bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of MODIS Aerosol Optical Depth and Surface Data Using an Ensemble Modeling Approach to Assess PM2.5 Temporal and Spatial Distributions
Authors: Carmona Johana M. , Gupta Pawan , Lozano-García Diego F. , Vanoye Ana Y. , Hernández-Paniagua Iván Y. , Mendoza Alberto
Published: August 2021

The use of statistical models and machine-learning techniques along satellite-derived aerosol optical depth (AOD) is a promising method to estimate ground-level particulate matter with an aerodynamic diameter of ≤2.5 μm (PM2.5), mainly in urban areas with low air quality monitor density. Nevertheless, the relationship between AOD and ground-level PM2.5 varies spatiotemporally and differences related to spatial domains, temporal schemes, and seasonal variations must be assessed. Here, an ensemble multiple linear regression (EMLR) model and an ensemble neural network (ENN) model were developed to estimate PM2.5 levels in the Monterrey Metropolitan Area (MMA), the second largest urban center in Mexico. Four AOD-SDSs (Scientific Datasets) from MODIS Collection 6 were tested using three spatial domains and two temporal schemes. The best model performance was obtained using AOD at 0.55 µm from MODIS-Aqua at a spatial resolution of 3 km, along meteorological parameters and daily scheme. EMLR yielded a correlation coefficient (R) of ~0.57 and a root mean square error (RMSE) of ~7.00 μg m−3. ENN performed better than EMLR, with an R of ~0.78 and RMSE of ~5.43 μg m−3. Satellite-derived AOD in combination with meteorology data allowed for the estimation of PM2.5 distributions in an urban area with low air quality monitor density.
Remote Sensing Image Defogging Networks Based on Dual Self-Attention Boost Residual Octave Convolution
Authors: Zhu Zhiqin , Luo Yaqin , Qi Guanqiu , Meng Jun , Li Yong , Mazur Neal
Published: August 2021

Remote sensing images have been widely used in military, national defense, disaster emergency response, ecological environment monitoring, among other applications. However, fog always causes definition of remote sensing images to decrease. The performance of traditional image defogging methods relies on the fog-related prior knowledge, but they cannot always accurately obtain the scene depth information used in the defogging process. Existing deep learning-based image defogging methods often perform well, but they mainly focus on defogging ordinary outdoor foggy images rather than remote sensing images. Due to the different imaging mechanisms used in ordinary outdoor images and remote sensing images, fog residue may exist in the defogged remote sensing images obtained by existing deep learning-based image defogging methods. Therefore, this paper proposes remote sensing image defogging networks based on dual self-attention boost residual octave convolution (DOC). Residual octave convolution (residual OctConv) is used to decompose a source image into high- and low-frequency components. During the extraction of feature maps, high- and low-frequency components are processed by convolution operations, respectively. The entire network structure is mainly composed of encoding and decoding stages. The feature maps of each network layer in the encoding stage are passed to the corresponding network layer in the decoding stage. The dual self-attention module is applied to the feature enhancement of the output feature maps of the encoding stage, thereby obtaining the refined feature maps. The strengthen-operate-subtract (SOS) boosted module is used to fuse the refined feature maps of each network layer with the upsampling feature maps from the corresponding decoding stage. Compared with existing image defogging methods, comparative experimental results confirm the proposed method improves both visual effects and objective indicators to varying degrees and effectively enhances the definition of foggy remote sensing images.
Subsidence Monitoring Base on SBAS-InSAR and Slope Stability Analysis Method for Damage Analysis in Mountainous Mining Subsidence Regions
Authors: Yuan Mingze , Li Mei , Liu Hui , Lv Pingyang , Li Ben , Zheng Wenbin
Published: August 2021

Surface subsidence caused by coal mining has a great impact on the geological and ecological environments and causes damage to houses, roads, and industrial buildings. In order to understand the subsidence pattern in the mountainous mining regions, three mining faces of the Zhangjiamao mining area in the north of Shaanxi province, northwestern China are taken as case study. Firstly, the small baseline subset (SBAS) technology is used to process 12 images obtained in the mining area to investigate the subsidence data from December 2019 to April 2020. The boundary of surface deformation of the mining area interpreted by the SBAS-InSAR technology is inconsistent with the theoretical boundary suggested by coal mine subsidence theories. Especially, there are some areas in which the real subsidence are larger than estimated area. This discrepancy must be corrected as steep slopes near the theoretical boundary may increase the likelihood of landslides. Our research indicates that: (1) The accumulated displacement and the maximum deformation rate reached −120.759 mm and −270.012 mm/yr in the study area, and the subsidence boundary of the three mining faces is revealed; (2) the combination of the predicted boundary and slope stability analysis can effectively identify the landslide region at the edge of subsidence boundary; (3) the field surveys have proved the effectiveness of this method. The mining area subsidence revealed by our research helps to further understand the impact of land subsidence caused by mining in the mountainous areas and provides a practical method to predict subsidence boundaries and the likelihood for landslides.
Geomagnetic Activity at Lampedusa Island: Characterization and Comparison with the Other Italian Observatories, Also in Response to Space Weather Events
Authors: Di Mauro Domenico , Regi Mauro , Lepidi Stefania , Del Corpo Alfredo , Dominici Guido , Bagiacchi Paolo , Benedetti Giovanni , Cafarella Lili
Published: August 2021

Regular automatic recordings of the time series of the magnetic field, together with routine manual absolute measurements for establishing dynamic baselines at Lampedusa Island—south of Sicily—Italy (geographic coordinates 35°31′N; 12°32′E, altitude 33 m a.s.l.), show a signature of very low electromagnetic noise. The observatory (provisional IAGA code: LMP) lays inside a restricted and remote wildlife reserve, far away from the built-up and active areas of the island, which at present is the southernmost location of the European territory for such observations. The availability of high-quality data from such site, whose survey started in 2005, is valuable for filling the spatial gap due to the lack of observatories in the whole south Mediterranean and North African sectors. We compare observations at Lampedusa, in both time and frequency domains, with those at the other Italian observatories (Castello Tesino and Duronia-L’Aquila), operating since the 1960s of last century, allowing us to report even the secular variation. Using data recorded in the last few years, we investigate higher frequency variations (from diurnal to Pc3-4 pulsations) in order to magnetically characterize the Italian territory and the local response to external forcing. In particular, we present a characterization in terms of diurnal variation and its seasonal dependence for the three observatories. This latter feature is in good agreement with a geomagnetic Sq-model, leading us to speculate about the position of the north Sq-current system vortex and its seasonal displacement with respect to the geographic positions of the observatories. We also study the geomagnetic individual response to intense space weather events by performing Superposed Epoch Analysis (SEA), with an ad-hoc significance test. Magnetic responses in the Ultra Low Frequency range (ULF) from spectral, local Signal-to-Noise Ratio (SNR) analyses under different local time, and polarization rates are computed. These latter studies lead us to search for possible signatures of magnetic field line resonances during intense space weather events, using cross-phase multi-observatory analysis, revealing the promising detection capability of such technique even at low latitudes. The geomagnetic observatories prove to be important points of observation for space weather events occurring at different spatial and time scales, originating in both upstream and ionospheric regions, here analyzed by several well-established methodologies and techniques. The quiet environmental site of LMP, providing high-quality geomagnetic data, allows us such investigations even at inner Earth’s magnetospheric shell.
Solving the SSVEP Paradigm Using the Nonlinear Canonical Correlation Analysis Approach
Authors: De la Cruz-Guevara Danni Rodrigo , Alfonso-Morales Wilfredo , Caicedo-Bravo Eduardo
Published: August 2021

This paper presents the implementation of nonlinear canonical correlation analysis (NLCCA) approach to detect steady-state visual evoked potentials (SSVEP) quickly. The need for the fast recognition of proper stimulus to help end an SSVEP task in a BCI system is justified due to the flickering external stimulus exposure that causes users to start to feel fatigued. Measuring the accuracy and exposure time can be carried out through the information transfer rate—ITR, which is defined as a relationship between the precision, the number of stimuli, and the required time to obtain a result. NLCCA performance was evaluated by comparing it with two other approaches—the well-known canonical correlation analysis (CCA) and the least absolute reduction and selection operator (LASSO), both commonly used to solve the SSVEP paradigm. First, the best average ITR value was found from a dataset comprising ten healthy users with an average age of 28, where an exposure time of one second was obtained. In addition, the time sliding window responses were observed immediately after and around 200 ms after the flickering exposure to obtain the phase effects through the coefficient of variation (CV), where NLCCA obtained the lowest value. Finally, in order to obtain statistical significance to demonstrate that all approaches differ, the accuracy and ITR from the time sliding window responses was compared using a statistical analysis of variance per approach to identify differences between them using Tukey’s test.
Multi-Perspective Anomaly Detection
Authors: Jakob Peter , Madan Manav , Schmid-Schirling Tobias , Valada Abhinav
Published: August 2021

Anomaly detection is a critical problem in the manufacturing industry. In many applications, images of objects to be analyzed are captured from multiple perspectives which can be exploited to improve the robustness of anomaly detection. In this work, we build upon the deep support vector data description algorithm and address multi-perspective anomaly detection using three different fusion techniques, i.e., early fusion, late fusion, and late fusion with multiple decoders. We employ different augmentation techniques with a denoising process to deal with scarce one-class data, which further improves the performance (ROC AUC =80%). Furthermore, we introduce the dices dataset, which consists of over 2000 grayscale images of falling dices from multiple perspectives, with 5% of the images containing rare anomalies (e.g., drill holes, sawing, or scratches). We evaluate our approach on the new dices dataset using images from two different perspectives and also benchmark on the standard MNIST dataset. Extensive experiments demonstrate that our proposed multi-perspective approach exceeds the state-of-the-art single-perspective anomaly detection on both the MNIST and dices datasets. To the best of our knowledge, this is the first work that focuses on addressing multi-perspective anomaly detection in images by jointly using different perspectives together with one single objective function for anomaly detection.
Multi-Dimensional Feature Fusion Network for No-Reference Quality Assessment of In-the-Wild Videos
Authors: Jiang Jiu , Wang Xianpei , Li Bowen , Tian Meng , Yao Hongtai
Published: August 2021

Over the past few decades, video quality assessment (VQA) has become a valuable research field. The perception of in-the-wild video quality without reference is mainly challenged by hybrid distortions with dynamic variations and the movement of the content. In order to address this barrier, we propose a no-reference video quality assessment (NR-VQA) method that adds the enhanced awareness of dynamic information to the perception of static objects. Specifically, we use convolutional networks with different dimensions to extract low-level static-dynamic fusion features for video clips and subsequently implement alignment, followed by a temporal memory module consisting of recurrent neural networks branches and fully connected (FC) branches to construct feature associations in a time series. Meanwhile, in order to simulate human visual habits, we built a parametric adaptive network structure to obtain the final score. We further validated the proposed method on four datasets (CVD2014, KoNViD-1k, LIVE-Qualcomm, and LIVE-VQC) to test the generalization ability. Extensive experiments have demonstrated that the proposed method not only outperforms other NR-VQA methods in terms of overall performance of mixed datasets but also achieves competitive performance in individual datasets compared to the existing state-of-the-art methods.
Impact of Cover Crop Monocultures and Mixtures on Organic Carbon Contents of Soil Aggregates
Authors: Topps Daphne , Khabir Md Imam ul , Abdelmagid Hagir , Jackson Todd , Iqbal Javed , Robertson Boakai K. , Pervaiz Zahida Hassan , Saleem Muhammad
Published: August 2021

Cover crops are considered an integral component of agroecosystems because of their positive impacts on biotic and abiotic indicators of soil health. At present, we know little about the impact of cover crop types and diversity on the organic carbon (OC) contents of different soil aggregate-size classes. In this study, we investigated the effect of cover plant diversity on OC contents of different soil aggregates, such as macro- (<2000–500 μm), meso- (<500–250 μm), and micro-aggregates (<250 μm). Our experiment included a total of 12 experimental treatments in triplicate; six different monoculture treatments such as chickling vetch (Vicia villosa), crimson clover (Trifolium incarnatum), hairy vetch (Vicia villosa), field peas (Pisum sativum), oilseed radish (Raphanus sativus), and mighty mustard (Brassica juncea), and their three- and six-species mixture treatments, including one unplanted control treatment. We performed this experiment usingdeep pots that contained soil collected from a corn-soybean rotation field. At vegetative maturity of cover plants (about 70 days), we took soil samples, and the soil aggregate-size classes were separated by the dry sieving. We hypothesized that cover crop type and diversity will improve OC contents of different soil aggregate-size classes. We found that cover plant species richness weakly positively increased OC contents of soil macro-aggregates (p = 0.056), whereas other aggregate-size classes did not respond to cover crop diversity gradient. Similarly, the OC contents of macroaggregates varied significantly (p = 0.013) under cover crop treatments, though neither monoculture nor mixture treatments showed significantly higher OC contents than the control treatment in this short-term experiment. Interestingly, the inclusion of hairy vetch and oilseed radish increased and decreased the OC contents of macro- and micro-aggregates, respectively. Moreover, we found a positive correlation between shoot biomass and OC contents of macroaggregates. Overall, our results suggest that species-rich rather than -poor communities may improve OC contents of soil macroaggregates, which constitute a major portion of soil systems, and are also considered as important indicators of soil functions.
Carbon Fluxes in Sustainable Tree Crops: Field, Ecosystem and Global Dimension
Authors: Montanaro Giuseppe , Amato Davide , Briglia Nunzio , Russo Carlo , Nuzzo Vitale
Published: August 2021

Carbon (C) budget at cropping systems has not only agronomic but also environmental relevance because of their contribution to both emissions and removals of greenhouse gases (GHGs). Ideally, sustainable orchards are expected to remove atmospheric CO2 at a rate greater than that of the emissions because of (i) optimized biology of the system and (ii) reduced on-site/offsite inputs sourced by the technosphere. However, such a computation might produce inconsistent results and in turn biased communication on sustainability of the cropping systems because C accounting framework(s) are used under unclear context. This study examined the sustainability of orchards in terms of impact on GHGs focusing its significance at the field, ecosystem and global dimension analyzing some operational aspects and limitations of existing frameworks (e.g., net ecosystem carbon balance (NECB), life cycle assessment (LCA)). Global relevance of sustainable orchard was also discussed considering the C sequestration at cropland as instructed by Intergovernmental Panel on Climate Change (IPCC). The uniqueness of olive tree lifespan duration and C sequestration is discussed within the Product Environmental Footprint of agrifood product. The paper also highlighted overlapping components among the NECB, LCA and IPCC frameworks and the need for an integrated C accounting scheme for a more comprehensive and detailed mapping of sustainability in agriculture.
Investigation of Bus Drivers’ Reaction to ADAS Warning System: Application of the Gaussian Mixed Model
Authors: Ye Wei , Xu Yueru , Zhou Feixiang , Shi Xiaomeng , Ye Zhirui
Published: August 2021

Road crashes cause serious loss of life and property. Among all vehicles, buses are more likely to encounter crashes. In recent years, the advanced driving assistance system (ADAS) has been widely used in buses to improve safety. The warning system is one of the key functions and has proven effective in reducing crashes. However, drivers often ignore or overreact to ADAS warnings during naturalistic driving scenarios. Therefore, reactions of bus drivers to warnings need further investigation. In this study, bus drivers’ responses to lane departure warning (LDW) and forward collision warning (FCW) were investigated using 20-day naturalistic driving data. These reactions could be classified into three categories, namely positive, negative, and overreaction or emergency, by employing the Gaussian mixture model. The authors constructed a framework to quantify drivers’ reactions to the warning and study the reaction characteristics in different environments. The results indicate that drivers’ reactions to FCW were more positive than to LDW, drivers reacted more positively to LDW and FCW while driving on highways than on urban roads, and drivers reacted more positively at night to LDW and FCW than during daytime. This study gives support to an adaptive ADAS considering varying bus driver characteristics and environments.
Rapid-Survey Methodology to Assess Litter Volumes along Large River Systems—A Case Study of the Tamsui River in Taiwan
Authors: Schneider Falk , Kunz Alexander , Hu Chieh-Shen , Yen Ning , Lin Hsin-Tien
Published: August 2021

Riverbanks are an important source of plastic pollution. However, the current assessment methods for riverbank litter are based on a point-based sampling which is time consuming and limited in scope. To quickly assess hotspot areas and litter compositions in larger areas, this study developed a new citizen science bicycle survey for riverine debris. Covering 281.5 km of the Tamsui river system in Taiwan, the new methodology was tested at one of the most plastics polluted rivers in the world. The results revealed an average litter density of 15.3 m3/km at the river mouth and of 0.2 m3/km to 2.8 m3/km along the riverbanks further upstream. The coastline was mainly polluted by derelict fishing gear whereas single-use plastics and illegally dumped waste dominated the upstream areas. A correlation between litter and population density could not be identified, but it was noted that litter hotspots occur at cut banks and near mangrove vegetation. Overall, the new methodology proved suitable to collect large quantities of data for scientific purposes and to quickly detect litter accumulations prior to clean-up activities.
A New Biofertilizer Formulation with Enriched Nutrients Content from Wasted Algal Biomass Extracts Incorporated in Biogenic Powders
Authors: Nekvapil Fran , Ganea Iolanda-Veronica , Ciorîță Alexandra , Hirian Razvan , Tomšić Sanja , Martonos Ildiko Melinda , Cintă Pinzaru Simona
Published: August 2021

Raw algae waste naturally thrown on shores could pose serious threats for landfilling and its reuse for composting or further processing as added-value by-products require knowledge-based decisions and management for the sustainable development of local ecosystems. Raw marine waste containing salt (halite) and heavy metals that eventually accumulate in algae hamper their safe applicability in soil fertilization or in other exploitations. Here, the suitability of algal biomass for use as an environmentally safe fertilizer was investigated, thereby supporting sustainable coastal management. The simple extraction of the dry algal biomass of three abundant Mediterranean species, Enteromorpha intestinalis, Corallina elongata, and Gelidium pulchellum, in water containing sodium carbonate resulted in a greenish extract containing a reduced heavy metals content, and nutrients such as K+, PO43−, SO42−, NO3−, Ca2+, and Mg2+. UV-Vis and Raman techniques, including surface-enhanced Raman scattering (SERS), were employed for the fast evidencing of polyphenols, carotenoids, and chlorophylls in the extracts content, while E. intestinalis extract additionally exhibited polysaccharide signals. Heavy metals analysis showed that the major metals in the extracts were Fe, Ni, Zn, and Cu; however, their levels were an order of magnitude lower than in the dry biomass. The extracts also showed a mild antibacterial effect. The combination option of aqueous extracts with powdered crustacean shells to obtain a novel, eco-friendly, solid biofertilizer complex was further shown, which could be pelleted for convenient use. The immersion of solid biofertilizer pellets in water is accompanied by re-solubilization of the compounds originating from algae extracts, presenting the opportunity for dry storage and easier handling and land applicability. In summary, aqueous extracts of marine algae waste present an environmentally safe and attractive way to recycle excessive algal biomass and to formulate a new, eco-friendly biofertilizer complex.
Housing for Sustainable Societies. Children′s Perception and Satisfaction with Their House in Countries around the World
Authors: Bacter Claudia , Săveanu Sorana , Buhaș Raluca , Marc Cristiana
Published: August 2021

(1) Background: Adequate housing conditions and access to basic house amenities are fundamental human rights and indicators of individual wellbeing. The paper aims to present children’s perception regarding housing conditions and household goods and their impact on children’s overall satisfaction with their house. (2) Methods: We aim to determine the contribution of housing conditions and household goods on children’s satisfaction with their home in 31 countries worldwide. To capture differences in children’s satisfaction with their house based on their housing conditions, we analyzed models conducted on data from 10 lower- and upper-middle-income and 20 high-income countries. We used secondary analysis on data from the third wave of Children’s Worlds: International Survey of Children’s Well-Being (ISCWeb) (87,000 children, aged 10–12, worldwide). (3) Results: The results show that there is a link between the material conditions of the family and children’s satisfaction with the house they live in, and also that having a place to study and access to internet are the main factors related to housing that explain children’s satisfaction. (4) Conclusions: Children mostly appreciate the way housing setting and household goods contribute and ensure their proper development through the creation of a stimulating home learning environment. Results are helpful in setting future standards to increase children’s wellbeing and quality of life, and ensure adequate housing as one of the pillars of sustainable development.
Impact of Alum Water Treatment Residues on the Methanogenic Activity in the Digestion of Primary Domestic Wastewater Sludge
Authors: Scalize Paulo , Albuquerque Antonio , Di Bernardo Luiz
Published: August 2021

The effect of adding alum water treatment residues (WTR) on the methanogenic activity in the digestion of primary domestic wastewater sludge was evaluated through laboratory experiments in sedimentation columns, using total suspended solids (TSS) concentrations from 0.37 to 1.23 g/L. The addition of WTR to primary clarifiers can benefit its effluent water quality in terms of colour, turbidity, chemical oxygen demand (COD), and TSS. However, the presence of WTR can negatively influence the production of methane gas during organic sludge digestion in primary clarifiers, for concentrations of TSS between 14.43 and 25.23 g/L and of VSS between 10.2 and 11.85 g/L. The activity of the Methanothrix sp., curved bacilli, methanococci, and Methanosarcina sp. decreases considerably after 16 days of anaerobic digestion, and methane production seems to only be associated with fluorescent methanogenic bacilli.
Analyses Implementation Realities of Legal Frameworks for Sustainable Management of Tanguar Haor Fisheries Resources in Bangladesh
Authors: Tima Tanjina Akter , Schneider Petra , Chanda Swapan Kumar , Mozumder Mohammad Mojibul Hoque , Hossain Mohammad Mosarof , Begum Amany , Shamsuzzaman Md. Mostafa
Published: August 2021

Tanguar Haor (TH) is considered one of the Ecologically Critical Areas (ECAs) of Bangladesh and is internationally recognized as RAMSAR wetland (2nd Ramsar site) known to provide multiple ecosystem services to the society. Nevertheless, multidimensional threats and stressors, the capacity to supply ESs, and the biodiversity of the TH significantly degrades and threatens this wetland’s conservation and sustainability. Although the legal framework promises the sustainable conservation of fisheries resources, information on the implementation scenarios of fisheries laws, regulations, and policies in the TH Ramsar are scant. By merging qualitative and quantitative data of primary and secondary sources, this research aimed to analyze the legal framework to check the effectiveness of regulations for non-conflicting fisheries resources and the sustainable conservation of the TH Ramsar. Primary empirical data were collected by employing Participatory Rural Appraisal (PRA) tools, i.e., 204 semi-structured questionnaire-based individual interviews with fishers, three focus group discussions, and 14 key informants’ interviews in three fishing villages in the TH. In contrast, secondary data was set by reviewing published literature and related official documents. Results showed that, due to weak enforcement with inadequate surveillance and poor implementation of the legal framework, there was a high non-compliance with fishing laws, rules, and policies. Destructive and prohibited fishing gears, e.g., the use of small mesh fine nylon nets (current jal), purse seine net (ber jal), and the harvesting during ban period-illicit catch were widespread in the study areas. In addition, catching undersized fish, fishing at the restricted areas (sanctuary area), and fishing during spawning seasons occur often. There is a crying need for a comprehensive legal and policy framework to contextualize the local context, ensure the proper implementation of the fishing laws and regulations, increase the managerial inefficiency of enforcing agencies, ensure livelihood support during the fishing ban, and afford good alternative income options are still significant issues for good governance in the Tanguar Haor ECA. Findings might help to identify the gaps and misunderstanding of the existing legal practice while submitting urgent attention to the need for drawing a comprehensive legal and policy framework (contextually modified according to the local context), taking initiatives and acting synchronously for proper implementation, and calling transdisciplinary collaboration and cooperation among the agencies that may ensure the non-conflicting use of the natural resources of the TH that can be also helpful for the better conservation of this Ramsar wetland.
Fruit Quality Characters of Myrtle (Myrtus communis L.) Selections: Review of a Domestication Process
Authors: Medda Silvia , Mulas Maurizio
Published: August 2021

Interest in myrtle (Myrtus communis L.) by food, cosmetics, and pharmaceutic industries generated the integration of biomasses harvested from wild populations as raw materials with yields of cultivated orchards. The domestication process is reviewed considering shoot, fruit, and leaf biometric characters of selections obtained in three steps of the program. The first step started in Sardinia (Italy) in 1995 by the analysis of wild germplasm variability. Seventy accessions were the object of the first studied population of mother plants. Agamic propagation tests, as well quality evaluations of fruit and leaves, were integrated into the first step. In the second step, a field of comparison of forty-two agamically propagated cultivars functional to biomass production and to food uses was planted and evaluated for phenotypic characters. In the third step, a new population of twenty selections was obtained by open cross-pollination of some of the cultivars and further phenotypic selection in seedling population. In this review, the three populations are compared for biometric shoot, leaves and fruit characters, in order to verify the pressure of domestication process on these traits. Wild populations showed high variability only partially used during the first step, while the hybridization may create new variability for use in the genetic improvement of myrtle.
Quantitative Estimation of the Hydroquinone, Mercury and Total Plate Count in Skin-Lightening Creams
Authors: Arshad Mehreen , Sadef Yumna , Shakoor Muhammad Bilal , Naeem Muhammad , Bashir Farzana , Ahmad Sajid Rashid , Ali Shafaqat , Abid Irfan , Khan Naeem , Alyemeni Mohammed Nasser
Published: August 2021

Generally white color of the skin is regarded as a feature of superiority and prettiness around the world. Both the males and females in Pakistan apply skin-lightening creams (SLC) but they do not know about the side-effects of their constituents. Skin-lightening products include SLC and related ointments. The SLC are made by mixing fates and water in standard procedure. Here, 20 SLC specimens were obtained and subjected to mercury, hydroquinone and the total plate count (TPC). The hydroquinone in SLC was determined using HPLC, mercury level was assessed by ICP OES and finally TPC were computing by utilizing nutrient media (Agar). The hydroquinone in SLC ranged from 0 to 7.14 ± 0.18% with a median value of 0.33%. In 25% of the studied samples, hydroquinone was not detected, 70% of the samples showed values within the limit and 5% of the samples (1 sample) had a hydroquinone concentration above the permissible limit defined by Pakistan (5%). The mercury ranged 0-7.7 ppm, with a median value of 2.5 ppm. Mercury was detected in 95% of the samples; thus, only 5% of the samples had no mercury. In turn, 20% had mercury within the limit value while 75% of the samples had concentration above the Pakistan standard limit (1 ppm). Moreover, TPC obtained in this study was less than the allowable value set according to European Union (EU). Hence, the SLC samples showed high concentration of toxic constituents which could cause deleterious skin diseases. Government must monitor such kind of cosmetic products regularly in order to reduce the danger.
Gender Differences in Work Satisfaction, Work Engagement and Work Efficiency of Employees during the COVID-19 Pandemic: The Case in Slovenia
Authors: Rožman Maja , Sternad Zabukovšek Simona , Bobek Samo , Tominc Polona
Published: August 2021

The COVID-19 pandemic and the resultant lockdown has caused massive economic disruption, leading businesses to make a rapid transition and take a new approach to business strategy. Therefore, the aim of the paper is to examine if there are statistically significant gender differences in work satisfaction, work engagement, and work efficiency among employees who work from home during the COVID-19 pandemic. Further, the paper aims to identify the importance of individual dimensions of work satisfaction, work engagement, and work efficiency, and gender differences perspective. The research is based on a survey of 785 employees in Slovenian companies. The factor analysis and the t-test for two independent samples were used to test the research hypotheses. Findings: The results show significant gender differences in work satisfaction, work engagement, and work efficiency among employees who work from home during the COVID-19 pandemic. The paper provides change management insights and recommendations to assist companies in minimizing the negative impact of the COVID-19 pandemic on their employees.
A Bibliometric Narrative Review on Modern Navigation Aids for People with Visual Impairment
Authors: Zhang Xiaochen , Yao Xiaoyu , Hui Lanxin , Song Fuchuan , Hu Fei
Published: August 2021

The innovations in the field of specialized navigation systems have become prominent research topics. As an applied science for people with special needs, navigation aids for the visually impaired are a key sociotechnique that helps users to independently navigate and access needed resources indoors and outdoors. This paper adopts the informetric analysis method to assess the current research and explore trends in navigation systems for the visually impaired based on bibliographic records retrieved from the Web of Science Core Collection (WoSCC). A total of 528 relevant publications from 2010 to 2020 were analyzed. This work answers the following questions: What are the publication characteristics and most influential publication sources? Who are the most active and influential authors? What are their research interests and primary contributions to society? What are the featured key studies in the field? What are the most popular topics and research trends, described by keywords? Additionally, we closely investigate renowned works that use different multisensor fusion methods, which are believed to be the bases of upcoming research. The key findings of this work aim to help upcoming researchers quickly move into the field, as they can easily grasp the frontiers and the trend of R&D in the research area. Moreover, we suggest the researchers embrace smartphone-based agile development, as well as pay more attention to phone-based prominent frameworks such as ARCore or ARKit, to achieve a fast prototyping for their proposed systems. This study also provides references for the associated fellows by highlighting the critical junctures of the modern assistive travel aids for people with visual impairments.
Microalgal Production of Biofuels Integrated with Wastewater Treatment
Authors: Jayaseelan Merrylin , Usman Mohamed , Somanathan Adishkumar , Palani Sivashanmugam , Muniappan Gunasekaran , Jeyakumar Rajesh Banu
Published: August 2021

Human civilization will need to reduce its impacts on air and water quality and reduce its use of fossil fuels in order to advance towards a more sustainable future. Using microalgae to treat wastewater as well as simultaneously produce biofuels is one of the approaches for a sustainable future. The manufacture of biofuels from microalgae is one of the next-generation biofuel solutions that has recently received a lot of interest, as it can remove nutrients from the wastewater whilst capturing carbon dioxide from the atmosphere. The resulting biomass are employed to generate biofuels, which can run fuel cell vehicles of zero emission, power combustion engines and power plants. By cultivating microalgae in wastewater, eutrophication can be prevented, thereby enhancing the quality of the effluent. Thus, by combining wastewater treatment and biofuel production, the cost of the biofuels, as well as the environmental hazards, can be minimized, as there is a supply of free and already available nutrients and water. In this article, the steps involved to generate the various biofuels through microalgae are detailed.
A Qualitative Insight into Gendered Vulnerabilities: A Case Study of the Shishper GLOF in Hunza Valley, Pakistan
Authors: Khalid Zainab , Meng Xing-Min , Khalid Abda
Published: August 2021

Gendered vulnerability from women’s point of view has gained popularity in disaster studies in recent decades especially in the Global South. The positioning of women in society during normal times gives rise to vulnerabilities that are revealed when a disaster strikes. These vulnerabilities are often deep-rooted in societal makeup, cultural and traditional norms, and the economic fabric of society. In the context of Pakistan, the role of women in disaster risk reduction programs is still an under-researched area. In this paper, the gendered vulnerability progression in one of the mountain rural communities of Hassanabad in Hunza Valley (Northern Pakistan) is analyzed post-Shishper glacier lake outburst flood (GLOF) in 2019 and 2020. The study uses empirical qualitative data. Semi-structured interviews were conducted with men and women of different age groups within Hassanabad village. A thematic gendered analysis unveiled several interlinked social, economic, and institutional vulnerabilities. The gendered transitional phase of Hassanabad society positively indicates women’s involvement in different spheres of life, including disaster management and mitigation. However, the lack of gender consideration on a formal institutional level exacerbates the gendered vulnerabilities in Hassanabad village. The case study of Hassanabad demonstrated that women not only have an awareness of hazards but are also willing to participate proactively in disaster mitigation activities. Therefore, to reduce community vulnerability and yield long-term positive outcomes of disaster management and mitigation strategies, women must be involved at the formal institutional levels.
Intrinsic Motivation Sources as Pillars of Sustainable Internal Marketing Communication in Turbulent Post-Pandemic Times
Authors: Majerova Jana , Gajanova Lubica , Nadanyiova Margareta , Kolnhofer Derecskei Anita
Published: August 2021

The main aim of the article is to identify the changes in employees’ sources of intrinsic motivation caused by the impact of the COVID-19 pandemic, and to discuss prospective modifications to formulated patterns of internal marketing communication. The novelty of the research lies in two main aspects: (1) the necessity to revise the traditional concept of motivation caused by the pandemic and (2) own methodological approach. While the first aspect reflects the lack of appropriate scientific attention paid to this issue, the second aspect develops methodological approaches applied so far in the research of intrinsic motivation sources. The goal of the paper has been achieved via own questionnaire research of the traditional quadratic structure of the intrinsic motivation sources of employees. The data from socio-demographically representative sample of 2000 respondents have been in accordance with contemporary trends in managerial analytics analysed via factor analysis and relevant statistic tests. It has been found that the ranking of intrinsic motivation sources before the COVID-19 pandemic was the following: (1) sense of choice; (2) sense of meaningfulness; (3) sense of progress and (4) sense of competence. The ranking of intrinsic motivation sources during the COVID-19 pandemic was the following: (1) sense of choice; (2) sense of progress; (3) sense of meaningfulness; and (4) sense of competence. Based on the identified changes in intrinsic motivation sources and their components, it can be stated that the pandemic has significantly influenced the existing principles and patterns of internal marketing communication. These should be critically reconsidered, and motivation systems should be revised to contribute to the optimal performance of the company on the market and its sustainable development by focusing on the financial situation of the company, significant for the economic pillar; the change in individual value scales, significant for the environmental pillar; and the phenomenon of millennials, significant for the social pillar. By intersecting these pillars, sustainability can be reached based on finding optimum motivation.
Mapping the Knowledge Domains of Emerging Advanced Technologies in the Management of Prefabricated Construction
Authors: Li Clyde Zhengdao , Hu Mingcong , Xiao Bing , Chen Zhe , Tam Vivian W. Y. , Zhao Yiyu
Published: August 2021

Emerging advanced technologies (EAT) have been regarded as significant technological innovations which can greatly improve the transforming construction industry. Given that research on EAT related to the management of prefabricated construction (MPC) has not yet been conducted, various researchers require a state-of-the-art summary of EAT research and implementation in the MPC field. The purpose of this paper is to provide a systematic literature review by analysing the selected 526 related publications in peer-reviewed leading journals during 2009–2020. Through a thorough review of selected papers from the state-of-the-art academic journals in the construction industry, EAT is recognised as the key area affecting the development of the MPC discipline. This study has value in offering original insights to summarise the advanced status quo of this field, helping subsequent researchers gain an in-depth understanding of the underlying structure of this field and allowing them to continue future research directions.
Human Resources Management Practices Perception and Extra-Role Behaviors: The Role of Employability and Learning at Work
Authors: Pace Francesco , Ingusci Emanuela , Signore Fulvio , Sciotto Giulia
Published: August 2021

Human Resource Management (HRM) processes are considered the beating heart of any successful organization. Recently, several studies have highlighted how organizations can use commitment-oriented HR practices to generate organizational and individual effectiveness. The aim of this study was to verify whether the perception of HRM practices could be able to elicit extra-role behaviors and, at the same time, whether this relationship could be mediated by employability and learning conditions. The analyses were carried out on a sample of 1219 Italian workers using Structural Equation Models. The structural model yielded good fit indices and the results showed a significant and positive effect of the perception of HRM practices on both employability and learning. However, the perception of HRM practices is not directly associated with extra-role behaviors, but only through the effect of both mediators (full mediation). Practical implications about the importance of creating working conditions that are adequately oriented to the development of individual skills in order to produce indirect beneficial effects on the organization are discussed.
Identifying Consensus and Open Questions around Assessing or Predicting the Quality and Success of Cartilage Repair: A Delphi Study
Authors: Hopkins Timothy , Richardson James , Kuiper Jan Herman
Published: August 2021

A range of surgical techniques have been developed for the repair or regeneration of lesioned cartilage in the human knee and a corresponding array of scoring systems have been created to assess their outcomes. The published literature displays a wide range of opinions regarding the factors that influence the success of surgical cartilage repair and which parameters are the most useful for measuring the quality of the repair at follow-up. Our objective was to provide some clarity to the field by collating items that were agreed upon by a panel of experts to be important in these areas. A modified, three-round Delphi consensus study was carried out consisting of one idea-generating focus-group and two subsequent, self-completed questionnaire rounds. In each round, items were assessed for their importance and level of consensus against pre-determined threshold levels. In total, 31 items reached consensus, including a hierarchy of tissues in the joint based on their importance in cartilage repair, markers of repair cartilage quality and the implications of environmental and patient-related factors. Items were stratified into those that can be employed for predicting the success of cartilage repair and those that could be used for assessing the structural quality of the resulting repair cartilage. Items that did not reach consensus represent areas where dissent remains and could, therefore, be used to guide future clinical and fundamental scientific research.
Digital Twin-Driven Tool Wear Monitoring and Predicting Method for the Turning Process
Authors: Zhuang Kejia , Shi Zhenchuan , Sun Yaobing , Gao Zhongmei , Wang Lei
Published: August 2021

Accurate monitoring and prediction of tool wear conditions have an important influence on the cutting performance, thereby improving the machining precision of the workpiece and reducing the production cost. However, traditional methods cannot easily achieve exact supervision in real time because of the complexity and time-varying nature of the cutting process. A method based on Digital Twin (DT), which establish a symmetrical virtual tool system matching exactly the actual tool system, is presented herein to realize high precision in monitoring and predicting tool wear. Firstly, the framework of the cutting tool system DT is designed, and the components and operations rationale of the framework are detailed. Secondly, the key enabling technologies of the framework are elaborated. In terms of the cutting mechanism, a virtual cutting tool model is built to simulate the cutting process. The modifications and data fusion of the model are carried out to keep the symmetry between physical and virtual systems. Tool wear classification and prediction are presented based on the hybrid-driven method. With the technologies, the physical–virtual symmetry of the DT model is achieved to mapping the real-time status of tool wear accurately. Finally, a case study of the turning process is presented to verify the feasibility of the framework.
Data Quality Affecting Big Data Analytics in Smart Factories: Research Themes, Issues and Methods
Authors: Liu Caihua , Peng Guochao , Kong Yongxin , Li Shuyang , Chen Si
Published: August 2021

Recent years have seen a growing call for use of big data analytics techniques to support the realisation of symmetries and simulations in digital twins and smart factories, in which data quality plays an important role in determining the quality of big data analytics products. Although data quality affecting big data analytics has received attention in the smart factory research field, to date a systematic review of the topic of interest for understanding the present state of the art is not available, which could help reveal the trends and gaps in this area. This paper therefore presents a systematic literature review of research articles about data quality affecting big data analytics in smart factories that have been published up to 2020. We examined 31 empirical studies from our selection of papers to identify the research themes in this field. The analysis of these studies links data quality issues toward big data analytics with data quality dimensions and methods used to address these issues in the smart factory context. The findings of this systematic review also provide implications for practitioners in addressing data quality issues to better use big data analytics products to support digital symmetry in the context of smart factory.