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Sodium alginate–arabinoxylan composite microbeads: preparation and characterization
Munish Ahuja,Meenakshi Bhatia,Komal Saini 한국약제학회 2016 Journal of Pharmaceutical Investigation Vol.46 No.7
The objective of present study was to prepare composite microbeads of psyllium arabinoxylan and sodium alginate by ionotropic gelation method using calcium chloride as a cross linker and was further evaluated for release study. The effect of concentration of sodium alginate/arabinoxylan and concentration of calcium chloride on the entrapment efficiency and on % release were studied employing 2-factor, 3-level central composite experimental design. The results of the study revealed that interaction effect of the concentration of sodium alginate/ arabinoxylan and calcium chloride influenced the entrapment efficiency and release of diclofenac sodium significantly. The optimal calculated parameters were found to be concentration of sodium alginate/arabinoxylan-5 and concentration of calcium chloride-0.75 M, that provided microbeads with entrapment efficiency-64.4 % and release of 28.5 % of the drug over 8 h period of study. Further, arabinoxylan–sodium alginate mucoadhesive microbeads were found to sustain the release of diclofenac sodium over a period of 8 h following zero order kinetics with the mechanism of release being diffusion.
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Munish Sood,Vikas Kulshrestha,Julie Sachdeva,Amresh Ghai,Ajaydeep Sud,Shalender Singh 대한정형외과학회 2020 Clinics in Orthopedic Surgery Vol.12 No.3
Background: Anterior cruciate ligament reconstruction (ACLR) remains the gold standard treatment for anterior cruciate ligament (ACL) injury. However, a good functional outcome even after a successful surgery depends on multiple factors. It has been observed that certain patients with a chronic ACL injury demonstrate knee instability voluntarily. The authors observed that these patients might not perform well even after a successful surgery. This study aims to assess the outcome after ACL and other ligament reconstruction in patients with voluntary knee instability. Methods: From a total of 824 patients who underwent ACLR, 13 patients with a history of voluntary knee instability were selected, and data of these patients (demographic and clinical profile) were obtained. Outcomes of surgery in this group of patients were evaluated by using Lysholm score and Tegner activity level. Results: All patients were young men with a chronic ACL injury and manifested instability. Associated injuries were lateral meniscus tear in 3 patients, medial meniscus tear in 2, and posterolateral corner (PLC) injury in 3. ACLR was done using the semitendinosus- gracilis graft in all patients. Further, anterolateral ligament reconstruction was done in 2 patients and PLC reconstruction, in 3 patients. The mean Lysholm score was 54.76 (range, 48–62) preoperatively and 60.92 (range, 54–78) at a mean follow-up of 14.3 months (range, 11–26 months). The median Tegner activity level was 6 (range, 5–7) before injury and 4 (range, 3–5) at the final follow-up. Twelve of the 13 patients were able to demonstrate instability voluntarily at the time of the final follow-up. Conclusions: In patients with ACL and other ligament injuries who demonstrated voluntary knee instability, the functional outcome even after successful ligament reconstruction was poor.
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Munish Sood,Vikas Kulshrestha,Julie Sachdeva,Amresh Ghai,Ajaydeep Sud,Shalendra Singh 대한정형외과학회 2020 Clinics in Orthopedic Surgery Vol.12 No.4
In the article entitled “Poor Functional Outcome in Patients with Voluntary Knee Instability after Anterior Cruciate Ligament Reconstruction,”1) the name of one of the authors was incorrectly presented: Shalender Singh should read Shalendra Singh.
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PCA-based Offline Handwritten Character Recognition System
Munish Kumar,M. K. Jindal,R. K. Sharma 한국산학기술학회 2013 SmartCR Vol.3 No.5
Principal component analysis (PCA) has been used widely in pattern recognition to reduce the extent of the data. In this paper, we explore using this technique to recognize offline handwritten Gurmukhi characters, and a system for offline handwritten Gurmukhi character recognition using PCA is proposed. The system first prepares a skeleton of the character so that meaningful feature information about the character can be extracted. For classification, we used k-nearest neighbor, Linear-SVM, polynomial-SVM and RBF-SVM based approaches and combinations of these approaches. In this work, we collected 16,800 samples of isolated offline handwritten Gurmukhi characters. These samples were divided into three categories. In category 1 (5600 samples), each Gurmukhi character was written 100 times by a single writer. In category 2 (5600 samples), each Gurmukhi character was written 10 times by 10 different writers, and in category 3 (5600 samples), each Gurmukhi character was written by 100 different writers. The set of the basic 35 akhars of Gurmukhi has been considered here. A partitioning strategy for selecting the training and testing patterns is also explored in this work. We used zoning, diagonal, directional, transition, intersection and open end point, parabola curve fitting?based and power curve fitting?based feature extraction in order to find the feature set for a given character. The proposed system achieves a recognition accuracy of 99.06% in category 1, 98.73% in category 2 and 78.30% in category 3.
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Munish Ashat,Kaartik Soota,Jagpal S. Klair,Sarika Gupta,Chris Jensen,Arvind R. Murali,Randhir Jesudoss,Rami El Abiad,Henning Gerke 대한소화기내시경학회 2020 Clinical Endoscopy Vol.53 No.4
Background/Aims: Endoscopic ultrasound (EUS)-guided fine-needle aspiration is very effective for providing specimens forcytological evaluation. However, the ability to provide sufficient tissue for histological evaluation has been challenging due to thetechnical limitations of dedicated core biopsy needles. Recently, a modified EUS needle has been introduced to obtain tissue coresamples for histological analysis. We aimed to determine (1) its ability to obtain specimens for histological assessment and (2) thediagnostic accuracy of EUS-guided fine-needle biopsy (EUS-FNB) using this needle. Methods: We retrospectively analyzed consecutive cases of FNB using modified EUS needles for 342 lesions in 303 patients. Thecytology and histological specimens were analyzed. Diagnostic accuracy was calculated. Results: Adequate cytological and histological assessment was possible in 293/342 (86%) and 264/342 (77%) lesions, respectively. Diagnostic accuracy of the cytological specimen was 294/342 (86%) versus 254/342 (74%) for the histological specimen (p<0.01). Diagnostic accuracy of the combined cytological and histological assessment was 323/342 (94.4%), which was significantly higher thanthat of both histology alone (p<0.001) and cytology alone (p=0.001). Conclusions: EUS-FNB with the modified EUS needle provided histologic tissue cores in the majority of cases and achieved excellentdiagnostic accuracy with few needle passes.
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MDP Feature Extraction Technique for Offline Handwritten Gurmukhi Character Recognition
Munish Kumar,M. K. Jindal,R. K. Sharma 한국산학기술학회 2013 SmartCR Vol.3 No.6
Character recognition is intricate work because of the various writing styles of different individuals. Most of the published work on handwritten character recognition problems deals with statistical features, and a few works deal with structural features, in general, and Gurmukhi script, in particular. In the present work, we propose a methodology for offline handwritten Gurmukhi character recognition by using a modified division points (MDP) feature extraction technique. We also compare this technique with other recently used feature extraction techniques, namely zoning features, diagonal features, directional features, intersection and open end points features, and transition features. To select a representative set of features is the most significant task for a character recognition system. After feature extraction, the classification stage makes use of the features extracted in the previous stage to recognize the character. In this work, we used linear-support vector machines (linear-SVM), k-nearest neighbor (k-NN), and multilayer perceptron (MLP) classifiers for recognition. For experimental analysis, we used 10,500 samples of the isolated, offline, handwritten, basic 35 akhars of Gurmukhi script. The proposed system achieved a maximum recognition accuracy of 84.57%, 85.85% and 89.20% with linear-SVM, MLP and k-NN classifiers, respectively, with a five-fold cross validation technique.
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Munish Kumar Gupta,P. Niesłony,Mehmet Erdi Korkmaz,Mustafa Kuntoğlu,G. M. Królczyk,Mustafa Günay,Murat Sarikaya 한국정밀공학회 2023 International Journal of Precision Engineering and Vol.10 No.6
Cutting energy must be reduced in order to make machining processes more eco-friendly. More energy was expended for the same amount of material removed, hence a higher specific cutting energy (SCE) implies inefficient material removal. Usually, the type of coolants or lubricants affects the SCE, or the amount of energy needed to cut a given volume of material. Therefore, the present work deals with a study of SCE in the turning of Ti–3Al–2.5V alloy under green cooling strategies. In spite of this, the research effort is also focused on the mechanism of tool wear, surface roughness, and cutting temperature under hybrid cooling, i.e., minimum quantity lubrication (MQL) and cryogenic. The tool wear rate, were explored with tool mapping analysis, and the results were compared with dry, MQL, and liquid nitrogen (LN2) conditions. The tool wear rate analysis claims that the dry condition causes more built up edge (BUE) formation. In addition, the hybrid cooling conditions are helpful in reducing the SCE while machining titanium alloys.
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Munish Kumar Gupta,P. Niesłony,Murat Sarikaya,Mehmet Erdi Korkmaz,Mustafa Kuntoğlu,G. M. Królczyk 한국정밀공학회 2023 International Journal of Precision Engineering and Vol.10 No.4
The aerospace and automotive industries make extensive use of aluminium and its alloys. Contrarily, machining of aluminium (Al) alloys presents a number of difficulties, including, but not limited to, poor surface finishing, excessive tool wear, decreased productivity etc. Therefore, it’s very important to measure the machining characteristics during machining of aluminium alloy with sustainable cooling strategies. In this work, a new approach of measurement was adopted to measure the critical geometrical aspects of tool wear, surface roughness, power consumption and microhardness while machining AA2024-T351 alloy under dry, minimum quantity lubrication (MQL), liquid nitrogen (LN2) and carbon dioxide (CO2) cooling conditions. Initially, the various aspects of tool wear were studied with the help of Sensofar Confocal Microscope integrated with Mountains map software and then, the other results such as surface roughness, power consumption and microhardness were measured as per the ISO standards. The outcome of these measurement studies confirms that LN2 and CO2 cooling is helpful in improving the machining characteristics of AA2024-T351 alloy. When compared to dry conditions, the surface roughness values of MQL, LN2, and CO2 all have values that are lowered by 11.90%, 30.95%, and 39.28% respectively, and also power consumption values were lowered by 3.11%, 6.46% and 11.5% for MQL, CO2 and LN2 conditions, respectively.
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