Linseed hydrogel (LSH) was isolated from linseeds (Linum usitatissimum L.) using hot water extraction method, characterized and used in various formulation designs. Characterization of LSH was carried out using Fourier transform infrared (FTIR), powdered X-ray diffraction (PXRD), nuclear magnetic resonance (NMR), scanning electron microscopy (SEM) and thermogravimetric analysis (TGA). LSH was also modified by acetylation and structures obtained were thoroughly characterized. Stimuli responsive swelling of LSH was evaluated at gastrointestinal pHs (1.2, 6.8 and 7.4) and in deionized water and also in different molar concentrations of NaCl and KCl solutions. Swelling-deswelling (on-off) response of LSH against environmental conditions was also observed. LSH has shown high swelling at pH 6.8, 7.4 and deionized water while negligible swelling was seen at pH 1.2 indicating potential of LSH as intestine targeting drug delivery system. Swelling behaviour of LSH at various pHs of gastrointestinal tract (GIT) has followed the second order kinetics. Inverse relation between swelling of LSH and molar concentrations (0.1, 0.2, 0.3, 0.4, 0.5, 1.0 and 2.0 M) of NaCl and KCl were observed. Moreover, the water swollen LSH when immersed in normal saline, shrinking was observed. A more abrupt shrinking of water swollen LSH was observed on immersing in ethanol. Similarly, swelling-deswelling response was also observed in buffer of pH 7.4 and 1.2, respectively. These results have revealed that LSH is a smart material and can be used to make intelligent drug delivery systems. High swelling and water holding capability of LSH were used to develop the sustained release formulation of diclofenac sodium. Drug release data from LSH tablets was compared with commercially available product (Voltral®) and found better results. It was observed that the release of diclofenac sodium from LSH matrix tablets was dependent on the concentration of LSH and followed the anomalous transport mechanism. Therefore, LSH can be used as a release retarding agent in sustained release formulation. LSH-caffeine and LSH-diacerein tablets were prepared to analyze the stimuli (pH, salt solution and ethanol) responsive swelling and swelling-deswelling (pH 7.4/1.2, water/normal saline and water/ethanol) behaviour of LSH when used in tablet formulation. Although, stimuli responsive properties of LSH remain the same even after compression in tablet form but less swelling capacity was observed after compression. This might be due to the packing arrangements of LSH and also less exposed area to the swelling medium in tablet form as compared to powder form. LSH appeared as a novel material for stimuli responsive and pH dependent release of NSAIDs in gastrointestinal tract. The elongated porous structure arranged in uniformly distributed layers were seen in FE SEM analysis of swollen then freeze dried powder sample of LSH. Similar pattern of porous channels was also observed even in tablet formulations of LSH. High swelling and water holding capability of LSH are due to these porous channels. Docetaxel loaded LSH Pluronic F-68 nanoparticles (DLP-NPs) were synthesized by core shell formation. Drug loaded core of LSH was protected and stabilized by Pluronic F-68. Size and morphological analysis of DLP-NPs was performed by dynamic light scattering (DLS), PXRD and TEM. Results indicated that DLP-NPs are spherical in shape having size range of 220-335 nm. In vitro drug release study has shown a prolong release pattern for more than 4 days. Cell viability study of LSH and DLP-NPs has proved even better results when compared with free docetaxel. Cell uptake behaviour of DLP-NPs was monitored using Nile red and high concentration of DLP-NPs was accumulated in the cytoplasmic region of the cell. Therefore, DLP-NPs have shown a promising anticancer drug delivery system. LSH was used as a reducing and capping agent for the green synthesis of Ag NPs. Aqueous suspension of LSH were mixed with silver nitrate solution and exposed to sunlight. Formation of Ag NPs was monitored by noting the colour of solution and through UV spectrophotometer. UV absorptions were observed from 410-437 nm. TEM images revealed the formation of spherical Ag NPs in the range of 10-35 nm. Face centered cubic array of Ag NPs was confirmed by characteristic diffraction peaks in PXRD spectrum. Significant antimicrobial activity was observed when microbial cultures (bacteria and fungi) were exposed to the synthesized Ag NPs. Wound healing studies revealed that Ag NPs impregnated in LSH thin films could have potential applications as an antimicrobial dressing in wound management procedures. Acute toxicity study of LSH was conducted on albino mice and albino rabbits. Three groups of mice were exposed to a single oral dose of LSH (1, 5 and 10 g/kg). For eye irritation study and dermal toxicity study, rabbits were exposed to LSH. After day 14, the haematological and biochemical testing were performed and the values obtained were within the normal range. Furthermore, the histopathological evaluation of the vital organs has not shown any abnormalities. After acute toxicity study, LSH was found safe up to the dose of 10g/kg of the body weight of the animal. Overall, LSH has shown itself as a highly swellable and smart biomaterial having stimuli responsive swelling-deswelling properties both in powder form and tablet formulation. Furthermore, the preparation of DTX loaded LSH NPs has proved its utilization in the development of novel drug delivery system for cancer treatment. Ag NPs embedded LSH matrix is a new biocomposite for wound dressing and wound healing. Therefore, LSH has proved as a potential material with wide range of pharmaceutical applications.
کچھ مصنف کے بارے میں بسم اللہ الرحمن الرحیم نحمدہٗ و نصلی علی رسولہِ الکریم قانون ِقدرت ہے کہ جب دنیا میں صدق و حقیقت پر خواہش اور نفس پرستی کے غبار اور پردے پڑ جاتے ہیں تو اللہ تعالیٰ اپنے بندے پیدا کرتا ہے جو صدق و سچائی اور حقیقت کو دنیا میں روشن کر دیتے ہیں۔ ایسے ہی میرے تایا زاد حافظ محمد اکرم راشدؔ صاحب کو اللہ تعالیٰ نے گو نا گوں صفات سے نوازا ہے۔ عارف والا کے نواحی گائوں 37 ای بی میں 1962 کے اوائل میں علمی خانوادے میں آنکھ کھولی والدِ محترم حافظ اللہ یار رحمۃ اللہ علیہ عالم باعمل تھے ابتدائی تعلیم اُ ن سے حاصل کی ۔ پانچ سال کی عمر میں والدِ محترم داغِ مفارقت دے گئے ۔ اُس کے بعد حقیقی چچا میرے والدِ محترم حضرت علامہ حافظ شیر علی رحمتہ اللہ علیہ نے آغوشِ محبت میں لیا اور علم کی تکمیل تک ساتھ دیا ۔ میٹرک کر نے کے بعد علمی پیاس بجھانے کے لئے کراچی گئے وہاں علم کی پیاس بجھاتے ہوئے علم کے سمندر بن گئے ۔ فاضل درسِ نظامی ، فاضل طب وجراحت، فاضل عربی، فاضل اردو کرنے کے بعد پنجاب گورنمنٹ میں بطورِ مدرس تعینات ہوئے ۔ دورانِ سروس ایم ۔اے ایجوکیشن ،ایم اے اسلامیات اور ایم اے عربی (گولڈ میڈلسٹ) پاس کیا۔ علمی زندگی میں روزنامہ ایکسپریس ، نوائے وقت میں مضامین لکھے اور عوام کی کثیر تعداد نے مضامین کو پسند کیا۔تاحال عارفوالا کے نواحی گائو ں میں ہیڈ مدرس ہیں اور عارفوالا شہر میں بطورِ خطیب خدمات سر انجام دے رہے ہیں ۔ حافظ صاحب اپنے حلقہ احباب میں اپنی خوش اخلاقی اور بذلہ سنجی کی وجہ سے بہت مقبول ہیں ۔ اِن کی مذکورہ کتاب اُن کے علمی تبحّر کی گواہ ہے اللہ تعالیٰ اُن...
Research on gender roles in relation to government bureaucratic structures is still minimal. This study aims to find answers to the main problem, namely how the role of women in the local government bureaucracy seen from human resource development aspect in Central Sulawesi Province. This research is a qualitative descriptive study which aims to create a picture of the gender presentation in the bureaucratic staffing and the role of women. The subjects of this study were women who hold echelons. The data collection technique used in this study was literature review. For the validity of the data, the cross check technique was used. The data analysis technique used is the inductive analysis technique. The results showed that the role of women in the local government bureaucracy in Central Sulawesi was still not fully implemented. The echelon holder ratio is still dominated by men. However, it is possible that this ratio will change over time.
Advancement in the myoelectric interfaces have increased the use of myoelectric controlled robotic arms for partial-hand amputees as compared to body-powered arms. Current clinical approaches based on conventional (on/off and direct) control are limited to few degree of freedom (DoF) movements which are being better addressed with pattern recognition (PR) based control schemes. Performance of any PR based scheme heavily relies on optimal features set. Although, such schemes have shown to be very effective in short-term laboratory recordings, but they are limited by unsatisfactory robustness to non-stationarities (e.g. changes in electrode positions and skin-electrode interface). Moreover, electromyographic (EMG) signals are stochastic in nature and recent studies have shown that their classification accuracies vary significantly over time. Hence, the key challenge is not the laboratory short term conditions but the daily use. Thus, this work makes use of the longitudinal approaches with deep learning in comparison to classical machine learning techniques to myoelectric control and explores the real potential of both surface and intramuscular EMG in classifying different hand movements recorded over multiple days. To the best of our knowledge, for the first time, it also explores the feasibility of using raw (bipolar) EMG as input to deep networks. Task are completed with two different studies that were performed with different datasets. In the first study, surface and intramuscular EMG data of eleven wrist movements were recorded concurrently over six channels (each) from ten able-bodied and six amputee subjects for consecutive seven days. Performance of stacked sparse autoencoders (SSAE), an emerging deep learning technique, was evaluated in comparison with state of art LDA using offline classification error as performance matric. Further, performance of surface and intramuscular EMG was also compared with respect to time. Results of different analyses showed that SSAE outperformed LDA. Although there was no significant difference found between surface and intramuscular EMG in within day analysis but surface EMG significantly outperformed intramuscular EMG in long-term assessment. In the second study, surface EMG data of seven able-bodied were recorded over eight channels using Myo armband (wearable EMG sensors). The protocol was set such that each subject performed seven movements with ten repetitions per session. Data was recorded for consecutive fifteen days with two sessions per day. Performance of convolutional neural network (CNN with raw EMG), SSAE (both with raw data and features) and LDA were evaluated offline using classification error as performance matric. Results of both the short and long-term analyses showed that CNN and SSAE-f outperformed the others while there was no difference found between the two. Overall, this dissertation concludes that deep learning techniques are promising approaches in improving myoelectric control schemes. SSAE generalizes well with hand-crafted features but fails to generalize with raw data. CNN based approach is more promising as it achieved optimal performance without the need to select features.