bluuebunny/crossref_metadata_2025 huggingface dataset:
Mineral Carbonation of Basic Oxygen Furnace Slags
Authors: Vollprecht Daniel , Wohlmuth Dominik
Published: November 2022

Mineral carbonation is a method in carbon capture and utilization (CCU) in which carbon dioxide reacts with natural or synthetic mineral phases to form carbonates. In this study, BOF slag consisting of alite, Ca3SiO5, belite, Ca2SiO4, melilite, (Ca,Na)2(Mg,Al)[4][Si2O7], brownmillerite, Ca(Fe,Al)2O5, calcium ferrite, Ca2FeO4 and Ca-, Mg- and Mn-bearing wuestite, (Mg,Ca,Mn,Fe)O, was crushed into different particle size fractions and exposed over various durations (1 d, 3 d, 9 d, 14 d, 24 d) at a grate to 120 °C hot off-gas with a CO2 content of 25%. However, the total inorganic carbon (TIC) content never increases above the detection limit of 0.5% throughout the experimental duration. The determination of the carbonation depth using phenolphthalein does not reveal a homogeneous carbonation front, but an irregular carbonation. This observation was confirmed by microprobe analyses using elemental mapping. The solubility of the slag increases with increasing carbonation, e.g., the leachability of sulfate increases from 7.8 to 8270 mg/kg dry matter (DM), and of calcium from 940 to 3860 mg/kg DM. The leaching of environmentally relevant element varies: the leachable concentration of molybdenum increases from 0.017 mg/kg DM to 0.089 mg/kg DM, that of chromium remains constant (ca. 0.05 mg/kg DM) whereas that of vanadium decreases from 1.1 to 0.45 mg/kg. In summary, the chosen carbonation technology must be improved to enhance carbonate yield.
The Influence of the Diaspora on the Transformation of the Main Elements of the Yazidi Religion
Authors: Kokaisl Petr , Hejzlarová Tereza , Kreisslová Sandra
Published: November 2022

This article discusses the transformations of the main elements of Yazidi religion in the diaspora—especially among Caucasian Yazidis, Yazidis in Central Asia, and Yazidis in Western European diasporas. The article focuses on the primary features of the Yazidi religion and highlights their distinctive stabilising social and religious functions. The functions of these various religious elements considered important by Yazidis vary considerably not only over time but also over geographic space. The same religious elements and precepts (e.g., an emphasis on marriage rules) that can significantly stabilise Yazidi society in Iraqi Kurdistan can just as significantly destabilise it in the diaspora (especially in Western Europe).
Adaptive Multi-Proxy for Remote Sensing Image Retrieval
Authors: Li Xinyue , Wei Song , Wang Jian , Du Yanling , Ge Mengying
Published: November 2022

With the development of remote sensing technology, content-based remote sensing image retrieval has become a research hotspot. Remote sensing image datasets not only contain rich location, semantic and scale information but also have large intra-class differences. Therefore, the key to improving the performance of remote sensing image retrieval is to make full use of the limited sample information to extract more comprehensive class features. In this paper, we propose a proxy-based deep metric learning method and an adaptive multi-proxy framework. First, we propose an intra-cluster sample synthesis strategy with a random factor, which uses the limited samples in batch to synthesize more samples to enhance the network’s learning of unobvious features in the class. Second, we propose an adaptive proxy assignment method to assign multiple proxies according to the cluster of samples within a class, and to determine weights for each proxy according to the cluster scale to accurately and comprehensively measure the sample-class similarity. Finally, we incorporate a rigorous evaluation metric mAP@R and a variety of dataset partitioning methods, and conduct extensive experiments on commonly used remote sensing image datasets.
Change Alignment-Based Image Transformation for Unsupervised Heterogeneous Change Detection
Authors: Xiao Kuowei , Sun Yuli , Lei Lin
Published: November 2022

Change detection (CD) with heterogeneous images is currently attracting extensive attention in remote sensing. In order to make heterogeneous images comparable, the image transformation methods transform one image into the domain of another image, which can simultaneously obtain a forward difference map (FDM) and backward difference map (BDM). However, previous methods only fuse the FDM and BDM in the post-processing stage, which cannot fundamentally improve the performance of CD. In this paper, a change alignment-based change detection (CACD) framework for unsupervised heterogeneous CD is proposed to deeply utilize the complementary information of the FDM and BDM in the image transformation process, which enhances the effect of domain transformation, thus improving CD performance. To reduce the dependence of the transformation network on labeled samples, we propose a graph structure-based strategy of generating prior masks to guide the network, which can reduce the influence of changing regions on the transformation network in an unsupervised way. More importantly, based on the fact that the FDM and BDM are representing the same change event, we perform change alignment during the image transformation, which can enhance the image transformation effect and enable FDM and BDM to effectively indicate the real change region. Comparative experiments are conducted with six state-of-the-art methods on five heterogeneous CD datasets, showing that the proposed CACD achieves the best performance with an average overall accuracy (OA) of 95.9% on different datasets and at least 6.8% improvement in the kappa coefficient.
Tracking Deforestation, Drought, and Fire Occurrence in Kutai National Park, Indonesia
Authors: Guild Ryan , Wang Xiuquan , Russon Anne E.
Published: November 2022

The dry lowland and mangrove forests of Kutai National Park (KNP) in Indonesia provide invaluable ecosystem services to local human populations (>200,000 in number), serve as immense carbon sinks to recapture anthropogenic emissions, and safeguard habitats for thousands of wildlife species including the critically endangered Northeast Bornean orangutan (Pongo pygmaeus morio). With recent reports of ongoing illegal logging and large-scale wildfires within this National Park, we sought to leverage the extensive catalogue and processing power of Google Earth Engine to track the rates and influences of forest loss within KNP over various time periods since 1997. We present estimates of forest loss from the Hansen Global Forest Change v1.9 dataset (2000–2021) which detected a loss of 15% (272 km2) of forest cover within KNP since 2000, half of which (137 km2) coincided with the El Niño-induced wildfires of 2015–2016. Using the MCD64A1 C6.1 MODIS dataset, we found significant spatial overlap between burned area and forest loss detections during the 2015–2016 period but identified considerable omissions in the burned area dataset over smallholder farms within KNP. We discuss the implications of deforestation in areas of primary orangutan habitat and how patterns of forest loss have influenced drought and fire dynamics within KNP. Finally, we compare time-series estimates of precipitation, the ENSO index, burned area, and forest loss to demonstrate that fire risk within KNP depends largely—but not exclusively—on drought severity, and that rates of non-fire (gradual) and fire-related (extreme) forest loss threaten the remaining forests of this National Park.
Phytochemical Compound Profile and the Estimation of the Ferruginol Compound in Different Parts (Roots, Leaves, and Seeds) of Juniperus procera
Authors: Salih Abdalrhaman M. , Al-Qurainy Fahad , Tarroum Mohamed , Khan Salim , Nadeem Mohammad , Shaikhaldein Hassan O. , Alansi Saleh
Published: November 2022

Secondary plant metabolites and their derivatives play a significant role in human health. Ferruginol is a diterpene phenol that has recently received attention for its pharmacological properties, including antibacterial, antitumor, antimalarial, and cardioprotective effects. Recently, we detected the ferruginol compound in the leaf and seed extracts of Juniperus procera using different analytical approaches. The present work aims at detecting phytochemical compounds in a root extract of J. procera and estimating the amount of ferruginol compound in different parts of Juniperus procera. To screen the phytochemical compounds present in the root extract of J. procera, Gas chromatography/mass spectrometry (GC/MS) was performed. For ferruginol identification and estimation, high-performance liquid chromatography (HPLC) with the ferruginol reference standard and high-resolution direct analysis in real-time (DART) time-of-flight mass spectrometry (TOFMS) (DART-TOF-MS) analysis were used. GC/MS analysis revealed more than 20 bioactive compounds related to secondary plant metabolites in the root extract of J. procera with biological activity. The DART-TOF-MS result showed the typical positive ion spectra of ferruginol, and the HPLC result confirmed that the root extract of J. procera contains the ferruginol compound. In contrast, the root extract of J. procera contained a significant amount of ferruginol compared to that in the leaf and seed extracts. All parts of the J. procera contained the ferruginol compound and proved that ferruginol might be accumulated in the roots, leaves, and seeds of J. procera.
A Lunar Backup Record of Humanity
Authors: Ezell Carson , Lazarian Alexandre , Loeb Abraham
Published: November 2022

The risk of a catastrophic or existential disaster for our civilization is increasing this century. A significant motivation for a near-term space settlement is the opportunity to safeguard civilization in the event of a planetary-scale disaster. A catastrophic event could destroy the significant cultural, scientific, and technological progress on Earth. However, early space settlements can preserve records of human activity by maintaining a backup data storage system. The backup can also store information about the events leading up to the disaster. The system would improve the ability of early space settlers to recover our civilization after collapse. We show that advances in laser communications and data storage enable the development of a data storage system on the lunar surface with a sufficient uplink data rate and storage capacity to preserve valuable information about the achievements of our civilization and the chronology of the disaster.
When the Wheelchair Is Not Enough: What Capabilities Approaches Offer Assistive Technology Practice in Rural Argentina
Authors: Layton Natasha , Contepomi Silvana , del Valle Bertoni Maria , Martinez Oliver Maria Helena
Published: November 2022

This article considers the lives of disabled people requiring assistive technology who live in contexts of urban poverty. Provision is often constrained by a range of contextual factors which seem outside the scope of health and rehabilitation services. We critically reflect on health, rehabilitation, and capabilities approaches. We explore both rehabilitation and capabilities approaches with posture and mobility practice in an area of urban poverty in Argentina. Contrasting rehabilitation and capabilities approaches to a composite posture and mobility case provides a range of insights. Rehabilitation approaches start with the individual as the locus for intervention. Capabilities approaches reframe interventions such as posture and mobility in terms of the freedoms they offer, and highlight the barriers or capability gaps that must be addressed to achieve outcomes. We conclude that capabilities approaches give practitioners the scope to go beyond posture and mobility processes and attend to the other factors, across the ecosystem, that prevent people from realizing their freedoms. To address capability gaps, a broader scope of practice for health practitioners may include consumer empowerment strategies; partnering with the community; and systemic advocacy with duty holders able to address systemic barriers.
Assessment of Three Automated Identification Methods for Ground Object Based on UAV Imagery
Authors: Zhang Ke , Maskey Sarvesh , Okazawa Hiromu , Hayashi Kiichiro , Hayashi Tamano , Sekiyama Ayako , Shimada Sawahiko , Fiwa Lameck
Published: November 2022

Identification and monitoring of diverse resources or wastes on the ground is important for integrated resource management. The unmanned aerial vehicle (UAV), with its high resolution and facility, is the optimal tool for monitoring ground objects accurately and efficiently. However, previous studies have focused on applying classification methodology on land use and agronomy, and few studies have compared different classification methods using UAV imagery. It is necessary to fully utilize the high resolution of UAV by applying the classification methodology to ground object identification. This study compared three classification methods: A. NDVI threshold, B. RGB image-based machine learning, and C. object-based image analysis (OBIA). Method A was the least time-consuming and could identify vegetation and soil with high accuracy (user’s accuracy > 0.80), but had poor performance at classifying dead vegetation, plastic, and metal (user’s accuracy < 0.50). Both Methods B and C were time- and labor-consuming, but had very high accuracy in separating vegetation, soil, plastic, and metal (user’s accuracy ≥ 0.70 for all classes). Method B showed a good performance in identifying objects with bright colors, whereas Method C showed a high ability in separating objects with similar visual appearances. Scientifically, this study has verified the possibility of using the existing classification methods on identifying small ground objects with a size of less than 1 m, and has discussed the reasons for the different accuracy of the three methods. Practically, these results help users from different fields to choose an appropriate method that suits their target, so that different wastes or multiple resources can be monitored at the same time by combining different methods, which contributes to an improved integrated resource management system.
Employees Perceptions about Corporate Social Responsibility—Understanding CSR and Job Engagement through Meaningfulness, Bottom-Up Approach and Calling Orientation
Authors: Cunha Sara , Proença Teresa , Ferreira Marisa R.
Published: November 2022

This article analyses the effect of employees’ perceptions of corporate social responsibility (CSR) on job engagement, and we measure meaningfulness experienced and the role of cross-level sensemaking factors, such as the bottom-up approach and calling orientation. Drawing on qualitative data, collected among workers that had CSR implemented in their companies, our findings suggest that both calling orientation and meaningfulness influence the positive impact of the CSR perceptions on job engagement through sequential mediation. The calling orientation has an important role in this relationship because meaningfulness alone does not influence the relationship between CSR and job engagement. Additionally, employees’ perceptions of CSR positively influence job engagement. Furthermore, our research indicates that the meaningfulness experienced by workers increases in the presence of a bottom-up approach in what concerns the definition and implementation of CSR actions of the company. Overall, this research expands our understanding of how people find meaningfulness through individual experiences of CSR.
How Much Organic Carbon Could Be Stored in Rainfed Olive Grove Soil? A Case Study in Mediterranean Areas
Authors: Lozano-García Beatriz , Aguilera-Huertas Jesús , González-Rosado Manuel , Parras-Alcántara Luis
Published: November 2022

Agricultural activities generate CO2, CH4, and N2O, affecting the global climate and the sustainability of agricultural production systems. This topic is essential in those areas where agriculture has caused soil decarbonization. The soil can regenerate by implementing sustainable soil management (SSM), and this regeneration is finite. Therefore, it is necessary to determine the maximum carbon (C) storage capacity to establish the most SSM for soil recarbonization. This research analyzes the C storage capacity in soils with rainfed olive groves and traditional tillage in the largest olive-oil-producing area in the world (Jaén, Andalusia, Spain). The results show that these soils had low soil organic C (SOC) content, ranging from 5.16 g kg−1 (topsoil) to 1.60 g kg−1 (subsoil) and low SOC stock (SOC-S) (43.12 Mg ha−1; 0–120 cm depth). In addition, the SOC fractionation showed that the highest SOC concentrations were in the particulate organic C form. The SOC-S linked to the fine mineral fraction (<20 µm) in topsoil was 21.93 Mg C ha−1, and the SOC-S saturated ranged between 50.69 and 33.11 Mg C ha−1. Therefore, on the soil surface (0–32.7 cm depth), these soils have a C storage maximum capacity of 28.76 Mg C ha−1, with a net C sink capacity of 105.55 Mg ha−1 of CO2-eq. All this suggests that these soils could have a high recarbonization capacity, and applying SSM (in the coming years) could be an essential C sink.
Effect of Land Use and Drainage System Changes on Urban Flood Spatial Distribution in Handan City: A Case Study
Authors: Liu Beibei , Xu Chaowei , Yang Jiashuai , Lin Sen , Wang Xi
Published: November 2022

This study simulated urban flooding under various land use and drainage system conditions and described the process of historical ground–underground construction and its influence on spatial variations in waterlogging, taking Handan City as an example. The obtained results can provide support for urban water security and sustainable urban water resource management. The land use change, represented by the expansion of sealed surfaces, has a positive impact on the distribution and the volume of flood in Handan City, while the drainage system has the opposite effect. The flooding distribution changes over decades reveal that flooding risk is reduced in most areas by improved drainage conditions but exacerbated in impervious areas and riversides due to increasing impermeable areas, the rapid draining of pipes, and poor outlet conditions. This study demonstrates how the dual changes in land use and drainage pipeline networks affect urban flooding distribution; we suggest considering land use and the extension of drainage pipelines in future construction.
Characteristics of Land Use Change in China before and after 2000
Authors: Zhu Zijuan , Zhang Zengxiang , Zhao Xiaoli , Zuo Lijun , Wang Xiao
Published: November 2022

China, with notable population blooming and economic development in the last decades, has experienced profound land-use changes, which, in turn, dramatically impacted the regional, even global and environment system. However, characteristics of land-use changes in China have not yet been well addressed, especially around the year 2000 when a series of land policies were put forward, such as the project of “returning farmland to forest”. To fill this gap, this paper investigated the temporal and spatial patterns of land use changes in China for the period from 1987 to 2010, by taking advantage of the continually updated China Land Use Database developed from remote sensing images. The land-use dynamic matrix, zonal model, and transition matrix were employed to characterize land-use change patterns for four time intervals (1987–1995, 1995–2000, 2000–2005, and 2005–2010) on the dimensions of conversion and modification. Results showed that land-use change affected 4 × 105 km2 (4.5%) of the total landscape in China for more than the past twenty years. Of the six land-use types, built-up land experienced the largest net increase by almost 30% (52,434 km2), with the rate of expansion accelerating after 1995. The area of cropland increased before 2000 and declined afterwards, ending with a net increase in 14,280 km2, approximately 1% of its original area. The loss in the eastern coastal region is attributed mainly to built-up land expansion, while the gain in northern China, with the price of grassland and woodland shrinking, reshaped the cropland distribution in China. The area of woodland decreased slightly by 7880 km2 without a clear pattern over time. The modification of woodland indicated an intensive forest management in terms of planting fast-growing trees in the south of China. Grassland continues to shrink at a decreasing rate, and the modification of grassland shows a tendency of transformation from sparse grassland into a dense one in the 21st century. Trade-offs among demands on food security, economic development, and environment protection forced and shaped the contemporary land-use change in China. These results contribute to understanding the trends and causes of land use change in China, which could provide underpinning knowledge for assessing environmental change, and provide insights on future land planning.
Freezing Damage to Tunnels in Cold Regions and Weights of Influencing Factors
Authors: Li Shuguang , Shen Yanjun , Dong Jianhua , Ma Wen , Lv You , Ren Shaoqiang , Xie Jiangsheng , Ji Shengli , Xu Jianping , Wang Xingli
Published: November 2022

Concrete materials are widely used in tunnel engineering. In China, the cold regions have gradually become the main area for highway and railway construction. Affected by high altitude, low temperature, turbulent wind, and other conditions, freezing damage, such as tunnel icing, occurs in concrete materials, which seriously affects the quality and operational safety of tunnels in cold regions. Therefore, it is necessary to carry out a quantitative analysis of various factors affecting freezing damage to protect concrete materials in tunnels. This paper summarizes various freezing damage phenomena in tunnels in cold regions and divides them into three types: water seepage and hanging ice type freezing damage, lining interface type freezing damage, and tunnel foundation ice accumulation type freezing damage. Based on the qualitative evaluation of each factor, the affiliation of each factor was divided. Then, the influence weight of each factor on freezing damage was obtained through the analytic hierarchy process, and then each factor was ranked. This study is helpful to the selection of anti-freezing measures for tunnels in cold regions.
Association between Land Surface Temperature and Green Volume in Bochum, Germany
Authors: Schmidt Pauline , Lawrence Bryce T.
Published: November 2022

Average temperatures continue to rise throughout the world due to climate change and, thus, also in Europe, often occurring as heat waves. The negative effects of climate change-related heat waves can be observed, especially in urban areas where land sealing is the greatest and so is population density. Past studies have indicated that green volume can provide climate improvement by balancing humidity and regulating temperature. This study aims to estimate the distribution of surface heat islands and green volume and test the relationship between these variables in a case study of Bochum, Germany. A method to develop a temporally longitudinal 30-m Landsat 8-based land surface temperature (LST) analysis and 30-m LiDAR-based green volume dataset are presented, and their relationship is tested using Pearson’s correlation (n = 148,204). The results show that heat islands are moderately negatively correlated with green volume (r = −0.482; p < 0.05), LST can vary as much as 28 degrees °C between heat islands and densely vegetated areas, and the distribution is heterogeneous across Bochum.
Performance Evaluation of LIDAR and SODAR Wind Profilers on the Brazilian Equatorial Margin
Authors: Torres Junior Audalio R. , Saraiva Natália P. , Assireu Arcilan T. , Neto Francisco L. A. , Pimenta Felipe M. , de Freitas Ramon M. , Saavedra Osvaldo R. , Oliveira Clóvis B. M. , Lopes Denivaldo C. P. , de Lima Shigeaki L. , Veras Rafael B. S. , Oliveira Denisson Q.
Published: November 2022

This article seeks to compare the performance of a LIDAR Windcube V2, manufactured by Leosphere, with that of a SODAR MFAS, manufactured by Scintec, in evaluating wind speed at different altitudes. The data from these two sensors were collected at three locations on the Brazilian equatorial margin in the state of Maranhão. The comparison of these sensors aims at their simultaneous use at different points. The horizontal velocity components, by altitude, showed Pearson correlation values above 0.9 and values for the vertical velocity component between 0.7 and 0.85. As for the sampling efficiency, the LIDAR had a performance slightly higher than that of SODAR, especially at the point closest to the coast. In general, both sensors showed similar values, despite the differences in sampling methods. The results showed that the joint performance of these sensors had good correlation, being reliable for application in estimating wind potential for power generation in coastal areas of the equatorial region.
Study of Dynamic Evolution of the Shear Band in Triaxial Soil Samples Using Photogrammetry Technology
Authors: Xia Yi , Mu Chunmei , Li Wenjie , Ye Kai , Wu Haojie
Published: November 2022

In order to avoid the influence of end restraint on triaxial stress and strain measurements, this study combines photogrammetry and computer technology to apply to the unconsolidated undrained test of triaxial soil samples. The novel method can establish an intuitive shear band evolution model of soil samples and help attain a clear and intuitive shear band evolution law. On the basis of the conventional triaxial test, this new method needs to paste the RAD (Ringed Automatically Detected) code points on the rubber film, plexiglass cover and brackets and then take pictures of the RAD code points in the loading process in a surrounding manner, with which the 3D shape of the restored soil samples can be determined. After eliminating the influence of refraction, the coded point cloud coordinates measured in the experiment can be used to calculate the axial deformation and radial deformation of the soil sample in the deformation process and determine the local stress–strain curve and three-dimensional displacement field diagram of the soil sample. The test shows that the new method can clearly determine the peak value and inflection point of the stress–strain curve in the middle region of soil samples, enabling it to reflect the shear change process of the soil sample more accurately. In addition, the displacement field can be used to directly observe the formation, development and penetration process of the shear band in soil samples.
Optimal PI-Controller-Based Hybrid Energy Storage System in DC Microgrid
Authors: Vijayan Maya , Udumula Ramanjaneya Reddy , Mahto Tarkeshwar , Lokeshgupta Bhamidi , Goud B Srikanth , Kalyan Ch Naga Sai , Balachandran Praveen Kumar , C Dhanamjayulu , Padmanaban Sanjeevikumar , Twala Bhekisipho
Published: November 2022

Power availability from renewable energy sources (RES) is unpredictable, and must be managed effectively for better utilization. The role that a hybrid energy storage system (HESS) plays is vital in this context. Renewable energy sources along with hybrid energy storage systems can provide better power management in a DC microgrid environment. In this paper, the optimal PI-controller-based hybrid energy storage system for a DC microgrid is proposed for the effective utilization of renewable power. In this model, the proposed optimal PI controller is developed using the particle swarm optimization (PSO) approach. A 72 W DC microgrid system is considered in order to validate the effectiveness of the proposed optimal PI controller. The proposed model is implemented using the MATLAB/SIMULINK platform. To show the effectiveness of the proposed model, the results are validated with a conventional PI-controller-based hybrid energy storage system.
Experimental Investigation on Performance Enhancement of Parabolic Trough Concentrator with Helical Rotating Shaft Insert
Authors: Allam Mohamed , Tawfik Mohamed , Bekheit Maher , El-Negiry Emad
Published: November 2022

The parabolic trough collector provides an extensive range of solar heating and electricity production applications in solar power plants. The receiver tube of the parabolic trough collector has a vital role in enhancing its performance by using different inserts inside it. In the present work, outdoor experimental tests were conducted to study the performance of a small-scale parabolic trough collector equipped with a centrally placed rotating helical shaft. Three cases were studied: a parabolic trough collector without helical shaft insert, a parabolic trough collector with stationary helical shaft insert, and a parabolic trough collector with a rotating helical shaft insert. The experiments are performed for different shaft rotational speeds (4, 11, and 21 RPM) and various flow rates (0.5, 1, 1.5, 2, and 2.5 LPM) of water as a heat transfer fluid. The fluid flow and heat transfer parameters (friction factor, Reynolds number, Nusselt number, and thermal enhancement factor) and performance parameters (thermal, overall, and exergetic efficiencies) are studied. The results indicated that the helical shaft insert had increased the required pumping power for the same flow rate. However, the parabolic trough collector thermal performance has enhanced with the shaft rotational speed. For all cases, the parabolic trough collector efficiency increases with the flow rate of the heat transfer fluid, but the percentage enhancement in efficiency decreases. Using a shaft rotational speed of 21 RPM and heat transfer fluid flow rates of 0.5 LPM leads to maximum thermal efficiency enhancement and a maximum friction factor ratio of 46.47% and 7.7 times, respectively, compared to plain tube. A comparison based on the same pumping power (thermal enhancement factor) shows that the maximum enhancement occurs at a flow rate of 1 LPM, and the efficiency enhancement is about 37% at a shaft rotational speed of 21 RPM. From an economic point of view, using a rotating helical shaft produces the lower annual cost of useful heat per kWh.
The Impact of Instability in the Business Environment on the Competitiveness of Enterprises Using the Example of the Apparel Industry
Authors: Milewska Beata
Published: November 2022

Recently, many disruptions have occurred in the environment of companies, mainly caused by the COVID-19 pandemic, but also, for example, by the war in Ukraine and by the sharp increase in fuel prices. The aim of the article was to present the competitive strategies of chosen companies from the garment industry and the impact of environmental instability on the competitiveness of enterprises using the example of the clothing industry in Poland. The author has been conducting comprehensive research in Polish clothing companies since mid-2017, using, first of all, the method of interviews with company management. This article presents partial results of these studies concerning the competitiveness of companies, especially in terms of the instability of the environment. On the basis of the conducted research, it can be concluded that the instability in the environment has a significant impact on the competitiveness of clothing enterprises. In the initial period, the COVID-19 pandemic had a negative impact on the level of logistic customer service. Because of this, availability of clothing in some stores and quality of deliveries to online customers deteriorated. The war in Ukraine also caused a temporary deterioration of the availability of clothing in the case of companies that outsourced production to Ukraine. Instability in the environment resulted in an increase in logistics and production costs, which in many cases resulted in an increase in the price of clothing for the end customer. The COVID-19 pandemic and the increase in fuel prices have reduced the efficiency of outsourcing clothing production in low-cost countries, but in the surveyed companies, this had not caused a shift of production from global to local. The problems resulting from the instability of the environment were more quickly overcome by those companies that were more flexible and that earlier on had diversified their sales channels (i.e., sold both in the stores and via e-commerce customers) and the sources of supply (production not only in low-cost countries but also in the local sewing factories). The research confirmed the significant impact of instability in the environment on the ability to compete with the level of logistic customer service and price. The instability in the environment did not affect the ability to compete with the quality of clothing in the surveyed companies.
Institutional Shareholders and Firm ESG Performance: Evidence from China
Authors: Jia Fang , Li Yanyin , Cao Lihong , Hu Lintong , Xu Beibei
Published: November 2022

It is a noteworthy phenomenon that institutional investors care more about the ESG performance of the firms in their portfolios in China. Exploring the role of institutional shareholders in firms’ ESG performance is vital for corporate sustainable growth. Using a sample of publicly listed firms from 2013 to 2020 in China, through the OLS model, order logistic model, and tobit model, we found that firms with higher institutional ownership had better ESG performance, especially in the environmental (E) aspect. The positive effect of institutional investors on ESG performance is more pronounced in SOE firms, and firms in low pollution industries. Furthermore, mechanism tests suggest that institutional shareholders can incentivize firms to engage in ESG by affecting management change and board voting.
A Steady-State Flight Control Algorithm Combining Stretching Ratio Coefficient and PID Control for UAVs in Uncertain Environments
Authors: Wang Jialiang , Tan Rui , Nie Liuyang
Published: November 2022

Unmanned aerial vehicle (UAV) has the advantages of flexible operation, simple structure, and low price, which has been widely researched. In recent years, the application of small UAVs has become more extensive, and the steady-state control of UAVs has great research prospects and value due to it being the key to better execute flight task. A PID steady-state control algorithm based on color recognition and target detection is designed herein. Firstly, it is necessary to calculate the distance between the coordinates of the center of the UAV screen and the geometric center of the target point. Secondly, a pixel distance correction algorithm based on actual distance is proposed so as to correct pixel distance deviation. Finally, it is necessary to control the speed of the UAV by a PID control algorithm to achieve the goal that the UAV is stable near the geometric center of the target point. In short, this algorithm realizes the functions of real-time video transmission of the UAV, flight data storage, color recognition, and speed control of the UAV based on the PID control algorithm and distance correction. The experimental results demonstrate that the proposed algorithm has good robustness, makes the UAV have better stability, and can be used for the process of target tracking in uncertain environments.
Circular Economy: Approaches and Perspectives of a Variable with a Growing Trend in the Scientific World—A Systematic Review of the Last 5 Years
Authors: Vargas-Merino Jorge Alberto , Rios-Lama Cristian Armando , Panez-Bendezú Miguel Humberto
Published: November 2022

The circular economy has become a topic of increasing relevance in the scientific field, and the literature on it has developed considerably in recent years. Therefore, a review is needed to contribute to the understanding of this term, which is under constant debate. This article aims to analyze scientific articles from qualitative and quantitative research approaches on the circular economy. The methodology used was a systematic review of scientific literature from Scopus and Web of Science; 67 scientific articles were systematized under inclusion and exclusion criteria related to the specific objectives sought. The results showed that there is still a long way to go in developing a theoretical framework that can be put into practice due to the divergence of existing perspectives or approaches, although its application to different fields of study is being considered. Likewise, its complex character is highlighted, while driving or limiting factors are observed. This research provides a theoretical contribution aimed at elucidating which implications of the circular economy need to be addressed in order to build a universal or flexible theory to understand what it means to plan for the implementation of the circular economy. In this way, it hopes to strengthen its practical application, which implies the need to create an overarching framework that can be adapted to different contexts and provide clear guidance on how to be part of the circular economy.
Learning Performance Prediction and Alert Method in Hybrid Learning
Authors: Zhuang Huijuan , Dong Jing , Mu Su , Liu Haiming
Published: November 2022

In online learning, students’ learning data such as time and logs are commonly used to predict the student’s learning performance. In a hybrid context, learning activities occur both online and offline. Thus, how to integrate online and offline learning data effectively for an accurate learning performance prediction becomes very challenging. This paper proposes a “prediction and alert” model for students’ learning performance in a hybrid learning context. The model is developed and evaluated through analyzing the 16-week (one semester) attributes of English learning data of 50 students in the eighth grade. Six significant variables were determined as learning performance attributes, namely, qualified rate, excellent rate, scores, number of practice sessions, practice time, and completion. The proposed model was put into actual practice through four months of application and modification, in which a sample of 50 middle school students participated. The model shows the feasibility and effectiveness of data analysis for hybrid learning. It can support students’ continuous online and offline learning more effectively.
Gender Sensitivity in Accessing Healthcare Services: Evidence from Saudi Arabia
Authors: Habib Sufyan , Khan Mohammed Arshad , Hamadneh Nawaf N.
Published: November 2022

Good health and reduced inequality are factors of sustainable development. Healthcare systems are considered on68e of the most important activities of the creative economy that arise from research and development activities. Therefore, facilitating access to healthcare is one of the most important challenges guiding the development of the healthcare systems. Access is a complex concept and requires at least four aspects of evaluation. These include whether services are available, whether there is an adequate supply of services, whether people could obtain healthcare, and finally, evaluating whether a population may have access to services. Most countries are working hard to explore the means of providing better healthcare services to their population, especially in the pandemic age of crisis. The Kingdom of Saudi Arabia (KSA) is one such country that is continuously trying to enhance healthcare access to its citizens by adopting different means and policy interventions. The primary objective of this study is to assess whether gender differences exist with unmet healthcare needs among the citizens of the KSA. In this study, we examined the factors affecting the healthcare system in the Kingdom through access to and use of primary healthcare centres in urban and rural areas and whether there is a gender gap in access to healthcare services. In addition, we have tried to explore the current challenges faced by the healthcare system and key points about immediate measures to overcome the crisis in this sector. A well-structured questionnaire was designed covering different dimensions of the study objectives. The population of the study includes both male and female citizens of Makkah city of the KSA. In a survey of 529 respondents, it was found that people’s access to the healthcare service system in the area is good. Test statistics confirm the significant difference in healthcare access across the gender categories of respondents. The availability of services, as well as the barriers to access, must be evaluated in the context of varied groups in society’s differing perspectives, health requirements, and material and cultural surroundings. Some theoretical and managerial implications, limitations, and scope of future research are also presented in the study.
The Paradox of Sustainability and Luxury Consumption: The Role of Value Perceptions and Consumer Income
Authors: Alghanim Sara , Ndubisi Nelson Oly
Published: November 2022

For many years, the concept of sustainability and luxury has been considered a paradox. Despite scholars’ efforts to highlight the compatibility between sustainability and luxury, the limited studies have shown mixed and inconclusive evidence. By adopting the luxury-seeking consumer behavior framework, this study examines the relationship between luxury value perceptions (i.e., conspicuous, unique, social, emotional, and quality values) and sustainable luxury products consumption. It also identifies the value dimensions that most discriminate between heavy and light consumers of sustainable luxury products and examines the moderating effects of consumer income. Using 348 survey responses from actual consumers of luxury goods in Qatar, hierarchical multiple regression and discriminant analyses were conducted to test the hypothesized relationships. The results suggest that all five value perceptions explain a significant amount of variance in sustainable luxury consumption and discriminate between heavy and light sustainable luxury consumers. However, the moderating effects of consumer income in the relationship between values and sustainable luxury consumption revealed mixed results. The findings of this research provide key theoretical and managerial implications.
On Disharmony in Batch Normalization and Dropout Methods for Early Categorization of Alzheimer’s Disease
Authors: Tufail Ahsan Bin , Ullah Inam , Rehman Ateeq Ur , Khan Rehan Ali , Khan Muhammad Abbas , Ma Yong-Kui , Hussain Khokhar Nadar , Sadiq Muhammad Tariq , Khan Rahim , Shafiq Muhammad , Eldin Elsayed Tag , Ghamry Nivin A.
Published: November 2022

Alzheimer’s disease (AD) is a global health issue that predominantly affects older people. It affects one’s daily activities by modifying neural networks in the brain. AD is categorized by the death of neurons, the creation of amyloid plaques, and the development of neurofibrillary tangles. In clinical settings, an early diagnosis of AD is critical to limit the problems associated with it and can be accomplished using neuroimaging modalities, such as magnetic resonance imaging (MRI) and positron emission tomography (PET). Deep learning (DL) techniques are widely used in computer vision and related disciplines for various tasks such as classification, segmentation, detection, etc. CNN is a sort of DL architecture, which is normally useful to categorize and extract data in the spatial and frequency domains for image-based applications. Batch normalization and dropout are commonly deployed elements of modern CNN architectures. Due to the internal covariance shift between batch normalization and dropout, the models perform sub-optimally under diverse scenarios. This study looks at the influence of disharmony between batch normalization and dropout techniques on the early diagnosis of AD. We looked at three different scenarios: (1) no dropout but batch normalization, (2) a single dropout layer in the network right before the softmax layer, and (3) a convolutional layer between a dropout layer and a batch normalization layer. We investigated three binaries: mild cognitive impairment (MCI) vs. normal control (NC), AD vs. NC, AD vs. MCI, one multiclass AD vs. NC vs. MCI classification problem using PET modality, as well as one binary AD vs. NC classification problem using MRI modality. In comparison to using a large value of dropout, our findings suggest that using little or none at all leads to better-performing designs.
Finite Difference Modeling of the Temperature Profile during the Biodrying of Organic Solid Waste
Authors: Orozco-Álvarez Carlos , Díaz-Megchún Javier , Osorio-Mirón Anselmo , García-Salas Sergio , Hernández-Sánchez Enrique , Palma-Orozco Gisela , Robles-Martínez Fabián
Published: November 2022

Biodrying is a complex process that is very useful in the treatment of solid waste, where variables, such as temperature, thermal conductivity and the moisture content of organic matter, oxygen concentration in the pore space of the waste mass, microbial heat generation, microbial biomass, among others, are involved. Given this complexity, the development of mathematical models that help us to understand this bioprocess is fundamental. In the present work, a mathematical model, based on the finite difference method, was developed to predict the temperature profile at nine recording points, in an organic solid waste pile, during the biodrying process. The bioprocess was carried out under natural convection and solar radiation conditions, inside a greenhouse-type structure. A network of 53 nodes, distributed in the x, y and z directions, on a rectangular prism, was developed. From this network, 27 base nodes were taken and the energy balance was developed for each node, and with this, the equation was obtained, in explicit form, to calculate the temperature. In these base equations, the microbial heat generation was considered, at between 2 and 140 W/m3; the convective coefficient was between 1 and 5 W/m2 °C; and the daily records were taken inside the greenhouse for the solar radiation (0 to 450 W/m2), temperature (15 to 50 °C) and RH% (70 to 30). The modeled temperature profiles of the center (C) and the midpoints of the pile were, on average, 91% close to the experimental values, during the period from 0 to 20 days of biodrying; 70% close, during the period from day 21 to 35, the period when the modeled values were lower, due to the turning of the pile; and 94% close to the experimental values from day 36 to 50, when the modeled values were higher, also due to turning. The modeled temperature profiles of the left, right, upper and lower surfaces were, on average 92% close to the experimental profiles over the 0–35 day period, and the modeled and experimental values were practically identical from day 36 to 50 of the biodrying process.
Moisture-Related Risks in Wood-Based Retrofit Solutions in a Mediterranean Climate: Design Recommendations
Authors: Urso Alessandra , Costanzo Vincenzo , Nocera Francesco , Evola Gianpiero
Published: November 2022

Nowadays, advanced hygrothermal simulation tools are available and they are widely used to predict moisture-related risks in building components, such as mold growth and increased conductive heat losses. This paper takes advantage of these capabilities to analyze moisture-related risks in the innovative wood-based retrofit solutions, developed in the ongoing H2020 “e-SAFE” project. In particular, simulations carried out through the Delphin software for the warm Mediterranean climate of Catania (Italy) allowed assessing the effectiveness of several insulating materials used in the wall assembly and the moisture-related performance determined by adopting either a waterproof membrane or a vapor barrier in convenient positions. The results show that the solutions with highly permeable and highly moisture-capacitive insulation (e.g., wood fiber) are mold free, but at the expense of increased heat losses by up to 12%, compared to dry materials). In some circumstances, foam glass or extruded polyurethane could be preferable, due to their high resistance to mold growth and their flat sorption curve. The vapor-open waterproof membrane applied to the outer side of the insulation is suggested, while a vapor barrier on the outer side of the existing wall worsens mold-related issues.