Search Results (92)

In the last several decades, metal oxide thin films have attracted significant attention for the development of various existing and emerging technological applications, including pH sensors. The mandate for consistent and precise pH sensing techniques has been increasing across various fields, including environmental monitoring, biotechnology, food and agricultural industries, and medical diagnostics. Metal oxide thin films grown using physical vapor deposition (PVD) with precise control over film thickness, composition, and morphology are beneficial for pH sensing applications such as enhancing pH sensitivity and stability, quicker response, repeatability, and compatibility with miniaturization. Various PVD techniques, including sputtering, evaporation, and ion beam deposition, used to fabricate thin films for tailoring materials’ properties for the advanced design and development of high-performing pH sensors, have been explored worldwide by many research groups. In addition, various thin film materials have also been investigated, including metal oxides, nitrides, and nanostructured films, to make very robust pH sensing electrodes with higher pH sensing performance. The development of novel materials and structures has enabled higher sensitivity, improved selectivity, and enhanced durability in harsh pH environments. The last decade has witnessed significant advancements in PVD thin films for pH sensing applications. The combination of precise film deposition techniques, novel materials, and surface functionalization strategies has led to improved pH sensing performance, making PVD thin films a promising choice for future pH sensing technologies. Full article

A basic urea technique was successfully used to synthesize Mg/Al-Layered double hydroxides (Mg/Al LDHs), which were then calcined at 400 °C to form Mg/Al-Layered double oxides (Mg/Al LDOs). To reconstruct LDHs, Mg/Al LDOs were fabricated with different feeding ratios of Ni by the co-precipitation method. After synthesis, the Ni/Mg/Al-layered double hydroxides (NMA-LDHs) with 20% and 30% Ni (S1 and S2) were roasted at 400 °C and transformed into corresponding Ni/Mg/Al-layered double oxides (NMA-LDOs) (S1a and S2b, respectively). The physiochemical properties of synthesized samples were also evaluated by various characterization techniques, such as X-ray diffraction (XRD), Scanning electron microscopy (SEM), Energy dispersive X-ray spectroscopy (EDS), Fourier transform infrared (FTIR), and Brunauer, Emmett, and Teller (BET). The adsorption behavior of methyl orange (MO) onto the synthesized samples was evaluated in batch adsorption mode under varying conditions of contact time, adsorbent quantity, and solution pH. As the dosage amount increased from 0.01–0.04 g, the removal percentage of MO dye also increased from 83% to 90% for S1, 84% to 92% for S1a, 77% to 87% for S2, and 93% to 98% for S2b, respectively. For all of the samples, the adsorption kinetics were well described by the pseudo-second-order kinetic model. The equilibrium adsorption data were well fitted to both Langmuir and Freundlich models for methyl orange (MO). Finally, three adsorption-desorption cycles show that NMA-LDHs and NMA-LDOs have greater adsorption and reusability performance for MO dye, signifying that the design and fabrication strategy can facilitate the application of the natural hydrotalcite material in water remediation. Full article

This study assesses quad-band metamaterial perfect absorbers (MPAs) based on a double X-shaped ring resonator for electromagnetic interference (EMI) shielding applications. EMI shielding applications are primarily concerned with the shielding effectiveness values where the resonance is uniformly or non-sequentially modulated depending on the reflection and absorption behaviour. The proposed unit cell consists of double X-shaped ring resonators, a dielectric substrate of Rogers RT5870 with 1.575 mm thickness, a sensing layer, and a copper ground layer. The presented MPA yielded maximum absorptions of 99.9%, 99.9%, 99.9%, and 99.8% at 4.87 GHz, 7.49 GHz, 11.78 GHz, and 13.09 GHz resonance frequencies for the transverse electric (TE) and transverse magnetic (TM) modes at a normal polarisation angle. When the electromagnetic (EM) field with the surface current flow was investigated, the mechanisms of quad-band perfect absorption were revealed. Moreover, the theoretical analysis indicated that the MPA provides a shielding effectiveness of more than 45 dB across all bands in both TE and TM modes. An analogous circuit demonstrated that it could yield superior MPAs using the ADS software. Based on the findings, the suggested MPA is anticipated to be valuable for EMI shielding purposes. Full article

The increased competitive academic environment pushes higher institutions to improve their service quality for meeting the market demands. It is thus necessary to assess the factors that satisfy students and make them loyal to the university. This study has focused on assessing service quality, using the SERVQUAL Model to measure students’ satisfaction with private universities in Bangladesh. In the study, the primary data collection method through a questionnaire with the 5-point Likert scale was adopted to collect data from 229 students who are currently studying in different private universities in Chattogram, Bangladesh. Structural equation modeling (SEM) has been performed to analyze the data through the AMOS 22 statistical package. The findings report that a comfortable lecture room under the tangible dimension, providing service on time under the reliability dimension, the capacity of administrative staff to solve immediate problems under the responsiveness dimension, proficient lecturers for teaching and research under the assurance dimension, and focus of university management on students under the empathy dimension have a great influence on student satisfaction. The study concludes that managers and authorities of private universities must focus on ensuring better service quality as student satisfaction largely affects the sustainability and recurrence development of the institutions. Full article

Numerous factors can contribute to the development of neurodegenerative disorders (NDs), such as Alzheimer’s disease, Parkinson’s disease, amyotrophic lateral sclerosis, Huntington’s disease, and multiple sclerosis. Oxidative stress (OS), a fairly common ND symptom, can be caused by more reactive oxygen species being made. In addition, the pathological state of NDs, which includes a high number of protein aggregates, could make chronic inflammation worse by activating microglia. Carotenoids, often known as “CTs”, are pigments that exist naturally and play a vital role in the prevention of several brain illnesses. CTs are organic pigments with major significance in ND prevention. More than 600 CTs have been discovered in nature, and they may be found in a wide variety of creatures. Different forms of CTs are responsible for the red, yellow, and orange pigments seen in many animals and plants. Because of their unique structure, CTs exhibit a wide range of bioactive effects, such as anti-inflammatory and antioxidant effects. The preventive effects of CTs have led researchers to find a strong correlation between CT levels in the body and the avoidance and treatment of several ailments, including NDs. To further understand the connection between OS, neuroinflammation, and NDs, a literature review has been compiled. In addition, we have focused on the anti-inflammatory and antioxidant properties of CTs for the treatment and management of NDs. Full article

Renewable energy can be harnessed from wastewater, whether from municipalities or industries, but this potential is often ignored. The world generates over 900 km³ of wastewater annually, which is typically treated through energy-consuming processes, despite its potential for energy production. Environmental pollution is a most important and serious issue for all and their adulterations to the aquatic system are very toxic in very low concentrations. Photocatalysis is a prominent approach to eliminating risky elements from the environment. The present study developed Zinc oxide (ZnO), Copper-doped Zinc oxide (CuZnO), and Cobalt-doped Zinc oxide (CoZnO) nanostructures (NSs) by facile hydrothermal route. The crystalline and structural stability of the synthesized nanostructures were evident from XRD and FESEM analysis. Metal, and oxygen bond and their interaction on the surfaces and their valency were explored from XPS spectra. Optical orientations and electron movements were revealed from UV-Visible analysis. After 100 min exposure time with 1 g of catalyst concentration 60%, 70%, and 89% of dye degraded, for dye concentration (5 mg/L to 50 mg/L), the huge variation observed (70% to 22%), (80% to 16%), (94% to 10%). The highest photodegradation rate (55%, 75%, 90%) was observed on pH~12 using ZnO, CoZnO, and CuZnO respectively. Photodegradation of methylene blue confirmed the largest surface area, rate of recombination, photo-excited charge carriers, photo-sensitivity range, and radical generations of ZnO, CuZnO, and CoZnO. The present study, therefore, suggested that CuZnO would be preferred to produce nanomaterials for industrial wastewater treatment like methylene. Full article

In order to achieve a sustainable mix design, this paper evaluates self-consolidating green concrete (SCGC) properties by experimental tests and then examines the design parameters with an artificial intelligence technique. In this regard, cement was partially replaced in different contents with granulated blast furnace slag (GBFS) powder, volcanic powder, fly ash, and micro-silica. Moreover, fresh and hardened properties tests were performed on the specimens. Finally, an adaptive neuro-fuzzy inference system (ANFIS) was developed to identify the influencing parameters on the compressive strength of the specimens. For this purpose, seven ANFIS models evaluated the input parameters separately, and in terms of optimization, twenty-one models were assigned to different combinations of inputs. Experimental results were reported and discussed completely, where furnace slag represented the most effect on the hardened properties in binary mixes, and volcanic powder played an effective role in slump retention among other cement replacements. However, the combination of micro-silica and volcanic powder as a ternary mix design successfully achieved the most improvement compared to other mix designs. Furthermore, ANFIS results showed that binder content has the highest governing parameters in terms of the strength of SCGC. Finally, when compared with other additive powders, the combination of micro-silica with volcanic powder provided the most strength, which has also been verified and reported by the test results. Full article

Background: Magnetic resonance imaging (MRI) exams may cause patients to feel anxious before or during the scan, which affects the scanning outcome and leads to motion artifacts. Adequate preparation can effectively alleviate patients’ anxiety before the scan. We aimed to assess the effect of different preparation methods on MRI-induced anxiety: We conducted a prospective randomized study on MRI patients between March and May 2022. We divided 30 patients into two groups: the control group, which received routine preparation (RP), and the experimental group, which received video preparation (VP). We used the State-Trait Anxiety Inventory (STAI) to measure anxiety levels before and after the interventions. We assessed patients’ self-satisfaction after the scan: After preparation, VP (STAI mean = 10.7500) and RP (STAI mean = 12.7857), we observed a significant association between the pre- and post-STAI results in VP (p = 0.025). The effects of both methods in decreasing anxiety were more significant for first-timers (p = 0.009 in RP/0.014 in VP). We noted high satisfaction levels for both forms of preparation. The VP technique was superior in reducing patient anxiety, especially in first-time MRI patients. Hence, VP techniques can be used in different clinical settings to reduce anxiety and facilitate patients’ understanding of the instructions given. Full article

In this study, successful synthesis of ZnO nanoparticles (NPs), CuO NPs, and ZnO/CuO nanocomposite through an eco-friendly method using Corriandrum sativum leaf extract as a capping agent is reported. Using XRD, FTIR, UV-Vis, and SEM techniques, the synthesized materials were characterized for structural analysis, functional groups identification, spectroscopic measurements, and morphological analysis. The percentage composition and purity of the samples were determined by using Energy Dispersive X-ray (EDX), which showed the synthesis of materials. Morphological analysis was done by Scanning Electron Microscopy (SEM) which reflected that the CuO NPs, ZnO NPs and ZnO/CuO nanocomposite were spherical, and the average size calculated by using Image J software was around 25 nm, 55 nm, and 11 nm, respectively. FTIR and UV-Vis analyses were used for synthetic confirmation through characteristic peaks of materials. The synthesized (ZnO, CuO, and CuO/ZnO) nanomaterials were evaluated for photocatalytic activity using methylene blue (MB) dye. Among all three photocatalysts, the composite showed maximum photodegradation compared to the other two materials. The present work could lead to a pathway for the decontamination of harmful dyes of wastewater released from different industries. Full article

A split-ring resonator (SRR)-based power tiller wheel-shaped quad-band ℇ-negative metamaterial is presented in this research article. This is a new compact metamaterial with a high effective medium ratio (EMR) designed with three modified octagonal split-ring resonators (OSRRs). The electrical dimension of the proposed metamaterial (MM) unit cell is 0.086λ × 0.086λ, where λ is the wavelength calculated at the lowest resonance frequency of 2.35 GHz. Dielectric RT6002 materials of standard thickness (1.524 mm) were used as a substrate. Computer simulation technology (CST) Microwave Studio simulator shows four resonance peaks at 2.35, 7.72, 9.23 and 10.68 GHz with magnitudes of −43.23 dB −31.05 dB, −44.58 dB and −31.71 dB, respectively. Moreover, negative permittivity (ℇ) is observed in the frequency ranges of 2.35–3.01 GHz, 7.72–8.03 GHz, 9.23–10.02 GHz and 10.69–11.81 GHz. Additionally, a negative refractive index is observed in the frequency ranges of 2.36–3.19 GHz, 7.74–7.87 GHz, 9.26–10.33 GHz and 10.70–11.81 GHz, with near-zero permeability noted in the environments of these frequency ranges. The medium effectiveness indicator effective medium ratio (EMR) of the proposed MM is an estimated 11.61 at the lowest frequency of 2.35 GHz. The simulated results of the anticipated structure are validated by authentication processes such as array orientation, HFSS and ADS for an equivalent electrical circuit model. Given its high EMR and compactness in dimensions, the presented metamaterial can be used in S-, C- and X-band wireless communication applications. Full article

This work focused on the novel and compact 1-bit symmetrical coding-based metamaterial for radar cross section reduction in terahertz frequencies. A couple of coding particles were constructed to impersonate the elements ‘0′ and ‘1′, which have phase differences of 180°. All the analytical simulations were performed by adopting Computer Simulation Technology Microwave Studio 2019 software. Moreover, the transmission coefficient of the element ‘1′ was examined as well by adopting similar software and validated by a high-frequency structure simulator. Meanwhile, the frequency range from 0 to 3 THz was set in this work. The phase response properties of each element were examined before constructing various coding metamaterial designs in smaller and bigger lattices. The proposed unit cells exhibit phase responses at 0.84 THz and 1.54 THz, respectively. Meanwhile, the analysis of various coding sequences was carried out and they manifest interesting monostatic and bistatic radar cross section (RCS) reduction performances. The Coding Sequence 2 manifests the best bistatic RCS reduction values in smaller lattices, which reduced from −69.8 dBm² to −65.5 dBm² at 1.54 THz. On the other hand, the monostatic RCS values for all lattices have an inclined line until they reach a frequency of 1.0 THz from more than −60 dBm². However, from the 1.0 THz to 3.0 THz frequency range the RCS values have moderate discrepancies among the horizontal line for each lattice. Furthermore, two parametric studies were performed to examine the RCS reduction behaviour, for instance, multi-layer structures and as well tilt positioning of the proposed coding metamaterial. Overall it indicates that the integration of coding-based metamaterial successfully reduced the RCS values. Full article

The current study investigates the water quality parameters of drinking water resources in District Neelam (DNLM), Azad Jammu & Kashmir (AJK), Northwestern Pakistan. The studied area has been recently reported with many waterborne diseases, which probed this analytical study. The samples were aseptically collected from springs, taps, and surface water bodies. The water quality parameters, such as physical, microbiological, anions, and heavy metals, were tested. Results showed that the electrical conductance (EC) and total dissolved solids (TDS), were 974.60 µS/cm and 912.10 mg/L, respectively, exacerbating the quality of drinking water in DNLM. For microbial water testing, we used 3M-Petrifilms as a detection source, which could separate coliform bacteria from E. coli by creating unique surface chromophores. Out of sixty collected samples, 76% had bacterial contamination. Nitrite, nitrate, and phosphate (9.8, 15.0, and 15.1 mg/L), were also surpassing the safe limits of the World Health Organization (WHO) standards for water quality measurement. The heavy metals, i.e., As, Cr, Cu, and Pb were also tested in current analysis. Pb and Cr (0.04 mg/L and 0.06 mg/L) exceeded from safe drinking water guidelines of the WHO and more than 50% of the collected samples had Pb as a major water pollutant in DNLM. Poor waste management, open sludge discharge, lack of municipality measures, and mineral leaching into the freshwaters of DNLM due to mining and metal extraction processes were the main sources of water pollution in the region. The inorganic pollutants were responsible for the sudden rise of different malignancies and other fatal diseases (vital organ failures and reproductive disorders) in the region, which has not been reported in the past. The current investigation yielded useful baseline data of the drinking water reserves of NW Pakistan that could help to develop techniques for the mitigation of water pollutants present in the region. Full article

Bergenia ciliata (B. ciliate) leaf extract was used as a capping and stabilizing agent to synthesize copper oxide nanoparticles (CuO NPs). The selection of B. ciliate is purely based on its rich phytochemical composition and less utilization in green chemistry. The X-ray diffraction (XRD) analysis showed that the CuO NPs were found to be highly crystalline, while the irregular morphology and other structural properties were investigated by scanning electron microscopy (SEM) and transmission electron microscopy (TEM), and the average particle size was found to be 50.05 nm. Energy dispersive X-ray (EDX) spectroscopy was used to determine the percentage composition and purity, whereas Fourier transform infrared (FTIR) spectroscopy was utilized to examine the surface functional groups. CuO NPs were tested for their antibacterial properties against Gram-positive and Gram-negative bacteria, and the activity was found to increase with an increasing concentration of CuO NPs in the wells. The dose-dependent antioxidant potential is slightly higher than ascorbic acid. Full article

The evolution of AI and data science has aided in mechanizing several aspects of medical care requiring critical thinking: diagnosis, risk stratification, and management, thus mitigating the burden of physicians and reducing the likelihood of human error. AI modalities have expanded feet to the specialty of pediatric cardiology as well. We conducted a scoping review searching the Scopus, Embase, and PubMed databases covering the recent literature between 2002–2022. We found that the use of neural networks and machine learning has significantly improved the diagnostic value of cardiac magnetic resonance imaging, echocardiograms, computer tomography scans, and electrocardiographs, thus augmenting the clinicians’ diagnostic accuracy of pediatric heart diseases. The use of AI-based prediction algorithms in pediatric cardiac surgeries improves postoperative outcomes and prognosis to a great extent. Risk stratification and the prediction of treatment outcomes are feasible using the key clinical findings of each CHD with appropriate computational algorithms. Notably, AI can revolutionize prenatal prediction as well as the diagnosis of CHD using the EMR (electronic medical records) data on maternal risk factors. The use of AI in the diagnostics, risk stratification, and management of CHD in the near future is a promising possibility with current advancements in machine learning and neural networks. However, the challenges posed by the dearth of appropriate algorithms and their nascent nature, limited physician training, fear of over-mechanization, and apprehension of missing the ‘human touch’ limit the acceptability. Still, AI proposes to aid the clinician tomorrow with precision cardiology, paving a way for extremely efficient human-error-free health care. Full article

Breast cancer is one of the most widely recognized diseases after skin cancer. Though it can occur in all kinds of people, it is undeniably more common in women. Several analytical techniques, such as Breast MRI, X-ray, Thermography, Mammograms, Ultrasound, etc., are utilized to identify it. In this study, artificial intelligence was used to rapidly detect breast cancer by analyzing ultrasound images from the Breast Ultrasound Images Dataset (BUSI), which consists of three categories: Benign, Malignant, and Normal. The relevant dataset comprises grayscale and masked ultrasound images of diagnosed patients. Validation tests were accomplished for quantitative outcomes utilizing the exhibition measures for each procedure. The proposed framework is discovered to be effective, substantiating outcomes with only raw image evaluation giving a 78.97% test accuracy and masked image evaluation giving 81.02% test precision, which could decrease human errors in the determination cycle. Additionally, our described framework accomplishes higher accuracy after using multi-headed CNN with two processed datasets based on masked and original images, where the accuracy hopped up to 92.31% (±2) with a Mean Squared Error (MSE) loss of 0.05. This work primarily contributes to identifying the usefulness of multi-headed CNN when working with two different types of data inputs. Finally, a web interface has been made to make this model usable for non-technical personals. Full article