bluuebunny/crossref_metadata_2025 huggingface dataset:
Building Height Extraction from GF-7 Satellite Images Based on Roof Contour Constrained Stereo Matching
Authors: Zhang Chenni , Cui Yunfan , Zhu Zeyao , Jiang San , Jiang Wanshou
Published: March 2022

Building height is one of the basic geographic information for planning and analysis in urban construction. It is still very challenging to estimate the accurate height of complex buildings from satellite images, especially for buildings with podium. This paper proposes a solution for building height estimation from GF-7 satellite images by using a roof contour constrained stereo matching algorithm and DSM (Digital Surface Model) based bottom elevation estimation. First, an object-oriented roof matching algorithm is proposed based on building contour to extract accurate building roof elevation from GF-7 stereo image, and DSM generated from the GF-7 stereo images is then used to obtain building bottom elevation. Second, roof contour constrained stereo matching is conducted between backward and forward image blocks, in which the difference of standard deviation maps is used for the similarity measure. To deal with the multi-height problem of podium buildings, the gray difference image is adopted to segment podium buildings, and re-matching is conducted to find out their actual heights. Third, the building height is obtained through the elevation difference between the building top and bottom, in which the evaluation of the building bottom is calculated according to the elevation histogram statistics of the building buffer in DSM. Finally, two GF-7 stereo satellite images, collected in Yingde, Guangzhou, and Xi’an, Shanxi, are used for performance evaluation. Besides, the aerial LiDAR point cloud is used for absolute accuracy evaluation. The results demonstrate that compared with other methods, our solution obviously improves the accuracy of height estimation of high-rise buildings. The MAE (Mean Absolute Error) of the estimated building heights in Yingde is 2.31 m, and the MAE of the estimated elevation of building top and bottom is approximately 1.57 m and 1.91 m, respectively. Then the RMSE (Root Mean Square Error) of building top and bottom is 2.01 m and 2.57 m. As for the Xi’an dataset with 7 buildings with podium out of 40 buildings, the MAE of the estimated building height is 1.69 m and the RMSE is 2.34 m. The proposed method can be an effective solution for building height extraction from GF-7 satellite images.
NDSRGAN: A Novel Dense Generative Adversarial Network for Real Aerial Imagery Super-Resolution Reconstruction
Authors: Guo Mingqiang , Zhang Zeyuan , Liu Heng , Huang Ying
Published: March 2022

In recent years, more and more researchers have used deep learning methods for super-resolution reconstruction and have made good progress. However, most of the existing super-resolution reconstruction models generate low-resolution images for training by downsampling high-resolution images through bicubic interpolation, and the models trained from these data have poor reconstruction results on real-world low-resolution images. In the field of unmanned aerial vehicle (UAV) aerial photography, the use of existing super-resolution reconstruction models in reconstructing real-world low-resolution aerial images captured by UAVs is prone to producing some artifacts, texture detail distortion and other problems, due to compression and fusion processing of the aerial images, thereby resulting in serious loss of texture detail in the obtained low-resolution aerial images. To address this problem, this paper proposes a novel dense generative adversarial network for real aerial imagery super-resolution reconstruction (NDSRGAN), and we produce image datasets with paired high- and low-resolution real aerial remote sensing images. In the generative network, we use a multilevel dense network to connect the dense connections in a residual dense block. In the discriminative network, we use a matrix mean discriminator that can discriminate the generated images locally, no longer discriminating the whole input image using a single value but instead in chunks of regions. We also use smoothL1 loss instead of the L1 loss used in most existing super-resolution models, to accelerate the model convergence and reach the global optimum faster. Compared with traditional models, our model can better utilise the feature information in the original image and discriminate the image in patches. A series of experiments is conducted with real aerial imagery datasets, and the results show that our model achieves good performance on quantitative metrics and visual perception.
Global GNSS-RO Electron Density in the Lower Ionosphere
Authors: Wu Dong L. , Emmons Daniel J. , Swarnalingam Nimalan
Published: March 2022

Lack of instrument sensitivity to low electron density (Ne) concentration makes it difficult to measure sharp Ne vertical gradients (four orders of magnitude over 30 km) in the D/E-region. A robust algorithm is developed to retrieve global D/E-region Ne from the high-rate GNSS radio occultation (RO) data, to improve spatiotemporal coverage using recent SmallSat/CubeSat constellations. The new algorithm removes F-region contributions in the RO excess phase profile by fitting a linear function to the data below the D-region. The new GNSS-RO observations reveal many interesting features in the diurnal, seasonal, solar-cycle, and magnetic-field-dependent variations in the Ne morphology. While the D/E-region Ne is a function of solar zenith angle (χ), it exhibits strong latitudinal variations for the same χ with a distribution asymmetric about noon. In addition, large longitudinal variations are observed along the same magnetic field pitch angle. The summer midlatitude Ne and sporadic E (Es) show a distribution similar to each other. The distribution of auroral electron precipitation correlates better with the pitch angle from the magnetosphere than from one at 100 km. Finally, a new TEC retrieval technique is developed for the high-rate RO data with a top reaching at least 120 km. For better characterization of the E- to F-transition in Ne and more accurate TEC retrievals, it is recommended to have all GNSS-RO acquisition routinely up to 220 km.
Tuning the Sensing Properties of N and S Co-Doped Carbon Dots for Colorimetric Detection of Copper and Cobalt in Water
Authors: Bisauriya Ramanand , Antonaroli Simonetta , Ardini Matteo , Angelucci Francesco , Ricci Antonella , Pizzoferrato Roberto
Published: March 2022

In this study, nitrogen and sulfur co-doped carbon dots (NS-CDs) were investigated for the detection of heavy metals in water through absorption-based colorimetric response. NS-CDs were synthesized by a simple one-pot hydrothermal method and characterized by TEM, STEM-coupled with energy dispersive X-ray analysis, NMR, and IR spectroscopy. Addition of Cu(II) ions to NS-CD aqueous solutions gave origin to a distinct absorption band at 660 nm which was attributed to the formation of cuprammonium complexes through coordination with amino functional groups of NS-CDs. Absorbance increased linearly with Cu(II) concentration in the range 1–100 µM and enabled a limit of detection of 200 nM. No response was observed with the other tested metals, including Fe(III) which, however, appreciably decreased sensitivity to copper. Increase of pH of the NS-CD solution up to 9.5 greatly reduced this interference effect and enhanced the response to Cu(II), thus confirming the different nature of the two interactions. In addition, a concurrent response to Co(II) appeared in a different spectral region, thus suggesting the possibility of dual-species multiple sensitivity. The present method neither requires any other reagents nor any previous assay treatment and thus can be a promising candidate for low-cost monitoring of copper onsite and by unskilled personnel.
Sensor-Based Gym Physical Exercise Recognition: Data Acquisition and Experiments
Authors: Hussain Afzaal , Zafar Kashif , Baig Abdul Rauf , Almakki Riyad , AlSuwaidan Lulwah , Khan Shakir
Published: March 2022

Automatic tracking and quantification of exercises not only helps in motivating people but also contributes towards improving health conditions. Weight training, in addition to aerobic exercises, is an important component of a balanced exercise program. Excellent trackers are available for aerobic exercises but, in contrast, tracking free weight exercises is still performed manually. This study presents the details of our data acquisition effort using a single chest-mounted tri-axial accelerometer, followed by a novel method for the recognition of a wide range of gym-based free weight exercises. Exercises are recognized using LSTM neural networks and the reported results confirm the feasibility of the proposed approach. We train and test several LSTM-based gym exercise recognition models. More specifically, in one set of experiments, we experiment with separate models, one for each muscle group. In another experiment, we develop a universal model for all exercises. We believe that the promising results will potentially contribute to the vision of an automated system for comprehensive monitoring and analysis of gym-based exercises and create a new experience for exercising by freeing the exerciser from manual record-keeping.
Condition Monitoring of Ball Bearings Based on Machine Learning with Synthetically Generated Data
Authors: Kahr Matthias , Kovács Gabor , Loinig Markus , Brückl Hubert
Published: March 2022

Rolling element bearing faults significantly contribute to overall machine failures, which demand different strategies for condition monitoring and failure detection. Recent advancements in machine learning even further expedite the quest to improve accuracy in fault detection for economic purposes by minimizing scheduled maintenance. Challenging tasks, such as the gathering of high quality data to explicitly train an algorithm, still persist and are limited in terms of the availability of historical data. In addition, failure data from measurements are typically valid only for the particular machinery components and their settings. In this study, 3D multi-body simulations of a roller bearing with different faults have been conducted to create a variety of synthetic training data for a deep learning convolutional neural network (CNN) and, hence, to address these challenges. The vibration data from the simulation are superimposed with noise collected from the measurement of a healthy bearing and are subsequently converted into a 2D image via wavelet transformation before being fed into the CNN for training. Measurements of damaged bearings are used to validate the algorithm’s performance.
Industry 4.0 Technologies Applied to the Rail Transportation Industry: A Systematic Review
Authors: Laiton-Bonadiez Camilo , Branch-Bedoya John W. , Zapata-Cortes Julian , Paipa-Sanabria Edwin , Arango-Serna Martin
Published: March 2022

Background: Industry 4.0 technologies have been widely used in the railway industry, focusing mainly on maintenance and control tasks necessary in the railway infrastructure. Given the great potential that these technologies offer, the scientific community has come to use them in varied ways to solve a wide range of problems such as train failures, train station security, rail system control and communication in hard-to-reach areas, among others. For this reason, this paper aims to answer the following research questions: what are the main issues in the railway transport industry, what are the technologic strategies that are currently being used to solve these issues and what are the technologies from industry 4.0 that are used in the railway transport industry to solve the aforementioned issues? Methods: This study adopts a systematic literature review approach. We searched the Science Direct and Web of Science database inception from January 2017 to November 2021. Studies published in conferences or journals written in English or Spanish were included for initial process evaluation. The initial included papers were analyzed by authors and selected based on whether they helped answer the proposed research questions or not. Results: Of the recovered 515 articles, 109 were eligible, from which we could identify three main application domains in the railway industry: monitoring, decision and planification techniques, and communication and security. Regarding industry 4.0 technologies, we identified 9 different technologies applied in reviewed studies: Artificial Intelligence (AI), Internet of Things (IoT), Cloud Computing, Big Data, Cybersecurity, Modelling and Simulation, Smart Decision Support Systems (SDSS), Computer Vision and Virtual Reality (VR). This study is, to our knowledge, one of the first to show how industry 4.0 technologies are currently being used to tackle railway industry problems and current application trends in the scientific community, which is highly useful for the development of future studies and more advanced solutions. Funding: Colombian national organizations Minciencias and the Mining-Energy Planning Unit.
Performance and Capability Assessment in Surgical Subtask Automation
Authors: Nagy Tamás D. , Haidegger Tamás
Published: March 2022

Robot-Assisted Minimally Invasive Surgery (RAMIS) has reshaped the standard clinical practice during the past two decades. Many believe that the next big step in the advancement of RAMIS will be partial autonomy, which may reduce the fatigue and the cognitive load on the surgeon by performing the monotonous, time-consuming subtasks of the surgical procedure autonomously. Although serious research efforts are paid to this area worldwide, standard evaluation methods, metrics, or benchmarking techniques are still not formed. This article aims to fill the void in the research domain of surgical subtask automation by proposing standard methodologies for performance evaluation. For that purpose, a novel characterization model is presented for surgical automation. The current metrics for performance evaluation and comparison are overviewed and analyzed, and a workflow model is presented that can help researchers to identify and apply their choice of metrics. Existing systems and setups that serve or could serve as benchmarks are also introduced and the need for standard benchmarks in the field is articulated. Finally, the matter of Human–Machine Interface (HMI) quality, robustness, and the related legal and ethical issues are presented.
Fairness Concern in Remanufacturing Supply Chain—A Comparative Analysis of Channel Members’ Fairness Preferences
Authors: Zhang Xuemei , Cao Jian , Zhao Yang , Lu Jiansha
Published: March 2022

Remanufacturing is a sustainable product reutilization strategy to realize responsible consumption and production. However, it has remained a largely untapped opportunity for enhancing productivity due to some behavioral matters such as fairness concerns of remanufacturing related firms. Concerning the emerging and development of remanufacturing industry, this paper provides a game-theoretic analysis for a remanufacturing supply chain (RSC) consisting of one leading manufacturer and a following retailer, with the inclusion of fairness concern. We propose and compare several scenarios of channel members’ fairness preferences as, both members are fairness concerned, only one member is fairness concerned, and both members are fair neutral, to expound how fairness concern affects RSC strategies and resulting utilities. We also demonstrate dynamic evolution and stable state of channel members’ selections of whether being fairness concerned in the long term. Analytical results show that favorable scenarios for the RSC to achieve desired objective are relevant to its preference for improved supply chain performance or enhanced environmental benefit. Whatever the preference is, however, it is detrimental for both members to be fairness concerned in the short term. In the long term, evolutionary stable strategies of fairness concerns indicate that both members or only one member would choose to be fairness concerned. The eventual status relies on the initial state of fairness preference. The results are especially relevant as a reference for remanufacturing related strategies, thus enhancing production sustainability as well as environmental benefits.
Operation-Driven Power Analysis of Discrete Process in a Cyber-Physical System Based on a Modularized Factory
Authors: Um Jumyung , Park Taebyeong , Cho Hae-Won , Shin Seung-Jun
Published: March 2022

As the legislative pressure to reduce energy consumption is increasing, data analysis of power consumption is critical in the production planning of manufacturing facilities. In previous studies, a machine, conducting a single continuous operation, has been mainly observed for power estimation. However, a modularized production line, which conducts complex discrete operations, is more like the actual factory system than an identical simple machine. During the information collection of such production lines, it is important to interpret and distinguish mixed signals from multiple machines to ensure that there is no reduction in the information quality due to noise and signal fusion and discrete events. A data pipeline from data collection from different sources to pre-processing, data conversion, synchronization, and deep learning classification to estimate the total power use of the future process plan is proposed herein. The pipeline also establishes an auto-labeled data set of individual operations that contributes to building power estimation models without manual data pre-processing. The proposed system is applied to a modular factory connected with machine controllers using standardized protocols individually and linked to a centralized power monitoring system. Specifically, a robot arm cell was investigated to evaluate the pipeline with the result of the power profile synchronized with the robot program.
Investigating the Impact of Wind Power Integration on Damping Characteristics of Low Frequency Oscillations in Power Systems
Authors: Chen Jian , Jin Tao , Mohamed Mohamed A. , Annuk Andres , Dampage Udaya
Published: March 2022

This paper investigates the impact of doubly-fed induction generator (DFIG) wind farms on system stability in multi-generator power systems with low-frequency oscillations (LFOs). To this end, this paper establishes the interconnection model of the equivalent generators and derives the system state equation. On this basis, an updated system state equation of the new power system with integrated wind power is further derived. Then, according to the updated system state equation, the impact factors that cause changes in the system damping characteristics are presented. The IEEE two-area four-machine power system is used as a simulation model in which the LFOs occur. The simulation results demonstrate that the connection of wind power to the power feeding area (PFA) increases the damping ratio of the dominant mode of inter-area oscillation from −0.0263 to −0.0107, which obviously improves the system stability. Furthermore, the wind power integration into PFA, as the connection distance of the wind power increases, gradually decreases the damping ratio of the dominant mode of the inter-area oscillation to −0.0236, approaching that of no wind power in the system. Meanwhile, with the increase in the wind power output capacity, the damping ratio of the dominant mode of the intra-area and inter-area oscillation increases, and the maximum damping ratios reach 0.1337 and 0.0233, respectively.
Sustainable Tourism Issues in European Countries during the Global Pandemic Crisis
Authors: Palazzo Maria , Gigauri Iza , Panait Mirela Clementina , Apostu Simona Andreea , Siano Alfonso
Published: March 2022

Sustainable economic growth can be achieved through tourism by protecting the environment, maintaining natural resources, creating employment, improving cultural diversity, and recognizing cultural heritage values. The concept of tourism sustainability is gradually growing globally and becoming a dominant aspect in modern business, as companies need to meet stakeholders’ demands regarding environmental management. Sustainable tourism incorporates environmental, social, economic, and cultural issues into operations. The demand for green tourism, ethical consumption, protection of natural resources, and living close to nature is expected to increase. In particular, the latter gains more and more popularity due to the stress caused by the global pandemic and also because values have been re-evaluated at every level of society. In this paper, we explore sustainability in the tourism industry within the international context during the COVID-19 pandemic, with a specific focus on tourism in 35 European countries for the period between January 2020 and September 2021. We aimed to study the impact of tourism on sustainability based on the Eurostat database, using cluster analysis and descriptive statistics. The results indicate that tourism will recover slightly, even though the pandemic will continue, recording different effects in European countries. Furthermore, we highlight the relationship between income and tourism, the clusters on tourism being significantly different according to income. The results also identify potential recovery options to align this business area with global sustainable development goals, generate effective transformational change, and suggest how to create a viable growth process pushed by a glocal perspective.
Towards Attaining Sustainable Retail Property Locations: The Relationships between Supply, Demand, and Accessibility of Retail Spaces
Authors: Adebayo Adejimi Alli , Greenhalgh Paul , Muldoon-Smith Kevin , Oyedokun Tunbosun
Published: March 2022

This study explored retail location performance of cities by investigating relationships between changes in retail property stock (supply), changes in retail rental value (demand), and spatial accessibility (retail consumer movement) across three UK cities, namely, Leeds, Newcastle, and York. This is to understand how retail locations and assets can be managed sustainably. In this sense, sustainability was considered through a dual focus in this paper: (1) the efficient use of retail property assets for economic purposes and (2) the impact of these physical retail assets on the local environment in terms of carbon footprint. The study relied on space syntax ideology in computing spatial accessibility index and adopted business rate datasets in computing changes in retail rental value and stock. Findings showed that spatial accessibility across retail locations could predict the performance of retail rental value (but not stock) across the sampled cities. The study further showed that extent of city analysis (scale) is significant in estimating retail location performance and understanding the influence of accessibility. This evidence has the potential to facilitate better decision-making concerning the planning, design, and management of retail locations and spaces. The study is significant because it can serve as a reference for promoting an urban sustainability agenda, especially in ensuring that urban land and properties are used optimally to maximise their social, economic, and environmental values.
Dietary Choices Impact on Greenhouse Gas Emissions: Determinants and Correlates in a Sample of Adults from Eastern Germany
Authors: Koelman Liselot , Huybrechts Inge , Biesbroek Sander , van ‘t Veer Pieter , Schulze Matthias B. , Aleksandrova Krasimira
Published: March 2022

The present study estimated diet-related greenhouse gas emissions (GHGE) and land use (LU) in a sample of adults, examined main dietary contributors of GHGE, and evaluated socio demographic, lifestyle, and wellbeing factors as potential determinants of high environmental impact. A cross-sectional design based on data collected from the European Prospective Investigation into Cancer and Nutrition (EPIC)—Potsdam cohort (2010–2012) was used. Usual diet was assessed using food frequency questionnaires. Diet-related GHGE and LU were calculated using a European-average lifecycle analyses-food-item database (SHARP-ID). Information on potential determinants were collected using self-administered questionnaires. Men (n = 404) and women (n = 401) at an average age of 66.0 ± 8.4 years were included. Dietary-related energy-adjusted GHGE in men was 6.6 ± 0.9 and in women was 7.0 ± 1.1 kg CO2 eq per 2000 kcal. LU in men was 7.8 ± 1.2 and in women was 7.7 ± 1.2 m2/year per 2000 kcal. Food groups contributing to most GHGE included dairy, meat and non-alcoholic beverages. Among women, being single, having a job, being a smoker and having higher BMI were characteristics associated with higher GHGE, whereas for men these included being married, longer sleeping duration and higher BMI. Further studies are warranted to provide insights into population-specific determinants of sustainable dietary choices.
Hybrid 4-Dimensional Trajectory Prediction Model, Based on the Reconstruction of Prediction Time Span for Aircraft en Route
Authors: Zhou Jinlun , Zhang Honghai , Lyu Wenying , Wan Junqiang , Zhang Jingpeng , Song Weikai
Published: March 2022

This paper presents the results from a test of the performance of several general trajectory prediction methods and proposes a hybrid trajectory prediction model that aims to increase the safety of flights en route and improve airspace management capabilities by predicting the aircraft’s four-dimensional trajectory (4DT) more accurately. The automatic dependent surveillance-broadcast (ADS-B) data from 589 trajectories of cruising aircraft from the Guangzhou area were extracted for experiments. Numerous trajectory prediction methods, including velocity trend extrapolation, long short-term memory (LSTM), stateful-LSTM, back propagation (BP) neural network, a one-dimensional convolutional neural network (1D-ConvNet), Kalman filter, and flight plan interpolation were used for prediction experiments, and their performance at different time spans of prediction is obtained. By extracting the best methods using different time spans of prediction, a hybrid prediction model is proposed based on the reconstruction of these methods. For the data in this paper, the mean squared error (MSE) of the hybrid prediction model is significantly reduced compared to other methods in different time spans of prediction, which has great significance for future trajectory prediction in a structured airspace.
Carbon Footprinting of Universities Worldwide Part II: First Quantification of Complete Embodied Impacts of Two Campuses in Germany and Singapore
Authors: Helmers Eckard , Chang Chia Chien , Dauwels Justin
Published: March 2022

Universities, as innovation drivers in science and technology worldwide, should attempt to become carbon-neutral institutions and should lead this transformation. Many universities have picked up the challenge and quantified their carbon footprints; however, up-to-date quantification is limited to use-phase emissions. So far, data on embodied impacts of university campus infrastructure are missing, which prevents us from evaluating their life cycle costs. In this paper, we quantify the embodied impacts of two university campuses of very different sizes and climate zones: the Umwelt-Campus Birkenfeld (UCB), Germany, and the Nanyang Technological University (NTU), Singapore. We also quantify the effects of switching to full renewable energy supply on the carbon footprint of a university campus based on the example of UCB. The embodied impacts amount to 13.7 (UCB) and 26.2 (NTU) kg CO2e/m2•y, respectively, equivalent to 59.2% (UCB), and 29.8% (NTU), respectively, of the building lifecycle impacts. As a consequence, embodied impacts can be dominating; thus, they should be quantified and reported. When adding additional use-phase impacts caused by the universities on top of the building lifecycle impacts (e.g., mobility impacts), both institutions happen to exhibit very similar emissions with 124.5–126.3 kg CO2e/m2•y despite their different sizes, structures, and locations. Embodied impacts comprise 11.0–20.8% of the total impacts at the two universities. In conclusion, efficient reduction in university carbon footprints requires a holistic approach, considering all impacts caused on and by a campus including upstream effects.
An Accelerated Fixed-Point Algorithm with an Inertial Technique for a Countable Family of G-Nonexpansive Mappings Applied to Image Recovery
Authors: Janngam Kobkoon , Wattanataweekul Rattanakorn
Published: March 2022

Many authors have proposed fixed-point algorithms for obtaining a fixed point of G-nonexpansive mappings without using inertial techniques. To improve convergence behavior, some accelerated fixed-point methods have been introduced. The main aim of this paper is to use a coordinate affine structure to create an accelerated fixed-point algorithm with an inertial technique for a countable family of G-nonexpansive mappings in a Hilbert space with a symmetric directed graph G and prove the weak convergence theorem of the proposed algorithm. As an application, we apply our proposed algorithm to solve image restoration and convex minimization problems. The numerical experiments show that our algorithm is more efficient than FBA, FISTA, Ishikawa iteration, S-iteration, Noor iteration and SP-iteration.
Tunable Geometries in Sparse Clifford Circuits
Authors: Hashizume Tomohiro , Kuriyattil Sridevi , Daley Andrew J. , Bentsen Gregory
Published: March 2022

We investigate the emergence of different effective geometries in stochastic Clifford circuits with sparse coupling. By changing the probability distribution for choosing two-site gates as a function of distance, we generate sparse interactions that either decay or grow with distance as a function of a single tunable parameter. Tuning this parameter reveals three distinct regimes of geometry for the spreading of correlations and growth of entanglement in the system. We observe linear geometry for short-range interactions, treelike geometry on a sparse coupling graph for long-range interactions, and an intermediate fast scrambling regime at the crossover point between the linear and treelike geometries. This transition in geometry is revealed in calculations of the subsystem entanglement entropy and tripartite mutual information. We also study emergent lightcones that govern these effective geometries by teleporting a single qubit of information from an input qubit to an output qubit. These tools help to analyze distinct geometries arising in dynamics and correlation spreading in quantum many-body systems.
Cubic q-Rung Orthopair Hesitant Exponential Similarity Measures for the Initial Diagnosis of Depression Grades
Authors: Ying Changyan , Slamu Wushour , Ying Changtian
Published: March 2022

The cubic q-rung orthopair hesitant fuzzy set (Cq-ROHFS) provides greater information and is capable of representing both the interval-valued q-rung orthopair hesitant fuzzy set (IVq-ROHFS) and the q-rung orthopair hesitant fuzzy set (q-ROHFS). The concept of Cq-ROHFS is more flexible when considering the symmetry between two or more objects. In social life, complex decision information is often too uncertain and hesitant to allow precision. The cubic q-rung orthopair hesitant fuzzy sets are a useful tool for representing uncertain and hesitant fuzzy information in uncertain decision situations. Using the least common multiple (LCM) extension method, we propose a decision-making method based on an exponential similarity measure and hesitancy in the cubic q-rung orthopair hesitant fuzzy environment. To represent assessment information more accurately, our proposed method adjusts parameters according to the decision maker’s preferences in the decision-making process. The Cq-ROHFS setting was used to develop a depression rating method based on the similarity measure for depressed patients. Finally, the validity and applicability of the decision method is demonstrated using an example of depression rating assessment. As a result of this study, the scientific community can gain insight into real-world clinical diagnostic problems and treatment options.
On the Bertrand Offsets of Timelike Ruled Surfaces in Minkowski 3-Space
Authors: Alluhaibi Nadia , Abdel-Baky Rashad A. , Naghi Monia
Published: March 2022

This work examines some classical results of Bertrand curves for timelike ruled and developable surfaces using the E. Study map. This provides the ability to define two timelike ruled surfaces which are offset in the sense of Bertrand. It is shown that every timelike ruled surface has a Bertrand offset if and only if an equation should be satisfied between the dual geodesic curvatures. Some new results and theorems related to the developability of the Bertrand offsets of timelike ruled surfaces are also obtained.
Genomics in Plant Viral Research
Authors: Maina Solomon , Rodoni Brendan
Published: March 2022

Plant viruses constitute a large group of pathogens causing damaging diseases in many agricultural and horticultural crops around the world [...]
Hepatitis B Virus Chronic Infection in Blood Donors from Asian and African High or Medium Prevalence Areas: Comparison According to Sex
Authors: Allain Jean-Pierre , Owusu-Ofori Shirley , Ye Xianlin , Bisseye Cyrille , Chaar Mira , Li Chengyao
Published: March 2022

Immune control of various infectious diseases, particularly viral, was shown to be more efficient for females than males. Response to viral vaccines (HAV, HBV) was higher in females. Data on hepatitis B virus (HBV) markers accumulated over 15 years in blood donors was stratified according to sex, including HBsAg, HBV viral load and levels of anti-HBs in areas where genotypes B and C (China), genotype D (Iran, Lebanon, Tunisia) and genotype E (Ghana, Burkina Faso, Gabon) were prevalent. HBsAg was screened by either ELISA or rapid tests, anti-HBc and anti-HBs by ELISA, HBV DNA load by a standardized method across sites. In Ghanaian children less than 5 years, HBV DNA load was significantly lower in females than in males (p = 0.035). In China, Ghana, Burkina Faso and Gabon blood donors, median HBsAg prevalence was ~5% and 3% in China, ~8.5% and 4.5% in Gabon, ~16% and 11% in Burkina Faso and ~11% and 7% in Ghana for male and female donors, respectively (p < 0.001). In HBsAg+ Ghanaian blood donors, distribution and median viral load were not significantly different between sexes; occult hepatitis B infections (OBI) were significantly more frequent in males. In Chinese blood donor anti-HBc+ and anti-HBs+, anti-HBs levels tended to be higher in males but vaccinated donors’ anti-HBs+ only, while anti-HBs levels were females > males. In areas where genotypes B-E are dominant, the prevalence of chronic HBV infection (HBsAg+) seems better controlled before age 16–18 by females infected vertically or horizontally. OBIs appear considerably more frequent in men, suggesting lower efficacy of HBV infection control. Female blood donors appear significantly safer from HBV than males, and their donation should be encouraged.
Changes of Lake Area, Groundwater Level and Vegetation under the Influence of Ecological Water Conveyance—A Case Study of the Tail Lake of Tarim River in China
Authors: Zhao Xinfeng , Xu Hailiang , Zhang Peng
Published: March 2022

To study the changes of water and vegetation coverage, groundwater level and plant diversity of lakes at the end of Tarim River in Northwest China, the changes of various indicators in more than 20 years (2000–2019) were analyzed through field investigation and indoor remote sensing methods. The results showed that (1): with the initiation of the development of ecological water conveyance project, water and vegetation areas increased significantly, especially the trend of vegetation areas becoming more significant, and area of sandy land decreased significantly. (2): the plant diversity increased in the early stage of ecological water conveyance, however, with the increase of lake area and groundwater level, the species composition tends to be simplified. According to the variation characteristics of species importance value in the overflow area in recent 20 years, it is found that the top communities of plant succession are Phragmites australis and Hexinia polydichotoma. (3): with the increase in the lake area, the groundwater level showed an up-lifted trend, the correlation between the two was significant, but there was a lag in the response of the groundwater level. (4): The intra-annual variations in the lake areas were considerable before and after the ecological water conveyance.
Stream Temperature Predictions for River Basin Management in the Pacific Northwest and Mid-Atlantic Regions Using Machine Learning
Authors: Weierbach Helen , Lima Aranildo R. , Willard Jared D. , Hendrix Valerie C. , Christianson Danielle S. , Lubich Michaelle , Varadharajan Charuleka
Published: March 2022

Stream temperature (Ts) is an important water quality parameter that affects ecosystem health and human water use for beneficial purposes. Accurate Ts predictions at different spatial and temporal scales can inform water management decisions that account for the effects of changing climate and extreme events. In particular, widespread predictions of Ts in unmonitored stream reaches can enable decision makers to be responsive to changes caused by unforeseen disturbances. In this study, we demonstrate the use of classical machine learning (ML) models, support vector regression and gradient boosted trees (XGBoost), for monthly Ts predictions in 78 pristine and human-impacted catchments of the Mid-Atlantic and Pacific Northwest hydrologic regions spanning different geologies, climate, and land use. The ML models were trained using long-term monitoring data from 1980–2020 for three scenarios: (1) temporal predictions at a single site, (2) temporal predictions for multiple sites within a region, and (3) spatiotemporal predictions in unmonitored basins (PUB). In the first two scenarios, the ML models predicted Ts with median root mean squared errors (RMSE) of 0.69–0.84 °C and 0.92–1.02 °C across different model types for the temporal predictions at single and multiple sites respectively. For the PUB scenario, we used a bootstrap aggregation approach using models trained with different subsets of data, for which an ensemble XGBoost implementation outperformed all other modeling configurations (median RMSE 0.62 °C).The ML models improved median monthly Ts estimates compared to baseline statistical multi-linear regression models by 15–48% depending on the site and scenario. Air temperature was found to be the primary driver of monthly Ts for all sites, with secondary influence of month of the year (seasonality) and solar radiation, while discharge was a significant predictor at only 10 sites. The predictive performance of the ML models was robust to configuration changes in model setup and inputs, but was influenced by the distance to the nearest dam with RMSE <1 °C at sites situated greater than 16 and 44 km from a dam for the temporal single site and regional scenarios, and over 1.4 km from a dam for the PUB scenario. Our results show that classical ML models with solely meteorological inputs can be used for spatial and temporal predictions of monthly Ts in pristine and managed basins with reasonable (<1 °C) accuracy for most locations.
The Influence of Greenery and Landscape Design on Solar Radiation and UHI Mitigation: A Case Study of a Boulevard in a Hot Climate
Authors: Shareef Sundus
Published: March 2022

Greenery is one of the most influential factors in reducing the outdoor air temperature and enhancing the microclimate in hot areas. Previous studies focused on studying Urban Heat Islands (UHI) on a specific level; this research investigates the impact of greenery on different levels and three types of UHI, pedestrian, canopy, and boundary, to provide a holistic image of greenery impact on the atmosphere. Further, whereas vegetation impact has been addressed in previous studies, no valuable study has been found that investigates the impact of vegetation within the local climate conditions of the UAE. In this research, different types of greenery will be investigated to find their impact on outdoor microclimate parameters and the UHI within the hot climate conditions of the UAE. The case study of this research is a boulevard located in Dubai; the International Media Protection Zone’s main boulevard was selected to simulate different scenarios based on vegetation type and Leaf Area Density (LAD) using ENVI-met. The results showed that 12 m trees and the cylindrical tree are the most effective vegetation in reducing the air temperature; the variation between these scenarios and the existing case reaches 0.70 °C and 0.66 °C, respectively. The 10 m trees also have an influencing impact on reducing the air temperature by 0.50 °C. The same vegetation types showed a positive performance in absorbing shortwave radiation. The reduction in the reflected wave compared to the reference case was 36.07 W/m2 and 31.45 W/m2 for the 12 m and 10 m trees, respectively. Furthermore, the reduction in air temperature of a proposed scenario can reach 2.41 °C, 1.12 °C, and 1.08 °C for the investigated UHI levels. The results of this study will provide a canyon greenery prototype, with optimized performance in hot, humid climate areas.
Complete blood count interpretation
Authors:   S.P. Botkin Clinical Infectious Diseases Hospital, St. Petersburg, Ilyin Pyotr Arkadyevich
Published: March 2022

A complete blood count (CBC) is one of the most frequently prescribed tests that allows studying the qualitative and quantitative composition of blood. Sometimes it is also called a general blood test. Previously, this analysis was carried out manually, and the number of studied characteristics was usually limited to 5–7 parameters. At the present stage, this analysis is increasingly carried out using automatic or semi-automatic hematological analyzers, and the number of studied parameters has increased to 24. During the interpretation of this test, an assessment of the main characteristics of erythrocytes and their specific indicators (red cell indices: MCV, MCH, MCHC, RDW), leukocytes and their varieties in percentage terms (white blood cell count), and platelets with a platelet index is made, and the erythrocyte sedimentation rate (ESR) is determined. This test is used to diagnose and control the treatment of many diseases, and in some cases, it plays an essential role in the correct diagnosis.
Work without injuries: how to protect your employees
Authors:   Occupational Health and Safety Department, AKFA Group, Rasulov O.A.
Published: March 2022

In Russia, the admission to the performance of duties of employees who have not been trained and tested for knowledge of labor protection requirements is illegal and entails a fine of up to 130 thousand rubles. Therefore, it is necessary to provide training in the field of labor protection. Occupational health and safety specialists of one of the world leaders in the production of aluminum extrusion AKFA Group (Uzbekistan) shared their experience in implementing systems to save the life and health of workers at the holding's enterprises.
Environmental control and compliance with legal requirements
Authors:   Financial University under the Government of the Russian Federation, Vasilyeva O. N.
Published: March 2022

In 2021, changes in legislation in the water sector and in the field of nature management came into force. We offer an overview of the main innovations in terms of environmental supervision.
Issue of forming of the uniform digital platform of the system of pricing in construction
Authors:   ", Vasilyeva E. Yu. ,   Budget-and-contracted work in construction",   Journal
Published: March 2022

The article is devoted to the matters of the creation and development of the uniform digital platform of the system of pricing in construction (FGIS CS), contains characteristic of its contents and structure, of the stages of the system forming, as well as the information on dynamics of the uses registration and the database filling. The benefits which are brought by FGIS CS within reforming of the system of budget pricing in Russia are listed. At the same time, the matters of argument and disadvantages of the FGIS CS system are revealed. The conditions, which are to be complied to make the positive impact on the construction industry possible, are named.
Matters of legal regulation of re-planning of premises in the Russian Federation
Authors:   Management and Innovations department, Moscow State Construction University (NIU MGSU), Dyadkova E. A. , Artsybashev N. S. ,   Moscow State Construction University (NIU MGSU)
Published: March 2022

The authors considered the matters of legal regulation of re-planning of premises in the Russian Federation. The legislation regulating this sphere as well as the examples of judicial proceedings concerning illegal cases of re-planning and reconstruction is analyzed.
Les conséquences d’un traité conçu à Târgoviste en 1543
Authors: Manea Nadia , Motoc Honorius
Published: March 2022

The Consequences of Treaty closed in 1543 at Târgoviste.

The accentuation of the Ottoman domination in the Romanian Countries during the first half of the XVIth century induced the orientation of Princes Neagoe Basarab and Radu Paisia to the alliance with Hungary and the Hasburgs.

After Radu Paisia was forced to hand Braila over to the Ottomans, on the 7th January 1543 he addressed a Declaration of Submittal to King Ferdinand.

The new external orientation had two important consequences :

• Radu Paisia lost the throne and

• the capital was moved to Bucharest.
Le passage du Paléolithique moyen au Paléolithique supérieur en Europe centrale et orientale
Authors: Otte Marcel
Published: March 2022

Les aptitudes moustériennes nous semblent amplement démontrées par la flexibilité étourdissante de la technologie, l’aptitude à la prévision des besoin et à la maîtrise du fonctionnement symbolique. La question se résout à bien distinguer les potentialités des réalisation au sein d’ensemble paléolitique. Ceux-ci nous semblent dus en particulier à la relation nouvelle entretenue entre homme et l’animal au début du Paléolitique supérieur : autant l’arme naturelle se retourne contre la proie (sagaies en bois de renne), autant l’image s’approprie les vertus et la puissance des espèces vivantes. L’Europe centrale et orientale contribuent alors non seulement à l’histoire des peuples européens, mais aussi à la réflexion sur la nature des processus permettant le passage d’une période à l’autre.
La société roumaine à la lumière des rapports consulaires français de Bucarest et de Iassy, pendant les années antérieures à l’union des Principautés (1856-1859)
Authors: Oncescu Iulian
Published: March 2022

During the 1856-1859 period, the Romanian society was clearly dominated by great expectations, stimulated by the favourable international perspectives for achieving the national Romanian aspirations shared by the population in Moldavia and Walachia. Both the general European and local conditions made France the aim of these expectations. France itself accepted to support the Romanians and trusted them. In a practical manner this made necessary for the French leaders to know much better the Romanian partner, the society and its perspectives. The Romanian energies and chances had to be more closely evaluated in the context of European politics.

From this new perspective the French consular despatches became instrumental for the policy makers in Paris. But they also remain a rich source of historical informations judging from both French and Romanian angles, as to their reciprocal approaches.
L'église orthodoxe de Maramureş
Authors: Nicolae Adrian
Published: March 2022

The beginnings of an organized ecclesiastical live in Maramureş, with a canonical proper Bishopric dates around the end of the 14,h century and it is related with the Perii Monastery, foundation of the voivod Sas. In 1391. the voivodes Sas and Bale dedicated the monastery to the ecumenical Patriarch Anthony, foutided by their father. Until the midie of the 17 ,h century Maramureş was under the constant political and ecclesiastical domination of the hangars. Between 1657-1700, Maramureş was submitted to the spiritual rule of the metropolitans from Alba lulia. An important orthodox personality was the metropolitan Sava Brancovici, who ruled the church from Maramureş until 1680. hi 1740. the Orthodox Bishopric from Maramureş is abolished by the austrian government and it will be reestablished only on 1st July 1937, having as residence the town Sighet and as ruler His Grace Bishop dr. Stan Răşinăreanul.