bluuebunny/crossref_metadata_2025 huggingface dataset:
Associations between Cardiovascular Outcomes and Rheumatoid Arthritis: A Nationwide Population-Based Cohort Study
Authors: Kang Seonyoung , Han Kyungdo , Jung Jin-Hyung , Eun Yeonghee , Kim In Young , Hwang Jiwon , Koh Eun-Mi , Lee Seulkee , Cha Hoon-Suk , Kim Hyungjin , Lee Jaejoon
Published: November 2022

Despite a growing burden posed by cardiovascular disease (CVD) in rheumatoid arthritis (RA) patients, large-scale studies on the association between the characteristics of RA patients and CVD risks and studies adjusted for various confounding factors are lacking. In this large-scale nationwide cohort study, we aimed to investigate the association between CVD risk and RA and factors that may increase CVD risk using a dataset provided by the Korean National Health Insurance Service (NHIS). We enrolled 136,469 patients with RA who participated in national health examinations within two years of RA diagnosis between 2010 and 2017 and non-RA controls matched by age and sex (n = 682,345). The outcome was the occurrence of myocardial infarction (MI) or stroke. MI was defined as one hospitalization or two outpatient visits with ICD-10-CM codes I21 or I22. Stroke was defined as one hospitalization with ICD-10-CM codes I63 or I64 and a claim for brain imaging (CT or MRI). The Cox proportional hazard model and Kaplan–Meier curve were used for analysis. The mean follow-up duration was 4.7 years, and the incidence rate of CVD was higher in the RA group than the control group (MI: 3.20 vs. 2.08; stroke: 2.84 vs. 2.33 per 1000 person-years). The risk of MI and stroke was about 50% and 20% higher, respectively, in RA patients. The association between RA and CVD was prominent in females after adjusting for confounding variables. The association between RA and risk of MI was significant in individuals without DM. Therefore, appropriate screening for CVD is important in all RA patients including females and younger patients.
COVID-19 Prevention: Vitamin D Is Still a Valid Remedy
Authors: Nicoll Rachel , Henein Michael Y.
Published: November 2022

Seven meta-analyses and systematic reviews and three later clinical trials argued that low vitamin D status increased susceptibility to COVID-19 and the risk of greater disease severity and mortality [...]
Hybrid Polyethylene Composites with Recycled Carbon Fibres and Hemp Fibres Produced by Rotational Moulding
Authors: Oliveira Maria , Pickering Kim L. , Gauss Christian
Published: November 2022

This study assessed polyethene composites produced by rotational moulding with hybrid reinforcement using recycled carbon fibre (RCF) and hemp fibre (HF). First, the RCF was treated with nitric acid to introduce hydroxyl groups on the fibres’ surface and was characterised by infrared spectroscopy and microscopy analyses. Although the fibre surface treatment improved the tensile properties of the composites, the use of grafted maleic anhydride polyethylene (MAPE) as a coupling agent was more effective in improving the interfacial bonding between the fibres and the matrix. Alkali-treated hemp fibres were then used in combination with RCF to produce rotationally moulded composites with an overall fibre content of 10 wt.% but with different ratios of HF/RCF, namely, (20/80) and (50/50). The results showed that the addition of RCF increased the composite’s Young’s modulus compared to neat PE, regardless of the fibre treatment. Similarly, the hybrid composites showed superior Young’s moduli than the HF–PE composites through the increase in the RCF content. It was also observed that adding RCF reduced the void size within the final composites compared to the HF–PE composites, which contributed to the greater performance of the hybrid composites compared to their natural counterparts.
The Creative Process and Emotions of Pupils in a Training Context with a Design Project
Authors: Botella Marion , Didier John , Lambert Marie-Dominique , Attanasio Rachel
Published: November 2022

For many years, researchers have been investigating how the creative process occurs and what factors influence it. The scope of these studies is essential in the school context to enable pupils to develop their creativity and thus address the needs of the 21st century society. Although very rich, these studies are generally not situated in a real teaching and learning context. The output of the present research will make it possible to model, to better understand, and to identify the creative process in pupils as they design and produce utility objects in an educational and training context with ecological validity (real context of training). In the context of teaching Creative and Manual Activities in education, in the French part of Switzerland, we are focusing on observations of the creative process in line with psychology, didactics, and pedagogy. During their class, 22 pupils were invited to create a water fountain and, in parallel, to complete a Creative process Report Diary about the stages they do and the multivariate factors (cognitive, conative, emotional, and environmental factors) they mobilize at each lesson. Results presented the main frequent stages and factors at each lesson and we proposed a model describing the transitions between the stages and how the multivariate factors are involved in each stage. They illustrate what pupils actually do in a creative learning context.
Influences of Seasonal Variability and Potential Diets on Stable Isotopes and Fatty Acid Compositions in Dominant Zooplankton in the East Sea, Korea
Authors: Kim Jieun , Yun Hee-Young , Won Eun-Ji , Choi Hyuntae , Youn Seok-Hyeon , Shin Kyung-Hoon
Published: November 2022

Despite their crucial roles in transporting primary productions in marine food webs, the trophic dynamics of zooplankton throughout the seasons have rarely been studied. In this study, four dominant zooplankton taxa with phytoplankton size composition and productivity were collected over four seasons in the East Sea, which is known to change more rapidly than global trends. We then analyzed the δ13C and δ15N values and fatty acid composition of zooplankton. The heavy δ13C values in February and August 2021 were observed with high concentrations of total chlorophyll-a, and the δ13C differences among the four zooplankton taxa in the coastal region (site 105-05) were most pronounced in February 2021. The relative amounts of eicosapentaenoic acid (C20:5(n-3)) and docosahexaenoic acid (C22:6(n-3)), indicators of phytoplankton nutritional quality, were also highest in February 2021. Non-metric multivariate analyses showed dissimilarity among zooplankton taxa during the high productivity period based on chlorophyll-a concentrations (51.6%), which may be due to an increase in available foods during the highly productive season. In conclusion, the dietary intake of zooplankton can be reduced by the transition of phytoplankton, which has important implications for the impact of climate change on planktonic ecosystems in the East Sea.
Sea Turtles Employ Drag-Reducing Techniques to Conserve Energy
Authors: van der Geest Nick , Garcia Lorenzo , Nates Roy , Gonzalez-Vazquez Alberto
Published: November 2022

Sea turtles are recognised as one of the ocean’s most remarkable migratory species, accomplishing journeys that cover thousands of kilometres. This fact is even more extraordinary when considering sea turtles consume mostly low-energy foods. The biology of sea turtles dominates the literature; however, the swimming strategies they employ to achieve their migratory success from a biomechanical and hydrodynamic viewpoint is relatively unexplored. In past research, the sea turtle’s upstroke has been debated among researchers as to whether it is passive or for thrust production. In this work, we recreate a model based on the green sea turtle (Chelonia mydas) and develop an ad hoc testing rig to uncover the secrets behind the sea turtle’s upstroke. Our findings suggest sea turtles utilise a passive upstroke that can substantially lower the animal’s drag coefficient to levels that cause insignificant losses in swim speed despite not developing any thrust force. This can conceivably save the animal a notable amount of energy as the upstroke is responsible for a large percentage of the overall limb beat cycle. These findings could potentially pave a path towards developing high-efficiency bioinspired underwater drone technologies.
Assessment of Wave Energy Resources in China
Authors: Shi Hongyuan , Zhang Xuri , Du Wenyan , Li Qingjie , Qu Hengliang , You Zaijin
Published: November 2022

The evolution of renewable energy technologies may surmount fossil fuel disadvantages. Wave energy is considered one of the best alternatives to fossil energy due to its advantages. The 40-year (1979–2018) spatio-temporal distribution of wave energy is presented using European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) datasets. In addition, the common formula used for wave energy evaluation is derived from the linear wave theory in deep water, which is not applicable in shallow water. Therefore, a new equation that is suitable for both shallow and deep water is derived, which improves the accuracy of the wave energy evaluation for various water depths. The main aim is to investigate the spatio-temporal wave energy for offshore China from 1979 to 2018 and combine the new standard of classification to recommend the optimal area. The nearshore zone from Zhejiang province to Guandong province is considered the ideal zone, and the average annual wave energy density in this area is above 10 kW/m.
Experimental Investigation of Mooring Performance and Energy-Harvesting Performance of Eccentric Rotor Wave Energy Converter
Authors: Xue Gang , Qin Jian , Zhang Zhenquan , Huang Shuting , Liu Yanjun
Published: November 2022

To obtain the optimal mooring mode and the best-matching wave condition of an eccentric rotor wave energy converter (ERWEC), a physical model of the ERWEC was developed. Ten mooring modes and eight wave conditions were set up. Several experiments were carried out to analyze the influence of mooring modes and wave conditions on the mooring and energy-harvesting performances of the ERWEC. The results showed that the mooring and energy-harvesting performances changed significantly for the same mooring mode under various regular wave conditions, but the opposite situation was found under irregular wave conditions. The wave-facing direction of the buoy was a critical factor affecting the mooring and energy-harvesting performances, while the number of anchor lines had little effect on them. In addition, a method to evaluate the motion response of the buoy based on the number of effective excitations and a method to evaluate the comprehensive performance based on the cloud chart are proposed. The mooring mode and wave condition combination that obtained the optimal mooring and energy-harvesting performances for the ERWEC was determined. This paper provides a novel perspective on how to balance the efficiency and reliability of wave energy converters.
A Study of Banks’ Systemic Importance and Moral Hazard Behaviour: A Panel Threshold Regression Approach
Authors: Gupta C. P. , Jain Arushi
Published: November 2022

This study has two objectives, first, to investigate if the lending behaviour of banks exhibits moral hazard in the Indian Banking Industry, and second, to investigate whether banks’ moral hazard behaviour changes when the systemic importance of the banks is taken into consideration. We studied banks’ moral hazard behaviour by observing the impact of their level of Net Non-Performing Loans (NNPL) on their lending behaviour. This study used threshold panel regression by using 1 year lagged values of NNPL as the threshold variable to find its endogenously determined value that impacts the lending behaviour of the banks. The 1 year lagged value of the NNPL (threshold variable) has been used to depict the level of distress faced by a bank. Assuming that loans may turn bad any year after they are granted, a banks’ lending behaviour has been shown through the relationship between various lags of Loan Growth Rate (LGR) and the contemporaneous values of Net Non-Performing Loans (NNPL). As per our analysis, the loan growth ratio raises NPLs with a relatively higher value when banks are experiencing prior sizable loan losses as compared to when banks are relatively safe, indicating moral hazard behaviour in the Indian banking industry. However, when the systemic importance of the bank is considered, the systemically important banks are found to be engaged in risky lending irrespective of their level of distress, whereas the opposite results are found for the least important banks.
Feasibility Study of a Small-Scale Recirculating Aquaculture System for Sustainable (Peri-)Urban Farming in Sub-Saharan Africa: A Nigerian Perspective
Authors: Benjamin Emmanuel O. , Ola Oreoluwa , Buchenrieder Gertrud R.
Published: November 2022

The (peri-)urban population in developing countries, especially sub-Saharan Africa, is rapidly increasing. As towns and cities grow, so does the demand for fish protein. While flow-through aquaculture can provide fresh, healthy and nutritious fish protein, it is plagued by extensive land requirements as well as effluent discharge and is thus unsuitable for city regions. Alternatively, small-scale Recirculating Aquaculture Systems (RAS) could improve food and nutritional security and livelihoods as well as reduce environmental degradation in (peri-)urban areas despite land and water constraints. The question, however, remains—what are the key technical, business and managerial issues surrounding small-scale RAS in (peri-)urban farming? To answer this question, first, a systematic literature review on RAS in sub-Saharan Africa is conducted. Second, the RAS prototype of the Sustainable Aquaponics for Nutritional and Food Security in Urban Sub-Saharan Africa (SANFU) II project is assessed. This assessment is based on the mass balance and stock density, relevant for fish survival and/or availability as well as net cash flow analyses. The results suggest that small-scale RAS are technically and financially viable with efficient filtration and family labor having proper aquaculture monitoring and management skills. Furthermore, access to adequate equipment and inputs as well as electricity for the recirculating system are crucial. (Peri-)urban innovation actors will adopt RAS if operations are profitable.
Spatial Pattern and Ecological Process Difference Analyses of the Boundary Habitats of a Treeline Patch: A Case Study from the Li Mountain, North China
Authors: Jia Meiyu , Zhang Jintun , Song Zhenhui , Sadia Sehrish
Published: November 2022

Treeline patches are among Earth’s most sensitive and are important model ecosystems for assessing climate change trends. To explore ecological factors that limit the species’ survival in treelines, the treeline patch of Li Mountain National Nature Reserve was selected as the research site. Pinus armandii (P. armandii), Betula albo-sinensis (B. albo-sinensis), and Betula utilis (B. utilis) were selected as research species based on their dominance. Two 50 m × 50 m plots were established separately from the upper and lower limits of the highest treeline patch for point pattern analysis. Five 10 m × 10 m quadrats per plot were sampled to investigate the flora and environmental factors. The results showed that: (1) Slope and community composition at tree layer in quadrates had significant differences between upper and lower limits. Pinus armandii had a greater population size at the upper limit. Seedling recruitment restricted population development for B. albo-sinensis at the lower limit and B. utilis at the upper limit and less regeneration of B. albo-sinensis at the upper limit. (2) More aggregation scales occurred at the upper limit, and P. armandii had more aggregation scales than the other two species at 0–25 m. The heterogeneity caused by density distribution affected P. armandii pattern at the upper limit, and heterogeneity of seed dispersal could explain species patterns in both limits. Distinctness of size difference may have an influence on inter-specific species correlations.
An Investigation of Green Roof Spatial Distribution and Incentive Policies Using Green Buildings as a Benchmark
Authors: Chen Siwei , Gou Zhonghua
Published: November 2022

The global spread of green roofs is becoming increasingly important in the context of increasing urbanization and climate change as they provide multiple benefits, including urban heat island effect (UHI) mitigation, stormwater retention and urban flood risk reduction. However, current research provides little insight into how green roofs are used and promoted globally. Therefore, it is essential to look at the global spatial distribution of green roofs and the related policies by using green buildings which have been successfully promoted as a benchmark. This study collected data from multiple sources, such as a dataset of spatial distribution of green roofs from eight countries, and 124 green roof incentive policy texts from 88 cities. Spatial analysis was conducted using ArcGIS Pro, and different types of incentive policies were explored using word frequency analysis. The results show that (1) the unbalanced distribution of green roofs in cities is prominent, with significant regional differences and clustering characteristics along water systems; (2) in the vast majority of countries, the types of incentive policies for green roofs lack diversity; (3) green roofs lack a well-developed rating system compared to how green buildings are promoted. Combining green buildings with green roofs and exploring the gaps between them, this study will help further explore the application of green roofs worldwide and guide governments or non-governmental organizations to develop and implement more efficient policies and provide recommendations to promote the popularity of green roofs worldwide.
Performance Comparison of Different Particle Size Distribution Models in the Prediction of Soil Particle Size Characteristics
Authors: Zhang Hao , Wang Chong , Chen Zhengyan , Kang Qingyu , Xu Xiaohua , Gao Tianpeng
Published: November 2022

Particle size distribution (PSD) is a rich source of information about soil properties, including soil gradation and soil particle size characteristics. This paper compared the PSD prediction ability of three types of mathematical model. We selected nine models that have been proven to accurately predict sample points in previous studies, and we fit 144 pieces of experimental data on 12 texture classes of soil samples from the UNSODA database. We compared the models’ capability for predicting non-sample points, which is important for predicting soil particle size characteristics. Each model’s ability to predict non-sample points of different texture classes of soil was studied using a comprehensive ranking method. The relative differences in the models’ prediction of non-sample points of different texture classes of soil were analyzed using the relative error method. The results showed no considerable correlation between the number of model parameters and the prediction accuracy. For the various texture classes of soil, the Skaggs model and Weipeng model had the highest accuracy in predicting non-sample points, and the Skaggs model had the widest range of application. The Zhongling model and the Weibull model were better in predicting only one texture class of soil, respectively. The Fredlund model, Kolve model, Rosin model, Van Genuchten model and Best model were not as successful as other models. The Weipeng model overestimated the solid particle mass proportion, while the Skaggs model underestimated it when the clay particle content was greater than 20%. Both the Weipeng model and the Skaggs model demonstrated good prediction accuracy when the particle size was within the silt particle size range. The Skaggs model overestimated the particle mass proportion, while the Weipeng model underestimated it when the particle size was within the sand particle size range.
Geospatial Analysis of Abandoned Lands Based on Agroecosystems: The Distribution and Land Suitability for Agricultural Land Development in Indonesia
Authors: Mulyani Anny , Mulyanto Budi , Barus Baba , Panuju Dyah Retno , Husnain
Published: November 2022

The Indonesian land area is 191.1 million ha, part of which is abandoned land in various agroecosystems that have the potential for expanding the agricultural area. The purpose of this research was to geospatially analyze abandoned land based on its agroecosystem at the national and district levels, as well as to evaluate the land suitability of the land for expanding agricultural development. The methods included: (1) geospatial analysis of the national land cover map at a scale of 1:250,000 combined with soil and climate information to identify abandoned land and examine its agroecosystem, (2) selecting representative districts in each agroecosystem for visual interpretation using high-resolution imagery, i.e., SPOT 6/7, (3) assessing the land suitability of abandoned land for agricultural development at the national and district levels, and (4) predicting national abandoned land and its land suitability. The essential finding is the identification of abandoned land at around 42.6 million ha in Indonesia distributed over six agroecosystems, with the widest being in dry lowland and wet climates. Then, 54 districts were selected to characterize abandoned land by using SPOT 6/7 high-resolution imagery and were interpreted visually. It was found that the abandoned land covered approximately 16.9 million ha. The distribution of abandoned land from the interpretation of satellite imagery was smaller than that of geospatial analysis due to differences in the map scale and the use of ancillary data. The identification of abandoned land from high-resolution imagery should be carried out for all regions of Indonesia to accurately map the distribution of the abandoned land and characterize the properties. However, it requires a large amount of time, cost, and facilities to complete the inventory. The geospatial analysis that combined imageries and ancillary data identified 27.7 million ha of abandoned land suitable for expanding the agricultural area. The largest suitable abandoned land for the purpose was found in the lowlands with a wet climate, especially in Papua, Kalimantan, and Sumatra islands. The identified suitable abandoned land of 54 districts differed by scale, in which it was 11.2 million ha at the scale of 1:250,000 and 8.5 million ha at the scale of 1:50,000, respectively. The potential land expansion for food crops, particularly paddy fields, was only 2.2 million ha, located in mineral swamp land, which was predominantly located in Papua, with inadequate accessibility. Expanding paddy fields for national food security in the future would be constrained by less suitable land resources, while the near future challenge is the competition of land allocation for agricultural and non-agricultural sectors, as well as for food crops and plantations.
Evaluating Agricultural Extension Agent’s Sustainable Cotton Land Production Competencies: Subject Matter Discrepancies Restricting Farmers’ Information Adoption
Authors: Seitz Paige , Strong Robert , Hague Steve , Murphrey Theresa P.
Published: November 2022

Cotton is more chemically intensive than many other commodities, which negatively impacts rural livelihoods at higher rates. Improvement in environmental stewardship of cotton would substantially impact the long-term sustainability of agriculture in cotton producing regions globally. Extension personnel provide producer education to improve these issues that ultimately impact economic growth and quality of life in rural areas, but their proficiency to foster innovation and diffusion of crop-specific content is unknown. A 48-item survey was administered to agricultural extension personnel in five U.S. states to develop an understanding of extension professionals’ current knowledge in sustainable cotton production and sustainability, identify pertinent training needs to address in future professional development curricula, and to discern the value of crop-specific competency evaluation in organizational needs assessment. A ranked discrepancy model and an exploratory factor analysis of survey results indicated a glaring need for training in all evaluated competency areas to improve sustainability in cotton producing regions. Synchronous or asynchronous trainings could be developed for change agents to better serve the needs of rural cotton producers. Knowledge transfer or adoption diffusion of rural land sustainability recommendations to farmers will be challenging to achieve in the study’s region until change agent’s proficiency of sustainable cotton production practices improves.
A Design for High-Speed Journal Bearings with Reduced Pad Size and Improved Efficiency
Authors: Hagemann Thomas , Vetter Daniel , Wettmarshausen Sören , Stottrop Michael , Engels Alexander , Weißbacher Christoph , Bender Beate , Schwarze Hubert
Published: November 2022

Improving efficiency is a general task in the design process of high-speed journal bearings. A specific fixed-pad bearing geometry featuring reduced pad length and additional design measures with the intention of reducing frictional power loss is investigated, experimentally and theoretically, for a journal diameter of 500 mm up to surface speeds of 94 m/s and unit loads of 5.0 MPa. To model fluid flow in the bearing outside the lubricant gap, an extension to Elrod’s cavitation algorithm based on assuming the inertia of fluid flow is proposed. Validation of the extended thermo-elasto-hydrodynamic lubrication (TEHL) model shows good agreement between measurement and prediction in wide operating ranges, however, with systematic tendencies of the remaining deviations. Furthermore, measured local pressure and film thickness distributions indicate a complex formation of cavitation with an influence of axial flow that is not covered by pure Couette-flow in the cavitation region. Measured as well as predicted data prove increased bearing efficiency for high rotor speeds. To provide understanding on the impact of the applied design measures improving efficiency, their combination is separated into the individual ones. Reduced axial and peripheral pad length both contribute almost equally to the reduction in power loss and improve its value by 37% compared to the standard design. Finally, further steps to deeper identify the behavior of the bearing are comprehensively discussed.
Synthesis and Crystal Structures of Halogen-Substituted 2-Aryl-N-phenylbenzimidazoles
Authors: Koptyaeva Anastasia G. , Zakharov Alexander Y. , Kiseleva Marina A. , Mariasina Sofia S. , Kalle Paulina , Churakov Andrei V. , Bezzubov Stanislav I.
Published: November 2022

Four 2-arylbenzimidazoles (aryl = 4-Br-phenyl (1), 3-Br-phenyl (2), 4-I-phenyl (3), 3-I-phenyl (4)) were synthesized and characterized by 1H, 13C{1H} NMR, UV–Vis spectroscopy and single-crystal X-ray diffraction. Both pairs of benzimidazoles bearing the halogen atom at the same position form isostructural crystals, in which para-substituted compounds 1 and 3 are assembled by weak C–H···π and π···π interactions while their meta-isomers 2 and 4 are linked via intermolecular halogen···nitrogen and C–H···π contacts.
Speed Tracking for IFOC Induction Motor Speed Control Using Hybrid Sensorless Speed Estimator Based on Flux Error for Electric Vehicles Application
Authors: Sepeeh Muhamad Syazmie , Zulkifli Shamsul Aizam , Sim Sy Yi , Chiu Huang-Jen , Wanik Mohd Zamri Che
Published: November 2022

This paper presents hybrid sensorless speed tracking by an indirect field-oriented control (IFOC) for an induction motor (IM). The sensorless model is based on an improved virtual estimation topology model to predict the virtual speed and flux of the IM using stator current components. The hybrid sensorless model, defined as a modification of voltage with a rotor flux-oriented current model, was also implemented with proportional-integral (PI) control for comparison with the conventional voltage model (CVM). The suggested adaptive mechanism for PI control in the hybrid estimator was able to compensate for the back-EMF error from the rotor flux-oriented current model into the voltage model and change the air gap flux of the IM. An accurate rotor flux position was estimated and used to estimate the speed with low speed error. This IFOC model, with various speed change references, was tested in a simulation environment by using the MATLAB/Simulink program. The proposed hybrid estimator was tested in two different EV operations, which were reverse and forward operations. The effectiveness of the proposed estimator was analyzed for its transient and steady-state performances based on settling time, recovery time and the overshoot and speed error percentages. All the results were in good agreement in terms of the stability of the speed and current controller with minimum speed error obtained, where the average errors were 0.08% and 0.16% for high speed and lower speed, respectively.
Research on a Visual Servoing Control Method Based on Perspective Transformation under Spatial Constraint
Authors: Cao Chenguang
Published: November 2022

Visual servoing has been widely employed in robotic control to increase the flexibility and precision of a robotic arm. When the end-effector of the robotic arm needs to be moved to a spatial point without a coordinate, the conventional visual servoing control method has difficulty performing the task. The present work describes space constraint challenges in a visual servoing system by introducing an assembly node and then presents a two-stage visual servoing control approach based on perspective transformation. A virtual image plane is constructed using a calibration-derived homography matrix. The assembly node, as well as other objects, are projected into the plane after that. Second, the controller drives the robotic arm by tracking the projections in the virtual image plane and adjusting the position and attitude of the workpiece accordingly. Three simple image features are combined into a composite image feature, and an active disturbance rejection controller (ADRC) is established to improve the robotic arm’s motion sensitivity. Real-time simulations and experiments employing a robotic vision system with an eye-to-hand configuration are used to validate the effectiveness of the presented method. The results show that the robotic arm can move the workpiece to the desired position without using coordinates.
Fisher-like Metrics Associated with ϕ-Deformed (Naudts) Entropies
Authors: Pripoae Cristina-Liliana , Hirica Iulia-Elena , Pripoae Gabriel-Teodor , Preda Vasile
Published: November 2022

The paper defines and studies new semi-Riemannian generalized Fisher metrics and Fisher-like metrics, associated with entropies and divergences. Examples of seven such families are provided, based on exponential PDFs. The particular case when the basic entropy is a ϕ-deformed one, in the sense of Naudts, is investigated in detail, with emphasis on the variation of the emergent scalar curvatures. Moreover, the paper highlights the impact on these geometries determined by the addition of some group logarithms.
Distributionally Robust Optimization Model for a Minimum Cost Consensus with Asymmetric Adjustment Costs Based on the Wasserstein Metric
Authors: Wu Ziqi , Zhu Kai , Qu Shaojian
Published: November 2022

When solving the problem of the minimum cost consensus with asymmetric adjustment costs, decision makers need to face various uncertain situations (such as individual opinions and unit adjustment costs for opinion modifications in the up and down directions). However, in the existing methods for dealing with this problem, robust optimization will lead to overly conservative results, and stochastic programming needs to know the exact probability distribution. In order to overcome these shortcomings, it is essential to develop a novelty consensus model. Thus, we propose three new minimum-cost consensus models with a distributionally robust method. Uncertain parameters (individual opinions, unit adjustment costs for opinion modifications in the up and down directions, the degree of tolerance, and the range of thresholds) were investigated by modeling the three new models, respectively. In the distributionally robust method, the construction of an ambiguous set is very important. Based on the historical data information, we chose the Wasserstein ambiguous set with the Wasserstein distance in this study. Then, three new models were transformed into a second-order cone programming problem to simplify the calculations. Further, a case from the EU Trade and Animal Welfare (TAW) program policy consultation was used to verify the practicability of the proposed models. Through comparison and sensitivity analysis, the numerical results showed that the three new models fit the complex decision environment better.
Exponential Graph Regularized Non-Negative Low-Rank Factorization for Robust Latent Representation
Authors: Yang Guowei , Zhang Lin , Wan Minghua
Published: November 2022

Non-negative matrix factorization (NMF) is a fundamental theory that has received much attention and is widely used in image engineering, pattern recognition and other fields. However, the classical NMF has limitations such as only focusing on local information, sensitivity to noise and small sample size (SSS) problems. Therefore, how to develop the NMF to improve the performance and robustness of the algorithm is a worthy challenge. Based on the bottlenecks above, we propose an exponential graph regularization non-negative low-rank factorization algorithm (EGNLRF) combining sparseness, low rank and matrix exponential. Firstly, based on the assumption that the data is corroded, we decompose a given raw data item with a data error fitting noise matrix, applying a low-rank constraint to the denoising data. Then, we perform a non-negative factorization on the resulting low-rank matrix, from which we derive the low-dimensional representation of the original matrix. Finally, we use the low-dimensional representation for graph embedding to maintain the geometry between samples. The graph embedding terms are matrix exponentiated to cope with SSS problems and nearest neighbor sensitivity. The above three steps will be incorporated into a joint framework to validate and optimize each other; therefore, we can learn latent data representations that are undisturbed by noise and preserve the local structure of known samples. We conducted simulation experiments on different datasets and verified the effectiveness of the algorithm by comparing the proposed with the lasting ones related to NMF, low rank and graph embedding.
Quantification of Aversion to Uncertainty in Intertemporal Choice through Subjective Perception of Time
Authors: Ventre Viviana , Martino Roberta
Published: November 2022

Intertemporal choices are those decisions structured over several periods in which the effects only manifest themselves with the passage of time. The main mathematical reference for studying the behavior of individuals with respect to this type of decision is the Discounted Utility Model which hypothesizes completely rational individuals. The empirical evidence that deviates from normative expectations has motivated the formulation of alternative models with the aim of better describing the behavior of individuals. The present paper investigates the characteristics behind hyperbolic discounting starting from the phenomenon of decision inconsistency, i.e., when individuals’ preferences vary over time. The mechanisms of inconsistency will be explored through the physical concept of relative time, proving the importance of uncertainty aversion in the hyperbolic trend of the discount function. The analysis of the mathematical characteristics of hyperbolic discounting and the relationship between decision inconsistency and subjective perception of time defines the maximum distance between rational and non-rational preferences. An experimental part empirically proves the relationship between uncertainty aversion and time inconsistency. The present paper contributes to the literature by defining a new characteristic of hyperbolic discounting and quantifying the impact of the subjective perception of time in the decision-making process.
Gain-Switched Short Pulse Generation from 1.55 µm InAs/InP/(113)B Quantum Dot Laser Modeled Using Multi-Population Rate Equations
Authors: Tunc Hilal S. Duranoglu , Dogru Nuran , Cengiz Erkan
Published: November 2022

The gain-switching properties of an InAs-InP (113)B quantum dot laser based on multi-population rate equations are examined theoretically in detail to generate shorter pulses with the application of a Gaussian pulse beam to the laser excited state. The numerical results demonstrated that as the homogeneous and the inhomogeneous broadening increase, the differential gain, the gain compression factor, and the threshold current of the excited state decrease while the threshold current of the ground state increases. It was also observed that the contribution of the excited state to gain-switched output pulses depend on not only the value of the inhomogeneous broadening but also the magnitude of the applied current. Additionally, it was found that without an optical beam, the output pulse has a long pulse width due to ground state emissions and the change in the parameters strongly affecting the output. However, under the optical beam, narrow pulses around 26 ps have high peak power owing to the excited state emission generated even at low currents and also the change in the laser parameters having a negligible effect. Finally, the gain-switching characteristics with and without a Gaussian pulse beam are shown to be similar for liner-gain and nonlinear-gain cases except that higher peak power and narrower output pulses are obtained for the linear-gain case.
Robust Appointment Scheduling in Healthcare
Authors: Gao Yuan , Zhang Qian , Lau Chun Kit , Ram Bhagwat
Published: November 2022

The quality and experience of healthcare systems affect the economy and prosperity of cities all over the world. Governments of several countries are struggling to improve the efficiency of their healthcare systems and decrease healthcare spending costs. In this paper, we discuss one of the most critical and busy processes among healthcare topics: ambulatory care center (ACC) appointment scheduling systems. We investigate the appointment-scheduling issue using a robust optimization framework to minimize operational costs while ensuring the improvement of healthcare service quality. Our findings and insights provide healthcare practitioners with tools to improve operational efficiency and service quality.
Correlational and Configurational Analysis of Factors Influencing Potential Patients’ Attitudes toward Surgical Robots: A Study in the Jordan University Community
Authors: de Andres-Sanchez Jorge , Almahameed Ala Ali , Arias-Oliva Mario , Pelegrin-Borondo Jorge
Published: November 2022

The literature on surgical robots (SRs) usually adopts the perspective of healthcare workers. However, research on potential patients’ perceptions and the publics’ points of view on SRs is scarce. This fact motivates our study, which assesses the factors inducing the SRs acceptance in the opinion of potential patients. We consider three variables, based on the unified theory of acceptance and the use of technology (UTAUT): the performance expectancy (PE), the effort expectancy (EE), and the social influence (SI); pleasure (PL), arousal (AR), and the perceived risk (PR). To deal with empirical data, we used the ordered logistic regression (OLR) and the fuzzy set comparative qualitative analysis (fsQCA). The OLR allowed us to check for a significant positive average influence of the UTAUT variables and PL, on the intention to undergo robotic surgery. However, the PR had a significant negative impact, and AR was not found to be significant. The FsQCA allowed the identification of the potential patient profiles, linked to acceptance of and resistance to SRs and confirmed that they are not symmetrical. The proposed input variables are presented as core conditions in at least one prime implicate robotic-assisted surgery acceptance. The exception to this statement is the PR, which is affirmed in some recipes and absent in others. The recipes explaining the resistance to SRs were obtained by combining the absence of PE, EE, SI, and PL (i.e., these variables have a negative impact on rejection) and the presence of the PR (i.e., the perceived risk has a positive impact on a resistance attitude toward SRs). Similarly, arousal played a secondary role in explaining the rejection.
Adaptive Sensorless PI+Passivity-Based Control of a Boost Converter Supplying an Unknown CPL
Authors: Riffo Sebastián , Gil-González Walter , Montoya Oscar Danilo , Restrepo Carlos , Muñoz Javier
Published: November 2022

This paper presents an adaptive control to stabilize the output voltage of a DC–DC boost converter that feeds an unknown constant power load (CPL). The proposed controller employs passivity-based control (PBC), which assigns a desired system energy to compensate for the negative impedance that may be generated by a CPL. A proportional-integral (PI) action that maintains a passive output is added to the PBC to impose the desired damping and enhance disturbance rejection behavior, thus forming a PI+PBC control. In addition, the proposed controller includes two estimators, i.e., immersion and invariance (I&I), and disturbance observer (DO), in order to estimate CPL and supply voltage for the converter, respectively. These observers become the proposed controller for an adaptive, sensorless PI+PBC control. Phase portrait analysis and experimental results have validated the robustness and effectiveness of the adaptive proposed control approach. These results show that the proposed controller adequately regulates the output voltage of the DC–DC boost converter under variations of the input voltage and CPL simultaneously.
Transient Dynamic Response Analysis of Two-Dimensional Saturated Soil with Singular Boundary Method
Authors: Liu Dongdong , Wei Xing , Li Chengbin , Han Chunguang , Cheng Xiaxi , Sun Linlin
Published: November 2022

In this paper, the singular boundary method (SBM) in conjunction with the exponential window method (EWM) is firstly extended to simulate the transient dynamic response of two-dimensional saturated soil. The frequency-domain (Fourier space) governing equations of Biot theory is solved by the SBM with a linear combination of the fundamental solutions. In order to avoid the perplexing fictitious boundary in the method of fundamental solution (MFS), the SBM places the source point on the physical boundary and eliminates the source singularity of the fundamental solution via the origin intensity factors (OIFs). The EWM is carried out for the inverse Fourier transform, which transforms the frequency-domain solutions into the time-domain solutions. The accuracy and feasibility of the SBM-EWM are verified by three numerical examples. The numerical comparison between the MFS and SBM indicates that the SBM takes a quarter of the time taken by the MFS.
Multi-Strategy Improved Sparrow Search Algorithm and Application
Authors: Liu Xiangdong , Bai Yan , Yu Cunhui , Yang Hailong , Gao Haoning , Wang Jing , Chang Qing , Wen Xiaodong
Published: November 2022

The sparrow search algorithm (SSA) is a metaheuristic algorithm developed based on the foraging and anti-predatory behavior of sparrow populations. Compared with other metaheuristic algorithms, SSA also suffers from poor population diversity, has weak global comprehensive search ability, and easily falls into local optimality. To address the problems whereby the sparrow search algorithm tends to fall into local optimum and the population diversity decreases in the later stage of the search, an improved sparrow search algorithm (PGL-SSA) based on piecewise chaotic mapping, Gaussian difference variation, and linear differential decreasing inertia weight fusion is proposed. Firstly, we analyze the improvement of six chaotic mappings on the overall performance of the sparrow search algorithm, and we finally determine the initialization of the population by piecewise chaotic mapping to increase the initial population richness and improve the initial solution quality. Secondly, we introduce Gaussian difference variation in the process of individual iterative update and use Gaussian difference variation to perturb the individuals to generate a diversity of individuals so that the algorithm can converge quickly and avoid falling into localization. Finally, linear differential decreasing inertia weights are introduced globally to adjust the weights so that the algorithm can fully traverse the solution space with larger weights in the first iteration to avoid falling into local optimum, and we enhance the local search ability with smaller weights in the later iteration to improve the search accuracy of the optimal solution. The results show that the proposed algorithm has a faster convergence speed and higher search accuracy than the comparison algorithm, the global search capability is significantly enhanced, and it is easier to jump out of the local optimum. The improved algorithm is also applied to the Heating, Ventilation and Air Conditioning (HVAC) system control optimization direction, and the improved algorithm is used to optimize the parameters of the HVAC system Proportion Integral Differential (PID) controller. The results show that the PID controller optimized by the improved algorithm has higher control accuracy and system stability, which verifies the feasibility of the improved algorithm in practical engineering applications.
An Efficient Two-Step Iterative Family Adaptive with Memory for Solving Nonlinear Equations and Their Applications
Authors: Sharma Himani , Kansal Munish , Behl Ramandeep
Published: November 2022

We propose a new iterative scheme without memory for solving nonlinear equations. The proposed scheme is based on a cubically convergent Hansen–Patrick-type method. The beauty of our techniques is that they work even though the derivative is very small in the vicinity of the required root or f′(x)=0. On the contrary, the previous modifications either diverge or fail to work. In addition, we also extended the same idea for an iterative method with memory. Numerical examples and comparisons with some of the existing methods are included to confirm the theoretical results. Furthermore, basins of attraction are included to describe a clear picture of the convergence of the proposed method as well as that of some of the existing methods. Numerical experiments are performed on engineering problems, such as fractional conversion in a chemical reactor, Planck’s radiation law problem, Van der Waal’s problem, trajectory of an electron in between two parallel plates. The numerical results reveal that the proposed schemes are of utmost importance to be applied on various real–life problems. Basins of attraction also support this aspect.