A study on water hyacinth Eichhornia crassipes as oil sorbent

The sorption of diesel, lubricant and castor oils onto different parts (root, stem and leaf) of the dry biomass water hyacinth was studied at the laboratory scale. The parts of the aquapyte water hyacinth (Eichhornia Crassipes) were characterized by physico-chemical methods and the characteristics were used to elucidate the oil sorption process. Hydrophobicity, wettability (capillarity), buoyancy and sorption capacity of oils in the presence/absence of water were studied to evaluate the suitability of the sorbent for application. In all the three sorbents, theoil sorption capacity increases with the increase of oil film thickness. However of the three parts, the stem has a greater sorption capacity of 9.3, 7.8 and 11.08 g/g for the three oils such as diesel, lubricant and castor oils respectively, even though the root of water hyacinth showed a higher hydrophobicity and surface area. These sorption capacities are comparable with widely used commercial oil sorbent such as nonwoven polypropylene which has a sorption capacity in the range of 10-16 g/g

Er-doped KY_(1-x-y)Gd_xLu_y(WO₄)₂ surface channel waveguides

Channel waveguides on KY1-x-yGdxLuy(WO4)2 epitaxial films doped with Er3+ were obtained by ion beam milling and guided modes at wavelengths near 1.5µm confirmed single mode behaviour. Absorption and emission spectra of these waveguides agree with those of bulk crystals of the same family, showing potential for a planar waveguide laser

Arsenic removal using silver-impregnated Prosopis spicigera L. wood (PSLW) activated carbon: batch and column studies

Silver-impregnated carbon (SIC) and its precursor (un-impregnated) derived from an easily available low cost plant material Prosopis spicigera L. wood (PSLW) carbon was investigated for their ability to remove arsenic from aqueous solutions in batch and column experiments. Arsenic uptake has no regular trend with increasing pH; contains two adsorption maxima, the first adsorption maximum at pH 4.0 and a second adsorption maximum at pH 10.0. The extent of As (III) removal increased with increase in temperature. As (III) sorption kinetics was well fitted by pseudo second order with pore diffusion as rate determining step. The applicability of Langmuir isotherm suggests the formation of monolayer coverage of As (III) at the outer surface of the adsorbent. Thermodynamic parameters show that the adsorption was spontaneous and endothermic in nature. Column experiments were done using Thomas model, the maximum adsorption capacity of SIC was found to be 9.36 mg/g.Keywords: Adsorption, Arsenic, batch adsorption, langmuir isotherm, silver-impregnated carbon (SIC), Thomas mode

Combined effect of adsorbent chitosan and photosensitizer polypyrrole in ternary chitosan-polypyrrole-TiO2 photocatalyst leading to visible light activity and superior functionality

The combined effect of the components in the ternary chitosan-polypyrrole-TiO2 (Chit-Ppy-TiO2) photocatalytic system has been investigated. The role of each component in this catalyst is validated by the visible light degradation of the model dye methylene blue. The reaction parameters, viz., amount of catalyst, dye concentration, oxidant concentration and temperature are studied in detail. The ternary system exhibits greater activity when compared to both the single and binary component catalysts (chitosan-TiO2 and polypyrrole-TiO2). The superior functionality of Chit-Ppy-TiO2 (1:1:100 wt ratio) originates from the combined effect of greater dye adsorption of chitosan, visible light sensitization of polypyrrole and the catalytic functionality of TiO2. The ternary photocatalyst is recyclable even after fourth  run without appreciable loss in its activity

Skolem Difference Mean Graphs

Skolem difference mean labelings of some predefined graphs are studied

Effect of lateral crushing on tensile property of bamboo, modal and tencel fibres

The effect of lateral crushing on the tensile properties of bamboo, modal and tencel fibres has been investigated. A fibre crushing apparatus has been used for the purpose of lateral crushing of fibres. The influence of transverse compression on the axial mechanical properties of these fibres has been analysed. The study reveals that modal fibre sustained a higher loss in tensile properties compared to bamboo and tencel. The general phenomenon obtained from the study is that the percentage loss of strength and breaking extension varies from one fibre to another based on the fibre type and morphology

Technology Educators Pedagogical Adjustment in the Post-pandemic Era: A Case Study of Lecturers in the Oil-rich Region, Nigeria

During the COVID-19 pandemic, a lot of lecturers switched to teaching online. There is reason to believe that educators\u27 pedagogy and teaching philosophies would have undergone a significant transformation. This survey, however, was created to examine the pedagogical and philosophical adjustments technology educators made in reaction to COVID-19. Eight technology educators were subjected to in-depth interviews to learn more about their teaching styles and how they handled the shift to online learning. Thematic and pattern analysis was performed on interview transcripts. Instructors made many changes during the changeover, some general and others specific. Based on the results of the interview, indicators point to several possible explanations for their decisions, such as the extent to which the course structure provided change unnecessary, the influence of the instructors\u27 existing skill set, their desire to preserve the integrity of grades, a set of questions to help lecturers restructure their curricula, and their understanding of the bounds of technology-based education pedagogy. These interviews help us understand how technology educators were affected by the sudden shift to online instruction. To meet the demands of COVID-19, technology education evolved quickly. However, constant adaptation is required to further improve pedagogy

Hyperelliptic curve based authentication for the internet of drones

Drones provide an alternative progression in protection submissions since they are capable of conducting autonomous seismic investigations. Recent advancement in unmanned aerial vehicle (UAV) communication is an internet of a drone combined with 5G networks. Because of the quick utilization of rapidly progressed registering frameworks besides 5G officialdoms, the information from the user is consistently refreshed and pooled. Thus, safety or confidentiality is vital among clients, and a proficient substantiation methodology utilizing a vigorous sanctuary key. Conventional procedures ensure a few restrictions however taking care of the assault arrangements in information transmission over the internet of drones (IOD) environmental frameworks. A unique hyper elliptical curve (HEC) cryptographically based validation system is proposed to provide protected data facilities among drones. The proposed method has been compared with the existing methods in terms of packet loss rate, computational cost, and delay and thereby provides better insight into efficient and secure communication. Finally, the simulation results show that our strategy is efficient in both computation and communication

Advancing chronic pain relief cloud-based remote management with machine learning in healthcare

Healthcare providers face a significant challenge in the treatment of chronic pain, requiring creative responses to enhance patient outcomes and streamline healthcare delivery. It suggests using cloud-based remote management with machine learning (ML) to alleviate chronic pain. Wearable device data, electronic health record (EHR) data, and patient-reported outcomes are all inputs into the suggested system’s data analysis pipeline, which combines support vector machines (SVM) with recurrent neural networks (RNN). SVM’s powerful classification skills make it possible to classify patients’ risks and predict how they will react to therapy. RNNs are very good at processing sequential data, which means they may identify trends in patient symptoms and drug adherence over time. By integrating these algorithms, healthcare professionals may create individualized treatment programs that consider each patient’s preferences and specific requirements. Early intervention and proactive treatment of pain symptoms are made possible by the system’s ability to monitor patients in real-time remotely. The system is further improved by using predictive analytics to identify patients who could benefit from extra support services and to forecast when they will have acute pain episodes. The proposed approach can change the game regarding managing chronic pain. It provides data-driven, individualized treatment that improves patient outcomes while cutting healthcare expenses

Prediction of patient survival from heart failure using a cox-based model

The existing heart failure risk prediction models are developed based on machine learning predictors. The objective of this study is to identify the key risk factors that affect the survival time of heart patients and to develop a heart failure survival prediction model using the identified risk factors. A cox proportional hazard regression method is applied to generate the proposed heart failure survival model. We used the dataset from the University of California Irvine (UCI) clinical heart failure data repository. To develop the model we have used multiple risk factors such as age, anemia, creatinine phosphokinase, diabetes history, ejection fraction, presence of high blood pressure, platelet count, serum creatinine, sex, and smoking history. Among the risk factors, high blood pressure is identified as one of the novel risk factors for heart failure. We have validated the performance of the model via statistical and empirical validation. The experimental result shows that the proposed model achieved good discrimination and calibration ability with a C-index (receiver operating characteristic (ROC) of being 0.74 and a log-likelihood ratio of 81.95 using 11 degrees of freedom on the validation dataset