GUAR GUM: A VERSATILE MATERIAL FOR PHARMACEUTICAL INDUSTRIES

Guar gum (GG) is galactomannan, derived from guar (cyamopsistetragonolobus) kernels which belong to family Leguminosae. The solution of guar gum in water has the highest viscosity amongst all the natural polysaccharide discovered till the date. Further it has better bio-degradability and bio-compatibility. Due to these properties, guar gum finds application in various industries like, Textile, Food, Petrochemical, Mining, Paper, Explosive etc. But due to uncontrollable rate of viscosity, uncontrollable rate of hydration, instability of its solution for a long time and susceptibility to microbial contamination restricts its use in pharmaceutical industries. To overcome these draw back guar gum should be chemically modified. Modified guar gum is widely used in pharmaceutical application due to its viscosity enhancing properties. Guar gum and derivatives are used as binders and disintegrate in tablet and also used as a control-released agent for the drug. In this review article we summarized different pharmaceutical applications of native guar gum and its derivatives

Does orthopaedic resident efficiency improve with respect to decreased fluoroscopic times in tibial intramedullary nailing? A measure of an ACGME milestone

Background: Intramedullary nailing of tibial fractures is a surgical milestone from the Accreditation Council for Graduate Medical Education (ACGME). Our purpose was to evaluate if fluoroscopic time decreased with increasing resident experience and could be used as a measure of this milestone. Methods: Current Procedural Terminology (CPT) codes were used to identify patients who underwent intramedullary nailing of tibial shaft fractures under the direction of fellowship-trained trauma attending staff. The data collected included patient demographics, fracture classification, fluoroscopic imaging total time, and the post-graduate years (PGY) of orthopaedic residency of the operating resident. Exclusions of patients included concomitant fluoroscopic procedures, inadequate records, or surgeries involving primary assisting residents with less than PGY-2 experience. We compared overall groups between half years and looked at individual resident years for each of the continuous variables. Results: When residents were grouped as senior (PGY-4 and PGY-5) or junior (PGY-2 and PGY-3), seniors used significantly less fluoroscopy than juniors (207.39 sec vs. 258.30 sec, P=0.018). In the first half of the academic year, PGY-2 residents completed tibial nailing slowest in terms of fluoroscopic usage (P=0.003). PGY-4 residents completed tibial nailing faster in terms of fluoroscopic usage than other years (P=0.031). In the second half of the academic year, PGY-5 residents used significantly less fluoroscopy than PGY-2 residents (P=0.035). Conclusions: As the ACGME currently has no measurement for resident progress and efficiency regarding tibial shaft intramedullary nailing, our data indicate that fluoroscopic measurements may be useful in assessing resident proficiency

Fault Diagnosis of Gearbox based on ITD-Tunable Q-Factor Wavelet Transform

223-228Gearboxes are an important part of the mechanical drives element that provides the several applications like automotive industry, wind turbine industry and power plant industry, etc. The condition monitoring of the gearbox reduces its operational cost, maintenance cost and avoid hazardous losses. The features selected for the health status of the gearbox has important parameter to calculate classification accuracy. In the current study the intrinsic time-scale decomposition (ITD) and tunable Q-factor wavelet transform (TQWT) are used to diagnose the faults in the gear. The ITD method decomposed the input signal into the baseline signal with instantaneous parameters of signal and sequence of the proper rotation components (PRCs). The PRC of higher kurtosis value is the input signal for TQWT. The TQWT is a discrete wavelet transform and decomposed the vibration signals of the gearbox into sub-bands. The feature vector is calculated for each sub-band of the TQWT. The proposed approach is analyzed by the classification accuracy of the feature vector. The recommended method is evaluated using experimental data of 2009 PHM Data of gearbox under various health conditions. The SVM and KNN methods are investigated that the improved classification accuracy with ITD-TQWT model are 97.9% and 96.9% respectively

Multi-Response Optimization of Abrasive Waterjet Machining of Ti6Al4V Using Integrated Approach of Utilized Heat Transfer Search Algorithm and RSM

Machining of Titanium alloys (Ti6Al4V) becomes more vital due to its essential role in biomedical, aerospace, and many other industries owing to the enhanced engineering properties. In the current study, a Box–Behnken design of the response surface methodology (RSM) was used to investigate the performance of the abrasive water jet machining (AWJM) of Ti6Al4V. For process parameter optimization, a systematic strategy combining RSM and a heat-transfer search (HTS) algorithm was investigated. The nozzle traverse speed (Tv), abrasive mass flow rate (Af), and stand-off distance (Sd) were selected as AWJM variables, whereas the material removal rate (MRR), surface roughness (SR), and kerf taper angle (θ) were considered as output responses. Statistical models were developed for the response, and Analysis of variance (ANOVA) was executed for determining the robustness of responses. The single objective optimization result yielded a maximum MRR of 0.2304 g/min (at Tv of 250 mm/min, Af of 500 g/min, and Sd of 1.5 mm), a minimum SR of 2.99 µm, and a minimum θ of 1.72 (both responses at Tv of 150 mm/min, Af of 500 g/min, and Sd of 1.5 mm). A multi-objective HTS algorithm was implemented, and Pareto optimal points were produced. 3D and 2D plots were plotted using Pareto optimal points, which highlighted the non-dominant feasible solutions. The effectiveness of the suggested model was proved in predicting and optimizing the AWJM variables. The surface morphology of the machined surfaces was investigated using the scanning electron microscope. The confirmation test was performed using optimized cutting parameters to validate the results

Fault Diagnosis of Gearbox based on ITD-Tunable Q-Factor Wavelet Transform

Gearboxes are an important part of the mechanical drives element that provides the several applications like automotive industry, wind turbine industry and power plant industry, etc. The condition monitoring of the gearbox reduces its operational cost, maintenance cost and avoid hazardous losses. The features selected forthe health status of the gearbox has important parameter to calculate classification accuracy. In the current study the intrinsic time-scale decomposition (ITD) and tunable Q-factor wavelet transform (TQWT) are used to diagnose the faults in the gear. The ITD method decomposed the input signal into the baseline signal with instantaneous parameters of signal and sequence of the proper rotation components (PRCs). The PRC of higher kurtosis value is the input signal for TQWT. The TQWT is a discrete wavelet transform and decomposed the vibration signals of the gearbox into sub-bands. The feature vector is calculated for each sub-band of the TQWT. The proposed approach is analyzed by the classification accuracy of the feature vector. The recommended method is evaluated using experimental data of 2009 PHM Data of gearbox under various health conditions. The SVM and KNN methods are investigated that the improved classification accuracy with ITD-TQWT model are 97.9% and 96.9% respectively

Ultrasound-triggered antibiotic release from PEEK clips to prevent spinal fusion infection: Initial evaluations.

Despite aggressive peri-operative antibiotic treatments, up to 10% of patients undergoing instrumented spinal surgery develop an infection. Like most implant-associated infections, spinal infections persist through colonization and biofilm formation on spinal instrumentation, which can include metal screws and rods for fixation and an intervertebral cage commonly comprised of polyether ether ketone (PEEK). We have designed a PEEK antibiotic reservoir that would clip to the metal fixation rod and that would achieve slow antibiotic release over several days, followed by a bolus release of antibiotics triggered by ultrasound (US) rupture of a reservoir membrane. We have found using human physiological fluid (synovial fluid), that higher levels (100–500 μg) of vancomycin are required to achieve a marked reduction in adherent bacteria vs. that seen in the common bacterial medium, trypticase soy broth. To achieve these levels of release, we applied a polylactic acid coating to a porous PEEK puck, which exhibited both slow and US-triggered release. This design was further refined to a one-hole or two-hole cylindrical PEEK reservoir that can clip onto a spinal rod for clinical use. Short-term release of high levels of antibiotic (340 ± 168 μg), followed by US-triggered release was measured (7420 ± 2992 μg at 48 h). These levels are sufficient to prevent adhesion of Staphylococcus aureus to implant materials. This study demonstrates the feasibility of an US-mediated antibiotic delivery device, which could be a potent weapon against spinal surgical site infection. Statement of Significance: Spinal surgical sites are prone to bacterial colonization, due to presence of instrumentation, long surgical times, and the surgical creation of a dead space (≥5 cm 3 ) that is filled with wound exudate. Accordingly, it is critical that new approaches are developed to prevent bacterial colonization of spinal implants, especially as neither bulk release systems nor controlled release systems are available for the spine. This new device uses non-invasive ultrasound (US) to trigger bulk release of supra-therapeutic doses of antibiotics from materials commonly used in existing surgical implants. Thus, our new delivery system satisfies this critical need to eradicate surviving bacteria, prevent resistance, and markedly lower spinal infection rates

Optimization of Activated Tungsten Inert Gas welding process parameters using heat transfer search algorithm: with experimental validation using case studies

The Activated Tungsten Inert Gas welding (A-TIG) technique is characterized by its capability to impart enhanced penetration in single pass welding. Weld bead shape achieved by A-TIG welding has a major part in deciding the final quality of the weld. Various machining variables influence the weld bead shape and hence an optimum combination of machining variables is of utmost importance. The current study has reported the optimization of machining variables of A-TIG welding technique by integrating Response Surface Methodology (RSM) with an innovative Heat Transfer Search (HTS) optimization algorithm, particularly for attaining full penetration in 6 mm thick carbon steels. Welding current, length of the arc and torch travel speed were selected as input process parameters, whereas penetration depth, depth-to-width ratio, heat input and width of the heat-affected zone were considered as output variables for the investigations. Using the experimental data, statistical models were generated for the response characteristics. Four different case studies, simulating the real-time fabrication problem, were considered and the optimization was carried out using HTS. Validation tests were also carried out for these case studies and 3D surface plots were generated to confirm the effectiveness of the HTS algorithm. It was found that the HTS algorithm effectively optimized the process parameters and negligible errors were observed when predicted and experimental values compared. HTS algorithm is a parameter-less optimization technique and hence it is easy to implement with higher effectiveness

Parametric Optimization and Effect of Nano-Graphene Mixed Dielectric Fluid on Performance of Wire Electrical Discharge Machining Process of Ni55.8Ti Shape Memory Alloy

In the current scenario of manufacturing competitiveness, it is a requirement that new technologies are implemented in order to overcome the challenges of achieving component accuracy, high quality, acceptable surface finish, an increase in the production rate, and enhanced product life with a reduced environmental impact. Along with these conventional challenges, the machining of newly developed smart materials, such as shape memory alloys, also require inputs of intelligent machining strategies. Wire electrical discharge machining (WEDM) is one of the non-traditional machining methods which is independent of the mechanical properties of the work sample and is best suited for machining nitinol shape memory alloys. Nano powder-mixed dielectric fluid for the WEDM process is one of the ways of improving the process capabilities. In the current study, Taguchi’s L16 orthogonal array was implemented to perform the experiments. Current, pulse-on time, pulse-off time, and nano-graphene powder concentration were selected as input process parameters, with material removal rate (MRR) and surface roughness (SR) as output machining characteristics for investigations. The heat transfer search (HTS) algorithm was implemented for obtaining optimal combinations of input parameters for MRR and SR. Single objective optimization showed a maximum MRR of 1.55 mm3/s, and minimum SR of 2.68 µm. The Pareto curve was generated which gives the optimal non-dominant solutions

Experimental Investigations of Using Aluminum Oxide (Al2O3) and Nano-Graphene Powder in the Electrical Discharge Machining of Titanium Alloy

In the present study, a comprehensive parametric analysis was carried out using the electrical discharge machining of Ti6Al4V, using pulse-on time, current, and pulse-off time as input factors with output measures of surface roughness and material removal rate. The present study also used two different nanopowders, namely alumina and nano-graphene, to analyze their effect on output measures and surface defects. All the experimental runs were performed using Taguchi’s array at three levels. Analysis of variance was employed to study the statistical significance. Empirical relations were generated through Minitab. The regression model term was observed to be significant for both the output responses, which suggested that the generated regressions were adequate. Among the input factors, pulse-off time and current were found to have a vital role in the change in material removal rate, while pulse-on time was observed as a vital input parameter. For surface quality, pulse-on time and pulse-off time were recognized to be influential parameters, while current was observed to be an insignificant factor. Teaching–learning-based optimization was used for the optimization of output responses. The influence of alumina and nano-graphene powder was investigated at optimal process parameters. The machining performance was significantly improved by using both powder-mixed electrical discharge machining as compared to the conventional method. Due to the higher conductivity of nano-graphene powder, it showed a larger improvement as compared to alumina powder. Lastly, scanning electron microscopy was operated to investigate the impact of alumina and graphene powder on surface morphology. The machined surface obtained for the conventional process depicted more surface defects than the powder-mixed process, which is key in aeronautical applications.This research received some help from the Basque government through University research groups, grant IT1573-22. Authors work in cooperation under a common agreement in the field of EDM