bluuebunny/crossref_metadata_2025 huggingface dataset:
The Impact of the Digital Economy on Carbon Emissions from Cultivated Land Use
Authors: Li Jie , Sun Zhengchuan , Zhou Jie , Sow Yaya , Cui Xufeng , Chen Haipeng , Shen Qianling
Published: March 2023

Is digitalization conducive to promoting carbon reduction in cultivated land use while empowering high-quality socio-economic development and intelligent territorial spatial planning? Derived from China’s provincial panel data from the period 2011 to 2019, in this paper, we employ a fixed-effect model to study the impact of the digital economy on carbon emissions from cultivated land use and apply an intermediary-effect model to estimate the impact that the structure of the digital economy has on carbon emissions from cultivated land use. The results indicate the following: (1) The expansion of the digital economy can significantly decrease the carbon emissions caused by cultivated land use. This conclusion is still valid after considering endogenous issues and conducting a series of robustness tests. (2) Green technical renovation has played a significant intermediary role in the effect the digital economy has on the amount of carbon emissions from cultivated land use. (3) Digital economy development has significantly promoted innovation in green technology by increasing the size of green invention patent applications and authorizations, thus effectively curbing carbon emissions from cultivated land use and achieving the carbon emission reduction effect of the digital economy. However, some suggestions are put forward, including speeding up the deep integration of digital technology and cultivated land use planning, strengthening the application of green technical renovation achievements in the agricultural field, and enhancing the government’s function in the institutional guarantee of the growth of the digital economy.
Spatial–Temporal Evolution and Prediction of Habitat Quality in Beijing–Tianjin–Hebei Region Based on Land Use Change
Authors: Zhao Li , Su Mengwei , Wang Xueyan , Li Xiaoqing , Chang Xinhan , Zhang Pengtao
Published: March 2023

In order to solve the problem of habitat fragmentation in the Beijing–Tianjin–Hebei region and realize the sustainable use of land, based on remote sensing data from 2010 to 2020, this paper uses GIS and the CA–Markov model to predict the land use structure in 2030, and uses the InVEST model to quantitatively analyze the changes in habitat quality in the Beijing–Tianjin–Hebei region from 2010 to 2030. The results indicate that (1) from 2010 to 2020, the area of construction land increased significantly, mainly from cultivated land, woodland and grassland; the proportion of cultivated land decreased by 7.2%. It was predicted that by 2030, the area of construction land will continue to expand, accounting for 19.6%. According to the results of land use dynamic degree, the conversion speed between land types in 2010–2015 was higher than that in 2015–2020. (2) The average habitat quality indexes of the study area in 2010, 2015, 2020 and 2030 were 0.57, 0.56, 0.55 and 0.52, respectively, and the habitat quality level was moderate and continued to decline. The habitat center of gravity moved in the north, from Fengning Manchu Autonomous County to the junction of Fengning Manchu Autonomous County and Longhua County, and then moved to the Mentougou District of Beijing. Therefore, in order to amendthe continuous decline in habitat quality, scientific measures should be taken according to local conditions to promote the improvement of habitat quality and the rational use of land.
The Function of Money in Water–Energy–Food and Land Nexus
Authors: Sargentis G.-Fivos , Koutsoyiannis Demetris
Published: March 2023

The water–energy–food (WEF) and land nexus is a basic element of prosperity. However, the elements of WEF are not equally distributed, and the dynamics of trading drives the distribution of goods. Money controls the trading, but money is just a convention and not a stable measure. Therefore, we have used the data of gross domestic product (GDP) and the price of electricity of each country in order to convert money to stable energy units. To evaluate the role of money in the WEF nexus, we also convert all the elements of the nexus, in energy units. In addition, we observe that land is the base of WEF and is positively correlated with all of its elements. However, we find that even the richest countries are facing critical deficits in WEF. Adding the money (GDP in energy units) to the WEF nexus, the balance becomes positive and we conclude that trading is necessary for both survival and prosperity. This may be obvious, but at present, global geopolitical conflicts which use economic sanctions as a tool transform the global balance of the WEF nexus, putting the global prosperity in jeopardy.
Increase in Productivity of Chestnut Soils on Irrigated Lands of Northern and Central Kazakhstan
Authors: Rau Alexey , Koibakova Yelzaveta , Nurlan Balgabayev , Nabiollina Madina , Kurmanbek Zhanymhan , Issakov Yerlan , Zhu Kai , Dávid Lóránt Dénes
Published: March 2023

Natural conditions in North and Central Kazakhstan and the energy potential of chestnut soil testify to the efficiency of agriculture, especially on irrigated lands. The humus horizon of chestnut soils is 35–50 cm, and the humus content is 3.0–3.5%. The majority of the humus (75%) is contained in a half-meter layer, which emphasizes the short humus level. The phosphorus content, both gross and mobile, is very low at 0.98–0.031%. Potassium is in elevated amounts. Soils are most susceptible to the application of nitrogen–phosphorus fertilizers. According to the mechanical composition, chestnut soils are predominantly lightly loamy, light clays with substrates of souses. Salinization is low, with a salt content in the 0–100 cm soil layer of 0.10–0.20%. The mass of the arable soil layer is 1.3–1.4 g/cm3. Deep plowing and loosening of soils improve the water and nutrition regime, creating good conditions for arid agriculture. With deep autumn plowing up to 30 cm, the accumulation of sediment and spring meltwater reaches 1200–1500 m3/ha more than in spring disposal. Deep plowing ensures absorption of irrigation water, eliminates run-off during irrigation, and reduces the number of crops requiring extra irrigation. In an average dry year, at 50% water availability and 70% soil moisture content (MC), the number of irrigations is 4, and the irrigation rate is 300–470 m3/ha; at 60% MC, 2 irrigations are performed, and the irrigation rate is 600–650 m3/ha. On irrigated land, the yield of cereals is 2.8–2.6 t/ha; perennial grasses, 3.0–4.5 t/ha; potatoes, 23.2–24.1 t/ha; carrots, 35.0–40.0 t/ha; and cabbage, 50.0–75.0 t/ha.
Photography, Land-Cover and Land-Use Changes, and Tourism Urbanization: A Narrative Focused on Hotel do Garbe, Armação de Pêra, Algarve, Portugal
Authors: Loureiro Nuno de Santos
Published: March 2023

This article is focused on the use of photography to characterize land-cover and land-use changes in a 7.59 km2 study area centered on Hotel do Garbe, in the village of Armação de Pêra, Algarve, Portugal. Orthorectified vertical aerial, oblique aerial and ground-level photographs were the main data sources required to carry out the analysis. In a preliminary approach, a conventional research design was adopted. Based on the available orthorectified vertical aerial photographs, a sixty-year time series, with four homogeneously distributed steps (1958, 1978, 1997 and 2018), was constructed, and maps were produced to support the description of the changes that have taken place. To deepen the analysis, photographs from fourteen picture postcards were recognized as a useful source of information, and the authors of these photographs were considered “involuntary or accidental photo-geographers” whose work was relevant to feed a case study in which human geography and landscape biography sciences are the main narrative axes. The final result proved to be richer than the interpretation only based on the orthorectified vertical aerial photographs, and the importance of combining photographs taken from different points of view, with different aims and for different recipients is highlighted.
Complete Cerebrospinal Fluid Response to T-DM1 in HER2 Positive Metastatic Breast Cancer: A Case Report
Authors: Zacchi Francesca , Giontella Elena , Nottegar Alessia , Fiorio Elena
Published: March 2023

Leptomeningeal carcinomatosis is a rare but serious consequence of pre-existing tumors, such as breast, lung, and gastrointestinal carcinomas. Further, leptomeningeal carcinomatosis is more frequently diagnosed with breast cancers, if only because breast cancers are diagnosed far more often than any other carcinomas. In this paper, we present the case of a leptomeningeal carcinomatosis patient who experienced complete remission following therapy targeted at the Her-2 (human epidermal growth factor receptor 2-positive) receptor. This patient’s diagnosis was complicated by the fact that brain and column MRI imaging were clear, but analysis of the cerebrospinal fluid led to the conclusion of leptomeningeal carcinomatosis. The tests were requested because the patient, under chemotherapy for advanced breast cancer at the time, reported some neurological symptoms. Following the diagnosis of leptomeningeal carcinomatosis and subsequent T-DM1 Her-2 receptor therapy, the patient showed a complete response to leptomeningeal carcinomatosis within 30 days and survived for another 16 months. This case offers compelling evidence that the effect TDM1 Her-2 receptor therapy has on a patient’s remission and long-term survivability is considerably better than other therapies for similar pre-existing conditions diagnosed with leptomeningeal carcinomatosis. Further prospective studies should confirm these findings.
EDTA and IAA Ameliorates Phytoextraction Potential and Growth of Sunflower by Mitigating Cu-Induced Morphological and Biochemical Injuries
Authors: Shah Naila , Irshad Muhammad , Hussain Anwar , Qadir Muhammad , Murad Waheed , Khan Asif , Awais Muhammad , Alrefaei Abdulwahed Fahad , Ali Sajid
Published: March 2023

As an essential micronutrient, copper is vital for normal growth and development of plants, however, its accumulation in soil exerts a severe negative impact on the agronomic characteristics and yield of the crop plants. Phytoextraction is a low-cost method for restoring soil fertility and avoiding losses due to heavy metal contamination. We found that using EDTA and IAA together improved sunflower hyperaccumulation capacity. Sunflowers were cultivated under various levels of Cu (0 (control), 25, 50, and 75 mg/kg of soil) and treated with EDTA alone or combined with IAA. The results revealed that the amended treatment significantly enhanced the absorption and accumulation of Cu in the sunflowers. Furthermore, the various doses of Cu significantly reduced the root and shoot growth of sunflowers in a concentration-dependent manner by impairing the chlorophyll content, hormones (indole 3-acetic acid, salicylic acid, and gibberellic acid), flavonoids, phenolics, and antioxidant response. The injurious effect of Cu was reduced by the addition of EDTA alone, and the supplementation of IAA led to a significant restoration of shoot growth (~70%) and root growth (~13%) as compared to the plant treated with Cu alone. Moreover, significantly higher levels of chlorophyll content, GA3, endogenous IAA, and flavonoids were recorded, indicating the effectiveness of the treatment in ameliorating plant health. The results also showed considerable restoration of the catalase and ascorbate peroxidase activities in plants treated with EDTA and IAA. These results are suggestive that application of EDTA and IAA enhances the Cu absorption potential of sunflower and increases its tolerance to copper, which may not only serve as a better technique for phytoextraction of Cu, but also to bring Cu contaminated soil under cultivation.
Nanoparticles Induced Oxidative Damage in Reproductive System and Role of Antioxidants on the Induced Toxicity
Authors: Samrot Antony V. , Noel Richard Prakash Lawrence Xavier
Published: March 2023

Nanotechnology is used in a variety of scientific, medical, and research domains. It is significant to mention that there are negative and severe repercussions of nanotechnology on both individuals and the environment. The toxic effect of nanoparticles exerted on living beings is termed as nanotoxicity. Nanoparticles are synthesized by various methods such as chemical, biological, physical, etc. These nanoparticles’ nanotoxicity has been observed to vary depending on the synthesis process, precursors, size of the particles, etc. Nanoparticles can enter the cell in different ways and can cause cytotoxic effects. In this review, the toxicity caused in the reproductive system and the role of the antioxidants against the nanotoxicity are briefly explained.
Study on Adhesion Force of Graphene under Cylinder–Plane Contact
Authors: Shi Kai , Hu Manfeng , Huang Ping
Published: March 2023

There are many cylinder–plane contacts in microaccelerators, microgyroscopes, and RF switches. Adhesion is one of the main factors affecting the manufacture and use of these micro–nano devices, but its research is insufficient. Graphene is expected to be used in these fields due to its excellent electrical and mechanical properties. Therefore, it is significant to research the adhesion force of graphene under cylinder–plane. Firstly, the meniscus formation process was introduced using the variable-water-contact-angle method. Secondly, the adhesion force of the graphene surface was measured with a cylindrical atomic-force-microscope probe. Finally, the contact area was considered as a number of nanoscale cylinders in contact with the plane, and the adhesion force of the cylinder–plane model was obtained. The results showed that there was a maximum adhesion force at a relative humidity of 65%. The adhesion force was evidently not time-dependent when the relative humidity was below 45%, because the meniscus cannot be formed on the graphene surface at low relative humidity. While the graphene contact surface formed a meniscus for higher relative humidity, and the adhesion force-versus-time curves first increased and then decreased to stability. Moreover, the relationship between adhesion force and substrate contact angle, roughness, relative humidity, and dwell time was established, and the number of cylinders was determined. The error between the modified theoretical model and the experimental values was only 6%.
A Feature-Extraction-Based Adaptive Refinement Method for Solving the Reynolds Equation in Piston–Cylinder System
Authors: Yang Jiashu , Zuo Bingquan , Luo Huixin , Xie Weikang
Published: March 2023

A fast local refinement algorithm based on feature extraction is developed. In the mesh-based Reynolds equation solutions, two refinement features based on the physical parameters of fluid lubrication are firstly defined, namely, pressure value feature and pressure gradient feature. Then, a fast adaptive strategy different from the traditional methods based on residuals or recovery errors is constructed according to the features, which are expected to determine the element needed to be refined. Considering the update requirement of the feature parameters, an adaptive update strategy for feature parameters is also developed. Finally, the feasibility of the scheme is verified on a single-cylinder gasoline engine. Results show that the current algorithm can effectively reduce the computational scale while ensuring the computational accuracy of the mesh-based model, compared with the traditional global and local refinement strategy.
Viscosity and Friction Reduction of Double-End-Capped Polyalkylene Glycol Nanolubricants for Eco-Friendly Refrigerant
Authors: Sharif Mohd Zaki , Azmi Wan Hamzah , Ghazali Mohd Fairusham , Zawawi Nurul Nadia Mohd , Ali Hafiz Muhammad
Published: March 2023

In sustainable tribology, researchers are investigating methods to enhance tribological performance by incorporating nanoparticles into lubricants. However, one potential drawback of this strategy is increased lubricant viscosity. The current study aimed to assess the impact of these nanoparticles on the viscosity and coefficient of friction (COF) of the nanolubricants. Three different nanolubricants were synthesized through a two-step process, including mono-nanolubricants (Al2O3/DEC PAG and SiO2/DEC PAG) and hybrid nanolubricants (Al2O3-SiO2/DEC PAG), at volume concentrations between 0.01% and 0.05%. The viscosity and shear flow behavior of these nanolubricants were evaluated using a digital rheometer, while the COF was measured using a Koehler four-ball tribometer. All the nanolubricants showed Newtonian behavior during the experiments. The dynamic viscosity velocity increment of SiO2/DEC PAG was found to be the lowest (1.88%), followed by Al2O3-SiO2/DEC PAG (2.74%) and Al2O3/DEC PAG (3.56%). The viscosity indices of all the nanolubricants were improved only at higher concentrations. At a volume concentration of 0.03%, the Al2O3-SiO2/DEC PAG nanolubricant reduced the COF by up to 8.1%. The results showed that the combination of nanoparticles, temperature, and volume concentration significantly influenced the viscosity and COF of nanolubricants. This study provides essential information for developing high-performance nanolubricants with improved viscosity and COF and advancing environmentally friendly tribology solutions.
Communication Safety of Cybernetic Systems in a Smart Factory Environment
Authors: Halenar Igor , Halenarova Lenka , Tanuska Pavol
Published: March 2023

The aim of this contribution is to propose the architecture for a layered design of the production system. This proposal uses the IEC 62443 norm, including the Defense-in-Depth strategy and proven technical principles applicable in a Smart Factory with a focus on communication security. Firstly, the identification of communication forms and trends in the Smart Factory environment was identified considering the spectrum of communication protocols used within various types of automation structures used in modern production facilities. The next part of the work deals with the definition of wired and wireless forms of data transfers in production systems including their advantages and disadvantages from the view of cybernetic safety and threads in communication systems, together with the description of norms from the field of security of communication systems applicable in the industrial environment. The core of this work is the proposal of the methodology to secure the Smart Factory production system in the Industry 4.0 environment. The proposal defines important implementation steps together with a summarization of the generally applicable basic principles suitable for the process of securing a Cyber production system or Smart Factory in an industrial environment, including the example of an Iptables firewall configuration within the OPC UA communication protocol and the real example of a Smart Factory production system segmentation.
Elucidating Powder-Mixed Electric Discharge Machining Process, Applicability, Trends and Futuristic Perspectives
Authors: Gul Iqtidar Ahmed , Abdul-Rani Ahmad Majdi , Al-Amin Md , Garba Elhuseini
Published: March 2023

Since the inception of electric discharge machining (EDM), it has facilitated the production industries, for instance, die & mold, automotive, aerospace, etc., by providing an effective solution for machining hard-to-cut materials and intricate geometries. However, achieving high machining rates and a fine surface finish is an inherent issue with the traditional EDM process. The emergence of the powder mixed electric discharge machining (PMEDM) process has not only provided the opportunity for enhancing productivity and surface finish but also opened a window for its potential application in surface modification/coating of biomaterials. The process incorporates simultaneous machining and coating of bioimplants, i.e., lacking in the already available chemical and physical coating methods while requiring costly post-treatment procedures. This study comprehends the influence of powder characteristics and EDM process parameters on the performance parameters. The impact of tool electrodes and additive powders on the machined and coated surface of commonly used biomaterials. Furthermore, the study depicts the most frequently used methods for optimizing the PMEDM process, future research directions, challenges, and research trends over the past decade.
Skew Class-Balanced Re-Weighting for Unbiased Scene Graph Generation
Authors: Kang Haeyong , Yoo Chang D.
Published: March 2023

An unbiased scene graph generation (SGG) algorithm referred to as Skew Class-Balanced Re-Weighting (SCR) is proposed for considering the unbiased predicate prediction caused by the long-tailed distribution. The prior works focus mainly on alleviating the deteriorating performances of the minority predicate predictions, showing drastic dropping recall scores, i.e., losing the majority predicate performances. It has not yet correctly analyzed the trade-off between majority and minority predicate performances in the limited SGG datasets. In this paper, to alleviate the issue, the Skew Class-Balanced Re-Weighting (SCR) loss function is considered for the unbiased SGG models. Leveraged by the skewness of biased predicate predictions, the SCR estimates the target predicate weight coefficient and then re-weights more to the biased predicates for better trading-off between the majority predicates and the minority ones. Extensive experiments conducted on the standard Visual Genome dataset and Open Image V4 and V6 show the performances and generality of the SCR with the traditional SGG models.
A Survey on GAN Techniques for Data Augmentation to Address the Imbalanced Data Issues in Credit Card Fraud Detection
Authors: Strelcenia Emilija , Prakoonwit Simant
Published: March 2023

Data augmentation is an important procedure in deep learning. GAN-based data augmentation can be utilized in many domains. For instance, in the credit card fraud domain, the imbalanced dataset problem is a major one as the number of credit card fraud cases is in the minority compared to legal payments. On the other hand, generative techniques are considered effective ways to rebalance the imbalanced class issue, as these techniques balance both minority and majority classes before the training. In a more recent period, Generative Adversarial Networks (GANs) are considered one of the most popular data generative techniques as they are used in big data settings. This research aims to present a survey on data augmentation using various GAN variants in the credit card fraud detection domain. In this survey, we offer a comprehensive summary of several peer-reviewed research papers on GAN synthetic generation techniques for fraud detection in the financial sector. In addition, this survey includes various solutions proposed by different researchers to balance imbalanced classes. In the end, this work concludes by pointing out the limitations of the most recent research articles and future research issues, and proposes solutions to address these problems.
Personalized Movie Recommendations Based on a Multi-Feature Attention Mechanism with Neural Networks
Authors: Yu Saisai , Guo Ming , Chen Xiangyong , Qiu Jianlong , Sun Jianqiang
Published: March 2023

With the rapid growth of the Internet, a wealth of movie resources are readily available on the major search engines. Still, it is unlikely that users will be able to find precisely the movies they are more interested in any time soon. Traditional recommendation algorithms, such as collaborative filtering recommendation algorithms only use the user’s rating information of the movie, without using the attribute information of the user and the movie, which has the problem of inaccurate recommendations. In order to achieve personalized accurate movie recommendations, a movie recommendation algorithm based on a multi-feature attention mechanism with deep neural networks and convolutional neural networks is proposed. In order to make the predicted movie ratings more accurate, user attribute information and movie attribute information are added, user network and movie network are presented to learn user features and movie features, respectively, and a feature attention mechanism is proposed so that different parts contribute differently to movie ratings. Text features are also extracted using convolutional neural networks, in which an attention mechanism is added to make the extracted text features more accurate, and finally, personalized movie accurate recommendations are achieved. The experimental results verify the effectiveness of the algorithm. The user attribute features and movie attribute features have a good effect on the rating, the feature attention mechanism makes the features distinguish the degree of importance to the rating, and the convolutional neural network adding the attention mechanism makes the extracted text features more effective and achieves high accuracy in MSE, MAE, MAPE, R2, and RMSE indexes.
The Data Privacy Protection Method for Hyperledger Fabric Based on Trustzone
Authors: Gao Wen , Hei Xinhong , Wang Yichuan
Published: March 2023

Hyperledger Fabric is a distributed ledger solution platform based on a modular architecture. The cryptographic algorithm is the core of the platform to ensure the security and tamper-resistant of the data on the chain. However, the original Fabric platform lacks the protection of user’s keys and cryptographic operations. To this end, this paper proposes a data privacy protection method for Hyperledger Fabric based on Trustzone technology, which places the user‘s key and the cryptographic operation process of private data in the trusted execution environment for protection. The experimental results based on the existing blockchain network show that the scheme can effectively ensure the security of data encryption process and key static storage, greatly reduce the trusted computing base and the attack surface. The performance loss is within an acceptable range.
A Full-Body Relative Orbital Motion of Spacecraft Using Dual Tensor Algebra and Dual Quaternions
Authors: Condurache Daniel
Published: March 2023

This paper proposes a new non-linear differential equation for the six degrees of freedom (6-DOF) relative rigid bodies motion. A representation theorem is provided for the 6-DOF differential equation of motion in the arbitrary non-inertial reference frame. The problem of the 6-DOF relative motion of two spacecraft in the specific case of Keplerian confocal orbits is proposed. The result is an analytical method without secular terms and singularities. Tensors dual algebra and dual quaternions play a fundamental role, with the solution representation being the relative problem. Furthermore, the representation theorems for the rotation and translation parts of the 6-DOF relative orbital motion problems are obtained.
Long-COVID Inducement Mechanism Based on the Path Module Correlation Coefficient
Authors: Liu Ziqi , Yin Ziqiao , Mi Zhilong , Guo Binghui
Published: March 2023

As the number of COVID-19 cases increases, the long-COVID symptoms become the focus of clinical attention. Based on the statistical analysis of long-COVID symptoms in European and Chinese populations, this study proposes the path module correlation coefficient, which can estimate the correlation between two modules in a network, to evaluate the correlation between SARS-CoV-2 infection and long-COVID symptoms, providing a theoretical support for analyzing the frequency of long-COVID symptoms in European and Chinese populations. The path module correlation coefficients between specific COVID-19-related genes in the European and Chinese populations and genes that may induce long-COVID symptoms were calculated. The results showed that the path module correlation coefficients were completely consistent with the frequency of long-COVID symptoms in the Chinese population, but slightly different in the European population. Furthermore, the cathepsin C (CTSC) gene was found to be a potential COVID-19-related gene by a path module correlation coefficient correction rate. Our study can help to explore other long-COVID symptoms that have not yet been discovered and provide a new perspective to research this syndrome. Meanwhile, the path module correlation coefficient correction rate can help to find more species-specific genes related to COVID-19 in the future.
Oscillation of Nonlinear Neutral Delay Difference Equations of Fourth Order
Authors: Vimala Ramasamy , Kodeeswaran Ramasamy , Cep Robert , Krishnasamy Majella Jenvi Ignatia , Awasthi Meenakshi , Santhakumar Govindasamy
Published: March 2023

This paper focuses on the study of the oscillatory behavior of fourth-order nonlinear neutral delay difference equations. The authors use mathematical techniques, such as the Riccati substitution and comparison technique, to explore the regularity and existence properties of the solutions to these equations. The authors present a new form of the equation: Δ(a(m)(Δ3z(m))p1−1)+p(m)wp2−1(σ(m))=0, where z(m)=w(m)+q(m)w(m−τ) with the following conditions: ∑s=m0∞1a(1p1−1(s))=∞. The equation represents a system where the state of the system at any given time depends on its current time and past values. The authors demonstrate new insights into the oscillatory behavior of these equations and the conditions required for the solutions to be well-behaved. They also provide a numerical example to support their findings.
Drivers of Realized Volatility for Emerging Countries with a Focus on South Africa: Fundamentals versus Sentiment
Authors: Gupta Rangan , Nel Jacobus , Pierdzioch Christian
Published: March 2023

We use a quantile machine learning (random forests) approach to analyse the predictive ability of newspapers-based macroeconomic attention indexes (MAIs) on eight major fundamentals of the United States on the realized volatility of a major commodity-exporting emerging stock market, namely South Africa. We compare the performance of the MAIs with the performance of a news sentiment index (NSI) of the US. We find that both fundamentals and sentiment improve predictive performance, but the relative impact of the former is stronger. We document how the impact of fundamentals and sentiment on predictive performance varies across the quantiles of the conditional distribution of realized volatility, and across different prediction horizons. Specifically, fundamentals matter more at the extreme quantiles at short horizons, and at the median in the long-run. In addition, we report several robustness checks (involving sample period and alternative definitions of realized volatility), and indicate that the obtained results for South Africa also tend to carry over to other emerging countries such as, Brazil, China, India, and Russia. Our results have important implications for investors with volatility being an input for portfolio allocation decisions. In addition, with stock market variability also capturing financial uncertainty, its accurate prediction based on US fundamentals and sentiment also has a role in policy design to prevent possible collapse.
Some Remarks on Local Fractional Integral Inequalities Involving Mittag–Leffler Kernel Using Generalized (E, h)-Convexity
Authors: Saleh Wedad , Lakhdari Abdelghani , Almutairi Ohud , Kiliçman Adem
Published: March 2023

In the present work, we introduce two new local fractional integral operators involving Mittag–Leffler kernel on Yang’s fractal sets. Then, we study the related generalized Hermite–Hadamard-type inequality using generalized (E,h)-convexity and obtain two identities pertaining to these operators, and the respective first- and second-order derivatives are given. In terms of applications, we provide some new generalized trapezoid-type inequalities for generalized (E,h)-convex functions. Finally, some special cases are deduced for different values of δ, E, and h.
Measures of Extropy Based on Concomitants of Generalized Order Statistics under a General Framework from Iterated Morgenstern Family
Authors: Husseiny Islam A. , Alawady Metwally A. , Alyami Salem A. , Abd Elgawad Mohamed A.
Published: March 2023

In this work, we reveal some distributional characteristics of concomitants of generalized order statistics (GOS) with parameters that are pairwise different, arising from iterated Farlie–Gumbel–Morgenstern (IFGM) family of bivariate distributions. Additionally, the joint distribution and product moments of concomitants of GOS for this family are discussed. Moreover, some well-known information measures, i.e., extropy, cumulative residual extropy (CRJ), and negative cumulative extropy (NCJ), are derived. Applications of these results are given for order statistics, record values, and progressive type-II censored order statistics with uniform marginals distributions. Additionally, the issue of estimating the CRJ and NCJ is looked into, utilizing the empirical technique and the concomitant of GOS. Finally, bivariate real-world data sets have been analyzed for illustrative purposes, and the performance of the proposed method is quite satisfactory.
Energy Flow Analysis Model of High-Frequency Vibration Response for Plates with Free Layer Damping Treatment
Authors: Teng Xiaoyan , Han Yuedong , Jiang Xudong , Chen Xiangyang , Zhou Meng
Published: March 2023

The energy flow analysis (EFA) model is developed for predicting the vibrational response of plates with free layer damping (FLD) treatment under high-frequency excitation. For the plate with fully free layer damping (FFLD) treatment, the energy density equation of the laminated plate with high damping is deduced by combining the equivalent complex stiffness method with the EFA theory. For the plate with partially free layer damping (PFLD) treatment, the relationship between energy density and energy intensity is obtained based on the wave theory of coupled plate by analyzing the energy transfer relationship at the damping boundary. The high-frequency energy density response of the structure with FLD treatment is solved through the energy finite element analysis (EFEA) method. To verify the developed EFEA model, several numerical analyses are performed for the plate with FFLD and PFLD treatments. The numerical results demonstrate that the obtained EFEA solutions consistently converge to the time-averaged modal analytical solutions at various analysis frequencies. Finally, the influences of the loss factor and the thickness of the damping layer on the resulting energy density are investigated in detail.
Underwater Image Enhancement Based on the Improved Algorithm of Dark Channel
Authors: Zhu Dachang
Published: March 2023

Enhancing underwater images presents a challenging problem owing to the influence of ocean currents, the refraction, absorption and scattering of light by suspended particles, and the weak illumination intensity. Recently, different methods have relied on the underwater image formation model and deep learning techniques to restore underwater images. However, they tend to degrade the underwater images, interfere with background clutter and miss the boundary details of blue regions. An improved image fusion and enhancement algorithm based on a prior dark channel is proposed in this paper based on graph theory. Image edge feature sharpening, and dark detail enhancement by homomorphism filtering in CIELab colour space are realized. In the RGB colour space, the multi-scale retinal with colour restoration (MSRCR) algorithm is used to improve colour deviation and enhance colour saturation. The contrast-limited adaptive histogram equalization (CLAHE) algorithm defogs and enhances image contrast. Finally, according to the dark channel images of the three processing results, the final enhanced image is obtained by the linear fusion of multiple images and channels. Experimental results demonstrate the effectiveness and practicality of the proposed method on various data sets.
Oscillation Criteria for Advanced Half-Linear Differential Equations of Second Order
Authors: Hassan Taher S. , Kong Qingkai , El-Matary Bassant M.
Published: March 2023

In this paper, we find new oscillation criteria for second-order advanced functional half-linear differential equations. Our results extend and improve recent criteria for the same equations established previously by several authors and cover the existing classical criteria for related ordinary differential equations. We give some examples to illustrate the significance of the obtained results.
A Strain-Gauge-Based Method for the Compensation of Out-of-Plane Motions in 2D Digital Image Correlation
Authors: Visser Carl-Hein , Venter Gerhard , Neaves Melody
Published: March 2023

When performing a digital image correlation (DIC) measurement, multi-camera stereo-DIC is generally preferred over single-camera 2D-DIC. Unlike 2D-DIC, stereo-DIC is able to minimise the in-plane strain error that results from out-of-plane motion. This makes 2D-DIC a less viable alternative for strain measurements than stereo-DIC, despite being less financially and computationally expensive. This work, therefore, proposes a strain-gauge-based method for the compensation of errors from out-of-plane motion in 2D-DIC strain measurements on planar specimens. The method was first developed using equations for the theoretical strain error from out-of-plane motions in 2D-DIC and was then applied experimentally in tensile tests to two different dog-bone specimen geometries. The compensation method resulted in a clear reduction in the strain error in 2D-DIC. The strain-gauge-based method thus improves the accuracy of a 2D-DIC measurement, making it a more viable option for performing full-field strain measurements and providing a possible alternative in cases where stereo-DIC is not practical or is unavailable.
Effect of Adhesive Materials in Re-Attachment of Crown and Crown–Root Fractures of Permanent Maxillary Anterior Tooth: A Computational Study
Authors: Garg Anshika , Gupta Shubham , Tewari Nitesh , Srivastav Sukeshana , Chanda Arnab
Published: March 2023

Traumatic dental injuries (TDI) are frequent among individuals of all ages, with a prevalence ranging from 12–22%, with crown and crown–root fractures being the most common. Fragment reattachment using light-cured nanocomposites is the recommended method for the management of these fractures. Though there are several clinical studies that have assessed the efficacy of such materials, an in-silico characterization of the effects of traumatic forces on the re-attached fragments has never been performed. Hence, this study aimed to evaluate the efficacy of various adhesive materials in crown and crown–root reattachments through computational modelling. A full-scale permanent maxillary anterior tooth model was developed by segmenting 3D scanned cone beam computed tomography (CBCT) images of the pulp, root, and enamel precisely. The full-scale 3D tooth model was then subjected to a novel numerical cutting operation to describe the crown and crown–root fractures. The fractured tooth models were then filled computationally with three commonly used filler (or adhesive) materials, namely flowable composite, resin cement, and resin adhesive, and subjected to masticatory and traumatic loading conditions. The flowable composite demonstrated a statistically significant difference and the lowest produced stresses when subjected to masticatory loading. Resin cement demonstrated reduced stress values for crown–root fractures that were masticatory loaded after being reattached using adhesive materials. During traumatic loading, resin cement demonstrated lower displacements and stress values across both fractures. The novel findings reported in this study are anticipated to assist dentists in selecting the most appropriate adhesive materials that induce the least stress on the reattached tooth when subjected to second trauma, for both crown and crown–root fractures.
Basic Operative Tactics for Pulmonary Echinococcosis in the Era of Endostaplers and Energy Devices
Authors: Bakinowska Estera , Kostopanagiotou Konstantinos , Wojtyś Małgorzata Edyta , Kiełbowski Kajetan , Ptaszyński Konrad , Gajić Darko , Ruszel Nikola , Wójcik Janusz , Grodzki Tomasz , Tomos Periklis
Published: March 2023

Human echinococcosis is a zoonotic infection caused by the larvae of the tapeworm species Echinococcus. The liver is the most common location for a primary echinococcosis. However, the parasite may bypass or spread from the liver to the lungs, causing primary or secondary pulmonary echinococcosis, respectively. Pulmonary echinococcosis is a clinically challenging condition in which anthelminthic regiments are important, but surgery has the central role in removing the cysts and preventing recurrences. Surgical treatment may involve cystotomy, enucleation, capitonnage, or atypical resections, which occasionally are in combination with hepatic procedures. The utilization of modern devices is greatly underdescribed in surgery for thoracic infections, even though these facilitate much of the work. Therefore, this article aims to describe pulmonary echinococcosis and the role of modern surgical devices in the treatment process. Furthermore, we report surgical treatment of three different cases of pulmonary echinococcosis. Surgeries of uncomplicated and ruptured hepatic or pulmonary cysts are described. Simple small pulmonary echinococcal lesions can be excised by endostaplers both for diagnostic and curative reasons. Larger cysts can be removed by energy devices unless large bronchial air leaks occur. Complicated cysts require treatment by more extensive techniques. Inexperienced surgeons should not abstain but should carefully decide preoperatively how to proceed.
Protective Attitudes toward Occupational Radiation Exposure among Spine Surgeons in Japan: An Epidemiological Description from the Survey by the Society for Minimally Invasive Spinal Treatment
Authors: Hijikata Yasukazu , Kotani Yoshihisa , Suzuki Akinobu , Morota Koichi , Funao Haruki , Miyagi Masayuki , Morimoto Tadatsugu , Kanno Haruo , Ishii Ken
Published: March 2023

Background and Objectives: The global trend toward increased protection of medical personnel from occupational radiation exposure requires efforts to promote protection from radiation on a societal scale. To develop effective educational programs to promote radiation protection, we clarify the actual status and stage of behavioral changes of spine surgeons regarding radiation protection. Materials and Methods: We used a web-based questionnaire to collect information on the actual status of radiation protection and stages of behavioral change according to the transtheoretical model. The survey was administered to all members of the Society for Minimally Invasive Spinal Treatment from 5 October to 5 November 2020. Results: Of 324 members of the Society for Minimally Invasive Spinal Treatment, 229 (70.7%) responded. A total of 217 participants were analyzed, excluding 12 respondents who were not exposed to radiation in daily practice. A trunk lead protector was used by 215 (99%) participants, while 113 (53%) preferred an apron-type protector. Dosimeters, thyroid protector, lead glasses, and lead gloves were used by 108 (50%), 116 (53%), 82 (38%), and 64 (29%) participants, respectively. While 202 (93%) participants avoided continuous irradiation, only 120 (55%) were aware of the source of the radiation when determining their position in the room. Regarding the behavioral change stage of radiation protection, 134 (62%) participants were in the action stage, while 37 (17%) had not even reached the contemplation stage. Conclusions: We found that even among the members of the Society for Minimally Invasive Spinal Treatment, protection of all vulnerable body parts was not fully implemented. Thus, development of educational programs that cover the familiar risks of occupational radiation exposure, basic protection methods in the operating room, and the effects of such protection methods on reducing radiation exposure in actual clinical practice is warranted.
Pre-Test Probability Assessment and d-Dimer Based Evaluation in Patients with Previous Acute Aortic Syndrome
Authors: Morello Fulvio , Santoro Marco , Giachino Francesca , Caciolli Francesca , Capretti Elisa , Castelli Matteo , Pivetta Emanuele , Nazerian Peiman , Lupia Enrico
Published: March 2023

Background and Objectives. Acute aortic syndromes (AASs) are emergencies burdened by high morbidity and mortality. Guideline-recommended diagnostic workup is based on pre-test probability assessment (PPA) and d-dimer testing. However, the performance of PPA and d-dimer has never been studied in individuals with previous AAS (pAAS), which represent a challenging population. Materials and Methods. We analyzed a registry of patients with pAAS evaluated in two Emergency Departments (EDs) for suspected novel AAS (nAAS). Enrolment criteria were history of pAAS and the presence of truncal pain, syncope or perfusion deficit. All patients underwent advanced imaging. Clinical data were registered prospectively and PPA was performed by applying the aortic dissection detection (ADD) and an aorta simplified (AORTAs) score. Results. A total of 128 patients were enrolled, including 77 patients with previous Stanford type A aortic dissection and 45 patients with previous Stanford type B aortic dissection. The final diagnosis was nAAS in 40 (31%) patients. Clinical variables associated with nAAS were: aortic valve disease, thoracic aortic aneurysm, severe pain, sudden pain, ripping/tearing pain and hypotension/shock. ADD score ≥ 2 had a sensitivity of 65% and a specificity of 83% for nAAS; AORTAs score ≥ 2 had a sensitivity of 48% and a specificity of 88%. d-dimer (cutoff ≥ 500 ng/mL or age-adjusted cutoff) had a sensitivity of 97% and a specificity of 13%/14.7%, for diagnosis of nAAS. Patients that were candidates for guideline-compliant PPA/d-dimer integrated rule-out were: 5 (4.9%) with ADD ≤ 1/d-dimer and 8 (7.8%) with AORTAs ≤ 1/d-dimer < age-adjusted cutoff. None of them had a nAAS. Conclusions. Patients with pAAS evaluated in the ED for red-flag symptoms showed intermediate-to-high pre-test probability of nAAS. The ADD score had lower sensitivity and specificity than in unselected patients. d-dimer, alone and integrated with PPA, was highly sensitive for nAAS, but very unspecific. PPA/d-dimer integrated strategies are unlikely to significantly reduce the number of patients with pAAS undergoing advanced imaging.