Solubility improvement of progesterone from solid dispersions prepared by solvent evaporation and co-milling

The aim of this contribution was to evaluate the impact of processing methods and polymeric carriers on the physicochemical properties of solid dispersions of the poorly soluble drug progesterone (PG). Five polymers: hydroxypropyl methylcellulose (HPMC), hydroxypropyl methylcellulose acetate succinate (HPMCAS), microcrystalline cellulose (MCC), polyvinylpyrrolidone (PVP) and silica (SiO2), and two processing methods: solvent evaporation (SE) and mechano-chemical activation by co-milling (BM) were applied. H-bonding was demonstrated by FTIR spectra as clear shifting of drug peaks at 1707 cm−1 (C20 carbonyl) and 1668 cm−1 (C3 carbonyl). Additionally, spectroscopic and thermal analysis revealed the presence of unstable PG II polymorphic form and a second heating DSC cycle, the presence of another polymorph possibly assigned to form III, but their influence on drug solubility was not apparent. Except for PG–MCC, solid dispersions improved drug solubility compared to physical mixtures. For SE dispersions, an inverse relationship was found between drug water solubility and drug–polymer Hansen solubility parameter difference (∆δt), whereas for BM dispersions, the solubility was influenced by both the intermolecular interactions and the polymer Tg. Solubility improvement with SE was demonstrated for all except PG–MCC dispersions, whereas improvement with BM was demonstrated by the PG–HPMC, PG–PVP and PG–HPMCAS dispersions, the last showing impressive increase from 34.21 to 82.13 μg/mL. The extensive H-bonding between PG and HPMCAS was proved by FTIR analysis of the dispersion in the liquid state. In conclusion, although SE improved drug solubility, BM gave more than twice greater improvement. This indicates that directly operating intermolecular forces are more efficient than the solvent mediated

Social Media and Political Changes in \u3cem\u3eAl-Alam Al-Arabi\u3c/em\u3e

The Arab countries are typically described as lacking democratic traditions, freedom of the press, human rights and civil liberties. The utilization of social media for political purposes became crucial to the widespread expression of pent-up social discontent that precipitated the Arab Spring. Uploaded videos, photos, and Twitter feeds served to outrage people in Tunisia, Egypt, Libya, Yemen, Bahrain, and Syria. This volatile combination of a young population, authoritarian rule, corruption and poverty is prompting youth to spearhead political demonstrations and the demand for regime change

Book Review: Inspirational Reading

Review of The Cambridge Companion to Modern Arab Culture by Dwight F. Reynolds. (Cambridge, UK: Cambridge University Press, 2015)

Effects of ellagic acid on extracted tooth socket healing in nicotinic diabetic rats / Mazen.M.Jamil Al-Obaidi

The resorption of alveolar bone that occurs after tooth extraction leads to many esthetic and functional problems. Ellagic acid (EA) is a member of the flavonoid family that regulates various processes of bone function. Statins are speculated to increase bone formation. This study was designed to evaluate the healing of extracted tooth sockets in diabetic and non-diabetic rats administered with EA orally and treated with rousavastatin (RSV) locally in nicotinic and non-nicotinic rats. Sixty-four male Sprague– Dawley rats weighing 250-300 g were selected to conduct the tooth extraction experimental study. The rats were divided into two main groups. The first main group was considered as the non-diabetic group and divided into four sub-groups; (A) The tooth rat socket filled with RSV+ The rats treated with NaCl orally (RSV+NaCl). (B) The tooth rat socket filled with RSV + the rats treated with EA orally (RSV+EA). (C) The tooth rat socket filled with RSV + The rats injected with Ni (RSV+Ni). (D) The tooth rat socket filled with RSV + the rats injected with Ni + treated with EA (RSV+Ni+EA). The second main group was considered as the diabetic group and divided into four sub-groups: (A) The tooth rat socket filled with RSV+ the rats treated with NaCl orally (RSV+NaCl). (B) The tooth rat socket filled with RSV + the rats treated with EA orally (RSV+EA). (C) The tooth rat socket filled with RSV + The rats injected with Ni (RSV+Ni). (D) The tooth rat socket filled with RSV + the rats injected with Ni + treated with EA (RSV+Ni+EA)

Preparation , Characterization, and Theoretical Treatment Complexes Of Some Transition Metals with N5 Acyclic Derived From 2,6-diacetyl pyridine

   A series  of  transition  metal  complexes with [2,6-diacetimino-pheylenediamine –[2,2,diyl] pyridine ]of the general  formula [MLCl]Cl , M= Co(II), Ni(II) and Cu(II) , respectively  have been  synthesized  and  fully characterized  on the bases  of C.H.N.M  elemental analysis, 1HNMR , UV- Visible and FTIR spectra , in addition the structure of complexes was characterized by  magnetic moments and molar conductance in DMSO solution ,and molar ratio of metal  were also determined. From the above of these studies and measurements suggest an octahedral geometry around Co(II) , Ni(II) and Cu(II) .A theoretical treatment of the formation of complexes in the gas phase was studied, this was done using the HYPERCHEM-6 program for the Molecular mechanics and Semi-empirical calculations.Â

Studying Structural Behavior of Concrete Faced Rockfill Dam Using Finite Element Method

Concrete faced rock fill dam has been increasingly popular among dam engineers due to their inherent advantages over other type of dams. The construction of concrete faced rockfill dam has been conducted in full swing in recent years. But still there is some crucial problems needed further investigation. In this study an attempt has been made to investigate various aspects related to the structural analysis of concrete face rockfill dams, this involved, physical modelling, constitutive modelling, effect of concrete slab and simulation of sequence of construction. To model sequential stages of construction of concrete faced rockfill dam the Dead- Birth-Ghost element technique was used. The physical modeling was carried out using finite-infinite elements to represent bedding media, eight and six noded isoparametric elements were used for modeling the dam body and the concrete face respectively. Moreover the interfacial behavior between the concrete face and the body of the dam was modeled using interface element. The constitutive modeling has body of the dam was modeled using interface element. The constitutive modeling has been accounted by employing the hyperbolic nonlinear elastic model. So based on the above physical and material modeling a two dimension linear and nonlinear finite element program with different type of isoparametric elements was written. The verification of the program was well established by analyzing certain bench mark examples. The applicability of the above program has been illustrated by analyzing two concrete faced rockfill dam namely; Kavar dam currently under construction in Iran (53.5 m), and Bakun dam currently under construction in the state of Sarawak Malaysia (205 m). The results indicates that the sequences of construction, reservoir filling and nonlinear material behavior have significant effects on the structural response of the dam in terms of displacement and stresses and need to be considered for accurate prediction of the structural behavior of the dam and focuses on the effect of face slab on the distribution of deformation and stresses developed due to the static loading including gravitation and reservoir loading

Economic removal of chlorophenol from wastewater using multi-stage spiral-wound reverse osmosis process: simulation and optimisation

YesThe successful use of Reverse Osmosis (RO) process has increased significantly in water desalination, water treatment and food processing applications. In this work, the economic feasibility of a multi-stage RO process including both retentate and permeate reprocessing for the removal of chlorophenol from wastewater is explored using simulation and optimisation studies. Firstly, a mathematical model of the process is developed based on the solution diffusion model, which was validated using experimental chlorophenol removal from the literature, is combined with several appropriate cost functions to form a full model package. Secondly, for a better understanding of the interactions between the different parameters on the economic performance of the process, a detailed process simulation is carried out. Finally, a multi-objective optimisation framework based on Non-Linear Programming (NLP) problem is developed for minimising the product unit cost, the total annualised cost, the specific energy consumption together with optimising the feed pressure and feed flow rate for an acceptable level of chlorophenol rejection and total water recovery rate. The results clearly show that the removal of chlorophenol can reach 98.8% at a cost of approximately 0.21 $/m³

Transparent Authentication Utilising Gait Recognition

Securing smartphones has increasingly become inevitable due to their massive popularity and significant storage and access to sensitive information. The gatekeeper of securing the device is authenticating the user. Amongst the many solutions proposed, gait recognition has been suggested to provide a reliable yet non-intrusive authentication approach – enabling both security and usability. While several studies exploring mobile-based gait recognition have taken place, studies have been mainly preliminary, with various methodological restrictions that have limited the number of participants, samples, and type of features; in addition, prior studies have depended on limited datasets, actual controlled experimental environments, and many activities. They suffered from the absence of real-world datasets, which lead to verify individuals incorrectly. This thesis has sought to overcome these weaknesses and provide, a comprehensive evaluation, including an analysis of smartphone-based motion sensors (accelerometer and gyroscope), understanding the variability of feature vectors during differing activities across a multi-day collection involving 60 participants. This framed into two experiments involving five types of activities: standard, fast, with a bag, downstairs, and upstairs walking. The first experiment explores the classification performance in order to understand whether a single classifier or multi-algorithmic approach would provide a better level of performance. The second experiment investigated the feature vector (comprising of a possible 304 unique features) to understand how its composition affects performance and for a comparison a more particular set of the minimal features are involved. The controlled dataset achieved performance exceeded the prior work using same and cross day methodologies (e.g., for the regular walk activity, the best results EER of 0.70% and EER of 6.30% for the same and cross day scenarios respectively). Moreover, multi-algorithmic approach achieved significant improvement over the single classifier approach and thus a more practical approach to managing the problem of feature vector variability. An Activity recognition model was applied to the real-life gait dataset containing a more significant number of gait samples employed from 44 users (7-10 days for each user). A human physical motion activity identification modelling was built to classify a given individual's activity signal into a predefined class belongs to. As such, the thesis implemented a novel real-world gait recognition system that recognises the subject utilising smartphone-based real-world dataset. It also investigates whether these authentication technologies can recognise the genuine user and rejecting an imposter. Real dataset experiment results are offered a promising level of security particularly when the majority voting techniques were applied. As well as, the proposed multi-algorithmic approach seems to be more reliable and tends to perform relatively well in practice on real live user data, an improved model employing multi-activity regarding the security and transparency of the system within a smartphone. Overall, results from the experimentation have shown an EER of 7.45% for a single classifier (All activities dataset). The multi-algorithmic approach achieved EERs of 5.31%, 6.43% and 5.87% for normal, fast and normal and fast walk respectively using both accelerometer and gyroscope-based features – showing a significant improvement over the single classifier approach. Ultimately, the evaluation of the smartphone-based, gait authentication system over a long period of time under realistic scenarios has revealed that it could provide a secured and appropriate activities identification and user authentication system