Introduction: Methadone hydrochloride (MDN) is an effective pharmacological substitution treatment for opioids dependence, adopted in different countries as methadone maintenance treatment (MMT) programmes. However, MDN can exacerbate the addiction problem if it is abused and injected intravenously, and the frequent visits to the MMT centres can reduce patient compliance. The overall aim of this study is to develop a novel extended-release capsule of MDN using the sol-gel silica (SGS) technique that has the potential to counteract medication-tampering techniques and associated health risks and reduce the frequent visits to MMT centres. Methods: For MDN recrystallisation, a closed container method (CCM) and hot-stage method (HSM) were conducted, and MDN crystals were characterised using the polarised light microscope (PLM). MDN crystal thickness was determined by scanning electron microscopy (SEM) and confocal microscopy (CM) to establish a relationship between MDN crystals thickness and their birefringence colours using the Michel-Levy Birefringence Colour Chart. The experimental series was continued to produce novel silica-based MDN formulations A and B capsules by adding MDN powder at the end and beginning of the SGS process, respectively. The silica-based MDN formulations were characterised by Fourier transform infrared (FT-IR), SEM, differential scanning calorimetry (DSC), thermogravimetric analysis (TGA), PLM and mean grey value (MGV) analyses. The in vitro release studies (n=3) for the silica-based MDN formulations and pure MDN capsules were conducted in a phosphate buffer solution (pH= 7.2) for 7 days. Stability studies were conducted for 1 month by keeping the silica-based MDN capsules under 25°C and 57% RH. Results: The optimal method to produce large numbers of MDN crystals was the CCM, and MDN crystals were characterised as diamond shaped with an intrinsic angle of 62o. The SEM surpassed the CM in measuring MDN crystal thickness, and Mann-Whitney U Test showed statistically significant differences between SEM and confocal thickness measurements (U= 1283, p < 0.05) as the SEM exhibited thinner diamond crystals (6.62 ± 2.9 µm) than the CM measurements (9.6 ± 4.6µm). According to the Michel-Levey birefringence colour chart (using the SEM mean thickness of MDN crystals and their retardation value of 428 nm), most of MDN crystals demonstrated a yellow colour. The FT-IR, SEM, DSC, MGV and PLM analyses of both silica-based MDN formulations revealed that MDN was successfully incorporated inside the silica network producing amorphous material (with no appearance of the melting peak of pure MDN at 233.4°C) with evidence of no physical or chemical interaction between sol-gel silica and MDN. However, the TGA analysis revealed a significantly greater amount of MDN was loaded inside the silica-based MDN formulation B compared to A (t = 2.80, p = 0.009, n=6), as 28.3 ± 0.6 mg of MDN was loaded in the former while 25.6 ± 0.7 mg in the latter. In addition, the silica-based MDN formulation B released 10% more MDN after 7 days than formulation A, and both formulations were stable when stored for 1 month under 57% RH and 25°C. Conclusion: The novel combined use of SEM and PLM techniques shows a potential for the identification of MDN in forensic science as it established a range of birefringence colours of MDN crystals. Moreover, the new silica-based MDN formulation B can help to deter MDN abuse and increase patient adherence to MMT due to its potential to sustain MDN release and reduce the frequent visits to MDN treatment centres.
Activity recognition (AR) is a new interesting and challenging research area with many applications (e.g. healthcare, security, and event detection). Basically, activity recognition (e.g. identifying user’s physical activity) is more likely to be considered as a classification problem. In this paper, a combination of 7 classification methods is employed and experimented on accelerometer data collected via smartphones, and compared for best performance. The dataset is collected from 59 individuals who performed 6 different activities (i.e. walk, jog, sit, stand, upstairs, and downstairs). The total number of dataset instances is 5418 with 46 labeled features. The results show that the proposed method of ensemble boost-based classif
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The seizure epilepsy is risky because it happens randomly and leads to death in some cases. The standard epileptic seizures monitoring system involves video/EEG (electro-encephalography), which bothers the patient, as EEG electrodes are attached to the patient’s head.
Seriously, helping or alerting the patient before the seizure is one of the issue that attracts the researchers and designers attention. So that there are spectrums of portable seizure detection systems available in markets which are based on non-EEG signal.
The aim of this article is to provide a literature survey for the latest articles that cover many issues in the field of designing portable real-time seizure detection that includes the use of multiple
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Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a
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In this study, the dynamic modeling and step input tracking control of single flexible link is studied. The Lagrange-assumed modes approach is applied to get the dynamic model of a planner single link manipulator. A Step input tracking controller is suggested by utilizing the hybrid controller approach to overcome the problem of vibration of tip position through motion which is a characteristic of the flexible link system. The first controller is a modified version of the proportional-derivative (PD) rigid controller to track the hub position while sliding mode (SM) control is used for vibration damping. Also, a second controller (a fuzzy logic based proportional-integral plus derivative (PI+D) control scheme) is developed for both vibra
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Virtual organization is similar to traditional organization in principles, but is different in the ways it operates. It requires small creation costs compared to the traditional and it uses electronic commerce as the market place and distribution channel for its products and services.The aim of this article is to applying electronic commerce for a proposed virtual organization. The tools used to build an effective web application for virtual organization to provide virtual environment to the customers to do the transaction activities online include PHP, MySQL and Apache. HTML is used for displaying forms and tables and JavaScript is used for verification in client side. Finally, connecting it to 2Checkout.com company as a third party to per
... Show MoreIn this paper, a literature survey was introduced to study of enhancing the hazy images , because most of the images captured in outdoor images have low contrast, color distortion, and limited visual because the weather conditions such as haze and that leads to decrease the quality of images capture. This study is of great importance in many applications such as surveillance, detection, remote sensing, aerial image, recognition, radar, etc. The published researches on haze removal are divided into several divisions, some of which depend on enhancement the image, some of which depend on the physical model of deformation, and some of them depend on the number of images used and are divided into single-image and multiple images dehazing model
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