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The flipped classroom aims to improve learning by engaging students in educational activities outside of traditional lessons. Flipped classrooms have steadily gained popularity in the last decade and are a topic of discussion in teaching and learning forums. However, its adoption in mathematics and statistics has been subdued. Most higher education mathematics and statistics are still delivered through traditional lectures where students are passive participants. In this study, experiences of flipping a large first-level statistics class are presented. The implementation included a combination of peer learning and tutor-assistance in lectures. Student performance, in the form of final examination and overall marks over four semesters (two with traditional delivery and two flipped), were analysed for differences with respect to the two teaching modes after adjusting for demographic differences. In addition, student survey data were analysed with a view to revealing any relationship between attitude towards a flipped classroom and performance. The results showed that students' performance improved and an increased understanding of concepts was achieved through the flipped classroom approach. Evidence also indicated an increase in learner engagement. Student feedback indicated a higher preference for a flipped mode overall and in particular for ages 20 and below.

This article presents and evaluates pipelined architecture designs for an improved high-frequency Fast Fourier Transform (FFT) processor implemented on Field Programmable Gate Arrays (FPGA) for Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM). The architecture presented is a Mixed-Radix Multipath Delay Commutator. The presented parallel architecture utilizes fewer hardware resources compared to Radix-2 architecture, while maintaining simple control and butterfly structures inherent to Radix-2 implementations. The high-frequency design presented allows enhancing system throughput without requiring additional parallel data paths common in other current approaches, the presented design can process two and four independent data streams in parallel and is suitable for scaling to any power of two FFT size N. FPGA implementation of the architecture demonstrated significant resource efficiency and high-throughput in comparison to relevant current approaches within literature. The proposed architecture designs were realized with Xilinx System Generator (XSG) and evaluated on both Virtex-5 and Virtex-7 FPGA devices. Post place and route results demonstrated maximum frequency values over 400 MHz and 470 MHz for Virtex-5 and Virtex-7 FPGA devices respectively.

This work investigated kinetics and thermal degradation of acrylonitrile butadiene styrene and polycarbonate (ABS/PC) blend using thermogravimetric analysis in the range of 25 to 520°C. For thermal degradation of blend, activation energy (Ea) and pre-exponential factor (A) were calculated under various heating rates as 5, 10, 15 and 20°C/min using iso-conversional model-free methods (Kissinger, Flynn-Wall- Ozawa and Friedman). Mass loss of the blend as a function of temperature was plotted as thermogravimetric curve (TG) while derivative values of mass loss were drawn as derivative thermogravimetric (DTG) curve. Using Kissinger method, Ea was 51.4 kJ/mol, while values calculated from FWO and Friedman method were 86–161 and 30–251 kJ/mol respectively. Results showed increasing trend of Ea with higher conversion values indicating different degradation mechanisms at the initial and final stages of the experiment. Thermodynamic parameters such as enthalpy change (ΔH), Gibbs free energy (ΔG) and entropy change (ΔS) were also calculated.

Conveyor belt wear is an important consideration in the bulk materials handling industry. We define four belt wear rate metrics and develop a model to predict wear rates of new conveyor configurations using an industry dataset that includes ultrasonic thickness measurements, conveyor attributes, and conveyor throughput. All variables are expected to contribute in some way to explaining wear rate and are included in modeling. One specific metric, the maximum throughput-based wear rate, is selected as the prediction target, and cross-validation is used to evaluate the out-of-sample performance of random forest and linear regression algorithms. The random forest approach achieves a lower error of 0.152 mm/megatons (standard deviation [SD] = 0.0648). Permutation importance and partial dependence plots are computed to provide insights into the relationship between conveyor parameters and wear rate. This work demonstrates how belt wear rate can be quantified from imprecise thickness testing methods and provides a transparent modeling framework applicable to other supervised learning problems in risk and reliability.

Unsuspected amebic colitis presenting as inflammatory bowel disease, as in our patient, has been previously reported (4, 7, 8). Misdiagnosis, delay in antibiotic treatment, and institution of immunosuppression were the result of failure to identify the parasite in stool specimens and have resulted in suffering, morbidity, mortality, and surgery. In all previously reported cases, routine stool studies failed to identify E. histolytica (4, 7, 8). The correct diagnosis was only established after reviewing the surgical specimen or biopsies obtained endoscopically. Because the erroneous diagnosis of inflammatory bowel disease can lead to disastrous complications, it is imperative to exclude amebic colitis prior to undertaking steroid therapy, especially in patients with a prior history of travel to or residence in areas with endemic E. histolytica (17). We recommend obtaining at least three stool specimens for microscopic examination, as well as testing for serum amebic antibody. Patients should submit fresh stool specimens directly to the laboratory to allow for prompt diagnostic evaluation. Such an approach might lead to the improved diagnosis of amebiasis. [ABSTRACT FROM AUTHOR]

Dry reforming of methane (DRM) which also known as CO2 reforming of methane is a well-investigated reaction to serve as an alternative technique to attenuate the abundance of greenhouse gases (CO2 and CH4). The syngas yielded is the main component for the liquid fuels and chemicals production in parallel with the fluctuating price of oil. Major researches were executed to seek for the well-suited catalysts before the commercialization of DRM can be realized. However, severe deactivation due to the carbon formation restricted the usage of promising Ni-based catalysts for DRM. Meanwhile, the deactivation on these catalysts can be associated with the operating conditions of DRM, which subsequently promoted the secondary reactions at different operating conditions. In fact, the parametric study could provide a benchmark for better understanding of the fundamental steps embodied in the CH4 and CO2 activation as well as their conversions. This review explores on the influences of the reaction operating parameters in term of the reaction temperatures, reactant partial pressures, feed ratios, and weight hourly space velocity (WHSV) on catalytic performance and carbon accumulation for the DRM.

Energy generation from biomass presents some serious problems like slagging, fouling and corrosion of boilers. To address these problems, demineralization of biomass is performed using different leaching agents. This study is focused on determining the influence of leaching agents and leaching time on the physiochemical structure of rice husk during demineralization. Dilute (5% wt) solutions of HCl and H2SO4 were used for the demineralization of rice husk separately with leaching time of 15, 60 and 120 minutes. It is shown that H2SO4 exhibited higher removal of alkali and alkaline earth metals (AAEM) comparatively as depicted by the 34.2% decrease in ash content along with an increase of 7.10% in the heating value. The acid has been seen to induce more notable changes in physiochemical structure as depicted by the FTIR spectra and SEM micrographs. The thermal degradation behavior of the demineralized rice husk has also been reported.

A process model for turbulent pressurized circulating fluidized-bed coal gasifier is created using ASPEN PLUS software. Both hydrodynamic and reaction kinetics parameter are taken into account, whose expressions for fluidized bed are adopted from the literature. Various reactor models available in ASPEN PLUS with calculator as External Block are nested to solve hydrodynamics and kinetics. Multiple operational parameters for a pilot-plant circulating fluidized-bed coal gasifier are used to demonstrate the effects on coal gasification characteristics. This paper presents detailed information regarding the simulation model, including robust analysis of the effect of stoichiometric ratio, steam to coal ratio, gasification temperature and gasification agent temperature. It is observed that, with the increase in the flow rate of air, the components hydrogen, carbon monoxide, carbon dioxide and methane reduce, which causes the Lower Heating Value (LHV) of synthesis gas (Syn. Gas) to decrease by about 29.3%, while increment in the steam flow rate shows a minute increase in heating value of only 0.8%. Stoichiometric ratio has a direct relationship to carbon conversion efficiency and carbon dioxide production. Increasing the steam to coal ratio boosts the production of hydrogen and carbon monoxide, and causes a drop in both carbon dioxide concentration and the conversion efficiency of carbon. High gasifying agent temperature is desired because of high concentration of CO and H2, increasing carbon conversion and LHV. A high gasifying agent temperature is the major factor that affects the coal gasification to enhance H2 and CO production rapidly along with other gasification characteristics.

An efficient approach for joint source and channel coding is presented. The proposed approach exploits the joint optimization of a wavelet-based scalable video coding framework and a forward error correction method based on turbo codes. The scheme minimizes the reconstructed video distortion at the decoder subject to a constraint on the overall transmission bitrate budget. The minimization is achieved by exploiting the source rate distortion characteristics and the statistics of the available codes. Here, the critical problem of estimating the bit error rate probability in error-prone applications is discussed. Aiming at improving the overall performance of the underlying joint source-channel coding, the combination of the packet size, interleaver, and channel coding rate is optimized using Lagrangian optimization. Experimental results show that the proposed approach outperforms conventional forward error correction techniques at all bit error rates. It also significantly improves the performance of end-to-end scalable video transmission at all channel bit rates.

Stimuli-responsive drug delivery carriers, particularly those exhibiting pH sensitivity, have attracted significant scholarly interest due to their promising potential in anticancer therapeutic applications. This phenomenon can primarily be ascribed to the inherently acidic nature of tumor microenvironments. However, pH-responsive carriers frequently require the incorporation of functional groups or materials sensitive to pH changes. Given the pH-sensitive characteristics of metal coordination with natural small-molecule drugs, organometallic supramolecules present a facile and effective strategy for integrating pH-responsive behavior into these systems. Meanwhile, utilizing the natural compound luteolin in conjunction with iron ions (Fe 3+ ) through the advanced engineering technique of flash nanoprecipitation (FNP) results in the synthesis of stable, highly loaded nanoparticles (NPs) exhibiting a supramolecular photothermal effect. Our experimental findings substantiate that the photothermal effect persists over time, even after the pH-responsive release phase has ended. Consequently, these polymeric pH-responsive metallic supramolecular nanoparticles integrate chemotherapy and photothermal therapy, creating a synergistic approach to cancer treatment. This bifunctional platform, which exhibits both pH-responsive and photothermal properties, presents a highly promising avenue for biomedical applications, particularly in the area of tumor therapies. Its dual function offers a potentially efficacious approach to tumor treatment.

This study presents a novel computational radio frequency identification (RFID) system designed specifically for assisting blind individuals, utilising software-defined radio (SDR) with coherent detection. The system employs battery-less ultra-high-frequency (UHF) tag arrays in Gen2 RFID systems, enhancing the transmission of sensed information beyond standard identification bits. Our method uses an SDR reader to efficiently manage multiple tags with Gen2 preambles implemented on a single transceiver card. The results highlight the system's real-time capability to detect movements and direction of walking within a four-meter range, indicating significant advances in contactless activity monitoring. This system not only handles the complexities of multiple tag scenarios but also delineates the influence of system parameters on RFID operational efficiency. This study contributes to assistive technology, provides a platform for future advancements aimed at addressing contemporary limitations in pseudo-localisation, and offers a practical, affordable assistance system for blind individuals.

The inability to see makes moving around very difficult for visually impaired persons. Due to their limited movement, they also struggle to protect themselves against moving and non-moving objects. Given the substantial rise in the population of those with vision impairments in recent years, there has been an increasing amount of research devoted to the development of assistive technologies. This review paper highlights the state-of-the-art assistive technology, tools, and systems for improving the daily lives of visually impaired people. Multi-modal mobility assistance solutions are also evaluated for both indoor and outdoor environments. Lastly, an analysis of several approaches is also provided, along with recommendations for the future.

Strokes are a leading global cause of mortality, underscoring the need for early detection and prevention strategies. However, addressing hidden risk factors and achieving accurate prediction become particularly challenging in the presence of imbalanced and missing data. This study encompasses three imputation techniques to deal with missing data. To tackle data imbalance, it employs the synthetic minority oversampling technique (SMOTE). The study initiates with a baseline model and subsequently employs an extensive range of advanced models. This study thoroughly evaluates the performance of these models by employing k-fold cross-validation on various imbalanced and balanced datasets. The findings reveal that age, body mass index (BMI), average glucose level, heart disease, hypertension, and marital status are the most influential features in predicting strokes. Furthermore, a Dense Stacking Ensemble (DSE) model is built upon previous advanced models after fine-tuning, with the best-performing model as a meta-classifier. The DSE model demonstrated over 96% accuracy across diverse datasets, with an AUC score of 83.94% on imbalanced imputed dataset and 98.92% on balanced one. This research underscores the remarkable performance of the DSE model, compared to the previous research on the same dataset. It highlights the model's potential for early stroke detection to improve patient outcomes., (© 2024. The Author(s).)

The integration of optimization techniques and deep learning models, which offer a promising avenue for improving the efficiency and sustainability of biodiesel production processes from baobab seed oil (BSO), is rare. This study utilized a multi-input-multioutput (MIMO) deep learning technique and the most recent central composite design (CCD) optimization tool to model and optimize the yield and properties of biodiesel produced from BSO. First, the baobab seed oil was extracted using a solvent extraction method. BSO was subsequently analyzed and converted to biodiesel by reacting CH 3 OH catalyzed by waste banana bunch stalk biochar activated by KOH. Multiobjective optimization and prediction of the biodiesel yield ( Y ) and several key fuel properties, including the cetane number (CN), kinematic viscosity (VS), and purity ( P ), were achieved. With better correlation coefficients of 0.9709, 0.9464, and 0.9714 for response training, response testing, and response validation, respectively, and a root-mean-square error of 0.00755, the MIMO model on the logsig transfer function accurately predicted the biodiesel yield and properties more than did the MISO and response surface methodology models. The optimum Y (96 wt %), CN (48), VS (3.3 mm 2 /s), and P (98.3%) were concurrently accomplished at a reaction temperature of 56 °C, a reaction time of 115 min, a CH 3 OH/BSO molar ratio of 15:1, a catalyst dosage of 6 wt %, and a stirring speed of 400 rpm with 98% optimal validation accuracy. CCD sensitivity analysis revealed that the CH 3 OH/BSO ratio was the most sensitive (50.9%) input predictor among the other input variables studied., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society.)

Fluorinated and formaldehyde-based compounds impart excellent hydrophobicity and flame-retardant properties to cotton fabrics. However, they come with various health and environmental risks. A novel hydrophobic, flame retardant, and antimicrobial finishing agent free from fluorine and formaldehyde was synthesized. The diammonium phosphate octadecyl citrate (DAPOC) was synthesized by using stearic acid (octadecanoic acid), citric acid (propane-1,2,3-tricarboxylic acid), and diammonium hydrogen phosphate. It was grafted onto the cotton fabrics by employing the conventional pad-dry-cure method. The results indicated that this newly developed finish could be chemically bonded to cotton fabrics through C-O-C covalent bonds. The contact angle of the cotton fabric finished with a 12% concentration of the finishing agent reached 151.9°. Additionally, the finished cotton fabrics displayed evident flame-retardant properties. After undergoing 20 laundering cycles, DAPOC maintained strong hydrophobic and flame-retardant characteristics, demonstrating its durability. The chemical structure of DAPOC was verified by nuclear magnetic resonance spectroscopy ( 1 H-NMR). The thermogravimetric analysis confirmed the flame-retardant nature of the treated cotton fabric samples. Scanning electron microscopy (SEM), Energy dispersive X-ray analysis (EDX), and Fourier-transform infrared spectroscopy (FTIR) results demonstrated the successful grafting of the newly created finish onto the cotton fiber. X-ray diffraction (XRD) spectra depicted that the crystalline structure of finished cotton fabric remained mostly unaltered. Furthermore, the finished cotton fabric exhibited commendable antimicrobial properties due to the inclusion of citric acid., Competing Interests: No conflicts of interest exist that need to be disclosed., (This journal is © The Royal Society of Chemistry.)

Ad-hoc wireless sensor networks face challenges of optimized node deployment for maximizing coverage and efficiently routing data to control centers in post disaster events. These challenges impact the outcome for extending the lifetime of wireless sensor networks. This study presents a uav assisted reactive zone based EHGR (energy efficient hierarchical gateway routing protocol) that is deployed in a situation where the natural calamity has caused communication and infrastructure damage to a major portion of the sensor network. EHGR is a hybrid multi layer routing protocol for large heterogeneous sensor nodes (smart nodes, basic nodes, user handheld devices etc.) EHGR is tailored to meet two important concerns for a disaster hit wsn ie. optimized deployment and energy efficient routing. The first part of EGHR focuses on maximized coverage during node deployments. Maximized coverage is an important aspect to be considered during the event of disaster since most of the nodes loose coverage and are detached from the wireless sensor network. The first part of EHGR uses state of the art game theory approach to build a model that maximizes the coverage of nodes during the deployment phase from all participating entities i.e. nodes and uavs. Rather than fixing the cluster head as is the case in traditional cluster-based approaches EHGR uses the energy centroid nodes. Energy centroid nodes evolve on the basis of aggregated energy of the zone. This approach is superior to simply electing cluster head nodes on the basis of some probability function. The nodes that fail to achieve any successful outcome from the game theory matching model fail to get any association. These nodes will use multi hop d2d relay approach to reach the energy centroid nodes. Gateway relay nodes used with the game theory approach during the deployment of the uav assisted wsn improves the overall coverage by 25% against traditional leach based hierarchical approaches. Once the optimum deployment phase is completed the routing phase is initiated. Aggregated data is sent by the energy centroid nodes from the ECN nodes to the servicing micro controller enabled un manned aerial vehicles. The routing process places partial burden of zone formation and data transmission to the control center for each phase on the servicing uavs. Energy centroid nodes engage only in the data aggregation process and transmission of data to servicing uav. Servicing-uavs reduce energy dissipated of the entire zone which result in gradual decrease of energy for the zone thus increasing the network lifetime. Node deployment phase and the routing phase of EHGR utilize the computations provide by the mirco controller enabled unmanned aerial vehicles such that the computationally intensive calculations are offloaded to the servicing uav. Experiment results indicate an increase in the first dead node report, half dead node report, and last dead node report. Network lifetime is extended to approximately 1800 rounds which is an increase by ratio of 100% against the traditional leach approach and increase by 50% percent against the latest approaches as highlighted in the literature., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Ahmad et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Doping with heteroatoms is the main method used to enhance energy storage with carbon materials, and polyatomic doping is one of the main challenges. Hydrothermal carbonization of cellulose was performed at 240 °C for 1 h. Ammonium sulfate and thiourea dopants were selected as the sources of inorganic nitrogen and organic nitrogen in the preparation of supercapacitor carbon. The effects of boric acid on the properties of the resulting hydrochar after KOH activation were examined. The results showed that the proportion of functional groups and the specific surface area of the activated hydrochar were reduced by the addition of boric acid, and the formation of micropores was inhibited. The hydrochar obtained from the reaction of cellulose and organic nitrogen compounds had a better pore size distribution and electrochemical properties after activation. The largest specific surface area (952.27 m 2 /g) was obtained when thiourea was used as the sole dopant. In a three-electrode system, the specific capacitance of the activated hydrochar reached 235.8 F/g at a current density of 1 A/g. After 20,000 charging and discharging cycles at a current density of 10 A/g, the capacitance retention rate was 99.96%. Therefore, this study showed that supercapacitor carbon with good electrochemical properties was obtained by the direct reactions of cellulose with organic nitrogen compounds.

Pesticides are widely used to increase agricultural productivity, however, weak adhesion and deposition lead to low efficient utilization. Herein, we prepare a nanopesticide formulation (tebuconazole nanopesticides) which is leaf-adhesive, and water-dispersed via a rapid nanoparticle precipitation method, flash nanoprecipitation, using temperature-responsive copolymers poly-(2-(dimethylamino)ethylmethylacrylate)-b-poly(ε-caprolactone) as the carrier. Compared with commercial suspensions, the encapsulation by the polymer improves the deposition of TEB, and the contact angle on foliage is lowered by 40.0°. Due to the small size and strong van der Waals interactions, the anti-washing efficiency of TEB NPs is increased by 37% in contrast to commercial ones. Finally, the acute toxicity of TEB NPs to zebrafish shows a more than 25-fold reduction as compared to commercial formulation indicating good biocompatibility of the nanopesticides. This work is expected to enhance pesticide droplet deposition and adhesion, maximize the use of pesticides, tackling one of the application challenges of pesticides., (© 2023. Springer Nature Limited.)

Aim of present study was to synthesize a novel chitosan-quercetin (CTS-QT) complex by making a carbodiimide linkage using maleic anhydride as cross-linker and to investigate its enhanced antibacterial and antioxidant activities as compare to pure CTS and QT. Equimolar concentration of QT and maleic anhydride were used to react with 100 mg CTS to form CTS-QT complex. For this purpose, three bacterial strains namely E. Coli , S. Aureus and P. Aeruginosa were used for in-vitro antibacterial analysis (ZOI, MIC, MBC, checker board and time kill assay). Later molecular docking studies were performed on protein structure of E. Coli to assess binding affinity of pure QT and CTS-QT complex. MD simulations with accelerated settings were used to explore the protein-ligand complex's binding interactions and stability. Antioxidant profile was determined by performing DPPH• radical scavenging assay, total antioxidant capacity (TAC) and total reducing power (TRP) assays. Delivery mechanism to CTS-QT complex was improved by synthesizing polycaprolactone containing microspheres (CTS-QT-PCL-Levo-Ms) using Levofloxacin as model drug to enhance their antibacterial profile. Resulted microspheres were evaluated by particle size, charge, surface morphology, in-vitro drug release and hemolytic profile and are all were found within limits. Antibacterial assay revealed that CTS-QT-PCL-Levo-Ms showed more than two folds increased bactericidal activity against E. Coli and P. Aeruginosa , while 1.5 folds against S. Aureus. Green colored formation of phosphate molybdate complexes with highest 85 ± 1.32% TAC confirmed its antioxidant properties. Furthermore, molecular docking and dynamics studies revealed that CTS-QT was embedded nicely within the active pocket of UPPS with binding energy greater than QT with RSMD value of below 1.5. Conclusively, use of maleic acid, in-vitro and in-silico antimicrobial studies confirm the emergence of CTS-QT complex containing microspheres as novel treatment strategy for all types of bacterial infections.Communicated by Ramaswamy H. Sarma.