Excel Add-in Research Articles

Mastering meta-analysis in Microsoft Excel with MetaXL add-in: A comprehensive tutorial and guide to meta-analysis.

Meta-analysis, a powerful technique for combining effect estimates from multiple studies, enhances statistical power and precision. However, its adoption can be hindered by challenges in statistical interpretation and the complexity of specialized software. MetaXL, a freely available Microsoft Excel add-in, aims to mitigate these barriers by providing comprehensive support and facilitating seamless integration of meta-analytical results into research publications. This tutorial illustrates the practical application of MetaXL for synthesizing meta-analytical evidence, with a focus on common effect sizes and their presentation. This paper reintroduce MetaXL's functions and provide concise explanations of common effect sizes employed in meta-analysis. The tutorial delves into fundamental concepts such as the selection of appropriate effect sizes for pooling and the choice of meta-analytical models. Eight illustrative examples are presented, incorporating diverse effect sizes and data formats, including scenarios involving incidence rate ratios, weighted and standardized mean differences, hazard ratios, and prevalence. Additionally, key concepts in network meta-analysis are discussed, along with their implementation in MetaXL. MetaXL provides convenient access to data formatting templates tailored to various data types and effect sizes encountered in included studies. This tutorial offers researchers, particularly those with limited resources, detailed explanations and insights into commonly used methodologies for pooling effect sizes. Furthermore, it introduces the new Excel functions that comes with the MetaXL add-in. Accurate population of this function and adherence to the correct format are essential to ensure error-free analyzes.

DEVELOPMENT AND IN VIVO EVALUATION OF ABACAVIR SULPHATE MUCOADHESIVE BUCCAL FILMS

Objective: The objective of the study was to evaluate the pharmacokinetic parameters of abacavir sulphate mucoadhesive buccal films in vivo. Methods: Abacavir sulphate mucoadhesive buccal films were developed using the solvent casting method and the prepared buccal films were evaluated for qualitative and quantitative parameters. Pharmacokinetic parameters (maximum plasma concentration [Cmax], maximum plasma concentration [Tmax], area under the curve [AUC], and biological half-life [t1/2]) were evaluated in vivo using healthy albino white rabbits. The blood samples were collected evaluated and the results were compared with Ziagen a reference standard. The Modern Version 6 software and the pharmacokinetic function (Microsoft Excel add-in) applications were used to conduct the statistical study. Results: The abacavir sulphate mucoadhesive buccal films were prepared successfully and the evaluated qualitative and quantitative parameters were within in the acceptable range. The results of the study stated that Cmax, Tmax, AUC0-t, AUC0-α, and t1/2 of abacavir sulphate mucoadhesive buccal film were found to be 93.86 ng/ml, 8 h, 1652.21 ng/ml×h, 2939.76 ng/ml×h, and 17.96 h, respectively. These results were comparable with the reference standard. Conclusion: The overall absorption of abacavir sulphate was more in the test formulation with respect to the reference product at the same dose. Hence the study concludes that abacavir sulphate mucoadhesive buccal films achieved prolonged muchoadhesion and improved bioavailability compared to the conventional formulation.

OCEAN—An EXCEL add-in for 17O correction using a novel approximation

In this publication, an alternative mathematical approach for 17O correction is presented. It is shown comprehensively how the newly developed formulas are derived and what the differences are to the established algorithm recommended by Brand et al. Additionally, two simulations are presented, which demonstrate the performance (in terms of accuracy and precision) of the approach. Part of this work is an EXCEL Add-In, which allows users to perform 17O correction, normalization and uncertainty propagation on their own. This enables the users - who are limited to measure only the masses 44 to 46 - to fully control their data evaluation.•Improved accuracy over a wider range.•Easy use and implementation of the scheme.•Convenient uncertainty calculation in accordance with international standards.

Optimization of Domestic and Industrial Biodigestors Based on Machine Learning Techniques

Purpose: Development of an application for determining the technical and economic feasibility of implementing and operating domestic biodigesters using rigorous mathematical modeling of the anaerobic digestion process in conjunction with Machine Learning techniques to obtain reduced metamodels. Theoretical Framework: The generation of biodegradable waste results from human activities and has detrimental environmental impacts. To mitigate this problem, anaerobic digestion in biodigesters emerges as a viable solution, promoting the production of biogas and biofertilizers, generating economic and environmental benefits. However, implementing and operating this system requires significant investments. Method/Design/Approach: The combination of the ADM1 model with Machine Learning techniques is used to create simplified metamodels, allowing for more feasible simulations and optimizations, thereby developing an application to assess the technical and economic feasibility of biodigesters. This application is obtained by packaging the reduced metamodel using the MATLAB Compiler, which will be made available as an Excel add-in. Results and Conclusion: The reduced metamodel effectively represented the rigorous Simulink model, and the optimization of the process proved satisfactory. Furthermore, the add-in generated through the MATLAB Compiler met expectations. Research Implications: Enhanced understanding of the waste biodigestion process, demonstrating the economic and environmental returns achieved when focusing more on this area. Originality/Value: Development of a tool that enables the simulation and evaluation of a biodigestion process without the need to purchase expensive software.

Особенности накопления тяжелых металлов в некоторых представителях родов Iris L., Narcissus L., Paeonia L.

Abstract. In modern conditions, heavy metals (HM) are considered as the main soil pollutants. On the one hand, they are necessary for the normal course of physiological processes, and on the other hand, at elevated HM concentrations, they are toxic. In this regard, it is important to study the content of heavy metals in plant objects. The aim of our research was to study the accumulation and distribution of elements (As, Cd, Pb, Ni, Mn, Cu, Fe, Cr) in the aboveground and underground parts of ornamental herbaceous perennials of the genus Iris L., Paeonia L., Narcissus L. The objects of research were aboveground and underground organs of four species of the genus Iris L., eight varieties of the genus Narcissus, and seven taxa of the genus Paeonia. Methods. The study of the elemental composition of the aboveground and underground parts was carried out according to the method No. M-02-1009-05 of atomic spectroscopy. Mathematical data processing was carried out using the generally accepted methods of variation statistics using the AgCStat software package as an Excel add-in. Scientific novelty. For the first time, representatives of three different generic complexes were taken for the study. Results. Studies have shown that in the aerial part of most of the taxa studied, As accumulates in concentrations exceeding the maximum allowable concentrations. An excessive amount of Cr, Cu, Ni, Pb was noted in the aboveground part of some representatives of irises and peonies. The content of Cd, Fe, and Mn in all studied taxa is within acceptable limits. It was revealed that the indicators of the content of most elements are characterized by great variability, which is confirmed by the results of other researchers. It was noted that in irises in larger quantities than in other taxa, As, Cr, Mn, Ni accumulate in the aboveground part, and Cd, Cr, Fe, Mn, Ni in the underground part, therefore, they can be recommended for use in landscaping urban areas.

Influence of Electrospun Fibre Secondary Morphology on Antibiotic Release Kinetic and Its Impact on Antimicrobic Efficacy.

Vascular graft infections are a severe complication in vascular surgery, with a high morbidity and mortality. Prevention and treatment involve the use of antibiotic- or antiseptic-impregnated artificial vascular grafts, but currently, there are no commercially available infection-proof small-diameter vascular grafts (SDVGs). In this work we investigated the antimicrobic activity of two SDVGs prototypes loaded with tobramycin and produced via the electrospinning of drug-doped PLGA (polylactide-co-glycolide) solutions. Differences in rheological and conductivity properties of the polymer solutions resulted in non-identical fibre morphology that deeply influenced the hydration profile and consequently the in vitro cumulative drug release, which was investigated by using a spectrofluorimetric technique. Using DDSolver Excel add-in, modelling of the drug release kinetic was performed to evaluate the release mechanism involved: Prototype 1 showed a sustained and diffusive driven drug release, which allowed for the complete elution of tobramycin within 2 weeks, whereas Prototype 2 resulted in a more extended drug release controlled by both diffusion and matrix relaxation. Time-kill assays performed on S. aureus and E. coli highlighted the influence of burst drug release on the decay rate of bacterial populations, with Prototype 1 being more efficient on both microorganisms. Nevertheless, both prototypes showed good antimicrobic activity over the 5 days of in vitro testing.

Consumer sentiment toward international activist advertising

Companies have been increasingly conveying activist advertising messages to international audiences in response to persisting social ills and unsustainable business practices. Given the ambiguity surrounding the effects of international advertising, this study aims to compare the response of local consumers to a multinational brand’s standardized activist advertising strategy with creative executions adapted to the national contexts of Greece and the USA. The selected brand originates from the USA. The paper used a systematic qualitative approach and sentiment analysis using Microsoft Excel and Azure Machine Learning add-in. Analysis conducted on 1,051 user comments in January 2023 regarding two publicly accessible social media posts of a multinational haircare brand showed both similarities and differences in consumer responses. 662 comments were in English and 389 comments were in Greek. The study’s dataset was anonymized entirely and de-identified. The results indicate that consumer sentiment was largely negative in both countries. Although the relative share of negative comments was significantly higher in the USA (96.7%) than in Greece (59.4%), both groups of consumers placed their emphasis on the same themes (e.g., children and products). Therefore, they have perceived the main message similarly, irrespective of the execution differences. Overall, the findings can be attributed to strategic and tactical issues of the activist advertising campaign, as well as to sociocultural particularities of the national context. In the case of international advertising, attempts to incorporate the brand’s stance on a controversial sociopolitical issue into its advertising strategy pose significant risks to business organizations.

Defining a Relationship Between Postoperative Antibiotic Use and Wound Complications in the Setting of an Uncomplicated Laparoscopic Appendectomy.

Appendicitis is a very common diagnosis that surgeons manage daily. Some surgeons are still giving antibiotics to patients suffering from uncomplicated appendicitis in the postoperative setting, despite an abundance of evidence to support a single preoperative dose of antibiotics.In this paper, we will describe the management of post-operative antibiotics at our institutions following uncomplicated appendicitis with regard to the use of antibiotics in the post-operative setting. A retrospective chart review was performed analyzing post-operative antibiotic use and postoperative complications in 179 patients undergoing laparoscopic appendectomy for uncomplicated appendicitis. We retrospectively examined the patients to change our future practices as we perform appendectomies routinely, and there is practice variation at our centers. Current Procedural Terminology (CPT) codes for 'laparoscopic appendectomy' were used to identify the patients within our inclusion criteria. Twenty-four patients were excluded from the analysis as they had complicated appendicitis or met other exclusion criteria. We only studied the patient with uncomplicated appendicitis, as those with complicated appendicitis have a different clinical course that involves post-operative antibiotic administration or prolonged antibiotic administration with or without drain placement. Both arms of the study were homogeneous regarding patient characteristics. An independent test of the development of wound infection for those patients receiving post-operative antibiotics versus those not receiving post-operative antibiotics was conducted using the SPC XL 2010 Microsoft Excel (Redmond, USA) add-in. A p-value of <0.05 was considered statistically significant. This included the odds ratio for the development of complications. Results: There was no difference in the risk of infection rate in patients given post-operative antibiotics; however, given the odds ratio of 6.53, there is an association between an increased wound infection rate and patients who received post-operative antibiotics. Discussion: An appendectomy is a standard surgical procedure for acute appendicitis. The guidelines for using pre-operative antibiotics in uncomplicated appendicitis are well established; however, there is no specific recommendation on whether to continue antibiotics post-operatively. However, there is significant provider variability on this topic. Antibiotic use post-operatively in clean-contaminated cases, such as uncomplicated acute appendicitis, has been associated with higher risks of surgical site infections. Conclusion: The use of antibiotics post-operatively may not be indicated for uncomplicated laparoscopic appendectomy and may increase wound infections. A large-scale study including a larger population and extending it to other hospitals may increase statistical significance and help guide physician management.

PENENTUAN TINGKAT RESIKO KEBAKARAN HUTAN DAN LAHAN MENGGUNAKAN METODE INDEKS CUACA KEBAKARAN (FIRE WEATHER INDEX) DAN JUMLAH TITIK PANAS (HOTSPOT) DI KABUPATEN BANJAR PROVINSI KALIMANTAN SELATAN

Various indicators of hotspot occurrence as a cause of forest and land fires (karhutla) in Banjar District are still difficult to determine due to limited information. The analysis of FFMC (Fine Fuel Moisture Code) and DC (Drought Code) as well as the monitoring of the number of hotspots aims to determine the level of risk of forest and land fire hazards and can be an early picture of future forest and land fire disasters in the Banjar District of South Kalimantan Province. The data processing process to obtain the FFMC and DC values and their relationship with the number of hotspots is to calculate the FFMC and DC values of station observations and model observations through the Microsoft Excel Add-In (FWI Add-in) program. The two models will then be verified with a scatter plot and through the Pearson correlation test the relationship between the FFMC and DC of the ERA5 model and the number of hotspots can be found. As a result, the FFMC and DC (station observation and model) showed extreme risk levels for the 2014, 2015 and 2018 forest and land fires. Both models show a positive and linear relationship on the scatter plot. And in the Pearson correlation test, both variables between the FFMC and DC of the ERA5 model and the number of hotspots are moderately to strongly correlated. This condition indicates that an increase in the risk level of forest and land fires will be followed by a significant increase in the incidence of forest and land fires in the Banjar Regency area of South Kalimantan Province.

Development and Validation of Innovative Machine Learning Models for Predicting Date Palm Mite Infestation on Fruits

The date palm mite (DPM), Oligonychus afrasiaticus (McGregor), is a key pest of unripe date fruits. The detection of this mite depends largely on the visual observations of the webs it produces on the green fruits. One of the most important problems of DPM control is the lack of an accurate decision-making approach for monitoring and predicting infestation on date fruits. Therefore, this study aimed to develop, evaluate, and validate prediction models for DPM infestation on fruits based on meteorological variables (temperature, relative humidity, wind speed, and solar radiation) and the physicochemical properties of date fruits (weight, firmness, moisture content, total soluble solids, total sugar, and tannin content) using two machine learning (ML) algorithms, i.e., linear regression (LR) and decision forest regression (DFR). The meteorological variables data in the study area were acquired using an IoT-based weather station. The physicochemical properties of two popular date palm cultivars, i.e., Khalas and Barhee, were analyzed at different fruit development stages. The development and performance of the LR and DFR prediction models were implemented using Microsoft Azure ML. The evaluation of the developed models indicated that the DFR was more accurate than the LR model in predicting the DPM based on the input variables, i.e., meteorological variables (R2 = 0.842), physicochemical properties variables (R2 = 0.895), and the combination of both meteorological and the physicochemical properties variables (R2 = 0.921). Accordingly, the developed DFR model was deployed as a fully functional prediction web service into the Azure cloud platform and the Excel add-ins. The validation of the deployed DFR model showed that it was able to predict the DPM count on date palm fruits based on the combination of meteorological and physicochemical properties variables (R2 = 0.918). The deployed DFR model by the web service of Azure Ml studio enhanced the prediction of the DPM count on the date fruits as a fast and easy-to-use approach. These findings demonstrated that the DFR model using Azure Ml Studio integrated into the Azure platform can be a powerful tool in integrated DPM management.

Rex: R-linked EXcel add-in for statistical analysis of medical and bioinformatics data.

Microsoft Excel has substantial functionalities for data management and analyses, and has been the most popular software in this field. However, in spite of Excel's user-friendly interface and functionality for data management, it provides very few functions for in-depth statistical analyses, which has limited its wider application for this purpose. Here, we introduce Rex, an Excel add-in software implementing the powerful analytical and graphical functions of R within Excel. Rex was implemented using three types of programming software: R, JavaScript, and Microsoft VB.Net. Rex provides a graphical user interface (GUI) through Excel, and statistical analysis can be conducted by pointing and clicking the menu without programming R. Rex covers a wide range of analyses from basic statistics to advanced analysis, including structural equation modeling, complex sampling design, and machine learning models, making it possible for researchers not skilled in using a command-line interface to conduct in-depth statistical analyses. Most Rex modules are available in a free version for non-commercial use, and it can be used for educational and public purposes. In this article, we introduce the framework and features of Rex with illustrative examples of its implementation.

Statistically Optimized Facile Development, Characterization and Evaluation of Niosomal Nasal Drug Delivery System of Ropinirole Hydrochloride: In vitro Drug Release, Cytotoxicity and ex vivo Permeability Studies

Abstract: Introduction: Nasal route is an alluring route for direct drug delivery to the central nervous system (CNS), owing to its avoidance of the hepatic first-pass metabolism and deciphering the blood–brain barrier passage issues. ROP-HCl has a lower experimental BBB permeability therefore ROP-HCl freighted niosomes were fabricated by ethanol injection method and served two purposes one being a novel Niosomal formulation impacting the permeability and other obtaining a sustained release property which likely would lead to an improved bioavailability of ROP-HCl. Objectives: The present study is aimed to develop a stable non-ionic surfactant vesicle; Niosomes embodying Ropinarole Hydrochloride (ROP-HCl) for ameliorated treatment of Parkinson’s disease (PD) by statistical optimization employing a 3-level factorial design using Design Expert® software. Materials and Methods: All the formulations were characterized physiochemically and morphologically. Additionally, the drug and excipients interaction studies were evaluated using Differential scanning calorimetry (DSC), X-ray diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR). Further, in vitro release kinetics using DD solver excel add-in and mechanism was studied for developed Niosomal formulation. Cytotoxicity study was studied in Raw 264.7 cells. in a concentration dependent manner and ex vivo, permeability was done using sheep mucosa. Toxicity was studied by histological examination. Results: The IC50 value of developed Niosomes was lower than drug itself and further the permeability of developed Niosomes was considerably enhanced compared to ROP-HCl alone. Histological examination revealed safe nature of developed formulation. Conclusion: These results conveyed that, Niosomes can be a valuable carrier for the nasal delivery of ROP-HCl to CNS. Keywords: Ropinirole hydrochloride, Statistical approach, Niosomes, Nasal drug delivery, cytotoxicity, Release kinetics, Ex-vivo permeability, Toxicity study.

"SEARCH FOR SOLUTIONS" IN THE PROBLEMS OF CALCULATION OF BUILDING STRUCTURES

Building structures are very diverse in their purpose and application. The reliability and safety of their operation depends on many factors: geometric dimensions, materials used, acting external loads and their combinations, etc. All these parameters determine the internal forces, stresses and strains that arise in structures, which determine their strength, rigidity and stability. In order to ensure the strength, rigidity and stability of buildings and their structural elements, appropriate calculations are performed. In the field of the theory of calculation of building structures, there is a constant refinement of the actual work of these structures, i.e. such design schemes are created that most accurately correspond to the actual operating conditions. The more optimally the design scheme is drawn up, the less time-consuming will be the stages of calculation and design of the corresponding structure. Therefore, the solution of the problem of optimization of design schemes is of great scientific and practical importance. One of the existing approaches to finding optimal solutions is discussed in the course "Operations Research". Operations Research deals with the development and application of methods for finding optimal solutions based on mathematical modeling. The operation model is an analytical dependence of the objective function on dependent (controlled) variables, which, within certain limits, we can choose at our discretion and set the range of their change. Solver is a Microsoft Excel add-in that can be used in Structural Analysis problems. With its help, you can find the optimal value (maximum or minimum) of the formula contained in one cell, called the target, taking into account restrictions on variable values in other cells. Simply put, with the Solver add-in, you can determine the maximum or minimum value of one cell by changing other cells. Most often, the add-on "Search for a solution" is used in solving optimization problems of the economy (simplex method, transport problem, etc. There are practically no results of using this approach in the calculations of building structures.

Development of mathematical model for predicting methane-to-carbon dioxide proportion in anaerobic biodegradability of cattle blood and rumen content

• Prediction of methane-to-carbon dioxide within mesophilic range. • Production of methane for use as renewable energy source. • Optimal methane-to-carbon dioxide ratio in relation to temperature and hydraulic retention time. The potential of methane yield depends on the composition of feedstock which is characterized by a diversity of biodegradable fractions. This study aims at constructing and using the novel kinetic model as a tool to predict methane-to-carbon dioxide ratio from slaughterhouse solid waste using hydraulic retention time and temperature as parameters. The slurries prepared were composed of cattle blood, rumen content and requisite nutrient solution which were fed into a continuously stirred tank reactors. The process was monitored at regular intervals of 3 days for a retention time of 54 days for thermostatically controlled temperatures of 35, 37 and 40 °C. The percentage methane and carbon dioxide gas concentrations in the headspace were measured. The phenomenon was idealized with scatter plots and co-efficient of determination used to establish a reasonable correlation between the identified parameters. In this study, simple, robust and reliable kinetic models have been developed using the Microsoft Excel Add-in Solver Tool with the Generalized Reduced Gradient. The optimum solution of seven unknown constants represented by adjusted values where simulated values adequately matched the observed values for the three zones of this study. Validation of the models also showed that the phenomenon can be produced in a continuum at any fixed temperature.

Development and examination of a cracker enriched with dietary fiber

Relevance. On the one hand, the lack of physiologically important nutrients in the diet has led to the need to develop enriched foods. On the other hand, the food industry generates a large amount of waste rich in various functional ingredients. Biscuits, and especially crackers, are widespread foodamong young people, for whom a healthy diet is of the utmost importance. In this regard, the development of these products with the added of dietary fibers obtained from plant by-products is relevant. Methods.The object of the study is a cracker enriched with dietary fiber concentrate obtained by banana peel fermentation. The concentrate of dietary fiber was obtained under laboratory conditions; its physicochemical indicators were studied according to standard methods. Cracker recipes with the addition of the concentrate into the composition were modeled, samples of biscuits were made according to optimized recipes.Results. Dietary fiber concentrate was obtained after banana peel fermentation. Its physico-chemical indicators were determined: protein content — 3.0%, fat — 0.2%, carbohydrates — 21.0%, dietary fiber — 60.4%. Cracker recipes with 4 g fiber per 100 g of product were modeled using the “Solver (“Excel) addin to provide 20% of the daily value consumption. According to the obtained recipes, cracker samples were made in laboratory conditions. Their sensory and physico-chemical indicators were determined. The obtained results showed that variants No. 1 and No. 2 are the most optimal options for cracker recipes that comply with GOST 14033-2015. Samplemade according to variant of recipe No. 3 does not comply with the normative documentation on the mass fraction of moisture. Thus, on the basis of a banana peel, it is possible to obtain a concentrate of dietary fiber, which effectively enriches food products with dietary fiber. With the addition of dietary fiber concentrate into the composition of the cracker, a product that is acceptable in terms of sensory indicators and beneficial to health is obtained.

On the Combination of Harmonics and Polynoms in Econometric Modeling of RUB/AZN Exchange Rate

Conducting a combinational polynomial and spectral analysis of time series formed on the basis of daily observations of changes in the RUB/AZN exchange rate with pronounced fluctuations for the period 11.05.2017- 02.11.2018 based on computer econometric modeling.The purpose of the research. The possibility of describing the global rate dynamics by approximation with a combination of a nonlinear polynomial trend and harmonic oscillations of various frequencies relative to this curve; the ability to calculate amplitudes and phases, which can be used to estimate the power spectrum of the Fourier approximation; the ability to develop a high-precision algorithm for predicting exchange rate changes in RUB/AZN.Materials and methodology. The official statistics of the State Statistics Committee of Azerbaijan were used; classical methods of mathematical analysis and economic analysis; methods of econometrics, harmonic (Fourier) analysis, statistical spectral analysis, “Fourier analysis” of the MS Excel add-in, tools of the Eviews 8 application package with the standard deviation and average approximation error being taken into account, the necessary statistical procedures required for identifying and estimating the parameters of the model and checking its adequacy and accuracy.Results. By breaking up the empirical analysis of given time series into time-scale polynomial and time-frequency components. Combinations of the optimal degree of variants of polynomials up to the 11th degree and the number of harmonics of sines and cosines of all possible discrete frequencies were revealed.Conclusion. This result allows us to reconsider the asymmetric impact of RUB/AZN exchange rate pressure on the foreign trade balance between Russia and Azerbaijan. An increase/decrease in exchange rate pressure affects the likelihood of a ruble-manat crisis, while this phenomenon may negatively/positively affect the foreign trade balance and may make it difficult/easier to import resources, goods and services between countries. This, in turn, adds significance to the task of further detailed structuring and analysis of exchange rate changes in RUB/AZN in the face of increased sanction pressures against Russia, thereby actualizing the development of the retrospective part of the study.

LinkingPark: An automatic semantic table interpretation system

In this paper, we present LinkingPark, an automatic semantic annotation system for tabular data to knowledge graph matching. LinkingPark is designed as a modular framework which can handle Cell-Entity Annotation (CEA), Column-Type Annotation (CTA), and Columns-Property Annotation (CPA) altogether. It is built upon our previous SemTab 2020 system, which won the 2nd prize among 28 different teams after four rounds of evaluations. Moreover, the system is unsupervised, stand-alone, and flexible for multilingual support. Its backend offers an efficient RESTful API for programmatic access, as well as an Excel Add-in for ease of use. Users can interact with LinkingPark in near real-time, further demonstrating its efficiency.

A Study of Educational Technology Startups in India

Background: EdTech startups are shaping the Indian education industry with the aim of making education truly interesting. The covid-19 pandemic has affected all businesses except EdTech sector. EdTech industry is among those sectors that has observed rapid growth during covid-19. EdTech startups has witnessed a flood of users, funding, and stakeholders like never before. All these reasons make EdTech an interesting topic to study. In order to know EdTech, this study makes an attempt to carry out sentiment analysis of customer reviews on apps of leading educational technology (EdTech) startups. Purpose: The objective of this paper is to study the sentiments of people towards different EdTech startups in India. The objective is achieved by conducting sentiment analysis of app reviews of three leading EdTech startups operating in India. Methods: The study uses qualitative research where descriptive research design is used. Data is collected in the form of consumer app reviews from google play store. Reviews were taken for last six months. Total sample of 750 reviews were taken in the study which include 300 reviews for Byju’s learning app, 220 reviews for Unacademy and 230 reviews for Physicswallah. Purposive sampling is applied in this study. Sentiment analysis techniques is applied with the help of Azure Machine Learning MS Excel add-in. Results: The results of the study suggest that majority of users have negative sentiments towards Physicswallah app, Byju’s learning app, and Unacademy learner app. Conclusions: The results of this study would be useful to predict people sentiment about Edtech startups apps. The findings of this study give information to management of Edtech startups about positive or negative opinions of their application users so that they can develop strategies exclusively. Further research can include greater number of reviews and also consider demographic data of the reviewers.

Comparison of the Use of Kinetic Model Plots and DD Solver Software to Evaluate the Drug Release from Griseofulvin Tablets

Awareness of the release kinetics of active drugs is important in formulating drugs that have the desired delivery and in predicting the behaviour of the formulated drug in vivo. The study aims to determine the mechanism of drug release from griseofulvin tablets formulated with different surfactants using mathematical models and to compare the use of graphs and DD solver software in fitting dissolution profiles to kinetic models. The batches P1 -P3 were composed of the surfactant - PEG 4000 in different concentrations. A control batch without surfactant and a commercial brand (Mycoxyl 500) were used for comparison. Granule and tablet quality tests indicated quality formulations. Dissolution profiles showed that the surfactant improved drug release of griseofulvin and batches (batches P1 -P3) formulated with PEG 4000 had the best release profiles comparable with the commercial brand. The Excel Add-in DD solver and kinetic plots were used to determine the kinetic model of best fit. The Higuchi model was the best fit for batches P1 -P3. The first order and Hixon -Crowell also fit batches P2 and P3. The Korsmeyer’s model showed that batches P1 -P3 exhibited anomalous diffusion. The tablets formulated with PEG were as good as the commercial brand and they had an anomalous diffusion of the drug from the tablet; meaning that drug diffused following Fickian law and also diffused through a swollen and porous matrix. Kinetic plots and the DD solver can be used for fitting dissolution profiles to kinetic models.&#x0D; Keywords: Griseofulvin, Kinetics, Models, Surfactants, Polyethylene glycol (PEG) 4000, DD solver, Dissolution profile, mathematical models

Development and Stability Analysis of a Self-propelled High Clearance Multi-utility Vehicle

A self-propelled hydraulically actuated vehicle was developed for field crops of up to 2.0 m in height to carry out different operations like spraying, weeding, harvesting. The vehicle has provision for variable/adjustable ground clearance and track width to suit different spacing and heights of horticultural crops. Gradability, torque, and power required for the vehicle were calculated based on the dimensions of the selected bias ply traction tyre. The centre of gravity of the vehicle was calculated by the weight moment method. Microsoft Excel add-in was used to create a point manipulation programme, and the positions of the standard components were determined through an iterative process. The static load over the rear wheel and front wheel was kept at 60% and 40%, respectively, for design purposes. Analysis of chassis mechanics was done to find out weight transfer and impending stability on level ground as well as longitudinal and lateral slope. In longitudinal slope, the developed vehicle was found to be stable up to 45.19° and 20.68° under static and dynamic conditions, respectively; whereas in lateral slope, the vehicle was stable up to 39.08° and 22.10° under static and dynamic conditions, respectively. The developed vehicle was tested for weeding and spraying of okra and maize crops with an average height of 1.1 m to 1.5 m. The field capacity for the spraying and weeding operations was 1.9 ha.h-1 and 0.16 ha.h-1, respectively. The cost of operation for spraying and weeding was 400 ?.ha-1 and 1,500 ?.ha-1, respectively. Weeding efficiency and plant damage of the weeder were 92.58% and 1.55%, respectively.