Modelling and simulation have now become standard methods that serve to cut the economic costs of R&D for novel advanced systems. This paper introduces the study of modelling and simulation of the infrared thermography process to detect defects in the hydroelectric penstock. A 3-D penstock model was built in ANSYS version 19.2.0. Flat bottom holes of different sizes and depths were created on the inner surface of the model as an optimal scenario to represent the subsurface defect in the penstock. The FEM was applied to mimic the heat transfer in the proposed model. The model’s outer surface was excited at multiple excitation frequencies by a sinusoidal heat flux, and the thermal response of the model was presented in the form of thermal images to show the temperature contrast due to the presence of defects. The harmonic approximation method was applied to calculate the phase angle, and its relationship with respect to defect depth and defect size was also studied. The results confirmed that the FEM model has led to a better understanding of lock-in infrared thermography and can be used to detect subsurface defects in the hydroelectric penstock.
The existing ample literature studied the factors for adopting computer-assisted audit techniques (CAATs) by internal and external auditors, frequently ignoring their impact on the quality of audits and companies’ efficiency. This study delivers new evidence on the kinds of CAATs utilized by internal auditors, examines their adoption impact on corporate sustainability, and studies the moderating impact of company characteristics. This study used data from internal auditors in Ethiopia gathered using a survey, and the study hypotheses were tested using the partial least squares-structural equation modeling (PLS-SEM) technique. The study found a moderate utilization of CAATs by internal auditors in executing their activities. The result also revealed a highly positive impact of internal auditors’ CAAT utilization on fraud discovery in the acquisition process. The study found that the intensity of this relationship is impacted by the companies’ characteristics of management commitment. However, the size and type of the company are not impacting it. This study finding complements prior studies and helps practitioners make decisions that can improve CAAT utilization in internal audit functions for a high level of companies’ sustainability.
Endosulfan (6,7,8,9,10,10-Hexachloro-1,5,5a,6,9,9a-hexahydro-6,9-methano-2,4,3-benzodioxathiepine-3-oxide) is an off-patent insecticide used in agricultural farms. Its usage as a pesticide has become highly controversial over the last few decades. This is due to its reported hazardous nature to health and side effects like growth retardation, hydrocephalus, and undesired changes in the male and female hormones leading to complications in sexual maturity. Endosulfan is the main culprit among all pesticide poisoning incidents around the world. Though the usage of this dreaded pesticide is banned by most countries, the high stability of this molecule to withstand degradation for a long period poses a threat to mankind even today. So, it has become highly essential to detect the presence of this poisonous pesticide in the drinking water and milk around these places. It is also advisable to check the presence of this toxic material in the blood of the population living in and around these places so that an early and appropriate management strategy can be adopted. With this aim, we have developed a sensor for endosulfan that displayed high selectivity and sensitivity among all other common analytes in water and biological samples, with a wide linear concentration range (2 fM to 2 mM), a low detection limit (2 fM), and rapid response. A citrate-functionalized cadmium-selenium quantum dot was used for this purpose, which showed a concentration-dependent fluorescence enhancement, enabling easy and sensitive sensing. This sensor was utilized to detect endosulfan in different sources of water, human blood serum, and milk samples with good recoveries. It is also noted that the quantum dot forms a stable complex with endosulfan and is easy to separate from the contaminated source, paving the way for purifying the contaminated water. More detailed tests and validation of the sensor are needed to confirm these observations.
Recently, carbon nanocomposites have garnered a lot of curiosity because of their distinctive characteristics and extensive variety of possible possibilities. Among all of these applications, the development of sensors with electrochemical properties based on carbon nanocomposites for use in biomedicine has shown as an area with potential. These sensors are suitable for an assortment of biomedical applications, such as prescribing medications, disease diagnostics, and biomarker detection. They have many benefits, including outstanding sensitivity, selectivity, and low limitations on detection. This comprehensive review aims to provide an in-depth analysis of the recent advancements in carbon nanocomposites-based electrochemical sensors for biomedical applications. The different types of carbon nanomaterials used in sensor fabrication, their synthesis methods, and the functionalization techniques employed to enhance their sensing properties have been discussed. Furthermore, we enumerate the numerous biological and biomedical uses of electrochemical sensors based on carbon nanocomposites, among them their employment in illness diagnosis, physiological parameter monitoring, and biomolecule detection. The challenges and prospects of these sensors in biomedical applications are also discussed. Overall, this review highlights the tremendous potential of carbon nanomaterial-based electrochemical sensors in revolutionizing biomedical research and clinical diagnostics.
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