The aim of this paper is to investigate the effects of the distances between the human head and internal cellular device antenna on the specific absorption rate (SAR). This paper also analyzes the effects of inclination angles between user head and mobile terminal antenna on SAR values. The effects of the metal-glass casing of mobile phone on the SAR values were observed in the vicinity of the human head model. Moreover, the return losses were investigated in all cases to mark antenna performance. This analysis was performed by adopting finite-difference time-domain (FDTD) method on Computer Simulation Technology (CST) Microwave Studio. The results indicate that by increasing the distance between the user head and antenna, SAR values are decreased. But the increase in inclination angle does not reduce SAR values in all cases. Additionally, this investigation provides some useful indication for future design of low SAR mobile terminal antenna.
The interaction of a dipole antenna with a human eye model in the presence of a metamaterial is investigated in this paper. The finite difference time domain (FDTD) method with convolutional perfectly matched layer (CPML) formulation have been used. A three-dimensional anatomical model of the human eye with resolution of 1.25 mm × 1.25 mm × 1.25 mm was used in this study. The dipole antenna was driven by modulated Gaussian pulse and the numerical study is performed with dipole operating at 900 MHz. The analysis has been done by varying the size and value of electric permittivity of the metamaterial. By normalizing the peak SAR (1 g and 10 g) to 1 W for all examined cases, we observed how the SAR values are not affected by the different permittivity values with the size of the metamaterial kept fixed.
The potential of solar cells have not been fully tapped due to the lack of energy conversion efficiency. There are three important mechanisms in producing high efficiency cells to harvest solar energy; reduction of light reflectance, enhancement of light trapping in the cell and increment of light absorption. The current work represent studies conducted in surface modification of single-crystalline silicon solar cells using wet chemical etching techniques. Two etching types are applied; alkaline etching (KOH:IPA:DI) and acidic etching (HF:HNO3:DI). The alkaline solution resulted in anisotropic profile that leads to the formation of inverted pyramids. While acidic solution formed circular craters along the front surface of silicon wafer. This surface modification will leads to the reduction of light reflectance via texturizing the surface and thereby increases the short circuit current and conversion rate of the solar cells.
Mammalian adipose tissue derived stem cells (AT-SC) have a tremendous potential in regenerative medicine for tissue engineering and somatic nuclear transfer (SNT). The isolation methods of human and bovine adipose tissue derived stem cells are compared in this paper to determine the feasibility and optimum method of isolation. The optimum isolation method will reduce the processing time, efforts and money as isolation is the first crucial and important step in stem cells research. Human abdominal subcutaneous adipose tissue and bovine abdominal subcutaneous adipose tissue are digested in three collagenase type 1 concentration 0.075%, 0.3% and 0.6% agitated at 1 h and 2 h under 37 °C in 5% CO2 incubator. The cultures are then morphologically characterised. Human adipose tissue stem cells are found to be best isolated using abdominal subcutaneous depot, using 0.075% collagenase type 1 agitated at 1 h under 37 °C in CO2 incubator. While bovine adipose tissue derived stem cells are best isolated using abdominal subcutaneous depot, using 0.6% collagenase type 1 agitated at 2 h under 37 °C in CO2 incubator.
The potential of organic semiconductor based devices for light generation is demonstrated by the commercialisation of display technologies using organic light emitting diode (OLED). In OLED, organic materials plays an important role of emitting light once the current is passed through. However OLED have drawbacks whereby it suffers from photon loss and exciton quenching. Organic light emitting transistor (OLET) emerged as a new technology to compensate the efficiency and brightness loss encountered in OLED. The structure has combinational capability to switch the electronic signal such as the field effect transistor (FET) as well as to generate light. Different colours of light could be generated by using different types of organic material. The light emission could also be tuned and scanned in OLET. The studies carried out in this paper focuses on investigation of fabricated MEH-PPV based OLED and also OLET via current voltage characteristics. These studies will continue with a view to develop an optimised MEH-PPV based OLET.
Biomarker-based tests may facilitate Tuberculosis (TB) diagnosis, accelerate treatment initiation, and thus improve outcomes. This review synthesizes the literature on biomarker-based detection for TB diagnosis using machine learning. The systematic review approach follows the PRISMA guideline. Articles were sought using relevant keywords from Web of Science, PubMed, and Scopus, resulting in 19 eligible studies after a meticulous screening. All the studies were found to have focused on the supervised learning approach, with Support Vector Machine (SVM) and Random Forest emerging as the top two algorithms, with the highest accuracy, sensitivity and specificity reported to be 97.0%, 99.2%, and 98.0%, respectively. Further, protein-based biomarkers were widely explored, followed by gene-based such as RNA sequence and, Spoligotypes. Publicly available datasets were observed to be popularly used by the studies reviewed whilst studies targeting specific cohorts such as HIV patients or children gathering their own data from healthcare facilities, leading to smaller datasets. Of these, most studies used the leave one out cross validation technique to mitigate overfitting. The review shows that machine learning is increasingly assessed in research to improve TB diagnosis through biomarkers, as promising results were shown in terms of model's detection performance. This provides insights on the possible application of machine learning approaches to diagnose TB using biomarkers as opposed to the traditional methods that can be time consuming. Low-middle income settings, where access to basic biomarkers could be provided as compared to sputum-based tests that are not always available, could be a major application of such models.
Quantum dots (QDs) are a class of remarkable materials that have garnered significant attention since their initial discovery. It is noteworthy to mention that it took approximately a decade for these materials to be successfully implemented in practical applications. While QDs have demonstrated notable optical properties, it is important to note that these attributes alone have not rendered them a feasible substitute for traditional organic dyes. Furthermore, it is worth noting that the substance under investigation exhibited inherent toxicity and instability in its initial state, primarily due to the presence of a heavy metal core. In the initial stages of research, it was observed that the integration of nanocomposites had a positive impact on the properties of QDs. The discovery of these nanocomposites was motivated by the remarkable properties exhibited by biocomposites found in nature. Recent discoveries have shed light on the potential utilization of QDs as a viable strategy for drug delivery, offering a promising avenue to enhance the efficacy of current pharmaceuticals and pave the way for the creation of innovative therapeutic approaches. The primary objective of this review was to elucidate the distinctive characteristics that render QDs highly suitable for utilization as nanocarriers. In this study, we will delve into the multifaceted applications of QDs as sensing nanoprobes and their utilization in diverse drug delivery systems. The focus of our investigation was directed toward the utilization of QD/polymer composites in sensing applications, with particular emphasis on their potential as chemical sensors, biosensors, and physical sensors.
Amyloidosis is a deleterious condition caused by abnormal amyloid fibril build-up in living tissues. To date, 42 proteins that are linked to amyloid fibrils have been discovered. Amyloid fibril structure variation can affect the severity, progression rate, or clinical symptoms of amyloidosis. Since amyloid fibril build-up is the primary pathological basis for various neurodegenerative illnesses, characterization of these deadly proteins, particularly utilising optical techniques have been a focus. Spectroscopy techniques provide significant non-invasive platforms for the investigation of the structure and conformation of amyloid fibrils, offering a wide spectrum of analyses ranging from nanometric to micrometric size scales. Even though this area of study has been intensively explored, there still remain aspects of amyloid fibrillization that are not fully known, a matter hindering progress in treating and curing amyloidosis. This review aims to provide recent updates and comprehensive information on optical techniques for metabolic and proteomic characterization of β-pleated amyloid fibrils found in human tissue with thorough literature analysis of publications. Raman spectroscopy and SAXS are well established experimental methods for study of structural properties of biomaterials. With suitable models, they offer extended information for valid proteomic analysis under physiologically relevant conditions. This review points to evidence that despite limitations, these techniques are able to provide for the necessary output and proteomics indication in order to extrapolate the aetiology of amyloid fibrils for reliable diagnostic purposes. Our metabolic database may also contribute to elucidating the nature and function of the amyloid proteome in development and clearance of amyloid diseases.
Gene regulatory network (GRN) comprises complicated yet intertwined gene-regulator relationships. Understanding the GRN dynamics will unravel the complexity behind the observed gene expressions. Insect gene regulation is often complicated due to their complex life cycles and diverse ecological adaptations. The main interest of this review is to have an update on the current mathematical modelling methods of GRNs to explain insect science. Several popular GRN architecture models are discussed, together with examples of applications in insect science. In the last part of this review, each model is compared from different aspects, including network scalability, computation complexity, robustness to noise and biological relevancy.
Dysregulation of long non-coding RNA (lncRNA) HOXA-AS3 has been shown to contribute to the development of multiple cancer types. Several studies have presented the tumour-modulatory role or prognostic significance of this lncRNA in various kinds of cancer. Overall, HOXA-AS3 can act as a competing endogenous RNA (ceRNA) that inhibits the activity of seven microRNAs (miRNAs), including miR-29a-3p, miR-29 b-3p, miR-29c, miR-218-5p, miR-455-5p, miR-1286, and miR-4319. This relieves the downstream messenger RNA (mRNA) targets of these miRNAs from miRNA-mediated translational repression, allowing them to exert their effect in regulating cellular activities. Examples of the pathways regulated by lncRNA HOXA-AS3 and its associated downstream targets include the WNT/β-catenin and epithelial-to-mesenchymal transition (EMT) activities. Besides, HOXA-AS3 can interact with other cellular proteins like homeobox HOXA3 and HOXA6, influencing the oncogenic signaling pathways associated with these proteins. Generally, HOXA-AS3 is overexpressed in most of the discussed human cancers, making this lncRNA a potential candidate to diagnose cancer or predict the clinical outcomes of cancer patients. Hence, targeting HOXA-AS3 could be a new therapeutic approach to slowing cancer progression or as a potential biomarker and therapeutic target. A drawback of using lncRNA HOXA-AS3 as a biomarker or therapeutic target is that most of the studies that have reported the tumour-regulatory roles of lncRNA HOXA-AS3 are single observational, in vitro, or in vivo studies. More in-depth mechanistic and large-scale clinical trials must be conducted to confirm the tumour-modulatory roles of lncRNA HOXA-AS3 further. Besides, no lncRNA HOXA-AS3 inhibitor has been tested preclinically and clinically, and designing such an inhibitor is crucial as it may potentially slow cancer progression.