Adsorption, oxidation, kinetic and thermodynamic studies of methyl orange by magnetic Fe3O4 NPs and their chitosan/alginate nanocomposites

Magnetic iron oxide (Fe3O4) nanoparticles, iron oxide chitosan (Fe3O4-CS) and iron oxide alginate (Fe3O4-AT) nanocomposite beads were synthesised using green synthesis method. They were used as both adsorbents for the adsorption of methyl orange (MO) dye from the wastewater and heterogeneous catalysts for the catalytic wet peroxidation (CWPO) of MO. While the dye removal was successfully performed with Fe(3)O(4)NPs, Fe3O4-CS and Fe3O4-AT in both adsorption studies and CWPO, the highest removal efficiency (99%) in the shortest time (8 min for adsorption, 20 min for CPWO) was obtained with Fe3O4-CS for MO removal. The adsorption experiments were performed with the batch techniques at different contact time, pH, initial dye concentration, temperature, amount of adsorbent and foreign ion effect parameters by Fe3O4-CS adsorbent. The equilibrium was quickly reached after 30 min at pH 3 and 298 K. Fitting equilibrium data to Langmuir, Temkin and Freundlich isotherms showed that Langmuir model was more suitable to describe MO adsorption with a maximum monolayer adsorption capacity of 132 mg/g at 298 K. The Experimental data were analysed using intra particle diffusion, pseudo-first-order and pseudo-second-order kinetic models and it was found that the adsorption kinetics followed a pseudo-second-order equation. Based on thermodynamic studies, adsorption process occurred as spontaneous and exothermic. The effects of the amount of catalyst, pH, temperature and H2O2 concentration were investigated to determine their catalytic activities for the decomposition of MO with CWPO technique. The reusability of Fe3O4-CS for both adsorption and CWPO techniques for MO removal was performed, and the adsorption and oxidation efficiency was found to be 97%. Moreover, the reaction kinetics was also investigated and the oxidation reaction was in good agreement with the pseudo-first order kinetic model. The activation energy (Ea) of the reaction was found to be 10.72 kJ/mol

Removal of naproxen and diclofenac using magnetic nanoparticles/nanocomposites

Magnetic iron oxide and iron/copper nanoparticles were synthesized using Lathyrus brachypterus extract, and then magnetic Fe3O4–CS, Fe3O4–AT, Fe/Cu–CS and Fe/Cu–AT nanocomposite beads were synthesized using chitosan and alginate natural polymers. They were used for both adsorption and heterogeneous catalysts for the catalytic wet peroxidation (CWPO) of naproxen (NPX), diclofenac (DCF) and NPX + DCF drugs which are important micro-organic pollutants, separately and together (NPX + DCF) from aqueous media. In adsorption studies, the drugs were adsorbed very quickly in the first minutes and then, desorbed in between 8 and 10 min. In competitive adsorption, the adsorbents showed selective properties for DCF and NPX. In CWPO technique, drug removal was achieved in 9 min with a conversion capacity of 92% for DCF with Fe/Cu–CS and 84% for NPX with Fe/Cu–AT optimum experimental conditions, such as pH 5, 30% of H2O2, 100 mg catalyst and 298 K. Based on reusability of the catalysts, it was seen that there was a slight decrease in the removal efficiencies in the third cycle and the stable and active structure of the catalyst was preserved to the desired extent. Furthermore, the oxidation reaction was in good agreement with the pseudo-first-order kinetic model. Graphical abstract: [Figure not available: see fulltext.] © 2022, The Author(s), under exclusive licence to Springer Nature B.V

Biosynthesis of Gold Nanoparticles (AuNPs) with Dimrit Raisin Extract and Their Degradation Activity for Water Contaminants

AuNPs are being conventionally synthesized by traditional methods (physical and/or chemical) with preferred and well-defined morphology, size and shape. On the other hand, it has been reported that these methods involve difficult reaction conditions and/or toxic chemicals. In this study, an easy, cost effective and more environmentally and biological-friendly method was described for the synthesis of gold nanoparticles with Dimrit raisin extract for the first time. The effects of some experimental parameters, such as concentrations of both raisin extracts and Au solutions, synthesis time and synthesis temperature were investigated for the synthesis of AuNPs. The synthesized AuNPs were extensively characterized by UV-Visible spectrometer, Transmission electron microscopy (TEM), X-ray diffraction patterns (XRD) and Fourier transform–infrared spectroscopy (FTIR). TEM results show spherical along with triangular and hexagonal shaped nanoparticles with an average size of 15 nm. Large amounts of toxic dyes are used in the different industrial area and dyes posed a threat for water sources. Therefore, it has become imperative to develop inexpensive and environmentally friendly methods to remove dyes from water. In recent years, degradation using green synthesized nanoparticles has become an efficient method to remove dyes from the water sources. In this study, the catalytic activity of the AuNPs for the degradation of both methylene blue (MB) and methyl orange (MO) dyes were also studied and AuNPs behaved as effective catalysts for both degradations of MB and MO dyes in terms of percentage removal and kinetics. The experiment results showed that AuNPs can be employed as strong candidate in wastewater treatment studies

Green synthesis of silver nanoparticles using Lathyrus brachypterus extract for efficient catalytic reduction of methylene blue, methyl orange, methyl red and investigation of a kinetic model

A facile, green, and an efficient method for the synthesis of AgNPs (silver nanoparticles) using Lathyrus brachypterus var. brachypterus extract is reported. AgNPs was characterized by UV-Vis, XRD, TEM and FTIR. The UV-Vis spectra of the AgNPs revealed a characteristic surface plasmon resonance peak at 452 nm. The synthesized AgNPs reacted as a heterogeneous catalyst for the reduction of dyes (methylene blue, methyl red and methyl orange) both in unary and ternary mixture (TM) with and without NaBH4 (sodium borohydride). The kinetic parameter (k) for the degradation reactions and half-life (t(1/2)) of dyes has been calculated according to Michaelis-Menten kinetics. Green synthesized of AgNPs effectively degraded the dyes at approximately 4-6 min. In addition, oxidation studies of methyl orange with H2O2 (hydrogen peroxide) have been also carried out and it has been reported that AgNPs can be reused as heterogeneous catalysts. The oxidation of MO was monitored with a UV-Vis spectrometer. AgNPs was separated using a filter paper after the oxidation of MO. The separated AgNPs were reused without important loss of its activity with a conversion efficiency of around 98%

The Combined Contribution of Fear and Perceived Danger of COVID-19 and Metacognitions to Anxiety Levels during the COVID-19 Pandemic.

Despite a wide base of research suggesting a major role for dysfunctional metacognitions in contributing to anxiety, their role in explaining psychological distress in the context of the COVID-19 pandemic remains unclear. In this study we investigated whether metacognitions would predict anxiety, while controlling for fear and perceived danger of COVID-19. A total of 862 individuals were included in this study. Participants completed sociodemographic questions, emotional state questions relating to COVID-19, the Metacognitions Questionnaire-30, and the Generalized Anxiety Disorder-7. Results showed that both negative beliefs about thoughts concerning uncontrollability and danger, and cognitive self-consciousness were significant predictors of anxiety beyond the fear and perceived danger of COVID-19. Future studies involving clinical populations are needed to investigate the longer-term impact of metacognitions in the maintenance and exacerbation of anxiety associated with the fear and perceived danger of COVID-19

Investigation of structural behavior of liquid storage tank with stiffening plates under wave load

Endüstriyel alanda sıkça yer bulan depolama yapıları, kullanıldıkları amaca göre değişken geometri, taşıyıcı sistem ve yapı malzemesine sahip olup silo olarak isimlendirilmektedir. Sıvı depolama için tasarlanan silo tipi yapılarda silindir tasarım ve çelik konstruksiyon tercih edilmektedir. Sıvı depolama amacıyla inşa edilen bir yapı, depolanan maddeye, sıvı yüzeyinde oluşabilecek dalga kuvvetine ve sıvının silo cidarına yapmakta olduğu hidrostatik basınç dikkate alınarak dizayn edilmektedir. Bu kapsamda silo taşıyıcı sisteminin yatay yönde etkiyen ve yüksekliğe bağlı artan gerilme değerleri altında yeter rijitlikçe çalışması gerekmektedir. Ayrıca, yapı duvarlarından birçok değişkene bağlı olan dalga yükününde karşılanması istenmektedir. Literatürde, dinamik etki altında göçme durumuna gelmiş silo tipi yapılar incelendiğinde; genellikle silo yapısının depolamakla görevli olduğu maddenin dinamik etki altındaki davranışına bağlı olarak yapı rijitliğinin ve periyodunun etkilendiği vurgulanmıştır. Yapı özelliklerinde meydana gelen bu değişimin yapının göçme moduna gelmesine sebep olduğu görülmüştür. Bu çalışmada, 12.5m çapında ve 12m yüksekliğinde tasarlanan sıvı depolama tankının dalga yükü altındaki davranışı incelenecektir. Dalga yükü etkisinde silo duvarında oluşabilecek gerilme ve deformasyon etkilerini sönümlemek amacı ile dikey ve yatay rijitleştirme levhaları kullanılmıştır. Tasarlanan yapı Ansys WB sonlu elemanlar programı kullanılarak analiz edilmiştir. Analiz sonuçlarına dayanılarak, rijitleştirme levhalarının yapı davranışına etkisi incelenmiştir. Levhaların birlikte kullanılmasının daha iyi sonuçlar verdiği görülmüştür.Storage structures, which are frequently found in the industrial areas, have variable; geometry, carrier system and building material according to their purpose of use. In liquid storage structures, cylinder designed steel silo constructions are quite common. A structure built for liquid storage is designed according to the stored mass, hydrostatic pressure and the wave load within the silo wall. In this case, the silo carrier system needs to operate sufficiently rigid under the horizontal and vertical stresses. Also, under the wave forces, it is desirable from walls, to be able to carry the wave load that varies depending on the mechanical properties of the liquid stored inside. In the literature; When the silo type structures that are collapsed under dynamic excitation effects are examined; it was emphasized that the behavior of stored material under the dynamic excitation; has affected, rigidity and period of the structure. This situation in the structure period and behavior has been shown to cause the structure to fail. In this study, behavior of a liquid storage tank designed with 12.5m diameter and 12m height is investigated under wave loads. Vertical and horizontal stiffening plates are used to dampen the stress and deformation effects that may occur on the structure wall due to wave load. The designed structure is analyzed using Ansys WB program. Based on the results of the analysis, the contribution of the stiffening plates to the behavior is examined. It has been seen that use of plates together has given better results

Flame Retardancy and Excellent Electrical Insulation Performance of RTV Silicone Rubber

Room temperature vulcanized (RTV) silicone rubber filled with aluminum trihydrate (ATH) is substantially engaged in electrical outdoor insulation applications. The pristine silicone rubber is highly combustible. ATH filled silicone rubber offers excellent electrical insulation but lacks in providing adequate flame retardancy. This short communication reports the novel results on improved flame retardancy of pristine and ATH filled silicone rubber whilst retaining the electrical insulation properties to a great extent. Results suggest that the presence of only one percent of graphene nanoplatelets with ATH sharply reduces the heat release rate and rate of smoke release. A minor reduction in dielectric breakdown strength and volume resistivity is noticed. Furthermore, permittivity and dielectric loss at power frequency suggest that a marginal 1% concentration of nanoplatelet with ATH is an excellent approach to fabricate flame retardant silicone rubber with an acceptable electrical insulation level

A novel medical image data protection scheme for smart healthcare system

The Internet of Multimedia Things (IoMT) refers to a network of interconnected multimedia devices that communicate with each other over the Internet. Recently, smart healthcare has emerged as a significant application of the IoMT, particularly in the context of knowledge-based learning systems. Smart healthcare systems leverage knowledge-based learning to become more context-aware, adaptable, and auditable while maintaining the ability to learn from historical data. In smart healthcare systems, devices capture images, such as X-rays, Magnetic Resonance Imaging. The security and integrity of these images are crucial for the databases used in knowledge-based learning systems to foster structured decision-making and enhance the learning abilities of AI. Moreover, in knowledge-driven systems, the storage and transmission of HD medical images exert a burden on the limited bandwidth of the communication channel, leading to data transmission delays. To address the security and latency concerns, this paper presents a lightweight medical image encryption scheme utilising bit-plane decomposition and chaos theory. The results of the experiment yield entropy, energy, and correlation values of 7.999, 0.0156, and 0.0001, respectively. This validates the effectiveness of the encryption system proposed in this paper, which offers high-quality encryption, a large key space, key sensitivity, and resistance to statistical attacks

An efficient deep learning model for brain tumour detection with privacy preservation

Internet of medical things (IoMT) is becoming more prevalent in healthcare applications as a result of current AI advancements, helping to improve our quality of life and ensure a sustainable health system. IoMT systems with cutting‐edge scientific capabilities are capable of detecting, transmitting, learning and reasoning. As a result, these systems proved tremendously useful in a range of healthcare applications, including brain tumour detection. A deep learning‐based approach for identifying MRI images of brain tumour patients and normal patients is suggested. The morphological‐based segmentation method is applied in this approach to separate tumour areas in MRI images. Convolutional neural networks, such as LeNET, MobileNetV2, Densenet and ResNet, are tested to be the most efficient ones in terms of detection performance. The suggested approach is applied to a dataset gathered from several hospitals. The effectiveness of the proposed approach is assessed using a variety of metrics, including accuracy, specificity, sensitivity, recall and F‐score. According to the performance evaluation, the accuracy of LeNET, MobileNetV2, Densenet, ResNet and EfficientNet is 98.7%, 93.6%, 92.8%, 91.6% and 91.9%, respectively. When compared to the existing approaches, LeNET has the best performance, with an average of 98.7% accuracy

Bloodstream Infections by Extended-spectrum β-lactamase-producing Klebsiella Species in Children

Infections caused by resistant Gram-negative bacteria are a serious public health problem, with Klebsiella spp. being the most common cause and increasing over the years. There is a striking increase in antibiotic resistance worldwide. The aim of this study was to retrospectively evaluate the characteristics and treatment of bloodstream infections (BSIs) caused by Klebsiella spp. and to identify possible risk factors for extended-spectrum β-lactamase (ESBL) resistance in our hospital between August 2019 and March 2023. Of 250 Klebsiella isolates, 112 (44.8%) were ESBL producers and 138 (55.2%) were ESBL nonproducers. Catheter-related BSIs (CRBSIs) accounted for 49.6% of infections and were more common in the ESBL nonproducer group. Most of the Klebsiella spp. were K. pneumoniae (233/250). Most of the infections were healthcare-associated infections (85.6%). Most patients had an underlying disease, the most common underlying disease in the ESBL-producing group was neurometabolic disease (26.8%), whereas in the ESBL-non-producing group it was malignancy (35.5%). The median age of the ESBL-producing group was 14 months and was younger (p=0.01). Previous antibiotic use in the last 30 days, especially aminoglycosides (p<0.006), β-lactam-β-lactamase inhibitor combinations (p<0.001) and cephalosporins (p<0.001), increased ESBL-resistant infection. Use of β-lactam-β-lactamase inhibitor combinations in the last 30 days increased the risk of ESBL resistance by approximately 7.4 times, and cephalosporins increased the risk by 5 times. In the ESBL-producing group, the median duration of treatment was longer at 14 days (p=0.01), and carbapenems were most commonly used (p<0.001). Thrombocytopenia (p=0.003), elevated C-reactive protein (p<0.001), CRBSI (p=0.009), presence of central venous catheter (p=0.03), urinary catheter (p<0.001), mechanical ventilation (p<0.001), intensive care admission (p=0.005), previous use of carbapenems, aminoglycosides, fluoroquinolones in the last 30 days (p=0.003, p=0.001, p=0.006, respectively) and colistin treatment (p<0.001) increased the risk of mortality. The 28-day mortality rate was 11.6%. Appropriate use of narrow-spectrum antibiotics and reduction of invasive procedures is important in reducing ESBL resistance and BSI-related mortality