bluuebunny/crossref_metadata_2025 huggingface dataset:
The Feasibility of Differentiating Lewy Body Dementia and Alzheimer’s Disease by Deep Learning Using ECD SPECT Images
Authors: Ni Yu-Ching , Tseng Fan-Pin , Pai Ming-Chyi , Hsiao Ing-Tsung , Lin Kun-Ju , Lin Zhi-Kun , Lin Chia-Yu , Chiu Pai-Yi , Hung Guang-Uei , Chang Chiung-Chih , Chang Ya-Ting , Chuang Keh-Shih ,   Alzheimer’s Disease Neuroimaging Initiative
Published: November 2021

The correct differential diagnosis of dementia has an important impact on patient treatment and follow-up care strategies. Tc-99m-ECD SPECT imaging, which is low cost and accessible in general clinics, is used to identify the two common types of dementia, Alzheimer’s disease (AD) and Lewy body dementia (LBD). Two-stage transfer learning technology and reducing model complexity based on the ResNet-50 model were performed using the ImageNet data set and ADNI database. To improve training accuracy, the three-dimensional image was reorganized into three sets of two-dimensional images for data augmentation and ensemble learning, then the performance of various deep learning models for Tc-99m-ECD SPECT images to distinguish AD/normal cognition (NC), LBD/NC, and AD/LBD were investigated. In the AD/NC, LBD/NC, and AD/LBD tasks, the AUC values were around 0.94, 0.95, and 0.74, regardless of training models, with an accuracy of 90%, 87%, and 71%, and F1 scores of 89%, 86%, and 76% in the best cases. The use of transfer learning and a modified model resulted in better prediction results, increasing the accuracy by 32% for AD/NC. The proposed method is practical and could rapidly utilize a deep learning model to automatically extract image features based on a small number of SPECT brain perfusion images in general clinics to objectively distinguish AD and LBD.
New Evaluation Method for Bone Formation around a Fully Hydroxyapatite-Coated Stem Using Digital Tomosynthesis: A Retrospective Cross-Sectional Study
Authors: Totsuka Sho , Nishino Tomofumi , Watanabe Ryunosuke , Yamazaki Masashi , Mishima Hajime
Published: November 2021

Digital tomosynthesis (DTS) is a new imaging technique derived from radiography, and its usefulness has been gradually reported in the field of orthopedic diagnosis in recent years. A fully hydroxyapatite (HA)-coated stem, which is used for total hip arthroplasty (THA), is a type of cementless stem that has been widely used recently and reported to have good results. However, stem loosening on plain radiographs is difficult to determine in some cases due to cancellous condensation around the stem. In this retrospective cross-sectional study, we compared the results of plain radiography versus DTS to evaluate the imaging findings after THA using a fully HA-coated stem. Twenty joints each in the 3 y and 1 y postoperative groups underwent plain radiography and DTS. On DTS, bone formation around the stem was confirmed in all cases; however, this formation was not reproducible on plain radiography, and there were cases in which the reaction could not be confirmed or cases with cancellous condensation resembling reactive lines. This reaction was not reproducible on plain radiographs, and in some cases, the reaction could not be confirmed, or there were cases with cancellous condensation that resembled reactive lines. Therefore, DTS was useful in the diagnosis of bone formation around the implant.
Parker’s Solar Wind Model for a Polytropic Gas
Authors: Shivamoggi Bhimsen , Rollins David , Pohl Leos
Published: November 2021

Parker’s hydrodynamic isothermal solar wind model is extended to apply for a more realistic polytropic gas flow that can be caused by a variable extended heating of the corona. A compatible theoretical formulation is given and detailed numerical and systematic asymptotic theoretical considerations are presented. The polytropic conditions favor an enhanced conversion of thermal energy in the solar wind into kinetic energy of the outward flow and are hence shown to enhance the acceleration of the solar wind, thus indicating a quicker loss of the solar angular momentum.
The Impact of Isolation Measures during COVID-19 Pandemic on Russian Students’ Motivation for Learning
Authors: Drozdikova-Zaripova Albina R. , Valeeva Roza A. , Latypov Niyaz R.
Published: November 2021

One of the leading problems of teaching is maintaining the students’ motivation for learning. In the current epidemiological situation, improvement of education quality using digital platforms and educational services by creating conditions for increasing the learning motivation of students is an essential and relevant task. Therefore, the aim of the research was to study the motivation of the educational activity of junior students during the COVID-19 lockdown period and the development of effective approaches to increase the learning motivation of students in the context of distance learning using the Microsoft Teams platform. Research methods: Theoretical analysis of psychological and pedagogical literature, generalization; experiment, questioning, testing and data processing methods. In total, 107 undergraduates took part in the study. The difficulties and benefits that students encountered during the lockdown, as well as the attitude of students to the distance learning format, were revealed. There were specified dominant motivators, intentions and motives that determine the educational activity of students. We have presented approaches to the content management of the educational process in a distance format, with various ways and techniques of increasing the educational motivation of students under the conditions of distance learning.
The Anxiety Caused by Secondary Schools for Autistic Adolescents: In Their Own Words
Authors: Costley Debra , Emerson Anne , Ropar Danielle , Sheppard Elizabeth
Published: November 2021

Secondary schools are increasingly becoming inclusive of all students whatever their individual needs, but we question whether teachers understand enough about specific needs in order to effectively support all their students. Research indicates that autistic students often struggle with aspects of school (conformity; social communication; sensory challenges; bullying) but very few studies ask autistic adolescents about their experiences. One of the key elements of the school experience for autistic adolescents is the levels of anxiety experienced by many students on a daily basis. This research set out to explore the extent to which autistic students in secondary schools in the UK were able to recognise and reflect on their own anxiety. The eighteen participants in this co-produced qualitative study took part in semi-structured interviews planned by a team of autistic and non-autistic researchers. The themes that emerged from this study, in terms of triggers for anxiety, included other people’s behaviour, fear of the unknown, and sensory sensitivities. A theoretical view of their difficulties concurs with the concept of intolerance of uncertainty. Our data suggest that autistic students continue to experience high levels of anxiety throughout their secondary education, despite supports put in place by some schools. Strategies are highlighted that could be implemented by all schools to promote truly inclusive settings.
Application of Machine Learning in Electromagnetics: Mini-Review
Authors: Sagar Md. Samiul Islam , Ouassal Hassna , Omi Asif I. , Wisniewska Anna , Jalajamony Harikrishnan M. , Fernandez Renny E. , Sekhar Praveen K.
Published: November 2021

As an integral part of the electromagnetic system, antennas are becoming more advanced and versatile than ever before, thus making it necessary to adopt new techniques to enhance their performance. Machine Learning (ML), a branch of artificial intelligence, is a method of data analysis that automates analytical model building with minimal human intervention. The potential for ML to solve unpredictable and non-linear complex challenges is attracting researchers in the field of electromagnetics (EM), especially in antenna and antenna-based systems. Numerous antenna simulations, synthesis, and pattern recognition of radiations as well as non-linear inverse scattering-based object identifications are now leveraging ML techniques. Although the accuracy of ML algorithms depends on the availability of sufficient data and expert handling of the model and hyperparameters, it is gradually becoming the desired solution when researchers are aiming for a cost-effective solution without excessive time consumption. In this context, this paper aims to present an overview of machine learning, and its applications in Electromagnetics, including communication, radar, and sensing. It extensively discusses recent research progress in the development and use of intelligent algorithms for antenna design, synthesis and analysis, electromagnetic inverse scattering, synthetic aperture radar target recognition, and fault detection systems. It also provides limitations of this emerging field of study. The unique aspect of this work is that it surveys the state-of the art and recent advances in ML techniques as applied to EM.
An Optimum Structure of Scalable Capacitors in 3D Crosspoint Memory Technology
Authors: Tone Yuya , Tanzawa Toru
Published: November 2021

Memory chips need large capacitors in their periphery to drive boosted word-lines and bit-lines for read and write operations. In a previous work, scalable capacitors were proposed for 3D crosspoint memory to keep the area for the capacitors constant over technology generations. This paper proposes the capacitance models of three types of wiring capacitors: (1) vertical capacitor, (2) vertical and horizontal capacitor with next-neighbor wires connected with the other terminal, and (3) vertical and horizontal capacitor with next-neighbor pairs connected with the other terminal. These models are based on Wong’s crossover capacitor model to determine the capacitor structure with the highest capacitance density in 3D crosspoint memory technology. One can determine the best structure through optimizing the process parameters such as the height H of the insulation material between the metal wires and the thickness T of the metal wires and the design rules such as the width W and space S of metal wires. The model accuracy was in good agreement with the measurement of twelve types of capacitor structures fabricated in a 180 nm 6 metal standard CMOS process with the maximum error of 20%. Contour plots of the capacitance density across H vs. S where it is assumed that W = T = S are shown. As a result, the boundary condition regarding H and S is determined per 3D crosspoint memory technology with three, four, or five levels of wires.
An Improved Deep Convolutional Neural Network-Based Autonomous Road Inspection Scheme Using Unmanned Aerial Vehicles
Authors: Hassan Syed-Ali , Rahim Tariq , Shin Soo-Young
Published: November 2021

Recent advancements in the field of machine learning (ML) provide opportunity to conduct research on autonomous devices for a variety of applications. Intelligent decision-making is a critical task for self-driving systems. An attempt is made in this study to use a deep learning (DL) approach for the early detection of road cracks, potholes, and the yellow lane. The accuracy is not sufficient after training with the default model. To enhance accuracy, a convolutional neural network (CNN) model with 13 convolutional layers, a softmax layer as an output layer, and two fully connected layers (FCN) are constructed. In order to achieve the deeper propagation and to prevent saturation in the training phase, mish activation is employed in the first 12 layers with a rectified linear unit (ReLU) activation function. The upgraded CNN model performs better than the default CNN model in terms of accuracy. For the varied situation, a revised and enriched dataset for road cracks, potholes, and the yellow lane is created. The yellow lane is detected and tracked in order to move the unmanned aerial vehicle (UAV) autonomously by following yellow lane. After identifying a yellow lane, the UAV performs autonomous navigation while concurrently detecting road cracks and potholes using the robot operating system within the UAV. The performance model is benchmarked using performance measures, such as accuracy, sensitivity, F1-score, F2-score, and dice-coefficient, which demonstrate that the suggested technique produces better outcomes.
Design of Low-Profile Single- and Dual-Band Antennas for IoT Applications
Authors: Abdulkawi Wazie M. , Sheta Abdel Fattah A. , Elshafiey Ibrahim , Alkanhal Majeed A.
Published: November 2021

This paper presents novel low-cost single- and dual-band microstrip patch antennas. The proposed antennas are realized on a square microstrip patch etched symmetrically with four slots. The antenna is designed to have low cost and reduced size to use in Internet of things (IoT) applications. The antennas provide a reconfigurable architecture that allows operation in different wireless communication bands. The proposed structure can be adjusted to operate either in single band or in dual-band operation. Two prototypes are implemented and evaluated. The first structure works at a single resonance frequency (f1 = 2.4 GHz); however, the second configuration works at two resonance frequencies (f1 = 2.4 GHz and f2 = 2.8 GHz) within the same size. These antennas use a low-cost FR-4 dielectric substrate. The 2.4 GHz is allotted for the industrial, scientific, and medical (ISM) band, and the 2.8 GHz is allocated to verify the concept and can be adjusted to meet the user’s requirements. The measurement of the fabricated antennas closely matches the simulated results.
Application of Empirical Mode Decomposition and Extreme Learning Machine Algorithms on Prediction of the Surface Vibration Signal
Authors: Shen Yan , Wang Ping , Wang Xuesong , Sun Ke
Published: November 2021

Accurately predicting surface vibration signals of diesel engines is the key to evaluating the operation quality of diesel engines. Based on an improved empirical mode decomposition and extreme learning machine algorithm, the characteristics of diesel engine surface vibration signal were detected, predicted, and analyzed. First, the surface vibration signal was decomposed into a series of signal components by an improved empirical mode decomposition algorithm. Then, the extreme learning machine algorithm was applied to each signal component to obtain the predicted value of the corresponding signal component and determine the characteristics of the ground vibration signal. Compared with the empirical mode decomposition–extremum learning machine algorithm and the extremum learning machine algorithm, the results show that the improved empirical mode decomposition–extremum learning machine algorithm is feasible and effective.
3D CFD Simulation of Phase Resonance in a Pump Turbine with an Acoustic Model
Authors: Fang Yujian , Huang Ping , Jin Shibing , Liu Demin , Zhang Jinfeng , Yuan Shouqi
Published: November 2021

In order to understand the complex nature of the system dynamic phenomena, such as the strong vibration and noise caused by blade passage in the pump turbine, a state-of-the-art three-dimensional (3D) compressible transient simulation would be desirable to study the problem in depth. This study investigated the phase resonance (PR) that occurred during a full-load operation in the turbine mode of a pump turbine on a prototype scale. As a first step, the wave reflection at the boundaries, and the influence of the timestep and sound speeds on the behavior of traveling pressure waves inside a spiral casing, were studied. It was found that nonreflective boundary conditions and an appropriately small timestep are critical to capturing the wave reflection and superposition process inside a spiral casing; a certain kind of direct PR risk was detected in its system design. The detected direct PR differed from the well-known PR with two features: firstly, it was almost independent of the sound speeds, and secondly, the pressure distribution over the spiral circumference varied among the amplitudes. The latter feature was caused by pressure waves at every stator channel induced by a rotor stator interaction (RSI). The 3D flow simulation with an acoustic model, which couples the RSI and PR phenomena, would predict better results for understanding the problem than the simplified one-dimensional (1D) method.
Combustion Characterisation of Bituminous Coal and Pinus Sawdust Blends by Use of Thermo-Gravimetric Analysis
Authors: Marangwanda Garikai T. , Madyira Daniel M. , Ndungu Patrick G. , Chihobo Chido H.
Published: November 2021

The cocombustion of coal and pinus sawdust waste is an economically viable and sustainable option for increasing the share of biomass in energy production. This technology also has the potential to reduce the emission of greenhouse gases from existing coal fired power plants. The thermal synergistic effects of cocombusting Hwange bituminous coal (HC) with Pinus sawdust (PS) were thus investigated using thermogravimetric analysis. Fuel blending mass ratios of 100HC, 90HC10PS, 80HC20PS, 70HC30PS, and 100PS under an oxidative atmosphere at three different heating rates of 5, 12.5, and 20 °C/min were used for the experimental setup. Zero to negative synergy was generally observed for the mass loss curves (TG) at different blending ratios. Generally positive synergy was observed with relation to rate of mass loss curves (DTG) for the 80HC20PS and 70HC30PS fuel blends only. The ignition index increased with blending ratio by an average of 42.86%, whilst the burnout index showed a maximum increase of 14.6% at 20 °C/min. However, the combustion index representative of stability showed a decreasing trend generally for all the heating rates. No combustion index produced a linear variation with temperature, though upon evaluation, an optimum mass ratio of 20% pinus sawdust was suggested. The chosen optimum blending ratio demonstrated increased ignition and burnout indexes whilst maintaining the stability of combustion at a reasonable range.
Numerical Simulation via CFD Methods of Nitrogen Flooding in Carbonate Fractured-Vuggy Reservoirs
Authors: Li Kexing , Chen Bowen , Pu Wanfen , Wang Jianhai , Liu Yongliang , Varfolomeev Mikhail , Yuan Chengdong
Published: November 2021

A reservoir-scale numerical conceptual model was established according to the actual geological characteristics of a carbonate fractured-vuggy reservoir. Considering the difference in density and viscosity of fluids under reservoir conditions, CFD (computational fluid dynamic) porous medium model was applied to simulate the process of nitrogen displacement in a fractured-vuggy reservoir after water flooding. The effects of gas injection rate, injection mode, and injector–producer location relation were studied. The results show that nitrogen flooding can yield additional oil recovery of 7–15% after water flooding. Low-speed nitrogen injection is beneficial in obtaining higher oil recovery. High speed injection can expand the sweep area, but gas channeling occurs more easily. In gas–water mixed injection mode, there is fluid disturbance in the reservoir. The gas channeling is faster in low injector–high producer mode, while the high injector–low producer mode is beneficial for increasing the gas sweep range. Nevertheless, the increment of recovery is closely related to well pattern. After nitrogen flooding, there are still a lot of remaining oil distributed in the trap area of gas cap and bottom water in the reservoir that water and gas injection can’t sweep. The establishment of the numerical conceptual model compensates for the deficiency of physical simulation research, stating that only limited parameters can be simulated during experiments, and provides theoretical bases for nitrogen flooding in fractured-vuggy reservoir.
Domestic Gas Meter Durability in Hydrogen and Natural Gas Mixtures
Authors: Jaworski Jacek , Kułaga Paweł , Ficco Giorgio , Dell’Isola Marco
Published: November 2021

Blending hydrogen into the natural gas infrastructure is becoming a very promising practice to increase the exploitation of renewable energy sources which can be used to produce “green” hydrogen. Several research projects and field experiments are currently aimed at evaluating the risks associated with utilization of the gas blend in end-use devices such as the gas meters. In this paper, the authors present the results of experiments aimed at assessing the effect of hydrogen injection in terms of the durability of domestic gas meters. To this end, 105 gas meters of different measurement capabilities and manufacturers, both brand-new and withdrawn from service, were investigated in terms of accuracy drift after durability cycles of 5000 and 10,000 h with H2NG mixtures and H2 concentrations of 10% and 15%. The obtained results show that there is no metrologically significant or statistically significant influence of hydrogen content on changes in gas meter indication errors after subjecting the meters to durability testing with a maximum of 15% H2 content over 10,000 h. A metrologically significant influence of the long-term operation of the gas meters was confirmed, but it should not be made dependent on the hydrogen content in the gas. No safety problems related to the loss of external tightness were observed for either the new or 10-year-old gas meters.
Optimisation of the FE Model Based on the No-Load Test Measurement for Estimating Electromagnetic Parameters of an Induction Motor Equivalent Circuit Including the Rotor Deep-Bar Effect
Authors: Rolek Jaroslaw , Utrata Grzegorz
Published: November 2021

The various measurement procedures for determination of electromagnetic parameters for the induction motor (IM) equivalent circuits including the rotor deep-bar effect were proposed in the literature. One of them is the procedure based on the load curve test (LCT). Since the execution of the LCT can pose some difficulties, especially in industrial conditions, as an alternative, the finite element method (FEM) can be employed to simulate the IM operation under the LCT. In this work we developed the optimisation technique for the finite element (FE) model. This technique is performed with the use of the stator current space-vector components which determine the IM input active and reactive power consumption during no-load operation. Relying on the LCT simulation carried out with the optimised FE model the inductance frequency characteristic can be determined and then used as the reference characteristic in the electromagnetic parameter estimation for the IM equivalent circuit including the rotor deep-bar effect. The presented research results demonstrate proper conformity between the inductance frequency characteristics obtained from the LCT performed experimentally and determined by means of the optimised FE model. Satisfactory conformity is also achieved in the case of the torque-versus-slip frequency curves acquired from the measurement and calculated by the IM space-vector model with estimated electromagnetic parameters. All of this validates the effectiveness of the proposed technique for the FE-model optimisation and the usefulness of the presented approach using the FEM in the electromagnetic parameter estimation for the IM equivalent circuit including the rotor deep-bar effect.
Reducing the Dimensions of the Ship’s Main Switchboard—A Contribution to Energy Efficiency
Authors: Krčum Maja , Zubčić Marko , Kaštelan Nediljko , Gudelj Anita
Published: November 2021

Energy efficiency generally implies the efficient use of energy in all sectors of final consumption—industry, services, agriculture, households and transport. Shipping accounts for nearly 3% of global greenhouse gas emissions, making it the sixth largest CO2 producer in the world. This is a result of inefficient ship design, lack of planning and optimal use of resources. As the transport sector expands, so does the pressure for a greener and cleaner maritime industry. Reducing fuel consumption is a major driver of the need for energy efficiency on ships. In this paper, due to the importance of maritime transport, we observed the impact of reducing the dimensions of the main switchboard as a contribution to energy efficiency. This contribution is not of great importance as is the case with the optimization of the navigation route, etc., but it certainly affects the weight and, thus, the fuel consumption, which contributes to energy efficiency in the designed system. The aim of this paper is to optimize the design of the main switchboard by using 2D simulations of possible bus topologies, in order to develop six different busbar models and find one that best meets the requirements. The simulation results indicate the optimal location and dimensions of the busbars in the main switchboard in accordance with the switchgear parameters. Apart from the change in layout and dimensions of the busbars, the replacement of conventional instrument transformers with new current/voltage sensors contributes to a significant reduction in the weight and size of the switchboard, which ultimately benefits energy efficiency.
Dynamics and Numerical Simulation of Contaminant Diffusion for a Non-Flushing Ecological Toilet
Authors: Zhang Zhonghua , Zeng Lingjie , Shi Huixian , Yang Gukun , Yu Zhenjiang , Yin Wenjun , Gao Jun , Wang Lina , Zhang Yalei , Zhou Xuefei
Published: November 2021

The poor indoor air quality (IAQ) of severely polluted toilets is associated with increased risk of severe disease. This study aimed to evaluate the overall IAQ according to the contaminant removal efficiency, volume average concentration, and breathing zone control level. The characteristics of contaminant transmission in a non-flushing ecological toilet (NFET) were analyzed using the computational fluid dynamics (CFD) methodology, and the proposed model was further validated based on experimental measurements. Both an orthogonal experimental design and CFD were used to analyze factors such as exhaust fan position (EFP), air change rate per hour (ACH), natural vent location (NVL), and grid height (G-h). The EFP and ACH were demonstrated to be the dominant factors affecting the IAQ, whereas NVL and G-h were found to play key roles. Single-factor analysis based on the significance levels of the ACH, EFP, and NVL was conducted using the CFD methodology to define three exhaust behaviors—namely, “ineffective”, “enhanced”, and “excessive”. These results provide key insights that may be used to improve the IAQ of NFETs.
Review on the Importance of Gender Perspective in Household Energy-Saving Behavior and Energy Transition for Sustainability
Authors: Shrestha Bindu , Tiwari Sudarshan R. , Bajracharya Sushil B. , Keitsch Martina M. , Rijal Hom B.
Published: November 2021

Energy-saving and efficiency represent a crucial role in achieving a clean environment as well as economic and social development, providing substantial benefits to stakeholders, including householders. Better cost savings can be achieved by simply changing behavior. However, real energy users lack proper technical energy knowledge, awareness, and education in most cases. In most countries, women are involved in a higher percentage of energy activities in household chores but have less gender participation in energy decisions. In this regard, a gender perspective effectively understands energy users’ pragmatic and strategic needs for energy-saving behavior improvement. Previous literature reviews have been focusing on specific aspects of energy sustainability; however, no review has focused on energy-saving from a gender perspective to the best of our knowledge. It aims to provide a systematic review of literature on energy-saving and management, highlighting the importance of gender roles and fulfilling the literature’s study gaps that provide future possible research streams. The review finds that females use lower energy than males in household activities that has supported in household energy-saving behavior. In addition, gender, income, family composition, ownership, and education are significant influencing factors in energy-saving behavior, and gender differences are rooted in socialization, responsibility, and choice of energy appliances that have impacted energy decisions influencing energy-saving behavior and sustainability goals.
Biomass Estimation, Nutrient Content, and Decomposition Rate of Shoot Sheath in Moso Bamboo Forest of Yixing Forest Farm, China
Authors: Zheng Yaxiong , Guan Fengying , Fan Shaohui , Yan Xinrong , Huang Lanying
Published: November 2021

The biomass, nutrient content and decomposition rate of shoot sheaths remain unexplored in the study of Moso bamboo forests. The rapid growth of shoots means many bamboo sheaths are produced each year, and therefore should not be neglected in the study of the Moso bamboo ecosystem. In our study, we selected 160 bamboo shoots of different sizes in Yixing forest farm, Jiangsu Province. Our analysis was based on the allometric growth equation, using diameter at breast height (DBH), internode length of bamboo at breast height (IL), and bamboo height (H) as independent variables to establish the biomass model of shoot sheaths using all samples. In addition, we also measured the nutrient content of shoots and estimated the decomposition rate of shoots by setting up litter decomposition bags. Our results found that logarithmic regression should be used to fit the biomass model of shoot sheaths. From the perspective of practical application, model W3 fitting DBH and IL was determined. The order of the nutrient elements in the shoot sheath is C > N > K > P. Decomposition tests showed that it took 0.47 years for 50% of sheaths to decompose, and 3.15 years for all sheaths to decompose.
Deforestation and Biomass Production in Miombo Forest in Huambo (Angola): A Balance between Local and Global Needs
Authors: Miapia Luis M. , Ariza-Mateos David , Lacerda-Quartín Virgínia , Palacios-Rodríguez Guillermo
Published: November 2021

Miombo is one of the most widely distributed ecosystems in Angola, with a great social and environmental value. Thus, the rural population uses the biomass as fuel and miombo provides important ecosystem services, such as its carbon sequestration capacity. The objectives of this work were (i) to assess deforestation in miombo forest in Huambo province (Angola) during the last 20 years, (ii) to evaluate carbon storage capacity of miombo, and (iii) to calculate the charcoal productive capacity of those forests. From 2000 to 2019, 359,130 ha (12.96%) were deforested in Huambo province. Thirty-six woody species were identified as major components of miombo forest, the most frequent being Albizia anthunesiana, Brachystegia spiciformis, Julbernardia paniculata, Monote spp., Brachystegia boemii, Isoberlinea angolensis, Anisophyllea boehmii, Syzygium guineense, and Erythrophleum africanum. The total biomass estimated in miombo forest was 195.05 Mg ha−1 (55.02 Mg ha−1 radical and 140.04 Mg ha−1 area), with a total wood volume of 78.57 m3 ha−1. This represents values of 91.67 Mg ha−1 of accumulated carbon and 336.13 Mg ha−1 of CO2 equivalent. The potential charcoal productivity was 15,359.9 kg ha−1, corresponding to 24.78 trees ha−1. The Annual Allowable Cutting Volume was 10.77 m3 ha−1 year−1, 14.13 m3 ha−1 year−1, 21.17 m3 ha−1, and 32.85 m3 ha−1 year−1 for rotation lengths of 55, 40, 25, and 15 years, respectively, corresponding to a potential annual charcoal productivity of 2107.08 Kg ha−1 year−1, 2762.96 Kg ha−1 year−1, 4139.21 Kg ha−1, and 422.56 Kg ha−1 year−1. However, deforestation rates in the last 19 years and low charcoal productive capacity could compromise the sustainability of the Miombo ecosystem and its value as an ecosystem service provider in the province if appropriate management strategies are not developed.
Provenance Variation in Early Survival, Growth, and Carbon Isotope Discrimination of Southwestern Ponderosa Pine Growing in Three Common Gardens across an Elevational Gradient
Authors: Dixit Aalap , Kolb Thomas , Burney Owen , Mock Karen , Grady Kevin
Published: November 2021

We investigated early survival, growth, and carbon isotope discrimination of ponderosa pine (Pinus ponderosa Lawson & C. Lawson var. scopulorum Engelm.) seedlings from different provenances using common gardens across an elevational gradient in order to examine the potential for adaptation to extreme environments and constraints to artificial regeneration. Twenty-one provenances from a range of elevations across Arizona and New Mexico were planted in three common gardens: a high-elevation meadow in aspen-mixed conifer forest, a mid-elevation ponderosa pine forest, and a low-elevation pinyon juniper woodland. Two years after planting in 2018, survival was highest at the mid-elevation site (54%), low at the high-elevation site (1.5%), and 0% at the low-elevation site. At the hot and dry low-elevation site, provenances from low-elevations survived longer than provenances from mid- and high-elevations, which suggests greater drought tolerance of low-elevation provenances. Mortality agents changed from abiotic (drought) to biotic (herbivory) with an increase in elevation across sites. High mortality of seedlings planted at high-elevation sites from biotic agents, such as rodents, may challenge efforts to establish ponderosa pine in assisted migration projects. Seedlings had significantly higher growth rate and carbon isotope discrimination (∆13C) at the mid-elevation site than the high-elevation site. Provenances differed significantly in diameter, and ∆13C, but not in height growth rate for the first year after planting. Provenance variation in ∆13C suggests genetic variation in water use efficiency that may be useful for future evaluation of southwestern ponderosa pine seed sources for reforestation.
Magnetron Sputtering Construction of Nano-Al Metallized Wood and Its Functional Research
Authors: Wang Yanan , Jin Chengzhu , Wang Xinyi , Li Qiushuang , Li Wenxuan , Xu Qiang , Li Jingkui
Published: November 2021

The magnetron sputtering method was used to deposit nano-Al film on the wood surface of Pinus sylvestris L. var. mongholica Litv., and the material structure, electrical conductivity, mechanical properties and wetting properties were tested and characterized. When the sputtering time was 60 min, the average cross-grain sheet resistance of metallized wood was 695.9 mΩ, and the average along-grain sheet resistance was 227.2 mΩ. Load displacement decreased by more than 88%,elastic modulus increased by 49.2 times, hardness increased by 46 times andsurface hydrophobic angle was close to 130°. The grain size of the Al film on the wood surface was presented as nanoparticles, and the arrangement was uniform and dense. The results indicate that without any burden on the environment, the use of magnetron sputtering can quickly and efficiently achieve Al metallization on wood surfaces, so that the wood surface can obtain conductivity and hydrophobic properties. The elastic modulus and hardness of the wood surface were improved, the mechanical properties of the wood were effectively improved and the functional improvement of the wood was realized. This study provides a feasible method and basis for the study of the simple, efficient and pollution-free modification of wood.
Dissection of the Complex Transcription and Metabolism Regulation Networks Associated with Maize Resistance to Ustilago maydis
Authors: Ruan Xinsen , Ma Liang , Zhang Yingying , Wang Qing , Gao Xiquan
Published: November 2021

The biotrophic fungal pathogen Ustilago maydis causes common smut in maize, forming tumors on all aerial organs, especially on reproductive organs, leading to significant reduction in yield and quality defects. Resistance to U. maydis is thought to be a quantitative trait, likely controlled by many minor gene effects. However, the genes and the underlying complex mechanisms for maize resistance to U. maydis remain largely uncharacterized. Here, we conducted comparative transcriptome and metabolome study using a pair of maize lines with contrast resistance to U. maydis post-infection. WGCNA of transcriptome profiling reveals that defense response, photosynthesis, and cell cycle are critical processes in maize response to U. maydis, and metabolism regulation of glycolysis, amino acids, phenylpropanoid, and reactive oxygen species are closely correlated with defense response. Metabolomic analysis supported that phenylpropanoid and flavonoid biosynthesis was induced upon U. maydis infection, and an obviously higher content of shikimic acid, a key compound in glycolysis and aromatic amino acids biosynthesis pathways, was detected in resistant samples. Thus, we propose that complex gene co-expression and metabolism networks related to amino acids and ROS metabolism might contribute to the resistance to corn smut.
Defining the Geotourism Potential of the CILENTO, Vallo di Diano and Alburni UNESCO Global Geopark (Southern Italy)
Authors: Valente Ettore , Casaburi Annarita , Finizio Michele , Papaleo Lorenzo , Sorrentino Alessia , Santangelo Nicoletta
Published: November 2021

The interest of the scientific community about geotourism is abruptly increasing, as well as that on geoparks. According to UNESCO, geoparks should define management policies addressed to increasing the awareness of local people and tourists about Earth’s dynamics to reduce the impact of climate change and natural disasters. With this aim in mind, we tried to provide a solid scientific approach to geotourism that could be useful to the development of a geotourism strategy in the Cilento, Vallo di Diano and Alburni (CVDA) Geopark, in Southern Italy. Starting from the official inventory of the CVDA Geopark, we defined the potential Education Value (EV) and potential Touristic Value (TV) of each of the 160 sites listed by applying the Brilha method. Then we selected 20 geosites and geomorphosites with high values of both the EV and TV, and we included them in two geoitineraries. The two geoitineraries move in the inner sector of the Geopark (i.e., from the Paestum archaeological area to the Vallo di Diano basin) and along a portion of the coastal stretch (i.e., from Punta Telegrafo cape to the Lambro and Mingardo rivers’ mouths). Selected sites are representative of several geoscience disciplines (e.g., geomorphology, structural geology, quaternary geology, hydrogeology), thus suggesting that the CVDA Geopark is an ideal place where dissemination of geoscience concepts may be carried out. The latter point enhances the high geotourism potential of the area. This kind of approach was not tried before in the CVDA Geopark and can be a useful example of how to promote touristic development strategies in the area.
Seismic Constrained Gravity Inversion: A Reliable Tool to Improve Geophysical Models Away from Seismic Information
Authors: Sampietro Daniele , Capponi Martina
Published: November 2021

The exploitation of gravity fields in order to retrieve information about subsurface geological structures is sometimes considered a second rank method, in favour of other geophysical methods, such as seismic, able to provide a high resolution detailed picture of the main geological horizons. Within the current work we prove, through a realistic synthetic case study, that the gravity field, thanks to the availability of freely of charge high resolution global models and to the improvements in the gravity inversion methods, can represent a valid and cheap tool to complete and enhance geophysical modelling of the Earth’s crust. Three tests were carried out: In the first one a simple two-layer problem was considered, while in tests two and three we considered two more realistic scenarios in which the availability on the study area of constraints derived from 3D or 2D seismic surveys were simulated. In all the considered test cases, in which we try to simulate real-life scenarios, the gravity field, inverted by means of an advanced Bayesian technique, was able to obtain a final solution closer to the (simulated) real model than the assumed a priori information, typically halving the uncertainties in the geometries of the main geological horizons with respect to the initial model.
Universal Screening in Positive School Mental Health Using the ASEBA Methodology for Teachers: A Pilot Epidemiological Study
Authors: Cortés-Ramos Antonio , Landa-Blanco Miguel
Published: November 2021

School-based detection and intervention are critical components in ensuring positive mental health in children, with teachers playing an essential role in assessing students’ well-being. The current research aims to be a pilot epidemiological study on positive school mental health in Malaga, Spain, using the Achenbach System of Empirically Based Assessment (ASEBA). Data were collected in the COVID-19 pre-pandemic setting, using the Caregiver-Teacher Report Form (C-TRF) and the Teacher Report Form (TRF) in a sample of 420 children, who were between 5 and 8 years old at the time of the data collection. In 5-year-old children, the DSM-oriented scale with the highest clinical prevalence corresponds to attention deficit and hyperactivity problems (1.13%). In this same sub-sample, clinical levels of externalizing problems (4.52%) were non-significantly more common than internalizing conditions (1.69%). As for children between 6 and 8 years old, the DSM-oriented scale with the highest prevalence of clinical scores corresponds to anxiety problems (4.12%) and conduct problems (2.88%). Clinical levels of externalizing problems (9.47%) were non-significantly more prevalent than internalizing problems (6.58%). The results present 95% confidence intervals prevalence data in the general population and sex-differentiated descriptive statistics. The results are discussed according to their implication for school mental health.
The Role of Gender in Association between Emotional Intelligence and Self-Control among University Student-Athletes
Authors: Dumciene Audrone , Sipaviciene Saule
Published: November 2021

The purpose of this study was to reveal the peculiarities of undergraduate studies university student-athletes’ emotional intelligence and self-control indicators, and the role of gender as a predictor in the association between emotional intelligence and self-control. The study included students regularly involved in training at least three times a week. The sample consisted of 1395 student athletes from Lithuanian universities, among them 59.2% female and 40.8% male. For measurement, the SSRI inventory and a self-control scale were used. All values of emotional intelligence indicators were significantly higher for males than females. Estimates of the components of the self-control construct varied. The score for the healthy habits component was significantly higher for women than for men, the self-discipline component did not differ significantly, and the other three components were higher for males. Estimates of the components of the self-control construct varied. Models for predicting the values of self-control components were proposed. Only one component of the emotional intelligence construct, optimism, was repeated in all forecasting models, as well as gender. Other components of emotional intelligence vary in models.
Causes of Sickness Absenteeism in Europe—Analysis from an Intercountry and Gender Perspective
Authors: Antczak Elżbieta , Miszczyńska Katarzyna M.
Published: November 2021

This study aims to extract and explain the territorially varied relation between socioeconomic factors and absence rate from work due to own illness or disability in European countries in the years 2006–2020. For this purpose, several causes were identified, depending on men and women. To explain the absenteeism and emphasize gender as well as intercountry differences, geographically weighted regression was applied. For men, there were five main variables that influenced sickness absence: body mass index, the average rating of satisfaction by job situation, employment in the manufacturing sector, social benefits by sickness/health care, and performing health-enhancing physical activity. For women, there were five main variables that increased the absence rate: the risk of poverty or social exclusion, long-standing illness or health problems, employment in the manufacturing sector, social protection benefits, and deaths due to pneumonia. Based on the conducted research, it was proven that the sickness absence observed in the analyzed countries was highly gender and spatially diverged. Understanding the multifactorial factors playing an important role in the occurrence of regional and gender-divergent sickness absence may be a good predictor of subsequent morbidity and mortality as well as be very useful to better prevent this outcome.
Conducting In-Depth Interviews via Mobile Phone with Persons with Common Mental Disorders and Multimorbidity: The Challenges and Advantages as Experienced by Participants and Researchers
Authors: Azad Azadé , Sernbo Elisabet , Svärd Veronica , Holmlund Lisa , Björk Brämberg Elisabeth
Published: November 2021

Qualitative interviews are generally conducted in person. As the coronavirus pandemic (COVID-19) prevents in-person interviews, methodological studies which investigate the use of the telephone for persons with different illness experiences are needed. The aim was to explore experiences of the use of telephone during semi-structured research interviews, from the perspective of participants and researchers. Data were collected from mobile phone interviews with 32 individuals who had common mental disorders or multimorbidity which were analyzed thematically, as well as field notes reflecting researchers’ experiences. The findings reveal several advantages of conducting interviews using mobile phones: flexibility, balanced anonymity and power relations, as well as a positive effect on self-disclosure and emotional display (leading to less emotional work and social responsibility). Challenges included the loss of human encounter, intense listening, and worries about technology, as well as sounds or disturbances in the environment. However, the positive aspects of not seeing each other were regarded as more important. In addition, we present some strategies before, during, and after conducting telephone interviews. Telephone interviews can be a valuable first option for data collection, allowing more individuals to be given a fair opportunity to share their experiences.
Does the Construction of a Water Ecological Civilization City Improve Green Total Factor Productivity? Evidence from a Quasi-Natural Experiment in China
Authors: Fan Hongzhong , Tao Shuang , Hashmi Shujahat Haider
Published: November 2021

Taking Water Ecological City Pilot (WECP) policy as a quasi-natural experiment, this paper adopts the PSM-DID method to investigate the impact of the WECP policy on the green total factor productivity (GTFP) of China’s prefecture-level cities. The results show that the implementation of the WECP policy significantly inhibits the improvement of GTFP. Furthermore, we find the implementation of the WECP policy has squeezed out government technological expenditures to some extent and aggravated the compliance cost of enterprises, which has not caused the “innovation compensation effect”, thus failing to improve GTFP. The heterogeneity analyses show that the policy effects vary with the imbalance of China’s regional development and resource endowments. Developed regions can better overcome the possible negative impact that comes with policy implementation. Governments need to formulate different policy strategies and plans from an overall macro perspective.