bluuebunny/crossref_metadata_2025_split huggingface dataset:
Smart Hydroponic Greenhouse (Sensing, Monitoring and Control) Prototype Based on Arduino and IOT
Authors: Abul-Soud M. A. , Emam M. S. A. , Mohammed Sh. M. 
Published: April 2021

Aims: Sensing, monitoring and control the micro-climate measurements and environmental conditions of greenhouse prototype to create a smart hydroponic greenhouse for maximizing the food production as well as minimizing the ecological footprint under the climate change impacts, Coved 19 crisis, and natural resources shortages.
Study Design: Factorial with 3 replicates.
Place and Duration of Study: Central Laboratory for Agriculture Climate (CLAC), Agriculture Research Center, Egypt during 2020.
Methodology: Two systems of hydroponic culture, nutrient film technique (NFT) and deep flow technique (DFT) that cultivated by lettuce plants were established under greenhouse (polycarbonate) prototype (0.8 * 1.2 * 0.6 m) designed with artificial grown light and cooling system. Based on Arduino Mega 2560 that programmed via the Arduino IDE program, different sensors and actuators were used to establishing the smart greenhouse. Internet of things (IoT) via Node MCU ESP 8266 that programmed to transmitted the data every 30 min. to the internet web google platform (Firebase) for presenting the real-time records and hosting the data. Vegetative characteristics; yield parameters and N, P, and K contents of lettuce plants were measured.
Results: the smart greenhouse worked according to the programming of Arduino Mega and Node MCU with high efficiency. Google firebase platform displays the real-time records and hosts about 100 thousand different sensor records during the lettuce season. Decreasing the distance between the lettuce and artificial lightning source led to increasing the intensity of light that had a positive impact on lettuce growth but it wasn't sufficient to give a high quality of lettuce yield under the experiment. NFT system gave higher values of average No. of leaves and fresh weight of lettuce plants than DFT system that presented higher plant length.
Conclusion: Integrated monitoring and control system and IOT provide a wireless sensors network that offered a high capability of accessing huge data anywhere and anytime. Smart management of nutrient solution (TDS, pH, temperature, and level), without smart control, were not useful enough regarding the rapid solution changes and the need for a high response.
Social Media Use, Addiction and Burnout Levels of Hospital Employees, Effective Factors: A Cross Sectional Study
Authors: Aydin Kübra Yildiz , Aydin Neriman , Özçirpici Birgül 
Published: April 2021

Background: As years passes by, the usage of social media has become an important public health issue. It is known that problematic social media use is related with health problems. With this study, it is aimed to determine the social media use of hospital employees, the relation between social media addiction and burnout levels and to determine effective factors.
Methods: Target population of the cross-sectional study consists of 2627 person between the ages of 18-60 who is working at a university hospital. Minimum sample size was calculated as 321 and reached up to 323 people. Question form, Burnout Scale and Social Media Addiction Adult Form were applied by interviewing the employees face-to-face between the months of March-April 2019.
Results: 80.2% of the participants use social media every day, 63.1% of them use social media mostly at evenings. 94.8% of people mostly connect to social media with their phone. Average time spent daily on social media is 91, 33±87, 89 minutes. Daily social media use is significantly higher in women, university graduates, nurses. There is a significant difference between age groups and between married and never married in terms of average time spent daily on social media. Social media addiction scale score is significantly higher in women, never married persons and in the age group 20-29. Weak correlation was determined between scores of social media addiction scale and burnout levels, and age and time spent on social media.
Conclusions: It is determined that social media usage in hospital employees is higher than Turkey’s average and there is a positive relation between scores of social media addiction scale and burnout levels. Providing education to employees in order to reduce social media usage, hanging posters related with how over-usage of social media may lead to burnout.
An Investigation on the Antiproliferative and Antibacterial Activity of Silver Nanoparticles of Quercus infectoria and Daucus carota subsp sativum
Authors: Prathimaa S. , Anbumalarmathi J. , Sharmili S. Aruna 
Published: April 2021

Plant mediated fabrication of nanoparticles and nanomaterials are gaining momentum as it is eco-friendly and cost-effective. In the present study, we synthesis of Silver nanoparticles using aqueous extract of Quercus infectoria nuts and Daucus carota subsp sativum leaves. The surface plasma resonance at 417 and 450 nm for Q. infectoria and D. carota respectively confirmed the formation of AgNPs. Scanning Electron Microscopic (SEM) confirmed the spherical shape of the nanoparticles, which had an average size of 67.5 nm and 49.2 nm for Q. infectoria nanoparticles (QAgNPs)and D. carota nanoparticles (DAgNPs). The elemental composition by Energy-Dispersive X-ray analysis of the nanoparticle showed an atomic percentage of silver as 73.64 % and 75.93% for Q. infectoria and D. carota.FT- IR analysis of the plant extracts and synthesized silver nanoparticles showed the presence of various functional groups. The total antioxidant activity of QAgNPs was 81.18% and that of DAgNPs was 73.36%. The QAgNPs and DAgNPs exhibited antibacterial activity against B. subtilis, E. coli and S. aureus. The percentage of cell viability for QAgNPs and DAgNPs assessed using HeLa cells was 21.1% and 6% respectively.
Reliability Analysis of a Home-scale Microgrid Based on a Threshold System
Authors: Hidayat Taufal , Rushdi Ali Muhammad 
Published: April 2021

The reliability of a microgrid power system is an important aspect to analyze so as to ascertain that the system can provide electricity reliably over a specified period of time. This paper analyzes a home-scale model of a microgrid system by using the threshold system model (inadvertently labeled as the weighted k-out-of-n:G system model), which is a system whose success is treated as a threshold switching function. To analyze the reliability of the system, we first proved that its success is a coherent threshold function, and then identified possible (non-unique) values for its weights and threshold. Two methods are employed for this. The first method is called the unity-gap method and the second is called the fair-power method. In the unity-gap method, we utilize certain dominations and symmetries to reduce the number of pertinent inequalities (turned into equations) to be solved. In the fair-power method, the Banzhaf index is calculated to express the weight of each component as its relative power or importance. Finally, a recursive algorithm for computing system reliability is presented. The threshold success function is verified to be shellable, and the non-uniqueness of the set of weights and thresholds is demonstrated to be of no detrimental consequence, as different correct sets of weights and threshold produce equivalent expressions of system reliability.
Glucose oxidase: Applications, sources, and recombinant production
Authors: Khatami Seyyed Hossein , Vakili Omid , Ahmadi Nahid , Soltani Fard Elahe , Mousavi Pegah , Khalvati Bahman , Maleksabet Amir , Savardashtaki Amir , Taheri‐Anganeh Mortaza , Movahedpour Ahmad 
Published: April 2021

AbstractGlucose oxidase is a subset of oxidoreductase enzymes that catalyzes the transfer of electrons from an oxidant to a reductant. Glucose oxidases use oxygen as an external electron acceptor that releases hydrogen peroxide (H2O2). Glucose oxidase has many applications in commercial processes, including improving the color and taste, increasing the persistence of food materials, removing the glucose from the dried egg, and eliminating the oxygen from different juices and beverages. Moreover, glucose oxidase, along with catalase, is used in glucose testing kits (especially in biosensors) to detect and measure the presence of glucose in industrial and biological solutions (e.g., blood and urine specimens). Hence, glucose oxidase is a valuable enzyme in the industry and medical diagnostics. Therefore, evaluating the structure and function of glucose oxidase is crucial for modifying as well as improving its catalytic properties. Finding different sources of glucose oxidase is an effective way to find the type of enzyme with the desired catalysis. Besides, the recombinant production of glucose oxidase is the best approach to produce sufficient amounts of glucose oxidase for various uses. Accordingly, the study of various aspects of glucose oxidase in biotechnology and bioprocessing is crucial.
Laboratory monitoring approaches for tailings settling and evaluation of flocculant and coagulant treatments
Authors: Babak Petro , Li Feng , Cabrera Sandra Motta , Kantzas Apostolos 
Published: April 2021

AbstractX‐ray computer tomography (CT), magnetic resonance imaging (MRI), and nuclear magnetic resonance (NMR) are applied for laboratory monitoring of the settling behaviour in tailings suspensions. It is shown that the developed monitoring techniques are consistent with each other and provide different levels of information from 2D density cross‐sections obtained using X‐ray CT to 1D and bulk water content using MRI and NMR. Analysis of coagulant and flocculant treatments based on obtained measurement information is conducted using linear and nonlinear kinetic modelling approaches. The linear Roberts' kinetic model describes the settling of original tailings suspensions very well, but it is not adequate for the suspensions treated with additives. A modified nonlinear Roberts' model is developed and successfully applied to analyze the suspension with additives. The analysis of combined flocculants and coagulants treatments reveals that flocculants significantly affect the settling rate; however, they decrease the efficiency of settling with respect to the residual water content. Coagulants affect mostly the residual water content in samples, but do not change the settling rate significantly. The trade‐off between concentrations of coagulants and flocculants needs to be achieved for optimal settling treatments.
Corporate social responsibility and financial performance: International evidence of the mediating role of reputation
Authors: Fourati Yosra Makni , Dammak Mariam 
Published: April 2021

AbstractThe aim of this article is to explore both the direct and indirect effect of corporate social responsibility (CSR) on corporate financial performance (CFP). Specifically, the mediating role of corporate reputation (CR) on the relationship between CSR and CFP is examined. We empirically investigate a sample of 3274 listed firms over the period 2009–2016 drawn from 25 countries located at Europe, Asia, Africa, and South and North America. Using four OLS regressions, we evince on the one side that CSR has a positive and direct impact on CFP. On the other side, we show that CR mediates the relationship between CSR and CFP: CSR has a significant and positive impact on CR and that CR has a significant and positive influence on CFP. The results of this study add to CSR‐related literature by providing international evidence and provide direction for a comparison across countries.
Light scattering pattern specific convolutional network static cytometry for label‐free classification of cervical cells
Authors: Liu Shanshan , Yuan Zeng , Qiao Xu , Liu Qiao , Song Kun , Kong Beihua , Su Xuantao 
Published: April 2021

AbstractCervical cancer is a major gynecological malignant tumor that threatens women's health. Current cytological methods have certain limitations for cervical cancer early screening. Light scattering patterns can reflect small differences in the internal structure of cells. In this study, we develop a light scattering pattern specific convolutional network (LSPS‐net) based on deep learning algorithm and integrate it into a 2D light scattering static cytometry for automatic, label‐free analysis of single cervical cells. An accuracy rate of 95.46% for the classification of normal cervical cells and cancerous ones (mixed C‐33A and CaSki cells) is obtained. When applied for the subtyping of label‐free cervical cell lines, we obtain an accuracy rate of 93.31% with our LSPS‐net cytometric technique. Furthermore, the three‐way classification of the above different types of cells has an overall accuracy rate of 90.90%, and comparisons with other feature descriptors and classification algorithms show the superiority of deep learning for automatic feature extraction. The LSPS‐net static cytometry may potentially be used for cervical cancer early screening, which is rapid, automatic and label‐free.
Integration, exploration, and analysis of high‐dimensional single‐cell cytometry data using Spectre
Authors: Ashhurst Thomas Myles , Marsh‐Wakefield Felix , Putri Givanna Haryono , Spiteri Alanna Gabrielle , Shinko Diana , Read Mark Norman , Smith Adrian Lloyd , King Nicholas Jonathan Cole 
Published: April 2021

AbstractAs the size and complexity of high‐dimensional (HD) cytometry data continue to expand, comprehensive, scalable, and methodical computational analysis approaches are essential. Yet, contemporary clustering and dimensionality reduction tools alone are insufficient to analyze or reproduce analyses across large numbers of samples, batches, or experiments. Moreover, approaches that allow for the integration of data across batches or experiments are not well incorporated into computational toolkits to allow for streamlined workflows. Here we present Spectre, an R package that enables comprehensive end‐to‐end integration and analysis of HD cytometry data from different batches or experiments. Spectre streamlines the analytical stages of raw data pre‐processing, batch alignment, data integration, clustering, dimensionality reduction, visualization, and population labelling, as well as quantitative and statistical analysis. Critically, the fundamental data structures used within Spectre, along with the implementation of machine learning classifiers, allow for the scalable analysis of very large HD datasets, generated by flow cytometry, mass cytometry, or spectral cytometry. Using open and flexible data structures, Spectre can also be used to analyze data generated by single‐cell RNA sequencing or HD imaging technologies, such as Imaging Mass Cytometry. The simple, clear, and modular design of analysis workflows allow these tools to be used by bioinformaticians and laboratory scientists alike. Spectre is available as an R package or Docker container. R code is available on Github (https://github.com/immunedynamics/spectre).
Northern landscapes in transition: Evidence, approach and ways forward using the Krycklan Catchment Study
Authors: Laudon Hjalmar , Hasselquist Eliza Maher , Peichl Matthias , Lindgren Kim , Sponseller Ryan , Lidman Fredrik , Kuglerová Lenka , Hasselquist Niles J. , Bishop Kevin , Nilsson Mats B. , Ågren Anneli M. 
Published: April 2021

AbstractImproving our ability to detect changes in terrestrial and aquatic systems is a grand challenge in the environmental sciences. In a world experiencing increasingly rapid rates of climate change and ecosystem transformation, our ability to understand and predict how, when, where, and why changes occur is essential for adapting and mitigating human behaviours. In this context, long‐term field research infrastructures have a fundamentally important role to play. For northern boreal landscapes, the Krycklan Catchment Study (KCS) has supported monitoring and research aimed at revealing these changes since it was initiated in 1980. Early studies focused on forest regeneration and microclimatic conditions, nutrient balances and forest hydrology, which included monitoring climate variables, water balance components, and stream water chemistry. The research infrastructure has expanded over the years to encompass a 6790 ha catchment, which currently includes 11 gauged streams, ca. 1000 soil lysimeters, 150 groundwater wells, >500 permanent forest inventory plots, and a 150 m tall tower (a combined ecosystem‐atmosphere station of the ICOS, Integrated Carbon Observation System) for measurements of atmospheric gas concentrations and biosphere‐atmosphere exchanges of carbon, water, and energy. In addition, the KCS has also been the focus of numerous high resolution multi‐spectral LiDAR measurements and large scale experiments. This large collection of equipment and data generation supports a range of disciplinary studies, but more importantly fosters multi‐, trans‐, and interdisciplinary research opportunities. The KCS attracts a broad collection of scientists, including biogeochemists, ecologists, foresters, geologists, hydrologists, limnologists, soil scientists, and social scientists, all of whom bring their knowledge and experience to the site. The combination of long‐term monitoring, shorter‐term research projects, and large‐scale experiments, including manipulations of climate and various forest management practices, has contributed much to our understanding of boreal landscape functioning, while also supporting the development of models and guidelines for research, policy, and management.
The effects of ditch dams on water‐level dynamics in tropical peatlands
Authors: Putra Santosa Sandy , Holden Joseph , Baird Andy J. 
Published: April 2021

AbstractA significant proportion of tropical peatlands has been drained for agricultural purposes, resulting in severe degradation. Hydrological restoration, which usually involves blocking ditches, is therefore a priority. Nevertheless, the influence of ditch blocking on tropical peatland hydrological functioning is still poorly understood. We studied water‐level dynamics using a combination of automated and manual dipwells, and also meteorological data during dry and wet seasons over 6 months at three locations in Sebangau National Park, Kalimantan, Indonesia. The locations were a forested peatland (Forested), a drained peatland with ditch dams (Blocked), and a drained peatland without ditch dams (Drained). In the dry season, water tables at all sites were deeper than the Indonesian regulatory requirement of 40 cm from the peat surface. In the dry season, the ditches were dry and water did not flow to them. The dry season water‐table drawdown rates — solely due to evapotranspiration — were 9.3 mm day−1 at Forested, 9.6 mm day−1 at Blocked, but 12.7 mm day−1 at Drained. In the wet season, the proportion of time during which water tables in the wells were deeper than the 40 cm limit ranged between 16% and 87% at Forested, 0% at Blocked, and between 0% and 38% at Drained. In the wet season, water flowed from the peatland to ditches at Blocked and Drained. The interquartile range of hydraulic gradients between the lowest ditch outlet and the farthest well from ditches at Blocked was 3.7 × 10−4 to 7.8 × 10−4 m m−1, but 1.9 × 10−3 to 2.6 × 10−3 m m−1 at Drained. Given the results from Forested, a water‐table depth limit policy based on field data may be required, to reflect natural seasonal dynamics in tropical peatlands. Revised spatial designs of dams or bunds are also required, to ensure effective water‐table management as part of tropical peatland restoration.
Bioremediation of coke plant wastewater from steel industry with mixed activated sludge–microalgal consortium in lab‐scale semi‐continuous mode
Authors: Kaur Nagi Gurpreet , Chetry Rosy , Singh Nisha , Sinha Apurva , Shinde Omkar Avinash 
Published: April 2021

AbstractBACKGROUNDRemoval of toxicities from wastewater has always demanded great attention as it has life‐threatening impacts on every living being and the environment. In the present study, bioremediation of ammonia and cyanide from coke plant wastewater (CPWW) by using bacterial consortia with activated sludge (AS) supplemented with microalgal (MA) biomass in semi‐continuous mode was performed. Parameters such as pH, total dissolved solids (TDS), dissolved oxygen (DO) and bacterial cell viability, along with any significant effect on the growth of microalgal cells in wastewater, was investigated by determining its specific growth rate (μ).RESULTSWith pH values remaining constant for the system, the ammonia removal rate with microalgae additions was approximately 38.3% lower than that with AS. Similarly, the cyanide removal rate after addition of microalgae to the system showed a difference of 43% with AS treatment. TDS levels dropped by 22.18% and the concentration of DO increased by 21.91% in comparison to the values obtained by treatment of CPWW with AS and MA to CPWW with AS alone.CONCLUSIONMicroalgae additions effectively increase the efficiency of AS treatment of CPWW and thus can be taken to field trials for developing a cost‐effective and environmentally friendly strategy of wastewater treatment. © 2021 Society of Chemical Industry
Enhancement of the quick lime‐based solidification/stabilization of oily wastes using modified clay
Authors: Jebeli Mojtaba Tayebi , Heidarzadeh Nima 
Published: April 2021

AbstractBACKGROUNDThis research investigated the solidification/stabilization process (S/S) efficiency of contaminated soil by total petroleum hydrocarbons (TPH) in the waste of a used oil treatment plant using quick lime (QL) as a binder and modified clay (MC) as an additive. Several objectives were considered, including reducing the mobility and leaching of TPH, investigating the effect of MC on the QL hydration process in the presence of organic matter, the possibility of S/S waste reuse, and estimating the S/S cost for the optimum mixture.RESULTSThe unconfined compressive strength (UCS) increased about 45% by increasing 25% of QL without MC, but these S/S wastes did not satisfy the waste reuse standards. Additionally, adding any ratio of MC to samples containing QL increased UCS significantly. The UCS of all samples at the age of 28 days with different QL and MC proportions obtained more than 350 kPa (the minimum UCS required for S/S waste disposal in the landfill). Moreover, the toxicity characteristic leaching procedure (TCLP) test revealed that TPH leaching of contaminated soil was 3.8 mg L−1 but adding only 15% of QL could reduce TPH leaching to less than 1 mg L−1, which is the maximum allowable TPH leaching.CONCLUSIONThe combination of QL and MC decreased TPH leaching, significantly. The scanning electron microscopy analysis also showed that QL hydration was improved by increasing the amount of MC. Finally, a sample with 35% QL and 15% MC was selected as an optimum sample due to its cost of $80.5/ton. © 2021 Society of Chemical Industry (SCI).