetation, this research studied the application of deep belief network model in mine vegetation identification. Through vegetation identification and classification, the ecological environment index of mining area was determined according to the analysis of vegetation and coverage. Deep learning algorithm is adopted to improve the depth study, the vegetation coverage in the analysis was studied. Parameters and parameter values were selected for identification by establishing the optimal experimental design. The experimental results were compared with remote sensing images to determine the accuracy of deep learning identification and the effectiveness of the algorithm. When the sample size is 2,000,000 pixels, through repeated tests and classification effect comparison, the optimal parameter setting suitable for mine vegetation identification is obtained. Parameter setting: the number of network layers is 3 layers; the number of hidden layer neurons is 60. The learning rate is 0.01 and the number of iterations is 2. The average recognition rate of vegetation coverage was 95.95%, outperforming some other models, and the accuracy rate of kappa coefficient was 0.95, which can accurately reflect the vegetation coverage. The clearer the satellite image is, the more accurate the recognition result is, and the accuracy is closer to 100%. The identification of vegetation coverage has important guiding significance for determining the area and area of ecological restoration.
OseIF3h Regulates Plant Growth and Pollen Development at Translational Level Presumably through Interaction with OsMTA2
Authors: Huang Yuqing , Zheng Peng , Liu Xuejiao , Chen Hao , Tu Jumin
Published: May 2021

The initiation stage of protein biosynthesis is a sophisticated process tightly regulated by numerous initiation factors and their associated components. However, the mechanism underlying translation initiation has not been completely understood in rice. Here, we showed knock-out mutation of the rice eukaryotic translation initiation factor 3 subunit h (OseIF3h) resulted in plant growth retardation and seed-setting rate reduction as compared to the wild type. Further investigation demonstrated an interaction between OseIF3h and OsMTA2 (mRNA adenosine methylase 2), a rice homolog of METTL3 (methyltransferase-like 3) in mammals, which provided new insight into how N6-methyladenosine (m6A) modification of messenger RNA (mRNA) is engaged in the translation initiation process in monocot species. Moreover, the RIP-seq (RNA immunoprecipitation sequencing) data suggested that OseIF3h was involved in multiple biological processes, including photosynthesis, cellular metabolic process, precursor metabolites, and energy generation. Therefore, we infer that OseIF3h interacts with OsMTA2 to target a particular subset of genes at translational level, regulating plant growth and pollen development.
A Dual Role of Vanadium in Environmental Systems—Beneficial and Detrimental Effects on Terrestrial Plants and Humans
Authors: Hanus-Fajerska Ewa , Wiszniewska Alina , Kamińska Iwona
Published: May 2021

The importance of vanadium (V) in the functioning of land systems is extremely diverse, as this element may exert both positive and harmful effects on terrestrial organisms. It recently become considered an element of beneficial character with a range of applications for human welfare. The health-ameliorative properties of this transition element depend on its degree of oxidation and on optimal concentration in the target cells. It was found that a similar relationship applies to vascular plants. However, excessive amounts of vanadium in the environment contaminate the soil and negatively affect the majority of living organisms. A significantly elevated level of V results in the destabilization of plant physiological balance, slowing down the growth of biomass which significantly reduces yield. In turn, low doses of the appropriate vanadium ions can stimulate plant growth and development, exert cytoprotective effects, and effectively enhance the synthesis of some biologically active compounds. We present the scientific achievements of research teams dealing with such topics. The issues discussed concern the role of vanadium in the environment, particular organisms, and highlight its dualistic influence on plants. Achievements in the field of V bioremediation, with the use of appropriately selected microorganisms and plant species, are emphasized.
Experimental Investigation on the Effect of Graphene Oxide Additive on the Steady-State and Dynamic Shear Properties of PDMS-Based Magnetorheological Elastomer
Authors: Liu Minzi , Zhang Mei , Zhang Jiangtao , Qiao Yanliang , Zhai Pengcheng
Published: May 2021

Isotropic polydimethylsiloxane (PDMS)-based magnetorheological elastomers (MREs) filled with various contents of graphene oxide (GO) additive were fabricated by the solution blending-casting method in this work. The morphologies of the produced MREs were characterized, and the results indicate that the uniform distribution of GO sheets and carbonyl iron particles (CIPs) becomes difficult with the increase of GO content. The steady-state and dynamic shear properties of the MREs under different magnetic field strengths were evaluated using parallel plate rheometer. It was found that the physical stiffness effect of GO sheets leads to the increase of the zero-field shear modulus with increasing GO content under both the steady-state and dynamic shear loads. The chemical crosslinking density of PDMS matrix decreases with the GO content due to the strong physical crosslinking between GO and the PDMS matrix. Thus, the MREs filled with higher GO content exhibit more fluid-like behavior. Under the dynamic shear load, the absolute MR effect increases with the GO content due to the increased flexibility of the PDMS matrix and the dynamic self-stiffening effect occurring in the physical crosslinking interfaces around GO sheets. The highest relative MR effect was achieved by the MREs filled with 0.1 wt.% GO sheets. Then, the relative MR effect decreases with the further increase of GO content due to the improved zero-field modulus and the increased agglomerations of GO and CIPs. This study shows that the addition of GO sheets is a possible way to prepare new MREs with high MR effect, while simultaneously possessing high zero-field stiffness and load bearing capability.
Ultrafast Room Temperature Synthesis of Porous Polythiophene via Atmospheric Pressure Plasma Polymerization Technique and Its Application to NO2 Gas Sensors
Authors: Park Choon-Sang , Kim Do Yeob , Jung Eun Young , Jang Hyo Jun , Bae Gyu Tae , Kim Jae Young , Shin Bhum Jae , Lee Hyung-Kun , Tae Heung-Sik
Published: May 2021

New nanostructured conducting porous polythiophene (PTh) films are directly deposited on substrates at room temperature (RT) by novel atmospheric pressure plasma jets (APPJs) polymerization technique. The proposed plasma polymerization synthesis technique can grow the PTh films with a very fast deposition rate of about 7.0 μm·min−1 by improving the sufficient nucleation and fragment of the thiophene monomer. This study also compares pure and iodine (I2)-doped PTh films to demonstrate the effects of I2 doping. To check the feasibility as a sensing material, NO2-sensing properties of the I2-doped PTh films-based gas sensors are also investigated. As a result, the proposed APPJs device can produce the high density, porous and ultra-fast polymer films, and polymers-based gas sensors have high sensitivity to NO2 at RT. Our approach enabled a series of processes from synthesis of sensing materials to fabrication of gas sensors to be carried out simultaneously.
Recording, Storage, and Reproduction of Information on Polyvinyl Chloride Films Using Shape Memory Effects
Authors: Kondratov Alexander , Cherkasov Egor , Paley Vladislav , Volinsky Alex
Published: May 2021

Partial dissolution and plasticization are used for recording, storing, and reproducing information with modified industrial screen-printing equipment and aqueous solutions of colorless organic liquids on small surface area shape memory polymer films. To justify the choice of “ink” and evaluate the effectiveness of using organic liquids as high-speed polymer solvents, the new method for recording hidden information uses the calculation of the solubility parameter, differential scanning calorimetry, and the method of one-sided swelling of films under isometric conditions. Using the example of tactile marking of shrink labels made of polyvinyl chloride, the optimal conditions for recording hidden information on a film are established in terms of the concentration of an aqueous solution of tetrahydrofuran, the contact time, and the processing temperature of the polymer using screen printing equipment.
Control of Surface Properties of Hyaluronan/Chitosan Multilayered Coatings for Tumor Cell Capture
Authors: Lima Giulia G. , Rocha Neto João B. M. , Carvalho Hernandes Faustino de , Beppu Marisa Masumi
Published: May 2021

Prostate cancer (PCa) is a slow-growing neoplasm that has, when diagnosed in its early stages, great chances of cure. During initial tumor development, current diagnostic methods fail to have the desired accuracy, thus, it is necessary to develop or improve current detection methods and prognostic markers for PCa. In this scenario, films composed of hyaluronic acid (HA) and chitosan (CHI) have demonstrated significant capture potential of prostate tumor cells (PC3 line), exploring HA as a CD44 receptor ligand and direct mediator in cell-film adhesion. Here, we present a strategy to control structural and cell adhesion properties of HA/CHI films based on film assembly conditions. Films were built via Layer-by-layer (LbL) deposition, where the pH conditions (3.0 and 5.0) and number of bilayers (3.5, 10.5, and 20.5) were controlled. The characterization of these films was carried out using profilometry, ultraviolet-visible (UV-VIS), atomic force microscopy (AFM) and contact angle measurements. Multilayer HA/CHI films produced at pH 3.0 gave optimum surface wettability and availability of free carboxyl groups. In turn, at pH 5.0, the coverings were thinner and presented a smoother surface. Films prepared with 3.5 bilayers showed greater tumor cell capture regardless of the pH condition, while films containing 10.5 and 20.5 bilayers presented a significant swelling process, which compromised their cell adhesion potential. This study shows that surface chemistry and morphology are critical factors for the development of biomaterials designed for several cell adhesion applications, such as rapid diagnostic, cell signaling, and biosensing mechanisms.
Techno Economic Analysis of the Modified MixAlco Process
Authors: Simchick Chloe , Zidek Brooke , Moder Devin , Madson Dustin , Payne Michael , Kelsey Jonathon , Shaikh Faisal , Ozturk Serdar
Published: May 2021

The MixAlco process is a patented biomass conversion technology used to produce valuable chemicals. The basis of this design relies on the use of fermentation, where acidophiles utilize their own enzymatic pathways to convert a variety of biomass, such as organic wastes, into carboxylic acid salts. Unlike previous MixAlco designs in which carboxylate salts are processed further into hydrocarbon fuels, this proposed design simulates the optimization and commercialization of mixed carboxylic acid salts as the final product. Sensitivity analyses identified four critical input factors of the base case process—biomass feed rate, selling price, distribution cost, and biomass composition. Increasing the biomass feed rate or population size has the most pronounced effect on process economics. Overall, the sensitivity analyses of all four critical input factors support that the new design is flexible in its ability to support populations of varying sizes, as well as different biomass feed rates and compositions.
Computational Fluid Dynamics (CFD) Modeling and Analysis of Hydrocarbon Vapor Cloud Explosions (VCEs) in Amuay Refinery and Jaipur Plant Using FLACS
Authors: Sajid Zaman , Khan Muhammad Kashif , Rahnama Alireza , Moghaddam Farzan Sahari , Vardhan Kirti , Kalani Reema
Published: May 2021

Process safety helps prevent the unexpected and unplanned release of flammable and toxic chemicals, leading to poisonous gas clouds, fires, and explosions. Vapor cloud explosions (VCEs) are among the most severe hazards to humans and the environment in process facilities. Therefore, process safety demands to use best and reliable techniques to model VCEs in process industries and storage tanks of flammable chemicals. In this regard, the Computational Fluid Dynamics (CFD) models are more appropriate, as these models provide three-dimensional (3D) modeling of all sequences of events in an accident. In this study, CFD is used to model VCE in two industrial accidents: the Amuay refinery disaster (happened in 2012) and the Indian Oil Corporation’s (IOC) Jaipur terminal (2009). This work studies 3D CFD modeling of flammable cloud explosion in the real-time configuration for both accidents. FLACS (FLame ACceleration Simulator), a CFD software, is used to simulate the loss of hydrocarbon containment, cloud formation, and explosion in both industrial case studies. The ignition locations and grid sizes were varied to analyze their influence on explosion overpressure, temperature, vapor velocity, and fuel mass. This work also investigated the effect of geometry complexity on the explosion. Results showed that, as opposed to the coarse grid, the fine grid provides more precision in the analysis. The study also reveals an explosion overpressure of the order 4–15 bar (g) for the given case studies. This study’s results can help perform a qualitative and quantitative risk assessment of the Amuay refinery accident and Jaipur fire. The simulation of different scenarios can help develop and improve safety guidelines to mitigate similar accidents.
An Atmospheric Origin for HCN-Derived Polymers on Titan
Authors: Perrin Zoé , Carrasco Nathalie , Chatain Audrey , Jovanovic Lora , Vettier Ludovic , Ruscassier Nathalie , Cernogora Guy
Published: May 2021

Titan’s haze is strongly suspected to be an HCN-derived polymer, but despite the first in situ measurements by the ESA-Huygens space probe, its chemical composition and formation process remain largely unknown. To investigate this question, we simulated the atmospheric haze formation process, experimentally. We synthesized analogues of Titan’s haze, named Titan tholins, in an irradiated N2–CH4 gas mixture, mimicking Titan’s upper atmosphere chemistry. HCN was monitored in situ in the gas phase simultaneously with the formation and evolution of the haze particles. We show that HCN is produced as long as the particles are absent, and is then progressively consumed when the particles appear and grow. This work highlights HCN as an effective precursor of Titan’s haze and confirms the HCN-derived polymer nature of the haze.
Special Issue: Biochemical and Thermochemical Conversion Processes of Lignocellulosic Biomass Fractionated Streams
Authors: Trubetskaya Anna , Matsakas Leonidas
Published: May 2021

Global consumption of materials such as forest resources, fossil fuels, earth metals and minerals are expected to double in the next 30 years, while annual waste production is estimated to increase by approximately 70% by 2050 [...]
Quantum Circuit Learning with Error Backpropagation Algorithm and Experimental Implementation
Authors: Watabe Masaya , Shiba Kodai , Chen Chih-Chieh , Sogabe Masaru , Sakamoto Katsuyoshi , Sogabe Tomah
Published: May 2021

Quantum computing has the potential to outperform classical computers and is expected to play an active role in various fields. In quantum machine learning, a quantum computer has been found useful for enhanced feature representation and high-dimensional state or function approximation. Quantum–classical hybrid algorithms have been proposed in recent years for this purpose under the noisy intermediate-scale quantum computer (NISQ) environment. Under this scheme, the role played by the classical computer is the parameter tuning, parameter optimization, and parameter update for the quantum circuit. In this paper, we propose a gradient descent-based backpropagation algorithm that can efficiently calculate the gradient in parameter optimization and update the parameter for quantum circuit learning, which outperforms the current parameter search algorithms in terms of computing speed while presenting the same or even higher test accuracy. Meanwhile, the proposed theoretical scheme was successfully implemented on the 20-qubit quantum computer of IBM Q, ibmq_johannesburg. The experimental results reveal that the gate error, especially the CNOT gate error, strongly affects the derived gradient accuracy. The regression accuracy performed on the IBM Q becomes lower with the increase in the number of measurement shot times due to the accumulated gate noise error.
Reassessing Shamanism and Animism in the Art and Archaeology of Ancient Mesoamerica
Authors: Harrison-Buck Eleanor , Freidel David A.
Published: May 2021

Shamanism and animism have proven to be useful cross-cultural analytical tools for anthropology, particularly in religious studies. However, both concepts root in reductionist, social evolutionary theory and have been criticized for their vague and homogenizing rubric, an overly romanticized idealism, and the tendency to ‘other’ nonwestern peoples as ahistorical, apolitical, and irrational. The alternative has been a largely secular view of religion, favoring materialist processes of rationalization and “disenchantment.” Like any cross-cultural frame of reference, such terms are only informative when explicitly defined in local contexts using specific case studies. Here, we consider shamanism and animism in terms of ethnographic and archaeological evidence from Mesoamerica. We trace the intellectual history of these concepts and reassess shamanism and animism from a relational or ontological perspective, concluding that these terms are best understood as distinct ways of knowing the world and acquiring knowledge. We examine specific archaeological examples of masked spirit impersonations, as well as mirrors and other reflective materials used in divination. We consider not only the productive and affective energies of these enchanted materials, but also the potentially dangerous, negative, or contested aspects of vital matter wielded in divinatory practices.
Special Issue on Catholic Youth & Young Adult Ministry
Authors: Canales Arthur D.
Published: May 2021

It gives me great pleasure to announce and provide the readership of Religions this special issue on Catholic youth and young adult ministry [...]
An Adaptive Human Activity-Aided Hand-Held Smartphone-Based Pedestrian Dead Reckoning Positioning System
Authors: Wu Bang , Ma Chengqi , Poslad Stefan , Selviah David R.
Published: May 2021

Pedestrian dead reckoning (PDR), enabled by smartphones’ embedded inertial sensors, is widely applied as a type of indoor positioning system (IPS). However, traditional PDR faces two challenges to improve its accuracy: lack of robustness for different PDR-related human activities and positioning error accumulation over elapsed time. To cope with these issues, we propose a novel adaptive human activity-aided PDR (HAA-PDR) IPS that consists of two main parts, human activity recognition (HAR) and PDR optimization. (1) For HAR, eight different locomotion-related activities are divided into two classes: steady-heading activities (ascending/descending stairs, stationary, normal walking, stationary stepping, and lateral walking) and non-steady-heading activities (door opening and turning). A hierarchical combination of a support vector machine (SVM) and decision tree (DT) is used to recognize steady-heading activities. An autoencoder-based deep neural network (DNN) and a heading range-based method to recognize door opening and turning, respectively. The overall HAR accuracy is over 98.44%. (2) For optimization methods, a process automatically sets the parameters of the PDR differently for different activities to enhance step counting and step length estimation. Furthermore, a method of trajectory optimization mitigates PDR error accumulation utilizing the non-steady-heading activities. We divided the trajectory into small segments and reconstructed it after targeted optimization of each segment. Our method does not use any a priori knowledge of the building layout, plan, or map. Finally, the mean positioning error of our HAA-PDR in a multilevel building is 1.79 m, which is a significant improvement in accuracy compared with a baseline state-of-the-art PDR system.
Influence of Image Quality and Light Consistency on the Performance of Convolutional Neural Networks for Weed Mapping
Authors: Hu Chengsong , Sapkota Bishwa B. , Thomasson J. Alex , Bagavathiannan Muthukumar V.
Published: May 2021

Recent computer vision techniques based on convolutional neural networks (CNNs) are considered state-of-the-art tools in weed mapping. However, their performance has been shown to be sensitive to image quality degradation. Variation in lighting conditions adds another level of complexity to weed mapping. We focus on determining the influence of image quality and light consistency on the performance of CNNs in weed mapping by simulating the image formation pipeline. Faster Region-based CNN (R-CNN) and Mask R-CNN were used as CNN examples for object detection and instance segmentation, respectively, while semantic segmentation was represented by Deeplab-v3. The degradations simulated in this study included resolution reduction, overexposure, Gaussian blur, motion blur, and noise. The results showed that the CNN performance was most impacted by resolution, regardless of plant size. When the training and testing images had the same quality, Faster R-CNN and Mask R-CNN were moderately tolerant to low levels of overexposure, Gaussian blur, motion blur, and noise. Deeplab-v3, on the other hand, tolerated overexposure, motion blur, and noise at all tested levels. In most cases, quality inconsistency between the training and testing images reduced CNN performance. However, CNN models trained on low-quality images were more tolerant against quality inconsistency than those trained by high-quality images. Light inconsistency also reduced CNN performance. Increasing the diversity of lighting conditions in the training images may alleviate the performance reduction but does not provide the same benefit from the number increase of images with the same lighting condition. These results provide insights into the impact of image quality and light consistency on CNN performance. The quality threshold established in this study can be used to guide the selection of camera parameters in future weed mapping applications.
Time Series InSAR Three-Dimensional Displacement Inversion Model of Coal Mining Areas Based on Symmetrical Features of Mining Subsidence
Authors: Dong Longkai , Wang Chao , Tang Yixian , Tang Fuquan , Zhang Hong , Wang Jing , Duan Wei
Published: May 2021

The three-dimensional (3-D) displacements of mining areas is the basis of studying the mining subsidence law and obtaining surface movement parameters. The traditional multi-temporal interferometry synthetic aperture radar (InSAR) technology can only obtain the surface deformation in line-of-sight (LOS) direction, even if some methods can obtain the 3-D displacements of mining area based on InSAR. However, it has high data requirements for data types, which are not conducive to the inversion of 3-D displacements. In this paper, the symmetry of the surface basin caused by mining subsidence under different mining degrees is analyzed. According to the basic symmetrical features of mining subsidence—that the surface vertical displacement and horizontal displacement in near horizontal coal seam is symmetrical with respect to the main section of the basin, combined with time series InSAR technology (TS-InSAR)—a novel method for retrieving the 3-D displacement results from a single-geometry InSAR dataset based on symmetrical features (hereafter referred to as the SGI-SF method) is proposed. The SGI-SF method first generates multi-temporal observations of LOS displacement from a single-geometry InSAR dataset, and then transforms them into multi-temporal observations of 3-D displacement datasets according to symmetrical features. There is no necessity to obtain the surface movement parameters from the measured data to calculate 3-D displacement fields. Finally, the time series of 3-D displacements are estimated from multi-temporal 3-D displacements using the singular value decomposition (SVD) method. Nine descending Sentinel-1 images from the Yulin mining area of China are used to test the proposed SGI-SF method. The results show that the average root mean square errors (RMSE) in the vertical and horizontal direction of the three-dimensional deformations are approximately 9.28 mm and 13.10 mm, respectively, which are much smaller than mining-induced displacements and can provide support for deformation monitoring in mining areas.
Smart Accounts for Decentralized Governance on Smart Cities
Authors: Coelho Vitor N. , Oliveira Thays A. , Tavares Wellington , Coelho Igor M.
Published: May 2021

This paper introduces state-of-the-art possibilities for using smart contracts capabilities for governance. Assisted by blockchain, the use of these tools can provide a transition that society currently needs due the huge amount of information that reaches citizens. The core mechanism of this study lies within the scope of smart accounts and digital identities. These topics enclose smart cities trends that seek to increase citizens’ participation in the social decision making process, in a transparent way that is usually managed throughout decentralized systems. We define a set of available features that can automatically guide the flow of resources, after the conclusions of voting processes also conducted on trusted environments of distributed ledgers. By presenting innovative ideas and didactically describing the possibilities, we aim to promote awareness of blockchain capabilities among readers, students, decisions makers and, mainly, the younger generation.
The Neoliberal University in Ireland: Institutional Bullying by Another Name?
Authors: Hodgins Margaret , Mannix-McNamara Patricia
Published: May 2021

New managerialism and the pervasive neoliberalisation of universities is by now a well-established phenomenon. Commentaries explore the political and economic drivers and effects of neoliberal ideology, and critique the impact on higher education and academic work. The impact on the health and well-being of academic staff has had less attention, and it is to that we turn in this paper. Much academic interest in neoliberalism stems from the UK, Australia and the United States. We draw particularly on studies of public Irish universities, where neoliberalism, now well entrenched, but something of a late-comer to the new public management party, is making its presence felt. This conceptual paper explores the concept of neoliberalism in higher education, arguing that the policies and practices of new public management as exercised in universities are a form of bullying; what we term institutional bullying. The authors are researchers of workplace culture, workplace bullying and incivility. Irish universities are increasingly challenged in delivering the International Labour Organisation (ILO) principles of decent work, i.e., dignity, equity, fair income and safe working conditions. They have become exposed in terms of gender imbalance in senior positions, precariat workforce, excessive workload and diminishing levels of control. Irish universities are suffering in terms of both the health and well-being of staff and organisational vibrancy. The authors conclude by cautioning against potential neoliberal intensification as universities grapple with the economic fallout from the COVID-19 pandemic. This paper reviews neoliberalism in higher education and concludes with insight as to how the current pandemic could act as a necessary catalyst to stem the tide and ‘call out’ bullying at the institutional level.
On the Mistaken Use of the Chi-Square Test in Benford’s Law
Authors: Kossovsky Alex Ely
Published: May 2021

Benford’s Law predicts that the first significant digit on the leftmost side of numbers in real-life data is distributed between all possible 1 to 9 digits approximately as in LOG(1 + 1/digit), so that low digits occur much more frequently than high digits in the first place. Typically researchers, data analysts, and statisticians, rush to apply the chi-square test in order to verify compliance or deviation from this statistical law. In almost all cases of real-life data this approach is mistaken and without mathematical-statistics basis, yet it had become a dogma or rather an impulsive ritual in the field of Benford’s Law to apply the chi-square test for whatever data set the researcher is considering, regardless of its true applicability. The mistaken use of the chi-square test has led to much confusion and many errors, and has done a lot in general to undermine trust and confidence in the whole discipline of Benford’s Law. This article is an attempt to correct course and bring rationality and order to a field which had demonstrated harmony and consistency in all of its results, manifestations, and explanations. The first research question of this article demonstrates that real-life data sets typically do not arise from random and independent selections of data points from some larger universe of parental data as the chi-square approach supposes, and this conclusion is arrived at by examining how several real-life data sets are formed and obtained. The second research question demonstrates that the chi-square approach is actually all about the reasonableness of the random selection process and the Benford status of that parental universe of data and not solely about the Benford status of the data set under consideration, since the focus of the chi-square test is exclusively on whether the entire process of data selection was probable or too rare. In addition, a comparison of the chi-square statistic with the Sum of Squared Deviations (SSD) measure of distance from Benford is explored in this article, pitting one measure against the other, and concluding with a strong preference for the SSD measure.
Cost-Effectiveness of Black Soldier Fly Larvae Meal as Substitute of Fishmeal in Diets for Layer Chicks and Growers
Authors: Sumbule Esther Khayanga , Ambula Mary Kivali , Osuga Isaac Maina , Changeh Janice Ghemoh , Mwangi David Miano , Subramanian Sevgan , Salifu Daisy , Alaru Peter A. O. , Githinji Macdonald , van Loon Joop J. A. , Dicke Marcel , Tanga Chrysantus M.
Published: May 2021

The acceptance of eco-friendly black soldier fly larvae meal (BSFLM) as sustainable alternative protein ingredient in poultry feeds continues to gain momentum worldwide. This study evaluates the impact of BSFLM in layer chick and grower diets on the growth, carcass quality and economic returns. Mean weekly weight gain and total live weight per chick and grower varied significantly. The highest final weight gain was achieved when birds were provided diet with 25.6% BSFLM. Average daily feed intake (ADFI), average daily weight gain (ADG) and overall weight gain of the chick varied significantly, except for the feed conversion ratio (FCR). For grower birds, ADFI, ADG, FCR and overall weight gain did not vary significantly across the various feeding regimes. The weight of the wings and drumsticks had a quadratic response with a maximum weight obtained at 33% inclusion of BSFLM. The weight of the internal organs were not significantly affected by dietary types. Positive cost–benefit ratio and return on investment was recorded for diet types with higher BSFLM inclusion levels (>75%). Diets with 25% and 100% BSFLM inclusion were the most suitable and cost-effective, respectively. Thus, BSFLM represents a promising alternative source of protein that could be sustainably used in the poultry industries.
Towards Sustainable Livestock Production: Estimation of Methane Emissions and Dietary Interventions for Mitigation
Authors: Prathap Pragna , Chauhan Surinder Singh , Leury Brian Joseph , Cottrell Jeremy James , Dunshea Frank Rowland
Published: May 2021

The increasing need for sustainable livestock production demands more research in the field of greenhouse gas (GHG), particularly methane (CH4), measurement and mitigation. Dietary interventions, management, and biotechnological strategies to reduce the environmental impacts and economic implications of enteric CH4 emissions are needed. While the use of biotechnological interventions and management strategies can be challenging on a routine basis, feed additive supplementation appears to be the most researched, developed, and ready to use strategy to mitigate enteric CH4 emissions. This paper discusses various recently developed feeding strategies to reduce enteric CH4 emissions in livestock. Additionally, the manuscript reviews various technologies developed for CH4 estimation since the accurate and reliable estimation of CH4 emissions can be a limiting step in the development and adoption of any mitigation strategy.
Natural Carbon Sinks Linked to Pastoral Activity in S Spain: A Territorial Evaluation Methodology for Mediterranean Goat Grazing Systems
Authors: Muñoz Vallés Sara , Mancilla-Leytón Juan Manuel , Morales-Jerrett Eduardo , Mena Yolanda
Published: May 2021

Exploring and developing new tools for the accounting and management of natural C sinks will provide a closer, more accurate option to remark the importance of such sinks in relation to livestock production, helping to support the persistence of some seriously endangered traditional, environmentally sustainable livestock farming. Following both precision and usability criteria, two main C sink databases covering the Andalusian region (S Spain) were developed from the Spanish Land Parcel Identification System (SIGPAC, coarse resolution) and the Spanish Information System on Land Cover (SIOSE, finer resolution) land use classes. Particular C sink factors based on growth rates for individual plant species were associated with detailed vegetation maps and, further, were linked to Land Use and Covers cartography across the region. In addition, eight ruminant farms were exhaustively studied in situ and used as a control. Results were compared with the obtained through the application of the developed C sink databases, and with the commonly used Petersen methodology. The sink capacity of vegetation associated with farms varied from 0.25 to 1.37 t CO2 ha−1 year−1, depending on the plant species composition and abundance. All the approaches showed significant differences from the control. C sink values were significantly higher when applying SIGPAC-based C sink database to farms, while values from the SIOSE and Petersen methodology approaches provided more moderate values, closer to the control. SIGPAC and Petersen approaches showed higher usability but presented lower precision due to a poor definition of plant cover. SIOSE-based C sink database provided suitable values able to be adapted to reality and used by farmers. In this regard, further research efforts to improve the adjustment of results and ease of use are required. The present approach means a methodological advance in the estimation of the C sink capacity associated with pastoral livestock farms, able to be incorporated into the CF calculation in contrasted areas worldwide, in the frame of the ‘eco-schemes’ being recently under development through the EU CAP.
Evaluation of the Efficiency of Maritime Transport Using a Network Slacks-Based Measure (SBM) Approach: A Case Study on the Korean Coastal Ferry Market
Authors: Kim Joohwan , Kim Hwayoung
Published: May 2021

Safety is a key performance indicator for the sustainable management of a coastal ferry service business. An efficiency strategy that balances safety and transport performance should be considered. The purpose of this study is to evaluate the relative transport efficiency of coastal ferry operators through undesirable safety-related output. Coastal ferry operators create added value through logistics activities such as cargo and passenger transport. Accordingly, this study designed a three-stage network-slacks-based measure (SBM) model that delineated production through ferry transport services such as service generation, service execution, and transport value creation. Detention records and marine accidents caused by human errors or technical faults were considered undesirable safety-related outputs. Moreover, the relative transport efficiency of 23 Korean firms that have continuously managed a coastal ferry transport business from 2015 to 2018 was analyzed. The results showed that the differentiation of transport efficiency of firms improved when applying the three-stage network SBM model compared to applying the SBM model that did not consider the internal production stage. This fact suggests that it is more desirable to apply the three-stage network SBM model proposed in this study when a more stringent comparison of transport performance is needed in terms of service quality.
Impact of COVID-19 on Sustainable University Sports: Analysis of Physical Activity and Positive and Negative Affects in Athletes
Authors: Duclos-Bastías Daniel , Vallejo-Reyes Felipe , Giakoni-Ramírez Frano , Parra-Camacho David
Published: May 2021

The suspension of university activities due to the pandemic affected training and sports competitions. However, some universities adapted online education, allowing students to carry out their activities without being infected by the virus. The aim of this study was to find out the impact of the pandemic on physical activity levels and the positive and negative effects on Chilean university athletes. The information was obtained by applying the PANAS scale and demographic and physical activity variables were also measured. The sample of Chilean university athletes (n = 254) were aged between 18 and 31 years (M = 22.17; SD = 2.76). This study led to the conclusion that maintaining the frequency of physical training during the pandemic was associated with a preservation in the levels of Positive Affect and Negative Affect compared to the non-pandemic period. Thus, physical activity training was protective of emotional well-being and, therefore, of mental health.
Analysis of Pavement Structures. By Animesh Das. CRC Press: Boca Raton, FL, USA, 2014; 194p; ISBN 978-1466558557
Authors: Jamshidi Ali
Published: May 2021

Significant differences exist between pavement and building structures, particularly with respect to the type and mode of loading conditions: structural elements, beams and columns of buildings are subjected to static loads and pavement to dynamic loads. However, the design of structural members for buildings might need to address temporary dynamic loads due to wind, earthquake or other factors depending on building or structure height and application. In contrast, pavements are subjected to the moving loads of vehicles as well as to further loads due to temperature gradients. Since the layers of various materials used in pavements may vary in thickness and the statically indeterminate nature of pavement (due to the full contact with the bed soil layer or the lower layers), any deformation caused by changes in the moisture content and temperature can result in internal stresses in pavement structures. Consequently, analysis of pavement structures can be very complicated, requiring skills in material characterization, mathematics and modeling. In this regard, a useful book that covers various subjects in the pavement design and analysis was reviewed. Th details of each chapter were briefly explained. This book is recommended for consultant engineers and pavement researchers.
Resource Assessment of Renewable Energy Systems—A Review
Authors: Yavor Kim Maya , Bach Vanessa , Finkbeiner Matthias
Published: May 2021

The reduction of greenhouse gas emissions by the energy transition may lead to trade-offs with other impacts on the environment, society, and economy. One challenge is resource use impacts due to increasing demand for high-tech metals and minerals. A review of the current state of the art resource assessment of energy systems was conducted to identify gaps in research and application. Publications covering complete energy systems and supplying a detailed resource assessment were the focus of the evaluation. Overall, 92 publications were identified and categorized by the type of system covered and the applied abiotic resource assessment methods. A total of 78 out of 92 publications covered sub-systems of renewable energy systems, and nine considered complete energy systems and conducted a detailed resource use assessment. Most of the publications in the group “complete energy system and detailed resource assessment” were found in grey literature. Several different aspects were covered to assess resource use. Thirty publications focused on similar aspects including criticality and supply risks, but technology-specific aspects are rarely assessed in the resource assessment of renewable energy systems. Few publications included sector coupling technologies, and among the publications most relevant to the aim of this paper one third did not conduct an indicator-driven assessment.