bluuebunny/crossref_metadata_2025 huggingface dataset:
Online Education and the COVID-19 Outbreak: A Case Study of Online Teaching during Lockdown
Authors: Peimani Nastaran , Kamalipour Hesam
Published: February 2021

The COVID-19 pandemic has become a critical challenge for the higher education sector. Exploring the capacity of this sector to adapt in the state of uncertainty has become more significant than ever. In this paper, we critically reflect on our experience of teaching urban design research methods online during the early COVID-19 lockdown in the UK. This is an exploratory case study with a qualitative approach with an aim to inform resilient practices of teaching in the face of public health emergencies. Drawing on the experience of teaching the Research Methods and Techniques subject during lockdown, we discuss the rapid transition from face-to-face to online teaching and point to the challenges and opportunities in relation to the learning and teaching activities, assessment and feedback, and digital platforms. This paper concludes by outlining some key considerations to inform the development of more adaptive and resilient approaches to online teaching in the context of unprecedented global health crises such as the COVID-19 pandemic. We argue that it is critical to move beyond fixed pedagogical frameworks to harness the productive capacities of adaptive teaching.
Adaptation and Validation of the Motivated Strategies for Learning Questionnaire for Spanish Adolescents
Authors: Segura-Robles Adrián , Moreno-Guerrero Antonio-José , Parra-González María-Elena , López-Belmonte Jesús
Published: February 2021

This work adapts and validates the scale of the motivated strategies for learning questionnaire (MSLQ), which is used to measure motivation. For this, an instrumental design was carried out with the purpose of analyzing the psychometric properties of the instrument. The sample consisted of 307 participants enrolled in compulsory secondary education. Reliability with fit indices were good in model B (proposed) with composite reliability, global reliability index, and Cronbach’s alpha. The original model (A) presented small problems that had to be adjusted when carrying out the translation. We concluded that adaptation and subsequent validation of the MSLQ instrument into a Spanish context was positive. In this sense, adequate adjustment rates have been achieved. However, in its contextual adequacy, the need arises to modify the presentation of the items alluding to intrinsic motivation due to the difficulty of measuring such a construct. Among the implications reached in this study is the possibility of having a validated instrument for the Spanish adolescent context to measure motivation on educational aspects. Furthermore, this tool can serve as the basis for the design of other instruments that measure this construct in other age ranges.
A Strategy Based on Genetic Algorithms for Forming Optimal Collaborative Learning Groups: An Empirical Study
Authors: Revelo Sánchez Oscar , Collazos César A. , Redondo Miguel A.
Published: February 2021

Considering that group formation is key when developing activities in collaborative learning scenarios, this paper aims to propose a strategy based on a genetic algorithm approach for achieving optimal collaborative learning groups, considering the students’ personality traits as grouping criteria. A controlled experiment was designed with 238 students, quantifying their personality traits through the “big five inventory” (BFI), forming working groups and developing a collaborative activity in programming and related courses. The experiment results allowed validation, not only from a computational point of view evaluating the algorithm performance but also from a pedagogical point of view, confronting the results obtained by students applying the proposed approach with those obtained through other group formation strategies. The highlight of the study is that those groups whose formation was pre-established by the teachers through the proposed strategy have generally had a better collaborative performance than the groups with traditional formation, except in the case of heterogeneous formation, at the time of developing a collaborative activity. In addition, through the experiment, it was found that not considering criteria related to personality traits before the group formation generally led to lower results.
Using Ultrasonic Sensors and a Knowledge-Based Neural Fuzzy Controller for Mobile Robot Navigation Control
Authors: Chen Cheng-Hung , Lin Cheng-Jian , Jeng Shiou-Yun , Lin Hsueh-Yi , Yu Cheng-Yi
Published: February 2021

This study proposes a knowledge-based neural fuzzy controller (KNFC) for mobile robot navigation control. An effective knowledge-based cultural multi-strategy differential evolution (KCMDE) is used for adjusting the parameters of KNFC. The KNFC is applied in PIONEER 3-DX mobile robots to achieve automatic navigation and obstacle avoidance capabilities. A novel escape approach is proposed to enable robots to autonomously avoid special environments. The angle between the obstacle and robot is used and two thresholds are set to determine whether the robot entries into the special landmarks and to modify the robot behavior for avoiding dead ends. The experimental results show that the proposed KNFC based on the KCMDE algorithm has improved the learning ability and system performance by 15.59% and 79.01%, respectively, compared with the various differential evolution (DE) methods. Finally, the automatic navigation and obstacle avoidance capabilities of robots in unknown environments were verified for achieving the objective of mobile robot control.
Success Factors for the Foundation of Municipal Utilities in Germany
Authors: Wagner Oliver , Berlo Kurt , Herr Christian , Companie Michael
Published: February 2021

More than 150 municipal utilities (so-called Stadtwerke) were established in Germany from the beginning of the millennium, bringing the total number of Stadtwerke currently established within the country to approximately 900. With responsibility for more than half of the supply of electricity, gas and heat in Germany, these Stadtwerke play a central role in the transformation of the energy sector, or Energiewende. In addition, due to their local and regional ties, Stadtwerke have a particular role to play in energy politics, the economy and across society. This article focuses on the motives behind, and grounds for, the current wave of newly established Stadtwerke. Further, it discusses the factors that were critical to the successful formation of new Stadtwerke in recent years. The results of our survey indicate that the establishment of municipal Stadtwerke is a suitable measure to implement the energy transition at the local level, whereby the concept of public value has a high level of importance for the local decision-makers. Collaboration and cooperation, as well as a resilience-oriented strategy, are important success factors for new Stadtwerke.
Experimental Study on Shear Mechanism of Rock-Like Material Containing a Single Non-Persistent Rough Joint
Authors: Fereshtenejad Sayedalireza , Kim Jineon , Song Jae-Joon
Published: February 2021

The geometrical and mechanical properties of non-persistent joints as well as the mechanical behavior of intact rock (rock bridges) are significantly effective in the shear strength of weakness planes containing non-persistent joints. Therefore, comprehensive knowledge of the shear mechanism of both joints and rock bridges is required to assess the shear strength of the planes. In this study, the shear behavior of specimens containing a single non-persistent rough joint is investigated. A novel procedure was used to prepare cast specimens embedding a non-persistent (disc-shaped) rough joint using 3D printing and casting technology, and the shear strength of the specimens was examined through an extensive direct shear testing program under constant normal load (CNL) condition. Three levels for three different variables of the joint roughness, rock bridge ratio, and normal stress were considered, and the effects of these factors on the shear behavior of prepared samples were tested. The experimental results show a clear influence of the three variables on the shear strength of the specimens. The results show that the normal stress applied to the jointed zone of weakness planes is considerable, and thus joint friction contribution should be taken into account during shear strength evaluation. Furthermore, the dilation mechanism of the specimens before and after failure was investigated through a digital image correlation analysis. Finally, a camcorder was used to analyze the location and sequence of the initiated cracks.
Is the Alternative Energy Sector COVID-19 Resistant? Comparison with the Conventional Energy Sector: Markov-Switching Model Analysis of Stock Market Indices of Energy Companies
Authors: Czech Katarzyna , Wielechowski Michał
Published: February 2021

The outbreak and rapid spread of the COVID-19 pandemic has hit the global financial markets, including the energy sector. Alternative energy belongs to the economy’s key sectors concerning environmental issues and seems to be a full-fledged alternative for fossil-based conventional energy. This paper aims to assess the impact of COVID-19 on the stock market indices related to the alternative and conventional energy sector. We use daily data on the Morgan Stanley Capital International (MSCI) Global Alternative Energy Index, the MSCI All Country World Index (ACWI) Energy Index, and self-developed Average-49 COVID-19 New Cases Index and Average-49 Stringency Index. The research covers the period January–October 2020. The average level of the MSCI Global Alternative Energy Index in COVID-19 year was more than a quarter higher than in 2019 while the MSCI ACWI Energy fell almost one-third in the same period. Based on the Markov-switching model, we show that both the MSCI Global Alternative Energy and the MSCI ACWI Energy are not significantly affected by the epidemic status. The analysed indices decline as the government anti-COVID-19 policy becomes more stringent, but the relationship is statistically significant only in the high-volatility regime. In comparison to the conventional energy index, we reveal that the alternative energy index stays most of its time in the low-volatility regime without being adversely and significantly affected by the COVID-19 related indicators. Our study shows that the alternative energy sector, represented by the MSCI Global Alternative Energy Index, seems to be more resistant to COVID-19 than the conventional energy sector. It might imply that the novel coronavirus pandemic has not depreciated but emphasised the growing concern about climate change and environmental pollution.
Voltage Optimization in MV Network with Distributed Generation Using Power Consumption Control in Electrolysis Installations
Authors: Pijarski Paweł , Kacejko Piotr
Published: February 2021

Connecting a large number of distributed sources to the medium and low voltage grid poses many problems. The most important of these are the voltage changes inside the network, what can be observed when the power flow from these sources towards the HV/MV (High Voltage/Medium Voltage) transformer station. In particular, if the power consumption in nodes of the MV network is small and the distance between the place of installation of the source and the substation is large, increases and changes in voltage may be dangerous for the insulation of the network and burdensome for the consumers connected to it. The solution most frequently used to control voltage increases is the appropriate setting of the controller that affects the on-load tap changer of the MV/HV or even MV/LV (Medium Voltage/Low Voltage) transformer. It is also possible to regulate the reactive power of the sources and, of course, to limit their generated active power (curtailment of generation). The development of energy storage technology has made it possible to introduce consumers into the network, whose power can be controlled in a wide range. The article proposes the concept of an innovative voltage control system in the MV network, whose output values are three groups of parameters: HV/MV transformer ratio, reactive power of sources and active power of consumers connected in generation nodes. In the technological sense, it has been assumed that the loads are installations of electrolyzers used to produce “green hydrogen”, according to the P2G (Power to Gas) formula. The tests consisting in the execution of several hundred calculation cycles for the IEEE 37 test network, using the Monte Carlo simulation, have shown that the subordination of the hydrogen production process to the objectives of voltage control in the MV network clearly contributes to stabilizing its value, while meeting the technological requirements. The control variables of the proposed control system are the result of the optimization algorithm described in the article, the function of which is the quality of network voltage.
A Heating Controller Designing Based on Living Space Heating Dynamic’s Model Approach in a Smart Building
Authors: Sadeghian Broujeny Roozbeh , Madani Kurosh , Chebira Abdennasser , Amarger Veronique , Hurtard Laurent
Published: February 2021

Most already advanced developed heating control systems remain either in a prototype state (because of their relatively complex implementation requirements) or require very specific technologies not implementable in most existing buildings. On the other hand, the above-mentioned analysis has also pointed out that most smart building energy management systems deploy quite very basic heating control strategies limited to quite simplistic predesigned use-case scenarios. In the present paper, we propose a heating control strategy taking advantage of the overall identification of the living space by taking advantage of the consideration of the living space users’ presence as additional thermal sources. To handle this, an adaptive controller for the operation of heating transmitters on the basis of soft computing techniques by taking into account the diverse range of occupants in the heating chain is introduced. The strategy of the controller is constructed on a basis of the modeling heating dynamics of living spaces by considering occupants as an additional heating source. The proposed approach for modeling the heating dynamics of living spaces is on the basis of time series prediction by a multilayer perceptron neural network, and the controlling strategy regarding the heating controller takes advantage of a Fuzzy Inference System with the Takagi-Sugeno model. The proposed approach has been implemented for facing the dynamic heating conduct of a real five-floor building’s living spaces located at Senart Campus of University Paris-Est Créteil, taking into account the occupants of spaces in the control chain. The obtained results assessing the efficiency and adaptive functionality of the investigated fuzzy controller designed model-based approach are reported and discussed.
Preparation of Boron Nitride and Silicone Rubber Composite Material for Application in Lithium Batteries
Authors: Zhang Yafang , Huang Juhua , Cao Ming , Du Guoping , Liu Ziqiang , Li Wang
Published: February 2021

Hexagonal boron nitride and silicone rubber (h-BN/SR) composites were prepared by the mechanical stirring method, and their crystal morphology, chemical structure, thermal properties, and compression stress–strain performance were investigated. The experimental results suggest that silicone rubber combined with h-BN exhibits better thermal conductivity and mechanical properties. When the proportion of h-BN is 30 wt%, the thermal conductivity of the h-BN/SR composite material is 0.58 W/m∙K, which is 3.4 times that of pure silicone rubber. At the same time, the compressive strength of h-BN/SR is 4.27 MPa, which is 6.7 times that of pure silicone rubber. Furthermore, the finite element model was employed to numerically analyze the thermal behavior of a battery with a h-BN/SR composite as the thermal interface material. The analytical results show that the highest temperature of the battery decreased when using h-BN/SR as the thermal interface material in the battery thermal management system. The h-BN/SR composite can thus effectively improve the safety properties of batteries.
Tissue Integrity and COVID-19
Authors: Kerch Garry
Published: February 2021

Tissue integrity depends on biological tissue stiffness. Tissue integrity can protect both against age-related diseases and against severity of COVID-19. The disruption of tight junctions and increase of tissue permeability with advancing age can be related with age-related diseases as well as with age-dependent COVID-19. Release of tightly bound water from collagen fibrils leads to the increase of extracellular matrix stiffness and to the associated with matrix stiffness increased tissue permeability. The link between arterial stiffness and oxidative stress has been reported and is expected to be studied in more detail in the future. Trehalose can be suggested for retardation of tightly bound water release and subsequent extracellular matrix crosslinking by advanced glycation end products. Increase in tissue permeability can be blocked by polyphenols that inhibit ICAM-1 expression and mitigate cytoskeleton reorganization. NF-κB activation as a result of increased stiffness and cytoskeleton reorganization can cause both cardiovascular pathologies and COVID-19. Increased cholesterol content in cell membrane leads to increased virus entry into cell and increase of cholesterol is linked with cardiovascular diseases. Statins and chitosan are known as cholesterol-lowering substances. Nrf2 inhibits NF-κB activation and NF-κB inhibits Nrf2 pathway.
Combination of Feature Selection and CatBoost for Prediction: The First Application to the Estimation of Aboveground Biomass
Authors: Luo Mi , Wang Yifu , Xie Yunhong , Zhou Lai , Qiao Jingjing , Qiu Siyu , Sun Yujun
Published: February 2021

Increasing numbers of explanatory variables tend to result in information redundancy and “dimensional disaster” in the quantitative remote sensing of forest aboveground biomass (AGB). Feature selection of model factors is an effective method for improving the accuracy of AGB estimates. Machine learning algorithms are also widely used in AGB estimation, although little research has addressed the use of the categorical boosting algorithm (CatBoost) for AGB estimation. Both feature selection and regression for AGB estimation models are typically performed with the same machine learning algorithm, but there is no evidence to suggest that this is the best method. Therefore, the present study focuses on evaluating the performance of the CatBoost algorithm for AGB estimation and comparing the performance of different combinations of feature selection methods and machine learning algorithms. AGB estimation models of four forest types were developed based on Landsat OLI data using three feature selection methods (recursive feature elimination (RFE), variable selection using random forests (VSURF), and least absolute shrinkage and selection operator (LASSO)) and three machine learning algorithms (random forest regression (RFR), extreme gradient boosting (XGBoost), and categorical boosting (CatBoost)). Feature selection had a significant influence on AGB estimation. RFE preserved the most informative features for AGB estimation and was superior to VSURF and LASSO. In addition, CatBoost improved the accuracy of the AGB estimation models compared with RFR and XGBoost. AGB estimation models using RFE for feature selection and CatBoost as the regression algorithm achieved the highest accuracy, with root mean square errors (RMSEs) of 26.54 Mg/ha for coniferous forest, 24.67 Mg/ha for broad-leaved forest, 22.62 Mg/ha for mixed forests, and 25.77 Mg/ha for all forests. The combination of RFE and CatBoost had better performance than the VSURF–RFR combination in which random forests were used for both feature selection and regression, indicating that feature selection and regression performed by a single machine learning algorithm may not always ensure optimal AGB estimation. It is promising to extending the application of new machine learning algorithms and feature selection methods to improve the accuracy of AGB estimates.
Characterizing Ectomycorrhizal Fungal Community Structure and Function of Two Varieties of Pinus clausa That Differ in Disturbance History
Authors: Rúa Megan A.
Published: February 2021

Despite the immense amount of diversity present in the soil biota, the ecological and evolutionary processes that regulate species diversity and abundance of ectomycorrhizal (ECM) fungi across space and time remain elusive. In forest ecosystems, ECM fungal diversity may be maintained by periodic disturbances which operate at different time scales due to their effects on host genetic and phenotypic characteristics and the associated environment. To investigate the degree to which these factors shape ECM fungal community composition and function, I sampled 10 independent sites for a pine species indicative of an endangered ecosystem, the Florida scrub, where disturbance history has driven the divergence of a single species into two genetically distinct varieties (Pinus clausa var. immuginata and var. clausa). A total of 300 ECM fungal species were identified based on rDNA ITS sequences, but each variety harbors different ECM species composition and function. A follow-up greenhouse experiment, in which the seed from each variety was grown in its own soil (“home”) and in the soil of the other variety (“away”), suggests these communities differentially impact the growth of their host seedlings. While var. clausa seedlings had the same total biomass regardless of soil origin, var. immuginata had higher biomass in their own soil compared to var. clausa. This is likely due to an increased number of ECM colonized tips in the home soil compared to in away soil. Taken together, these results may suggest different evolutionary histories where structure host genetic and phenotypic characteristics may be important for structuring their dynamics with ECM fungi.
Continuous Urban Tree Cover Mapping from Landsat Imagery in Bengaluru, India
Authors: Nölke Nils
Published: February 2021

Percent tree cover maps derived from Landsat imagery provide a useful data source for monitoring changes in tree cover over time. Urban trees are a special group of trees outside forests (TOFs) and occur often as solitary trees, in roadside alleys and in small groups, exhibiting a wide range of crown shapes. Framed by house walls and with impervious surfaces as background and in the immediate neighborhood, they are difficult to assess from Landsat imagery with a 30 m pixel size. In fact, global maps based on Landsat partly failed to detect a considerable portion of urban trees. This study presents a neural network approach applied to the urban trees in the metropolitan area of Bengaluru, India, resulting in a new map of estimated tree cover (MAE = 13.04%); this approach has the potential to also detect smaller trees within cities. Our model was trained with ground truth data from WorldView-3 very high resolution imagery, which allows to assess tree cover per pixel from 0% to 100%. The results of this study may be used to improve the accuracy of Landsat-based time series of tree cover in urban environments.
An Accelerating Approach for Blockchain Information Transmission Based on NDN
Authors: Yang Zhi-Peng , Hua Lu , Gao Ning-Jie , Huo Ru , Liu Jiang , Huang Tao
Published: February 2021

Blockchain is becoming more and more popular in various fields. Since the information transmission mode of the blockchain is data broadcasting, the traditional TCP/IP network cannot support the blockchain system well, but the Named-Data Networking (NDN) could be a good choice because of its multi-path forwarding and intra-network caching functions. In this article, we propose a new blockchain information transmission acceleration strategy (AITS) combining with graph theory and probability theory based on the NDN architecture. We select some more important nodes in the network as “secondary nodes”, and give them more bandwidth and cache space to assist the NDN network in data transmission. In order to select the correct node as the secondary node, we present a method to calculate the number of secondary nodes, and give the function to calculate the importance of each node. The simulation results show that in complex networks, the proposed method has superior performance in accelerating information transmission and reducing data overhead.
Effect of Different Cooking Methods on Lipid Content and Fatty Acid Profiles of Mytilus galloprovincialis
Authors: Biandolino Francesca , Parlapiano Isabella , Denti Giuseppe , Di Nardo Veronica , Prato Ermelinda
Published: February 2021

The effect of cooking (barbecue-grilling, boiling, microwaving, oven cooking and frying) on lipids, fatty acids (FAs) and lipid quality indices of the mussel Mytilus galloprovincialis was investigated. In general, all processing methods significantly (p < 0.05) modified the fatty acid profiles of mussels, although with major changes in fried samples, which exhibited the lowest saturated fatty acids and n-3 and highest polyunsaturated (PUFA) and n-6 FAs content. A significant decrease in the n-3 PUFA from the raw sample to five cooking methods was observed. The n-3/n-6 ratio decreased from raw (6.01) to cooked mussels, exhibiting the lowest value in fried ones (0.15). C20:5 n-3 and C22:6 n-3 significantly decreased during all cooking processes, and overall in fried mussels. It can be concluded that cooking does not compromise the nutritional quality of mussels except with frying, although it resulted in a decrease of the atherogenic and thrombogenic indices.
A Long-Term Stable Sensor Based on Fe@PCN-224 for Rapid and Quantitative Detection of H2O2 in Fishery Products
Authors: Hu Pei , Sun Zhentao , Shen Yunwen , Pan Yiwen
Published: February 2021

Hydrogen peroxide (H2O2) has been reported to be used for the illegal treatment of fishery products in order to obtain “fake” freshness. Residues of H2O2 in food may be of toxicology concern. In this study, a nonenzymatic sensor was developed based on Fe@PCN-224 metal–organic frameworks wrapped by Nafion to detect H2O2 concentration. The hybrid structure of Fe@PCN-224 was fabricated by incorporated free FeIII ions into the center of PCN-224, which was ultra-stable due to the strong interactions between Zr6 and the carboxyl group. Scanning electron spectroscopy images exhibited that Nafion sheets crossed together on the surface of Fe@PCN-224 nanoparticles to form a hierarchical and coherent structure for efficient electron transfer. Electrochemical investigations showed that the Fe@PCN-224/Nafion/GCE possessed good linearity from 2 to 13,000 μM (including four orders of magnitude), low detection limits (0.7 μM), high stability in continuous monitoring (current remained nearly stable over 2300 s) and in long-term measurement (current decreased 3.4% for 30 days). The prepared nanohybrid modified electrode was effectively applied to H2O2 detection in three different fishery products. The results were comparable to those measured using photometrical methods. The developed electrochemical method has a great potential in detecting the illegal management of fishery products with H2O2.
Consumers’ Perspectives on Eggs from Insect-Fed Hens: A UK Focus Group Study
Authors: Spartano Sabrina , Grasso Simona
Published: February 2021

In recent years, there has been growing interest in insects as an alternative to soybean meal as laying hen feed due to nutrition, sustainability, and animal welfare benefits. Although some studies have investigated consumer acceptance and intentions towards insect-fed foodstuffs, no studies are available on eggs from insect-fed hens. This qualitative study aimed to explore consumers’ attitudes and perceptions towards eggs from insect-fed hens and factors influencing intentions to consume and purchase the product. Three focus group discussions were employed with a total of 19 individuals from the UK. Results showed that the environmental, animal welfare, and food waste benefits of feeding hens with insects positively influenced attitudes. Results also indicated price and disgust towards insects as feed were the main barriers, while enhanced welfare standards (e.g., free-range labelling) and information on benefits were main drivers. Therefore, the study suggests that educating and informing consumers about the benefits of feeding hens with insects may increase intentions to consume and purchase eggs from insect-fed hens. Given this emerging area of research, this study contributes to the limited literature on insect-fed foodstuffs and paves the way for further research on the topic.
Evaluation Warriorship: Raising Shields to Redress the Influence of Capitalism on Program Evaluation
Authors: Robinson Nicole
Published: February 2021

Evaluation warriorship, as defined by ¡Milwaukee Evaluation! Inc., links the practice of evaluation learning, reflection, and storytelling to the evaluator’s social responsibility as a warrior for justice. Unchecked global capitalism has led to extreme economic and racial injustice, undermined democracies, and accelerated environmental catastrophe. This paper argues that more evaluation warriorship is needed to resist this particular system of oppression. It presents examples of how evaluators reproduce neoliberal logic (e.g., in landscape analyses and collective impact assessments), which ultimately undermines transformative change. Evaluator reflexivity questions are proposed to incite change within the field and to help individual evaluators and evaluation teams unpack neoliberalism in their own practice. Evaluation education should include instruction on the effects of neoliberalism and how it shapes both programs and evaluation approaches. Future research should expand the body of knowledge of how neoliberalism has impacted the field of evaluation, support the development of an anti-capitalist praxis, and offer new opportunities for evaluation resistance.
HMGA2 as a Critical Regulator in Cancer Development
Authors: Mansoori Behzad , Mohammadi Ali , Ditzel Henrik J. , Duijf Pascal H. G. , Khaze Vahid , Gjerstorff Morten F. , Baradaran Behzad
Published: February 2021

The high mobility group protein 2 (HMGA2) regulates gene expression by binding to AT-rich regions of DNA. Akin to other DNA architectural proteins, HMGA2 is highly expressed in embryonic stem cells during embryogenesis, while its expression is more limited at later stages of development and in adulthood. Importantly, HMGA2 is re-expressed in nearly all human malignancies, where it promotes tumorigenesis by multiple mechanisms. HMGA2 increases cancer cell proliferation by promoting cell cycle entry and inhibition of apoptosis. In addition, HMGA2 influences different DNA repair mechanisms and promotes epithelial-to-mesenchymal transition by activating signaling via the MAPK/ERK, TGFβ/Smad, PI3K/AKT/mTOR, NFkB, and STAT3 pathways. Moreover, HMGA2 supports a cancer stem cell phenotype and renders cancer cells resistant to chemotherapeutic agents. In this review, we discuss these oncogenic roles of HMGA2 in different types of cancers and propose that HMGA2 may be used for cancer diagnostic, prognostic, and therapeutic purposes.
Identification of Phosphorylated Amino Acids in Human TNRC6A C-Terminal Region and Their Effects on the Interaction with the CCR4-NOT Complex
Authors: Munakata Fusako , Suzawa Masataka , Ui-Tei Kumiko
Published: February 2021

Human GW182 family proteins have Argonaute (AGO)-binding domains in their N-terminal regions and silencing domains, which interact with RNA silencing-related proteins, in their C-terminal regions. Thus, they function as scaffold proteins between the AGO protein and RNA silencing-related proteins, such as carbon catabolite repressor4-negative on TATA (CCR4-NOT) or poly(A)-binding protein (PABP). Our mass spectrometry analysis and the phosphorylation data registered in PhosphoSitePlus, a post-translational modification database, suggested that the C-terminal region of a human GW182 family protein, TNRC6A, has at least four possible phosphorylation sites, which are located near the region interacting with the CCR4-NOT complex. Among them, two serine residues at amino acid positions 1332 and 1346 (S1332 and S1346) were certainly phosphorylated in human HeLa cells, but other two serine residues (S1616 and S1691) were not phosphorylated. Furthermore, it was revealed that the phosphorylation patterns of TNRC6A affect the interaction with the CCR4-NOT complex. When S1332 and S1346 were dephosphorylated, the interactions of TNRC6A with the CCR4-NOT complex were enhanced, and when S1616 and S1691 were phosphorylated, such interaction was suppressed. Thus, phosphorylation of TNRC6A was considered to regulate the interaction with RNA silencing-related factors that may affect RNA silencing activity.
The First 40 Million Years of Planktonic Foraminifera
Authors: Gradstein Felix , Waskowska Anna , Glinskikh Larisa
Published: February 2021

We provide a biochronology of Jurassic planktonic foramininfera, using first order linkage to ammonite and nannofossil stratigraphy and geochronology. This enigmatic and understudied group of microfossils occurred from middle Toarcian through Tithonian time, from ~180 to ~143 Ma; its origin is unknown. There are three genera: Globuligerina, Conoglobigerina and Petaloglobigerina. The genus Globuligerina, with a smooth to pustulose test surface texture appeared in Toarcian (late Early Jurassic) and Conoglobigerina, with a rough reticulate test surface texture in Oxfordian (early Late Jurassic) time. The genus Petaloglobigerina, having a petaloid last whorl with one or more claviform and twisted chambers evolved in early Kimmeridgian time from Globuligerina balakhmatovae. Biochronologic events for Jurassic planktonic foraminifera are most like First Common Appearance or Last Common Appearance events. The very first or very last appearance levels of taxa are not easily sampled and detected. We recognize stratigraphic events from eleven species across four postulated evolutionary lineages, calibrated to Geologic Time Scale 2020. A faunal change, which is not well documented led to the survival of only one taxon, most likely Gobuligerina oxfordiana in the Tithonian.
Stability of Embankments Resting on Foundation Soils with a Weak Layer
Authors: Ziccarelli Maurizio , Rosone Marco
Published: February 2021

The presence of weak layers in geotechnical systems, including soil or rock masses, both natural and man-made, is more frequent than is normally believed. Weak layers can affect both failure mechanisms, in drained and in undrained conditions, as well as in static and seismic conditions, and the safety factor. In the present study, conducted numerically using the finite-element method (FEM) Plaxis 2D code, the influence of a horizontal thin weak layer on stress and strain distribution, on failure mechanisms and on the overall stability of an embankment was evaluated. The results obtained prove that when the weak layer is located at a significant depth from the foundation plane, the failure mechanisms are normally mixtilinear in shape because the shear strains largely develop on the weak layer. As a result, the safety factor highly decreases compared to the same case without a weak layer. Then, in the presence of weak layers, even embankments that, if founded on homogeneous soils, would have very high global safety factors (higher than 2) can become unstable, i.e., the safety factor can become unitary. So particular attention must be paid during detail ground investigations to finding thin weak layers.
Exploring the Potential of Emerging Technologies to Meet the Care and Support Needs of Older People: A Delphi Survey
Authors: Abdi Sarah , Witte Luc de , Hawley Mark
Published: February 2021

Some emerging technologies have potential to address older people’s care and support needs. However, there is still a gap in the knowledge on the potential uses of these technologies in some care domains. Therefore, a two-round Delphi survey was conducted to establish a consensus of opinion from a group of health and social technology experts (n = 21) on the potential of 10 emerging technologies to meet older people’s needs in five care and support domains. Experts were also asked to provide reasons for their choices in free-text spaces. The consensus level was set at 70%. Free-text responses were analyzed using thematic analysis. Voice activated devices was the technology that reached experts consensus in all assessed care domains. Some technologies (e.g., Artificial intelligence (AI) enabled apps and wearables and Internet of things (IoT) enabled homes) also show potential to support basic self-care and access to healthcare needs of older people. However, most of the remaining technologies (e.g., robotics, exoskeletons, virtual and augmented reality (VR/AR)) face a range of technical and acceptability issues that may hinder their adoption by older people in the near future. Findings should encourage the R & D community to address some of the identified challenges to improve the adoption of emerging technologies by older people.
Multistakeholder Participation in Disaster Management—The Case of the COVID-19 Pandemic
Authors: Panneer Sigamani , Kantamaneni Komali , Pushparaj Robert Ramesh Babu , Shekhar Sulochana , Bhat Lekha , Rice Louis
Published: February 2021

The coronavirus disease 2019 (COVID-19) pandemic is affecting society’s health, economy, environment and development. COVID-19 has claimed many lives across the globe and severely impacted the livelihood of a considerable section of the world’s population. We are still in the process of finding optimal and effective solutions to control the pandemic and minimise its negative impacts. In the process of developing effective strategies to combat COVID-19, different countries have adapted diverse policies, strategies and activities and yet there are no universal or comprehensive solutions to the problem. In this context, this paper brings out a conceptual model of multistakeholder participation governance as an effective model to fight against COVID-19. Accordingly, the current study conducted a scientific review by examining multi-stakeholder disaster response strategies, particularly in relation to COVID-19. The study then presents a conceptual framework for multistakeholder participation governance as one of the effective models to fight against COVID-19. Subsequently, the article offers strategies for rebuilding the economy and healthcare system through multi-stakeholder participation, and gives policy directions/decisions based on evidence to save lives and protect livelihoods. The current study also provides evidence about multidimensional approaches and multi-diplomatic mechanisms during the COVID-19 crisis, in order to examine dimensions of multi-stakeholder participation in disaster management and to document innovative, collaborative strategic directions across the globe. The current research findings highlight the need for global collaboration by working together to put an end to this pandemic situation through the application of a Multi-Stakeholder Spatial Decision Support System (MS-SDSS).
Analysis of Farmland Abandonment and Government Supervision Traps in China
Authors: Li Yemei , Shan Yanfei , Chen Ying
Published: February 2021

Farmland abandonment has become relatively common in rural China. In the context of food security, the Chinese government has introduced policies for farmland abandonment supervision, but the effect of these policies has proven to be marginal. By constructing an evolutionary game model, our research explores the evolutionary logic during the supervision of farmland abandonment by governments and rural households. The results indicate that low food yield and high opportunity costs are the leading causes of farmland abandonment. The probable punishment administered by the central government for dereliction is a major motivation for the local government to practice farmland abandonment supervision. The low supervision avoidance cost for rural households leads local governments and households to form collaborations to jointly cope with central government supervision. When this occurs, local governments’ supervision of farmland abandonment falls into a trap, as it leads to continued supervision practices that are costly and ineffective. Food security risk comes from the contradictory population and land resources demands. To improve food security while managing these contradictory demands, it is both necessary and feasible for the government to control population growth and focus on farmland protection, whereas it is unnecessary and unfeasible for the government to supervise whether or not farmland should be abandoned.
How Seasonality of Malnutrition Is Measured and Analyzed
Authors: Marshak Anastasia , Venkat Aishwarya , Young Helen , Naumova Elena N.
Published: February 2021

Seasonality is a critical source of vulnerability across most human activities and natural processes, including the underlying and immediate drivers of acute malnutrition. However, while there is general agreement that acute malnutrition is highly variable within and across years, the evidence base is limited, resulting in an overreliance on assumptions of seasonal peaks. We review the design and analysis of 24 studies exploring the seasonality of nutrition outcomes in Africa’s drylands, providing a summary of approaches and their advantages and disadvantages. Over half of the studies rely on two to four time points within the year and/or the inclusion of time as a categorical variable in the analysis. While such approaches simplify interpretation, they do not correspond to the climatic variability characteristic of drylands or the relationship between climatic variability and human activities. To better ground our understanding of the seasonality of acute malnutrition in a robust evidence base, we offer recommendations for study design and analysis, including drawing on participatory methods to identify community perceptions of seasonality, use of longitudinal data and panel analysis with approaches borrowed from the field of infectious diseases, and linking oscillations in nutrition data with climatic data.
A Family-Based Lifestyle Intervention Focusing on Fathers and Their Children Using Co-Creation: Study Protocol of the Run Daddy Run Intervention
Authors: Latomme Julie , Morgan Philip J. , De Craemer Marieke , Brondeel Ruben , Verloigne Maïté , Cardon Greet
Published: February 2021

Fathers play a unique and important role in shaping their children’s physical activity (PA), independent from the mother. Lifestyle interventions focusing simultaneously on PA of fathers and their children (“co-PA”) are therefore a novel and promising way to improve PA of both. A theory-based lifestyle intervention was co-created with fathers (i.e., the Run Daddy Run intervention), using the behavior change wheel as a theoretical framework. The aim of the present study is to describe the protocol of the Run Daddy Run intervention study, focusing on improving (co-)PA of fathers and children, and the prospected outcomes. The developed intervention consists of six (inter)active father-child sessions and an eHealth component, delivered over a 14-week intervention period. Baseline measurements will be conducted between November 2019–January 2020, post-test measurements in June 2020, and follow-up measurements in November 2020, with (co-)PA as the primary outcome variable. Outcomes will be measured using accelerometry and an online questionnaire. To evaluate the intervention, multilevel analyses will be conducted. This study will increase our understanding on whether a theory-based, co-created lifestyle intervention focusing exclusively on fathers and their children can improve their (co-)PA behavior and has important implications for future research and health policy, where targeting fathers might be a novel and effective approach to improve (co-)PA and associated health behaviors of both fathers and their children.
Mechanisms of Bone Impairment in Sickle Bone Disease
Authors: Giordano Paola , Urbano Flavia , Lassandro Giuseppe , Faienza Maria Felicia
Published: February 2021

Sickle bone disease (SBD) is a chronic and invalidating complication of Sickle cell disease (SCD), a multisystem autosomal recessive genetic disorder affecting millions of people worldwide. Mechanisms involved in SBD are not completely known, especially in pediatric age. Among the hypothesized pathogenetic mechanisms underlying SBD are bone marrow compensatory hyperplasia and bone ischemic damage, both secondary to vaso-occlusive crisis (VOC), which leads to cell sickling, thus worsening local hypoxia with a negative impact on osteoblast recruitment. Furthermore, the hypoxia is a strong activator of erythropoietin, which in turn stimulates osteoclast precursors and induces bone loss. Hemolysis and iron overload due to a chronic transfusion regimen could also contribute to the onset of bone complications. Vitamin D deficiency, which is frequently seen in SCD subjects, may worsen SBD by increasing the resorptive state that is responsible for low bone mineral density, acute/chronic bone pain, and high fracture risk. An imbalance between osteoblasts and osteoclasts, with a relative decrease of osteoblast recruitment and activity, is a further possible mechanism responsible for the impairment of bone health in SCD. Moreover, delayed pubertal growth spurt and low peak bone mass may explain the high incidence of fracture in SCD adolescents. The aim of this review was to focus on the pathogenesis of SBD, updating the studies on biochemical, instrumental, and biological markers of bone metabolism. We also evaluated the growth development and endocrine complications in subjects affected with SCD.
Prior Elicitation for Use in Clinical Trial Design and Analysis: A Literature Review
Authors: Azzolina Danila , Berchialla Paola , Gregori Dario , Baldi Ileana
Published: February 2021

Bayesian inference is increasingly popular in clinical trial design and analysis. The subjective knowledge derived from an expert elicitation procedure may be useful to define a prior probability distribution when no or limited data is available. This work aims to investigate the state-of-the-art Bayesian prior elicitation methods with a focus on clinical trial research. A literature search on the Current Index to Statistics (CIS), PubMed, and Web of Science (WOS) databases, considering “prior elicitation” as a search string, was run on 1 November 2020. Summary statistics and trend of publications over time were reported. Finally, a Latent Dirichlet Allocation (LDA) model was developed to recognise latent topics in the pertinent papers retrieved. A total of 460 documents pertinent to the Bayesian prior elicitation were identified. Of these, 213 (45.4%) were published in the “Probability and Statistics” area. A total of 42 articles pertain to clinical trial and the majority of them (81%) reports parametric techniques as elicitation method. The last decade has seen an increased interest in prior elicitation and the gap between theory and application getting narrower and narrower. Given the promising flexibility of non-parametric approaches to the experts’ elicitation, more efforts are needed to ensure their diffusion also in applied settings.