A pilot-scale hybrid constructed wetland with vertical flow and horizontal flow in series was constructed and used to investigate organic material and nutrient removal rate constants for wastewater ...treatment and establish a practical predictive model for use. For this purpose, the performance of multiple parameters was statistically evaluated during the process and predictive models were suggested. The measurement of the kinetic rate constant was based on the use of the first-order derivation and Monod kinetic derivation (Monod) paired with a plug flow reactor (PFR) and a continuously stirred tank reactor (CSTR). Both the Lindeman, Merenda, and Gold (LMG) analysis and Bayesian model averaging (BMA) method were employed for identifying the relative importance of variables and their optimal multiple regression (MR). The results showed that the first-order–PFR (M2) model did not fit the data (P > 0.05, and R2 < 0.5), whereas the first-order–CSTR (M1) model for the chemical oxygen demand (CODCr) and Monod–CSTR (M3) model for the CODCr and ammonium nitrogen (NH4−N) showed a high correlation with the experimental data (R2 > 0.5). The pollutant removal rates in the case of M1 were 0.19 m/d (CODCr) and those for M3 were 25.2 g/m2∙d for CODCr and 2.63 g/m2∙d for NH4-N. By applying a multi-variable linear regression method, the optimal empirical models were established for predicting the final effluent concentration of five days' biochemical oxygen demand (BOD5) and NH4-N. In general, the hydraulic loading rate was considered an important variable having a high value of relative importance, which appeared in all the optimal predictive models.
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•A two-stage hybrid constructed wetland (HCW) system was constructed and evaluated for performance.•Multi-kinetic models for predicting the HCW performance were applied to analyze the results.•The HCW performance was modeled using linear and nonlinear regression analysis.•An optimal predictive model for experimental development of HCW was presented.
This study investigated methyl orange (MO) dye adsorption using three biochars produced from agro-waste and invasive plants; the latter consisted of wattle bark (BA), mimosa (BM), and coffee husks ...(BC). BC had the lowest specific surface area (2.62 m2/g) compared to BA (393.15 m2/g) and BM (285.53 m2/g). The adsorption efficiency of MO was stable at pH 2–7 (95%–96%), whilst it had reduced stability at pH 7–12. Between 0 and 30 min, MO adsorption efficiency was >82%, and at 120 min, representative adsorption equilibrium had occurred. The maximum adsorption capacity of the biochars was 12.3 mg/g. The underlying adsorption mechanisms of the three biochars were governed by electrostatic adsorption and pore diffusion. There was an abundance of active sites for adsorption in BA and BM, while chemical adsorption appeared to be more vital for BC, as it contained more functional groups on its surface. The highest MO adsorption efficiency occurred with BM. BC was not recommended for MO removal, as it was observed to stain the water when a dose exceeding 5.0 g/L was utilized.
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•Biochars were successfully derived from agro-waste and invasive plants.•After only 30 min the methyl orange adsorption efficiency on biochar was more than 82%.•The adsorption equilibrium was established at 120 min.•The highest adsorption occurred with biochar from mimosa.
Nowadays, breast cancer is one of the leading cancers in Vietnam, and it causes approximately 6000 deaths every year. The rate of breast cancer patients was calculated as 26.4/100000 persons in 2018. ...There are 21,555 new cases reported in 2020. However, these figures can be reduced with early detection and diagnosis of breast cancer disease in women through mammographic imaging. In many hospitals in Vietnam, there is a lack of experienced breast cancer radiologists. Therefore, it is helpful to develop an intelligent system to improve radiologists' performance in breast cancer screening for Vietnamese patients. Our research aims to develop a convolutional neural network-based system for classifying breast cancer X-Ray images into three classes of BI-RADS categories as BI-RADS 1 ("normal"), BI-RADS 23 ("benign") and BI-RADS 045 ("incomplete and malignance"). This classification system is developed based on the convolutional neural network with ResNet 50. The system is trained and tested on a breast cancer image dataset of Vietnamese patients containing 7912 images provided by Hanoi Medical University Hospital radiologists. The system accuracy uses the testing set achieved a macAUC (a macro average of the three AUCs) of 0.754. To validate our model, we performed a reader study with the breast cancer radiologists of the Hanoi Medical University Hospital, reading about 500 random images of the test set. We confirmed the efficacy of our model, which achieved performance comparable to a committee of two radiologists when presented with the same data. Additionally, the system takes only 6 seconds to interpret a breast cancer X-Ray image instead of 450 seconds interpreted by a Vietnamese radiologist. Therefore, our system can be considered as a "second radiologist," which can improve radiologists' performance in breast cancer screening for Vietnamese patients.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Increasing levels of displacement and the need to integrate refugees in the workforce pose new challenges to organizations and societies. Extant research on refugee employment and workforce ...integration currently resides across various disconnected disciplines, posing a significant challenge for management scholars to contribute to timely and relevant solutions. In this paper, we endeavour to address this challenge by reviewing and synthesizing multidisciplinary literature on refugee employment and workforce integration. Using a relational framework, we organize our findings around three levels of analysis – institutional, organizational and individual – to outline the complexity of factors affecting refugees’ employment outcomes. Based on our analysis, we introduce and elaborate on the phenomenon of the canvas ceiling ‒ a systemic, multilevel barrier to refugee workforce integration and professional advancement. The primary contributions of this paper are twofold. First, we map and integrate the multidisciplinary findings on the challenges of refugee workforce integration. Second, we provide management scholarship with a future research agenda to address the knowledge gap identified in this review and advance practical developments in this domain.
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•Recent pretreatment techniques for improving anaerobic digestion of sewage sludge were reviewed.•Sludge pretreatment ameliorates anaerobic digestion and increases the biogas ...yield.•Pretreatment technique efficiency depends on sewage sludge composition.•Microbes play a crucial role in sewage sludge stabilization.•Very few pretreatment techniques are suitable for full-scale implementation.
Anaerobic digestion (AD) of sewage sludge is one of the most efficient, effective, and environmentally sustainable remediation techniques; however, the presence of complex floc structures, hard cell walls, and large amounts of molecular organic matter in the sludge hinder AD hydrolysis. Consequently, sewage sludge pretreatment is a prerequisite to accelerate hydrolysis and improve AD efficiency. This review focuses on pretreatment techniques for improving sewage sludge AD, which include mechanical, chemical, thermal, and biological processes. The various pretreatment process effects are discussed in terms of advantages and disadvantages, including their effectiveness, and recent achievements are reviewed for improved biogas production.
•Porous network Fe2O3 effectively prepared from Fe3O4/rGO.•The porous network Fe2O3 exhibited good performance to ethanol gas.•The developed strategy can employed for preparation of other porous ...network metal oxide.
Nanoporous network metal oxides are potential candidates for various applications such as filtration, biomaterials devices, and sensing materials. The present work focused on the simple and scalable fabrication of the α-Fe2O3 nanoporous network for ethanol gas sensor using Fe3O4/reduced graphene oxide (rGO) as a precursor. The analyzed morphology and crystal structure indicated that the α-Fe2O3 nanoporous network was formed due to some factors during thermal procedures such as the phase transformation from magnetite to hematite, nanoparticle agglomeration, and combustion of rGO. The ethanol gas-sensing properties of the α-Fe2O3 nanoporous network were investigated. The response to 100ppm ethanol gas was as high as 9.5, while the cross-gas responses to 100ppm NH3, H2, and CO gases were all lower than 2.0. These values indicated a good selectivity of the sensors. Furthermore, the 90% response times to ethanol gas were less than 5s at 400°–450°C. The proposed strategy has potential in the preparation of other porous network metal oxides to achieve high-performance gas sensors.
Background. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a pandemic of pneumonia spreading around the world, leading to serious threats to public health and attracting ...enormous attention. There is an urgent need for sensitive diagnostic testing implementation to control and manage SARS-CoV-2 in public health laboratories. The quantitative reverse transcription PCR (RT-qPCR) assay is the gold standard method, but the sensitivity and specificity of SARS-CoV-2 testing are dependent on a number of factors. Methods. We synthesized RNA based on the genes published to estimate the concentration of inactivated virus samples in a biosafety level 3 laboratory. The limit of detection (LOD), linearity, accuracy, and precision were evaluated according to the bioanalytical method validation guidelines. Results. We found that the LOD reached around 3 copies/reaction. Furthermore, intra-assay precision, accuracy, and linearity met the accepted criterion with an RSD for copies of less than 25%, and linear regression met the accepted R2 of 0.98. Conclusions. We suggest that synthesized RNA based on the database of the NCBI gene bank for estimating the concentration of inactivated virus samples provides a potential opportunity for reliable testing to diagnose coronavirus disease 2019 (COVID-19) as well as limit the spread of the disease. This method may be relatively quick and inexpensive, and it may be useful for developing countries during the pandemic era. In the long term, it is also applicable for evaluation, verification, validation, and external quality assessment.
Antioxidants are a diverse group of chemicals with proven health benefits and thus potential preventive medicine and therapeutic applications. While most of these compounds are natural products, ...determining their mechanism of radical scavenging and common motifs that contribute to antioxidant activity would allow the rational design of novel antioxidants. Here the origins of the antioxidant properties of ten natural products of the lignan family were studied in silico by calculating their thermochemical properties by using ROB3LYP/6-311++G(2df,2p)//B3LYP/6-311G(d,p) model chemistry. Three conditions were modelled: gas phase, ethanol and water solvents. The results allowed assigning the antioxidant activity to specific moieties and structural features of these compounds. It was found that the benzylic hydrogen atoms are the most likely to be abstracted to form radicals and hence define antioxidant properties in most of the studied compounds. The results also suggested that the most likely mechanism of HOO
radical scavenging differs by the key moiety: it is hydrogen atom transfer in case the benzylic C-H bonds, however it is proton coupled electron transfer in case of the compounds where O-H bonds are responsible for radical scavenging.
Ballbots are omnidirectional self-balancing platforms that can be exploited in many applications to detect, track, or interact with objects or humans, such as a service robot. Ballbot will enable ...mobile robots to stand tall and move elegantly through busy environments. However, maintaining equilibrium through synchronization of motion between the ball and the body of a Ballbot is still an open research problem. This article presents a synchronization control (SC) design, with synchronization and coupling errors for Ballbots to stabilize the body and control ball transfer simultaneously. The proposed SC method is applied to the two 2-D planar models of a Ballbot robot. The dynamic model of the Ballbot is derived, and parameters are identified online using the intelligent particle swarm optimization method. The proposed controller is proven to guarantee asymptotic convergence to zero errors in tracking and synchronization. The stabilizing and transferring problems are investigated through several simulations and experiments by using an actual Ballbot platform. Moreover, the controller performance is compared with an augmented proportional derivative controller and a partial feedback linearization controller. The results and comparisons demonstrate a superior stabilization accuracy of the proposed SC method.
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•CuFe2O4@tetracarboxy-porphyrin nanofiber hybrid materials were synthesized.•Hybrid material exhibited good photoenergy-harvesting from solar fuel.•Hybrid material was magnetically ...separable and recyclable.•Self-assembly was used to produce efficient photocatalysts for water splitting.•Rhodamine B degradation mechanism using composite material is proposed.
The main aim of this study was to synthesize an innovative magnetic CuFe2O4@porphyrin nanofiber hybrid material via one-step re-precipitation self-assembly of freebase-tetracarboxy-porphyrin (TCPP), in the presence of CuFe2O4 nanoparticles. The resultant hybrid materials were thoroughly characterized using scanning electron microscopy, energy-dispersive X-ray mapping, X-ray diffractometry, and Fourier-transform infrared, and UV–vis spectroscopy. Results showed well-integration of CuFe2O4 nanoparticles into TCPP nanofiber network, with the average size of CuFe2O4 being less than 100 nm and diameter and length of TCPP aggregate being approximately 20 nm and several µm, respectively. The as-prepared hybrid material possessed strong magnetic properties with a saturated magnetization value of approximately 25 emu/g. This photocatalyst was highly efficient in the removal of rhodamine B (RhB) dye, with the rate constant reaching 2.1 × 10−2 min−1. This paper describes in detail a plausible photocatalytic mechanism for RhB removal by CuFe2O4@porphyrin nanofiber hybrid material.
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