bluuebunny/crossref_metadata_2025 huggingface dataset:
Arrhythmias in COVID-19/SARS-CoV-2 Pneumonia Infection: Prevalence and Implication for Outcomes
Authors: Denegri Andrea , Sola Matteo , Morelli Marianna , Farioli Francesco , Tosetti Alberto , D’Arienzo Matteo , Savorani Fulvio , Pezzuto Giuseppe , Boriani Giuseppe , Szarpak Lukasz , Magnani Giulia
Published: March 2022

Arrhythmias (ARs) are potential cardiovascular complication of COVID-19 but may also have a prognostic role. The aim of this study was to explore the prevalence and impact of cardiac ARs in hospitalized COVID-19 patients. All-comer patients admitted to the emergency department of Modena University Hospital from 16 March to 31 December 2020 and diagnosed with COVID-19 pneumonia infection were included in the study. The primary endpoint was 30-day mortality. Out of 902 patients, 637 (70.6%) presented a baseline 12-lead ECG registration; of these, 122 (19.2%) were diagnosed with ARs. Atrial fibrillation (AF, 40.2%) was the most frequent AR detected. The primary endpoint (30-day mortality) occurred in 33.6% (p < 0.001). AR-patients presented an almost 3-fold risk of mortality compared to non-AR-patients at 30d (Adj. OR = 2.8, 95%CI: 1.8–4.3, p < 0.001). After adjustment for significant baseline characteristics selected by a stepwise backward selection, AR-patients remained at increased risk of mortality (Adj. HR = 2.0, 95%CI: 1.9–2.3, p < 0.001). Sub-group analysis revealed that among ARs patients, those with AF at admission presented the highest risk of 30-day mortality (Adj. HR = 3.1, 95%CI: 2.0–4.9, p < 0.001). In conclusion, ARs are a quite common manifestation in COVID-19 patients, who are burdened by even worse prognosis. AR patients with AF presented the highest risk of mortality; thus, these patients may benefit from a more aggressive secondary preventive therapy and a closer follow up.
Distributed Authentication and Authorization Models in Cloud Computing Systems: A Literature Review
Authors: Mohammad Abdulghafour
Published: March 2022

As the functionality and services provided by cloud computing increase, control access to these services becomes more complex, and more security breaches are generated. This is mainly based on the emergence of new requirements and constraints in the open, dynamic, heterogeneous, and distributed cloud environment. Despite the importance of identifying these requirements for designing and evaluating access control models, the available studies do not provide a rigorous review of these requirements and the mechanisms that fulfill them. The purpose of this study was to conduct a literature review of the published articles that have dealt with cloud access control requirements and techniques. This paper allowed us to answer the following two research questions: What cloud access control security requirements have been presented in the published literature? What access control mechanisms are proposed to fulfill them? This review yielded 21 requirements and nine mechanisms, reported by 20 manuscripts. The identified requirements in this review will help researchers, academics and practitioners assess the effectiveness of cloud access control models and identify gaps that are not addressed in the proposed solutions. In addition, this review showed the current cloud access control mechanisms used to meet these requirements such as access control based on trust, risk, multi-tenant, and attribute encryption.
The Formulation of the Quadratic Failure Criterion for Transversely Isotropic Materials: Mathematical and Logical Considerations
Authors: Li Shuguang , Xu Mingming , Sitnikova Elena
Published: March 2022

The quadratic function of the original Tsai–Wu failure criterion for transversely isotropic materials is re-examined in this paper. According to analytic geometry, two of the troublesome coefficients associated with the interactive terms—one between in-plane direct stresses and one between transverse direct stresses—can be determined based on mathematical and logical considerations. The analysis of the nature of the quadratic failure function in the context of analytic geometry enhances the consistency of the failure criterion based on it. It also reveals useful physical relationships as intrinsic properties of the quadratic failure function. Two clear statements can be drawn as the outcomes of the present investigation. Firstly, to maintain its basic consistency, a failure criterion based on a single quadratic failure function can only accommodate five independent strength properties, viz. the tensile and compressive strengths in the directions along fibres and transverse to fibres, and the in-plane shear strength. Secondly, amongst the three transverse strengths—tensile, compressive and shear—only two are independent.
Optimising Crystallisation during Rapid Prototyping of Fe3O4-PA6 Polymer Nanocomposite Component
Authors: Gupta Ranjeetkumar , Njuguna James , Pancholi Ketan
Published: March 2022

Polymer components capable of self-healing can rapidly be manufactured by injecting the monomer (ε-caprolactam), activator and catalyst mixed with a small amount of magnetic nanoparticles into a steel mould. The anionic polymerisation of the monomer produces a polymer component capturing magnetic nanoparticles in a dispersed state. Any microcracks developed in this nanocomposite component can be healed by exposing it to an external alternating magnetic field. Due to the magnetocaloric effect, the nanoparticles locally melt the polymer in response to the magnetic field and fill the cracks, but the nanoparticles require establishing a network within the matrix of the polymer through effective dispersion for functional and uniform melting. The dispersed nanoparticles, however, affect the degree of crystallinity of the polymer depending on the radius of gyration of the polymer chain and the diameter of the magnetic nanoparticle agglomerates. The variation in the degree of crystallinity and crystallite size induced by nanoparticles can affect the melting temperature as well as its mechanical strength after testing for applications, such as stimuli-based self-healing. In the case of in situ synthesis of the polyamide-6 (PA6) magnetic nanocomposite (PMC), there is an opportunity to alter the degree of crystallinity and crystallite size by optimising the catalyst and activator concentration in the monomer. This optimisation method offers an opportunity to tune the crystallinity and, thus, the properties of PMC, which otherwise can be affected by the addition of nanoparticles. To study the effect of the concentration of the catalyst and activator on thermal properties, the degree of crystallinity and the crystallite size of the component (PMC), the ratio of activator and catalyst is varied during the anionic polymerisation of ε-caprolactam, but the concentration of Fe3O4 nanoparticles is kept constant at 1 wt%. Differential Scanning Calorimetry (DSC), Fourier-transform infrared spectroscopy (FTIR), XRD (X-ray diffraction) and Thermogravimetric analysis (TGA) were used to find the required concentration of the activator and catalyst for optimum properties. It was observed that the sample with 30% N-acetyl caprolactam (NACL) (with 50% EtMgBr) among all of the samples was most suitable to Rapid Prototype the PMC dog-bone sample with the desired degree of crystallinity and required formability.
Surface Properties of Ti6Al7Nb Alloy: Surface Free Energy and Bacteria Adhesion
Authors: Krzywicka Monika , Szymańska Jolanta , Tofil Szymon , Malm Anna , Grzegorczyk Agnieszka
Published: March 2022

The laser micro-machining was carried out on a station equipped with a TruMicro 5325c laser emitting ultraviolet radiation (343 nm wavelength) in picosecond pulses. On the surface of the Ti6Al7Nb alloy, dimple texturing with a constant diameter of ~200 μm, different depths (from ~5 to ~78 μm) and density (from 10% to 50%) were produced. The value of surface free energy was determined with the Owens–Wendt method using two measuring liquids: distilled water and diodomethane. The Staphylococcus epidermidis strain was used to test the adhesion of bacteria. It was found that the surface free energy value is influenced by both of the texture parameters (density, depth). The density also affects the potential for biofilm formation. Based on the analysis, it was shown that with an increase in surface free energy, the number of adhering microorganisms increases exponentially. Moreover, the study shows that there is a correlation between the number of adhering microorganisms and surface free energy.
Utilizing the Metaverse for Learner-Centered Constructivist Education in the Post-Pandemic Era: An Analysis of Elementary School Students
Authors: Suh Woong , Ahn Seongjin
Published: March 2022

Due to COVID-19, numerous new technologies are being implemented in education, with a growing interest in the metaverse. The term “metaverse” refers to an immersive digital environment where one can interact with virtual avatars. This study aims to analyze the experiences and attitudes of the metaverse for learner-centered education from a constructivist perspective to determine how closely related this virtual environment is to the lives of elementary school students. This study also examined how students are becoming the focal point of new educational technologies. After reviewing the literature on this topic, a survey of 336 elementary school students in Korea was conducted using 18 items for measuring each factor in the metaverse, followed by statistical analyses that included a difference of means and an independent sample t-test. The results revealed that, on average, 97.9% of elementary school students had experiences with the metaverse, with 95.5% of them considering it closely related to their everyday life. In addition, various conclusions according to each metaverse factor and each participant’s gender are provided.
Effects of Land Use/Land Cover Changes on Carbon Storage in North African Coastal Wetlands
Authors: Aitali Rajaa , Snoussi Maria , Kolker Alexander S. , Oujidi Bouchra , Mhammdi Nadia
Published: March 2022

Healthy wetlands are among the most effective sinks for carbon on the planet, and thus contribute to mitigate climate change. However, in North Africa, coastal wetlands are under high pressure especially from urban sprawl and tourism development, due to the rapid population growth and migration. This paper analyzed the effects of land use/land cover changes on carbon stocks, over 20 years, in six North African coastal wetlands, and estimated the economic value of the carbon sequestered during the considered period. The methodology used combined remote sensing and modeling. The results showed that among the six studied sites, only two (Moulouya and Moulay Bouselham) showed an increase in stored carbon and therefore are potential carbon sinks. In turn, the other four showed a more or less significant loss of carbon, which will likely be released into the atmosphere. The underlying processes that drive changes in carbon dynamics are mainly urban expansion and land use conversion, which often occurs at the expense of the natural habitats surrounding the wetlands. Understanding these processes can provide valuable decision-making information for land use planning, wetlands conservation and carbon reduction policies.
A Model for Translation and Rotation Resistance Tensors for Superellipsoidal Particles in Stokes Flow
Authors: Štrakl Mitja , Hriberšek Matjaž , Wedel Jana , Steinmann Paul , Ravnik Jure
Published: March 2022

In this paper, forces and torques on solid, non-spherical, orthotropic particles in Stokes flow are investigated by using a numerical approach on the basis of the Boundary Element Method. Different flow patterns around a particle are considered, taking into account the contributions of uniform, rotational and shear flows, to the force and the torque exerted on the particle. The expressions for the force and the toque are proposed, by introducing translation, rotation and deformation resistance tensors, which capture each of the flow patterns individually. A parametric study is conducted, considering a wide range of non-spherical particles, determined by the parametric superellipsoid surface equation. Using the results of the parametric study, an approximation scheme is derived on the basis of a multivariate polynomial expression. A coefficient matrix for the polynomial model is introduced, which is used as a tunable parameter for a minimization problem, whereby the polynomials are fitted to the data. The developed model is then put to the test by considering a few examples of particles with different shapes, while also being compared to other, currently available solutions. On top of that, the full functionality of the model is demonstrated by considering an example of a pollen grain, as a realistic non-spherical particle. First, a superellipsoid, which best fits the actual particle shape, is found from the considered range. After that, the coefficients of the translation, rotation and deformation resistance tensors are obtained from the present model and compared to the results of other available models. In the conclusion, a superior accuracy of the present model, for the considered range of particles, is established. To the best of the authors knowledge, this is also one of the first models to extend the torque prediction capabilities beyond sphere and prolate particles. At the same time, the model was demonstrated to be simple to implement and very conservative with the computational resources. As such, it is suitable for large scale studies of dispersed two-phase flows, with a large number of particles.
Coupled Wave Energy Converter and Nearshore Wave Propagation Models for Coastal Impact Assessments
Authors: Flanagan Timma , Wengrove Meagan , Robertson Bryson
Published: March 2022

Future nearshore wave energy converter (WEC) arrays will influence coastal wave and sediment dynamics, yet there are limited numerical methodologies to quantify their possible impacts. A novel coupled WEC-Wave numerical method was developed to quantify these possible influences on the nearshore coastal wave climate. The power performance of an Oscillating Surge Wave Energy Converter (OSWEC) array was simulated to quantify the wave energy dissipation due to the array. The OSWEC’s effect on the local wave climate was quantified by a novel coupling of two numerical models, WEC–Sim and XBeach. WEC–Sim characterizes the power extraction and wave energy transmission across the OSWEC, while XBeach captures the change in wave dynamics due to the WEC and propagates the waves to shore. This novel methodology provides the ability to directly quantify the impact of the effect of a WEC array on the local wave climate. Three case studies were analyzed to quantify the impact of a single WEC on breaking conditions and to quantify the impact of number of WECs and the array spacing on the local nearshore wave climate. Results indicate that when the WEC is placed 1100 m offshore, one WEC will cause a 1% reduction in wave height at the break point (Hsbp). As the WEC is placed further offshore, the change in Hsbp will become even smaller. Although the change in wave height from one WEC is small, WEC arrays magnify the cross–shore extent, area of influence and the magnitude of influence based on the spacing and number of WECs. For arrays with 10 or 15 WECs, the cross–shore extent was on average 200–300 m longer when the WECs were placed one to two WEC widths apart, compared with being spaced three or four widths apart. When the spacing was one WEC width apart (18 m), there was a 30% greater spatial impact on the nearshore region than arrays spaced three or four widths apart. The trend for the average transmission coefficient is within 5% for a 5, 10 or 15 WEC array, with a cumulative average of 78% transmission across all conditions.
Experimental Study of a Gurney Flap on a Pitching Wind Turbine Airfoil under Turbulent Flow Conditions
Authors: Yang Junwei , Yang Hua , Wang Xiangjun , Li Nailu
Published: March 2022

The present work aimed to investigate the aerodynamic characteristics of a pitching wind turbine airfoil with a Gurney flap under turbulent inflow. Experiments were carried out for the DTU-LN221 offshore wind turbine airfoil under different turbulence levels at Reynolds number 105 order of magnitude by replacing the grilles in the wind tunnel. The dynamic stall characteristics were analyzed by measuring surface pressure and near-wake flow field. The pressure results demonstrated that with the increase of turbulence intensity, the differences in lift hysteresis loops between baseline airfoil and flapped airfoil became smaller. With the turbulence intensity from 0.5% to 10.18%, the maximum lift increment of the Gurney flap decreased from 14.32% to 4.34% (i.e., 0–20° pitching oscillation). In a more extensive range of oscillation, the capability for the lift-improvement dropped down a bit more (i.e., 0–25°). A brief aerodynamic damping analysis indicated that the Gurney flap was more stable in turbulent conditions than the baseline airfoil. Besides, hysteresis loops of the wake were analyzed to compare the difference between the flapped airfoil and the baseline airfoil. Unlike the studies of static airfoils, the results may help better understand the dynamic characteristics of offshore wind turbines with Gurney flaps for practical situations.
Evaluating eDNA for Use within Marine Environmental Impact Assessments
Authors: Hinz Shawn , Coston-Guarini Jennifer , Marnane Michael , Guarini Jean-Marc
Published: March 2022

In this review, the use of environmental DNA (eDNA) within Environmental Impact Assessment (EIA) is evaluated. EIA documents provide information required by regulators to evaluate the potential impact of a development project. Currently eDNA is being incorporated into biodiversity assessments as a complementary method for detecting rare, endangered or invasive species. However, questions have been raised regarding the maturity of the field and the suitability of eDNA information as evidence for EIA. Several key issues are identified for eDNA information within a generic EIA framework for marine environments. First, it is challenging to define the sampling unit and optimal sampling strategy for eDNA with respect to the project area and potential impact receptor. Second, eDNA assay validation protocols are preliminary at this time. Third, there are statistical issues around the probability of obtaining both false positives (identification of taxa that are not present) and false negatives (non-detection of taxa that are present) in results. At a minimum, an EIA must quantify the uncertainty in presence/absence estimates by combining series of Bernoulli trials with ad hoc occupancy models. Finally, the fate and transport of DNA fragments is largely unknown in environmental systems. Shedding dynamics, biogeochemical and physical processes that influence DNA fragments must be better understood to be able to link an eDNA signal with the receptor’s state. The biggest challenge is that eDNA is a proxy for the receptor and not a direct measure of presence. Nonetheless, as more actors enter the field, technological solutions are likely to emerge for these issues. Environmental DNA already shows great promise for baseline descriptions of the presence of species surrounding a project and can aid in the identification of potential receptors for EIA monitoring using other methods.
Object Detection and Classification Based on YOLO-V5 with Improved Maritime Dataset
Authors: Kim Jun-Hwa , Kim Namho , Park Yong Woon , Won Chee Sun
Published: March 2022

SMD (Singapore Maritime Dataset) is a public dataset with annotated videos, and it is almost unique in the training of deep neural networks (DNN) for the recognition of maritime objects. However, there are noisy labels and imprecisely located bounding boxes in the ground truth of the SMD. In this paper, for the benchmark of DNN algorithms, we correct the annotations of the SMD dataset and present an improved version, which we coined SMD-Plus. We also propose augmentation techniques designed especially for the SMD-Plus. More specifically, an online transformation of training images via Copy & Paste is applied to solve the class-imbalance problem in the training dataset. Furthermore, the mix-up technique is adopted in addition to the basic augmentation techniques for YOLO-V5. Experimental results show that the detection and classification performance of the modified YOLO-V5 with the SMD-Plus has improved in comparison to the original YOLO-V5. The ground truth of the SMD-Plus and our experimental results are available for download.
Fanconi Anemia Pathway in Colorectal Cancer: A Novel Opportunity for Diagnosis, Prognosis and Therapy
Authors: Parsa Fatemeh Ghorbani , Nobili Stefania , Karimpour Mina , Aghdaei Hamid Asadzadeh , Nazemalhosseini-Mojarad Ehsan , Mini Enrico
Published: March 2022

Colorectal cancer (CRC) is the third most commonly diagnosed malignancy and has the second highest mortality rate globally. Thanks to the advent of next-generation sequencing technologies, several novel candidate genes have been proposed for CRC susceptibility. Germline biallelic mutations in one or more of the 22 currently recognized Fanconi anemia (FA) genes have been associated with Fanconi anemia disease, while germline monoallelic mutations, somatic mutations, or the promoter hypermethylation of some FANC genes increases the risk of cancer development, including CRC. The FA pathway is a substantial part of the DNA damage response system that participates in the repair of DNA inter-strand crosslinks through homologous recombination (HR) and protects genome stability via replication fork stabilization, respectively. Recent studies revealed associations between FA gene/protein tumor expression levels (i.e., FANC genes) and CRC progression and drug resistance. Moreover, the FA pathway represents a potential target in the CRC treatment. In fact, FANC gene characteristics may contribute to chemosensitize tumor cells to DNA crosslinking agents such as oxaliplatin and cisplatin besides exploiting the synthetic lethal approach for selective targeting of tumor cells. Hence, this review summarizes the current knowledge on the function of the FA pathway in DNA repair and genomic integrity with a focus on the FANC genes as potential predisposition factors to CRC. We then introduce recent literature that highlights the importance of FANC genes in CRC as promising prognostic and predictive biomarkers for disease management and treatment. Finally, we represent a brief overview of the current knowledge around the FANC genes as synthetic lethal therapeutic targets for precision cancer medicine.
An Entropy Approach to Multiple Sclerosis Identification
Authors: Alfonso Perez Gerardo Alfonso , Caballero Villarraso Javier Caballero
Published: March 2022

Multiple sclerosis (MS) is a relatively common neurodegenerative illness that frequently causes a large level of disability in patients. While its cause is not fully understood, it is likely due to a combination of genetic and environmental factors. Diagnosis of multiple sclerosis through a simple clinical examination might be challenging as the evolution of the illness varies significantly from patient to patient, with some patients experiencing long periods of remission. In this regard, having a quick and inexpensive tool to help identify the illness, such as DNA CpG (cytosine-phosphate-guanine) methylation, might be useful. In this paper, a technique is presented, based on the concept of Shannon Entropy, to select CpGs as inputs for non-linear classification algorithms. It will be shown that this approach generates accurate classifications that are a statistically significant improvement over using all the data available or randomly selecting the same number of CpGs. The analysis controlled for factors such as age, gender and smoking status of the patient. This approach managed to reduce the number of CpGs used while at the same time significantly increasing the accuracy.
4-Hydroxyphenyllactic Acid in Cerebrospinal Fluid as a Possible Marker of Post-Neurosurgical Meningitis: Retrospective Study
Authors: Pautova Alisa K. , Meglei Anastasiia Yu. , Chernevskaya Ekaterina A. , Alexandrova Irina A. , Beloborodova Natalia V.
Published: March 2022

The search for new potential biomarkers for the diagnostics of post-neurosurgical bacterial meningitis is required because of the difficulties in its early verification using results of the routine laboratory and biochemical analyses of the cerebrospinal fluid (CSF). The goal of the study was to determine the contents of the aromatic metabolites and biomarkers in the CSF samples of the post-neurosurgical patients (n = 82) and their potential diagnostical significance for the evaluation of the risk of post-neurosurgical meningitis. Patients with signs of post-neurosurgical meningitis (n = 30) had lower median values of glucose and higher values of cell count, neutrophils, lactate, protein, 3-(4-hydroxyphenyl)lactic acid (p-HPhLA), and interleukin-6 (IL-6) than patients without signs of post-neurosurgical meningitis (n = 52). ROC analysis for IL-6 and p-HPhLA resulted in 0.785 and 0.734 values of the area under the ROC curve, with sensitivity 96.30 and 66.67%; specificity 54.17 and 82.69%, respectively. IL-6 should be considered as a non-specific biomarker, in contrast to the microbial metabolite p-HPhLA. If the concentration of p-HPhLA was more or equal to 0.9 µmol/L, the risk of bacterial complications was 9.6 times higher. p-HPhLA is a promising marker for the prognosis of post-neurosurgical meningitis, and its determination on a larger group of post-neurosurgical patients can subsequently prove its diagnostic significance for the verification of CNS infections.
Genetic and Phenotypic Spectrum of KBG Syndrome: A Report of 13 New Chinese Cases and a Review of the Literature
Authors: Gao Fenqi , Zhao Xiu , Cao Bingyan , Fan Xin , Li Xiaoqiao , Li Lele , Sui Shengbin , Su Zhe , Gong Chunxiu
Published: March 2022

KBG syndrome (KBGS) is a rare autosomal dominant inherited disease that involves multiple systems and is associated with variations in the ankyrin repeat domain 11 (ANKRD11) gene. We report the clinical and genetic data for 13 Chinese KBGS patients diagnosed by genetic testing and retrospectively analyse the genotypes and phenotypes of previously reported KBGS patients. The 13 patients in this study had heterozygous variations in the ANKRD11 gene, including seven frameshift variations, three nonsense variations, and three missense variations. They carried 11 variation sites, of which eight were previously unreported. The clinical phenotype analysis of these 13 patients and 240 previously reported patients showed that the occurrence rates of craniofacial anomalies, dental anomalies, global developmental delays, intellectual disability/learning difficulties, limb anomalies, and behavioural anomalies were >70%. The occurrence rates of short stature, delayed bone age, and spinal vertebral body anomalies were >50%. The frequency of global developmental delays and intellectual disability/learning difficulties in patients with truncated ANKRD11 gene variation was higher than that in patients with missense variation in the ANKRD11 gene (p < 0.05). Collectively, this study reported the genotypic and phenotypic characteristics of the largest sample of KBGS patients from China and discovered eight new ANKRD11 gene variations, which enriched the variation spectrum of the ANKRD11 gene. Variation in the ANKRD11 gene mainly caused craniofacial anomalies, growth and developmental anomalies, skeletal system anomalies, and nervous system anomalies. Truncated variation in the ANKRD11 gene is more likely to lead to global growth retardation and intellectual disability/learning difficulties than missense variation in ANKRD11.
Financial Institution Type and Firm-Related Attributes as Determinants of Loan Amounts
Authors: Mallinguh Edmund , Zoltan Zeman
Published: March 2022

Access to formal credit remains critical for business operations, particularly for firms unable to generate sufficient funds internally. Using the World Bank’s Enterprise Survey dataset, 2018, we analyzed 230 Kenyan firms that applied for loans. These loans are sourced from banks (private, commercial, or state-owned) or non-banking financial institutions. Specifically, the paper explores the effect of financial institution type and firm-related characteristics on loan amounts advanced. The results show that the preferred credit provider matters, with the sensitivity level varying among the three institutional types. Additionally, the collateralization value, the owner’s equity proportion of fixed assets, and any existing credit facility correlate positively with the outcome variable. There is an inverse relationship between the largest shareholder’s ownership and the loan amount. The study uses the new product (service) launches to measure innovation. The findings suggest that firms in the innovation process access higher loan amounts than their non-innovative peers. Be that as it may, the difference in amount effect size between the two groups is small based on Cohen’s d rule. The paper highlights the theoretical and practical implications of these findings.
Housing Real Estate Economics and Finance
Authors: Li Rita Yi Man
Published: March 2022

Housing research is one of the hot topics in many countries. This paper provides a quick review of the housing economics research in the US, Sweden, Latvia, China, Corsica, and Italy published in this special issue. Bao and Shah studied the effects of home-sharing platforms in general and the effects of the US’ Airbnb on neighbourhood rent. Wilhelmsson’s results showed that interest rates directly affected house prices and indirectly affected bank loans in Sweden. Caudill and Mixon threw light on the relative negotiating power of the buyer and seller as a key element of real estate price models. Čirjevskis presented a real application of “step-by-step” valuation options for real estate development projects as a managerial risk management tool for similar real estate development projects in the EU to make investment decisions during COVID-19 and in the post-COVID-19 era. Pelizza and Schenk-Hoppé used an exponential Ornstein–Uhlenbeck process to model price dynamics provincially and regionally to estimate the liquidation value.
The Effect of Financial Inclusion and Competitiveness on Financial Stability: Why Financial Regulation Matters in Developing Countries?
Authors: Jungo João , Madaleno Mara , Botelho Anabela
Published: March 2022

This study aims to assess the effect of financial inclusion and competitiveness on banks’ financial stability, considering the moderating role of financial regulation. To do so, we compare the effects of these variables in Sub-Saharan African (SSA) and Latin American and Caribbean (LAC) countries. Our results suggest that inclusion enhances bank stability in SSA and LAC countries, and financial regulation contributes to increasing financial stability in LAC countries, while we find no statistical significance in the effect of financial regulation on financial stability in SSA countries. Moreover, competitiveness negatively impacts financial stability, and financial regulation moderates the negative effect of competitiveness on financial stability in SSA and LAC countries. We also find that financial inclusion reduces credit risk in SSA countries, and for LAC countries financial inclusion increases credit risk and reduces bank profitability. Regarding the practical implications, this study shows that fostering financial inclusion in the countries under study contributes significantly to improving the welfare of households and especially to the stability of the financial system. The present study allows expanding of the scarce literature by examining the effect of financial inclusion and market structure on financial stability in two different samples, consisting of 41 countries in the SSA region and 31 countries in the LAC region, throughout 2005–2018.
The Impact of the U.S. Macroeconomic Variables on the CBOE VIX Index
Authors: Prasad Akhilesh , Bakhshi Priti , Seetharaman Arumugam
Published: March 2022

The purpose of this study is to find the influence of various macroeconomic factors on the volatility index, as macroeconomic factors affect stock market volatility, resulting in an impact on the VIX Index, representing the risk in the stock market. To estimate the significance and importance of the U.S. macroeconomic variables on stock market volatility and risk, classification problems from machine learning are constructed to predict the daily and weekly trends of the VIX Index. Data from May 2007 to December 2021 is considered for analysis. The selected models are trained with twenty-four daily features and twenty-four plus nine weekly features. The outcomes suggest that the decisions made by the Light GBM and XG Boost on ranking features can be significantly accepted over logistic regression. It is found from the results that economic policy uncertainty indices, gold price, the USD Index, and crude oil are signified as strong predictors. The Financial Stress Index, initial claims, M2, TED spread, Fed rate, and credit spread are also strong predictors, while various yields on fixed income securities make a little less impact on the VIX Index. The TED spread, Financial Stress Index, and Equity Market Volatility (Infectious Disease Tracker) are positively associated with the VIX.
Spatio-Temporal Patterns of the Land Carrying Capacity of Tibet Based on Grain Demand and Calorie Requirement
Authors: Zhang Chao , Yang Yanzhao , Xiao Chiwei , You Zhen , Song Xinzhe
Published: March 2022

Tibet constitutes a major part of the Qinghai–Tibet Plateau (QTP) and is a typical ethnic minority (e.g., Tibetan) and ecologically fragile area in the world. Land resources are one of the most important foundations of food production, and Tibet’s increasingly multi-type food demands are putting new pressure on land resources. However, there is still debate on how many people can be supported with the food production in Tibet. Investigating the land carrying capacity (LCC) in Tibet is very important for maintaining food security and formulating sustainable land management and utilization. Based on an analysis of the unique characteristics of the local farming, pastoral production, and dietary consumption, the spatio-temporal patterns of theLCC in Tibet in 2000–2019 were quantitatively assessed against the grain demands and calorie requirements at three different standards of living (i.e., basic prosperity, comprehensive moderate prosperity, and affluence). The dietary consumption was characterized by the high consumption of grains and meat products, and the low consumption of fruits and vegetables. The LCC in Tibet has continued to increase. The LCC in approximately 60% of the counties increased, with the high-LCC counties concentrated mainly in the Yarlung Zangbo River—Nyangqu River—Lhasa River area, and municipal districts and pastoral counties generally experiencing a low LCC. The load on land resources (LoL) in Tibet exhibited the characteristic of overall balance with local overloads and increasing tensions. More than 50% of the counties experienced population overload, mainly in municipal districts and pastoral counties. Food surplus was mainly found in farming counties, while the food production in pastoral counties was generally unable to meet the calorie demand. Considering the important role of land use in maintaining regional food security and ecological security, the conversion of grassland to cultivated land, the occupation of cultivated land, and the phenomenon of cultivated land was used to non grain should be avoided. Trans-regional transport of food should be strengthened to meet the calorie needs in population overload areas in the future. Our study provides a perspective for evaluating the pressure of land resources. The result can provide a reference for realizing the balance of grain and calorie supply–demand and lay a foundation for formulating sustainable land use policies in the QPT.
Prediction of Soil Organic Carbon at Field Scale by Regression Kriging and Multivariate Adaptive Regression Splines Using Geophysical Covariates
Authors: De Benedetto Daniela , Barca Emanuele , Castellini Mirko , Popolizio Stefano , Lacolla Giovanni , Stellacci Anna Maria
Published: March 2022

Knowledge of the spatial distribution of soil organic carbon (SOC) is of crucial importance for improving crop productivity and assessing the effect of agronomic management strategies on crop response and soil quality. Incorporating secondary variables correlated to SOC allows using information often available at finer spatial resolution, such as proximal and remote sensing data, and improving prediction accuracy. In this study, two nonstationary interpolation methods were used to predict SOC, namely, regression kriging (RK) and multivariate adaptive regression splines (MARS), using as secondary variables electromagnetic induction (EMI) and ground-penetrating radar (GPR) data. Two GPR covariates, representing two soil layers at different depths, and X geographical coordinates were selected by both methods with similar variable importance. Unlike the linear model of RK, the MARS model also selected one EMI covariate. This result can be attributed to the intrinsic capability of MARS to intercept the interactions among variables and highlight nonlinear features underlying the data. The results indicated a larger contribution of GPR than of EMI data due to the different resolution of EMI from that of GPR. Thus, MARS coupled with geophysical data is recommended for prediction of SOC, pointing out the need to improve soil management to guarantee agricultural land sustainability.
Variations of Soil Physico-Chemical and Biological Features after Logging Using Two Different Ground-Based Extraction Methods in a Beech High Forest—A Case Study
Authors: Venanzi Rachele , Latterini Francesco , Stefanoni Walter , Tocci Damiano , Picchio Rodolfo
Published: March 2022

Considering that forests are crucial in the ecosystem of our planet and that forests provide timber products as well as several ecosystem services, it is evident that the application of sustainable forest operations (SFOs) is of substantial importance to achieve sustainable forest management (SFM). One of the most important issues to be evaluated when dealing with SFOs is limiting the disturbance and impacts related to logging. Harvesting activities can indeed alter the conditions of soil through compaction and litter removal which can also lead to modifications from the biological point of view, for example, diminishing the presence of soil microarthropods. While keeping these objectives in focus, the aim of the present study was to evaluate physico-chemical and biological impacts on forest soil in Mediterranean beech forests after forest logging with two different extraction systems, which are forestry-fitted farm tractors equipped with winch and forwarder. Specifically, authors aimed to investigate: (i) soil disturbance levels of ground-based extraction methods; (ii) soil disturbance levels of the applied forestry intervention; (iii) soil disturbance levels between winching-skidding and forwarding. Findings showed that the physical, chemical, and biological soil features were slightly disturbed by the forestry itself. In addition, forest operations and machine traffic showed clear soil disturbance, resulting in a substantial alteration of the characteristics. Between the two extraction techniques tested, winching caused less disturbance while forwarding had stronger impacts. However, it should be noted that these impact levels are found only on approximately 28% of the surface where operations were carried out. From the evidence gathered in this study, winching seems a less impactful extraction method in the studied context. On the other hand, to decrease the impact of forwarding, some technical adjustments such as bogie-tracks, as well as improved operator training, should be applied.
Land Use in Flood-Prone Areas and Its Significance for Flood Risk Management—A Case Study of Alpine Regions in Austria
Authors: Junger Lena , Hohensinner Severin , Schroll Karin , Wagner Klaus , Seher Walter
Published: March 2022

Increasing flood damage has led to a rising importance of land use in flood risk management policies, commonly referred to as the spatial turn in flood risk management. This includes policies aiming at making space for rivers, which, in practice, lead to an increasing demand for land. Although research has been conducted on the variety of policies, the resulting land use conflicts in flood-prone areas have not been paid much attention to. This paper therefore analyses the current land use and its changes in Alpine flood-prone areas in Austria. The results show that space for rivers has been decreasing due to human activities (e.g., river straightening and channel narrowing) since the middle of the 19th century, and settlements have been expanding into flood-prone areas. Furthermore, the share of valuable agricultural land (which is important for food production) located in flood hazard zones is higher in more mountainous areas. Given the limited space for permanent settlement in Alpine regions, these land use changes exert pressure on the availability of land suitable for flood risk management. Therefore, making space for rivers as part of flood risk management policies faces considerable restrictions in Alpine areas.
Deep Convolutional Neural Network-Based Visual Stimuli Classification Using Electroencephalography Signals of Healthy and Alzheimer’s Disease Subjects
Authors: Komolovaitė Dovilė , Maskeliūnas Rytis , Damaševičius Robertas
Published: March 2022

Visual perception is an important part of human life. In the context of facial recognition, it allows us to distinguish between emotions and important facial features that distinguish one person from another. However, subjects suffering from memory loss face significant facial processing problems. If the perception of facial features is affected by memory impairment, then it is possible to classify visual stimuli using brain activity data from the visual processing regions of the brain. This study differentiates the aspects of familiarity and emotion by the inversion effect of the face and uses convolutional neural network (CNN) models (EEGNet, EEGNet SSVEP (steady-state visual evoked potentials), and DeepConvNet) to learn discriminative features from raw electroencephalography (EEG) signals. Due to the limited number of available EEG data samples, Generative Adversarial Networks (GAN) and Variational Autoencoders (VAE) are introduced to generate synthetic EEG signals. The generated data are used to pretrain the models, and the learned weights are initialized to train them on the real EEG data. We investigate minor facial characteristics in brain signals and the ability of deep CNN models to learn them. The effect of face inversion was studied, and it was observed that the N170 component has a considerable and sustained delay. As a result, emotional and familiarity stimuli were divided into two categories based on the posture of the face. The categories of upright and inverted stimuli have the smallest incidences of confusion. The model’s ability to learn the face-inversion effect is demonstrated once more.
Prophylactic Addition of Glucose Suppresses Cyanobacterial Abundance in Lake Water
Authors: Vesper Stephen , Sienkiewicz Nathan , Struewing Ian , Linz David , Lu Jingrang
Published: March 2022

To mitigate harmful cyanobacterial blooms (HCBs), toxic algicides have been used, but alternative methods of HCB prevention are needed. Our goal was to test the prophylactic addition of glucose to inhibit HCB development, using Microcystis and the toxin microcystin as the HCB model. Water samples were collected weekly, from 4 June to 2 July, from Harsha Lake in southwestern Ohio during the 2021 algal bloom season. From each weekly sample, a 25 mL aliquot was frozen for a 16S rRNA gene sequencing analysis. Then, 200 mL of Harsha Lake water was added to each of the three culture flasks, and glucose was added to create concentrations of 0 mM (control), 1.39 mM, or 13.9 mM glucose, respectively. The microcystin concentration in each flask was measured after 1 and 2 weeks of incubation. The results showed an 80 to 90% reduction in microcystin concentrations in glucose-treated water compared to the control. At the end of the second week of incubation, a 25 mL sample was also obtained from each of the culture flasks for molecular analysis, including a 16S rRNA gene sequencing and qPCR-based quantification of Microcystis target genes. Based on these analyses, the glucose-treated water contained significantly lower Microcystis and microcystin producing gene (mcy) copy numbers than the control. The 16S rRNA sequencing analysis also revealed that Cyanobacteria and Proteobacteria were initially the most abundant bacterial phyla in the Harsha Lake water, but as the summer progressed, Cyanobacteria became the dominant phyla. However, in the glucose-treated water, the Cyanobacteria decreased and the Proteobacteria increased in weekly abundance compared to the control. This glucose-induced proteobacterial increase in abundance was driven primarily by increases in two distinct families of Proteobacteria: Devosiaceae and Rhizobiaceae. In conclusion, the prophylactic addition of glucose to Harsha Lake water samples reduced Cyanobacteria’s relative abundance, Microcystis numbers and microcystin concentrations and increased the relative abundance of Proteobacteria compared to the control.
Hydration of Hybrid Cements at Low Temperatures: A Study on Portland Cement-Blast Furnace Slag—Na2SO4
Authors: Joseph Shiju , Cizer Özlem
Published: March 2022

Replacement of Portland cement with high volumes of blast furnace slag is known to negatively affect the early-age properties of concrete, particularly at low temperatures. In this study, the effectiveness of Na2SO4 on the mechanical properties, hydration kinetics and microstructure development of a commercial CEM III/B (~69% slag) is investigated at 10 and 20 °C. Na2SO4 enhances compressive strength at both 10 and 20 °C, and at both early (1 and 7 days) and later ages (28 and 90 days). QXRD shows an increase in the degree of alite hydration at 1 day with Na2SO4 addition, while the degree of clinker and slag hydration is similar for all the systems from 7 to 90 days. An increase in ettringite content is observed at all ages in the systems with Na2SO4. Microstructure and pore structure shows densification of hydrates and reduction in porosity on addition of Na2SO4.
High-Power Diode Laser Surface Transformation Hardening of Ferrous Alloys
Authors: Czupryński Artur , Janicki Damian , Górka Jacek , Grabowski Andrzej , Wyględacz Bernard , Matus Krzysztof , Karski Wojciech
Published: March 2022

A high-power direct diode laser (HPDDL) having a rectangular beam with a top-hat intensity distribution was used to produce surface-hardened layers on a ferrous alloy. The thermal conditions in the hardened zone were estimated by using numerical simulations and infrared (IR) thermography and then referred to the thickness and microstructure of the hardened layers. The microstructural characteristics of the hardened layers were investigated using optical, scanning electron and transmission electron microscopy together with X-ray diffraction. It was found that the major factor that controls the thickness of the hardened layer is laser power density, which determines the optimal range of the traverse speed, and in consequence the temperature distribution in the hardened zone. The increase in the cooling rate led to the suppression of the martensitic transformation and a decrease in the hardened layer hardness. The precipitation of the nanometric plate-like and spherical cementite was observed throughout the hardened layer.