Miracle-dz/UniFAR-FTUs huggingface dataset:
New Stability Indicating Method for Quantification of Impurities in Amlodipine and Atorvastatin calcium Tablets by Validated HPLC

A stability indicating LC method was developed for the simultaneous determination of Amlodipine and Atorvastatin calcium in pharmaceutical dosage form. Efficient chromatographic separation was achieved on X-Select CSH, C18 4.6 x 150 mm, 3.5 µ or Equivalent stationary phase with simple combination of a mobile phase containing Buffer : Acetonitrile : Tetrahydrofuran (575 : 400 : 25, v/v/v)with pH 3.00 ± 0.05 using Ortho-Phosphoric Acid + 2 g of 1-Octane Sulfonic Acid Sodium Salt delivered in an Isocratic mode and quantification was carried out using UV detection at 246 nm at a flow rate of 1.0 mL min -1 with injection volume of 20 μl and ambient column temperature. This method is capable to detect both the drug components of Amlodipine and Atorvastatin calcium in presence of their degradation products (Amlodipine Imp-A and Atorvastatin Impurity-D, F, G and H) with detection level of 0.05 %. Amlodipine / Atorvastatin calcium in their combination drug product were exposed to thermal, photolytic, hydrolytic and oxidative stress conditions, and the samples were analyzed. Peak homogeneity data of Amlodipine and Atorvastatin calcium is obtained using PDA detector, in the stressed sample chromatograms, demonstrating the specificity. The method shows excellent linearity over a range of 0.05-2.0% for Amlodipine, Amlodipine Impurity-A and 0.05-1.5 % for Atorvastatin calcium and Atorvastatin calcium Impurity-D,F,G and H. The correlation coefficient for Amlodipine and Atorvastatin calcium is 1. The relative standard deviation (RSD) was always less than 2%. The proposed method was found to be suitable and accurate for quantitative determination and the stability study of Amlodipine and Atorvastatin calcium in pharmaceutical preparations. The developed HPLC method was validated with respect to linearity, range, accuracy, precision and robustness.
ANFIS Based Speed Control for Sensor Less BLDC Motor

Owing to its good torque to inertia ratio, less electromagnetic interference problems (EMI), good efficiency and roughness, the Brushless Direct Current (BLDC) motor finds broader applications. It is ideally suited to super fans, electric and hybrid cars, such as industrial robot actuators, extruder drive motors, and machine tools and home appliances for computer numerical control (CNC) drive. Various speed control strategies were implemented. Existing system uses fuzzy controller logic to control the speed. The proposed system aims in regulating the speed of sensor less BLDC fed with 4 switches 3 phase inverter. The proposed controller is ANFIS. The proposed system is estimated with less cost as it is working with no sensor and a smaller number of solid-state switches. Here, we are implementing back emf difference zero cross approximation technique and hence filter design is made easier. The MATLAB simulation was done and the prototype is developed in the laboratory. A comparison has been done between conventional fuzzy controller and ANFIS controller for the speed response characteristics. The experimental results were specified to bear out the uniqueness of the circuit and regulation of speed using ANFIS is better when compared with fuzzy.
Arduino based platform for process control learning

This work deals with implementation of an experimental flowrate control unit using free and low-cost hardware and software. The open-source software Processing was used to develop the source codes and user graphical interface and the open-source electronic prototyping platform Arduino was used to acquire data from an experimental unit. Work presents descriptions of the experimental setup, the real-time PID controllers used and theoretical/conceptual issues of Arduino. PID controllers based on internal model control, minimization of the integral of time-weighted absolute error, Ziegler-Nichols, and others were tuned for setpoint and load changes and real-time runs were carried out in order to make real-time use of control theory learned in academy. Results showed the developed platform proved to be suitable for use in experimental setups allowing users compare their ideas and expectations with the experimental evidence in a real and low-cost fashion. In addition, the instrumentation is simple to configure with acceptable level noise and particularly useful for control/automation learning with educational purposes.
Evaluation of Cholesterol and c-Reactive Protein as Prognostic Factors for Survival in Critically Ill Patients

The aims of the study were to evaluate serum total cholesterol and serum C-reactive protein as a prognostic factor for survival in critical ill patients . The study population consisted of 50 patients (age range, 18-90 years; median, 55 years; men/women ratio, 2:3) in critical ill patients . Patients' serum levels of total cholesterol and Creactive protein were measured upon admission to citical care unit, three days later, and on the day discharge from ICU. Total cholesterol levels were significantly lower among the non-surviving patients (day 0,1 15 .4 ± 29.66 mg/dL; day 3,113.2 ± 37.19 mg/dL; day of discharge,104.0 ±42.96 mg/dL) than surviving patients (day 0,142.5 ± 23.93 mg/dL [P = 0.001]; day 3 ,145.5 ± 28.17 mg/dL [P = 0.001]; day of discharge 147.5 ± 35.97 mg/dL [P = 0.001]). C-reactive protein levels were significantly higher among the non-survivors (day 0,136.8 18.77 mg/dL; day 3,155.1 ± 18.94 mg/dL; day of discharge178.5 ± 22.30 mg/dL) than survivors (day 0,68.85 ±19.73 mg/dL[P = 0.001]; day 3,63.08 ± 18.05 mg/dL[P = 0.001]; day of discharge,52.98 ± 14.25 mg/dL;[P = 0.001]). Serum cholesterol and C-reactive protein can be used as markers for predicting survival in critical ill patients . Low cholesterol and high C-reactive protein levels appear as a valuable tool for individual risk assessment in critical ill patient.
Towards Autonomous Intralogistics: A Testbed Environment for the Coordination of a Robotic Fleet

In this paper we present a testbed implementation, in which a production plant for airplane wings is simulated. The simulated environment can be used for the evaluation of different approaches to multi-agent task allocation and path ﬁnding. We outline the relation to the relevant problems of job-shop scheduling and multi-agent path ﬁnding and describe our approach towards a system architecture and a baseline implementation of the required software components for a multi-agent system to tackle these challenges. Our approach facilitates a centralized database where the state of the production environment is consolidated (a so called ”digital twin”), a high-level planner that continuously dispatches the available agents to tasks, and a multi-agent simulation to simulate the task execution. In general our sys-tem is designed in a modular fashion, which allows the developer to extend or replace the distinct components easily. The modular design also makes it possible to factor out the multi-robot simulation in favor of a real-world test environment with actual robotic agents. We describe the relevant parameters that are tracked about the environment, the design of the planner, and the interactions between the planner and the agents, that are executing the plans autonomously. We present ﬁrst experiments conducted within this environment as a starting point for a series of runs of experimentation.
Reference Detection for Off-road Self-Driving Vehicles Using Deep Learning

—This paper proposes the application of deep neural network models to detect references in off-road driving for autonomous vehicles. Due to the absence of trafﬁc signs in non-urban areas, the work searched for a low-cost sensory-based solution for autonomous localization in this environment. Given the advancement of Machine Learning techniques, we used Object Detection algorithms to solve the localization problem. For this reason, we trained three existing object detection models (Fast YOLOv2, SSD300 and Faster R-CNN) to detect a reference at the road boundary. The project analyzed these three architectures performance after training with a small dataset (around 300 images), regarding the detection distance, the number of detection and image processing time. Through two experiments, one in the same environment as the training step and another with a different background, we evaluate the pros and cons of each model and the possible application scenario for each one in autonomous cars.
Efficiency of Opuntia ficus-indica (L) Mill. in Removal of Chromium from Synthetic Solution.

Chromium is one of the pollutants in waste waters and many methods are being used to purify the water including natural coagulants of plant origin. Prickly pear mucilage is reported as a natural coagulant and it has been used as water purifier since ancient times. The present study was undertaken to determine the efficiency of prickly pear mucilage in removal of chromium from waste water. Synthetic chromium solution was prepared by using potassium dichromate (K2Cr2O7) solution. A standard graph was prepared using different concentrations of chromium (4, 8, 12, 16, and 20µg/ml). Chromium was analyzed by spectophotometric method at 540 nm. Prickly pear mucilage was prepared by boiling 20 g of nopal pads in 150 ml of distilled water for 90 min and filtering the residues. The filtrate was tested for chromium removal. To test the efficiency of prickly pear mucilage in removal of chromium, four parameters i.e., mucilage concentration, time, temperature and agitation speed were optimized. The results showed that 1ml of mucilage for120 min of incubation at 30 0 C temperature and 150 rpm are optimal for higher removal i.e., approximately 98.75% of chromium. It is concluded that prickly pear mucilage is having the potential to reduce chromium concentration in synthetic waste water. Hence, it may be used as a low
Stability Indicating Reverse Phase-HPLC Method for the Estimation of Doxorubicin in

The current research goal was to develop a novel specific method for the quantitation of the Doxorubicin. The method development was done by using a HighPerformance Liquid Chromatography (HPLC). The extensive method development was conducted to identify a right combination of chromatographic conditions and validated as per the regulatory guidelines. The current method overcome the disadvantages of complex sample preparation, long runtime and improved peak shape. The simple combination of organic modifier and buffer (40:60) used to elute the Doxorubicin in isocratic mode. The shorter run time of the method was achieved by optimizing the flow rate of 0.8mL per minute along with L1-octadecyl chemistry column. The doxorubicin peak was detected by using a sensitive Ultra violet detector at 254nm. The method was completely wetted with all the key validation parameters likewise suitability, precision, selectivity, linearity, robustness and recovery. The purity threshold of more than 990 proves that the method is free from any possible interferences and the linearity was established at 5 different levels with a correlation coefficient 0.999. The overall %RSD (relative standard deviation) of mean recovery was 1.1%. The marketed commercial formulation of Doxorubicin injection was tested on the developed method to confirm the suitability of the method for both bulk active substance and pharmaceutical formulations. Based on the experimental outcome method can be regarded as inventive, short run time, specific to quantitate Doxorubicin.
pseu-Real-time Shape Manipulation using Defor mable Cur ve-Skeleton

Variational methods, which cast deformation as an energy-minimization problem, are known to provide a good trade-off between practicality and speed. However, the time required to deform a fully detailed shape means that these methods are largely unsuitable for real-time applications. We simplify a 2D shape into a curve skeleton, which can be deformed much more rapidly than the original shape. The curve skeleton also provides a simplified control for the user, utilizing a small number of control handles. Our system deforms the curve skeleton using an energy-minimization method and then applies the resulting deformation to the original shape using linear blend skinning. This approach effectively reduces the size of the variational optimization problem while producing deformations of a similar quality to those obtained from full-scale nonlinear variational methods
A new acoustic assumption for orthorhombic media1

In exploration seismology, the acquisition, processing and inversion of P-wave data is a routine. However, in orthorhombic anisotropic media, the governing equations that describe the P-wave propagation are coupled with two S waves that are considered as redundant noise. The main approach to free the P-wave signal from the S-wave noise is the acoustic assumption on the wave propagation. The conventional acoustic assumption for orthorhombic media zeros out the S-wave velocities along three orthogonal axes, but leaves significant S-wave artefacts in all other directions. The new acoustic assumption that we propose mitigates the S-wave artefacts by zeroing out their velocities along the three orthogonal symmetry planes of orthorhombic media. Similar to the conventional approach, our method reduces the number of required model parameters from nine to six. As numerical experiments on multiple orthorhombic models show, the accuracy of the new acoustic assumption also compares well to the conventional approach. On the other hand, while the conventional acoustic assumption simplifies the governing equations, the new acoustic assumption further complicates them— an issue that emphasizes the necessity of simple approximate equations. Accordingly, we also propose simpler rational approximate phase-velocity and eikonal equations for the new acoustic orthorhombic media. We show a simple ray-tracing example and find out that the proposed approximate equations are still highly accurate.
Experimental and Numerical Study of the Effects of the Reversal Hot Rolling Conditions on the Recrystallization Behavior of Austenite Model Alloys

The experimental and numerical study of the effects of the recrystallization behavior of austenite model alloys during hot plate rolling on reverse rolling is the main goal of the paper. The computer models that are currently applied for simulation of reverse rolling are not strain-path-sensitive, thus leading to overestimation of the processing parameters outside the accepted process window (e.g., deformation in the partial austenite recrystallization region). Therefore, in this work, a particular focus is put on the investigation of strain path effects that occur during hot rolling and their influence on the microstructure evolution and mechanical properties of microalloyed austenite. Both experimental and numerical techniques are employed in this study, taking advantage of the integrated computational material engineering concept. The combined isotropic–kinematic hardening model is used for the macroscale predictions to take into account softening effects due to strain reversal. The macroscale model is additionally enriched with the full-field microstructure evolution model within the cellular automata framework. Examples of obtained results, highlighting the role of the strain reversal on the microstructural response, are presented within the paper. The combination of the physical simulation of austenitic model alloys and computer modeling provided new insights into optimization of the processing routes of advanced high-strength steels (AHSS).
A Multi-Heuristic Search-based Motion Planning for Autonomous Parking

Planning is a crucial component of autonomous vehicle con-trol. It is responsible for ﬁnding a collision-free sequence of states that take the vehicle towards its goal. In unstructured environments like parking lots or construction sites, due to the large search-space and kinodynamic constraints of the vehicle, real-time planning is challenging. Several state-of-the-art solutions utilize heuristic search-based planning algorithms. However, they heavily rely on the quality of the single heuristic function used to guide the search, and they are not capable to achieve reasonable performance, resulting in unnecessary delays in the response of the vehicle. This work solves the planning problem by adopting a Multi-Heuristic Search approach, that enables the use of multiple heuristic functions and their advantages to capture different complexities of a given search space. Based on our knowledge, this approach was not used for this domain so far. For this purpose, multiple admissible and non-admissible heuristic functions are deﬁned, original Multi-Heuristic A* Search was extended for bidirectional use and dealing with hybrid continuous-discrete search space and a mechanism for adapting scale of motion primitives is introduced. To demonstrate the advantage, Multi-Heuristic A* algorithm is benchmarked against a very popular heuristic search-based algorithm, Hybrid A*. The Multi-Heuristic A* algorithm outperformed Hybrid A* in terms of computation efﬁciency and motion plan (path) quality.
Impact of Organizational Culture on the Accounting Information System and Operational Performance of Small and Medium Sized Enterprises in Ho Chi Minh City

This study focuses on determining the impacts of organizational culture on the accounting information system and the operational performance of small and medium-sized enterprises in Ho Chi Minh City. The paper is organized in five parts: introduction, literature review, research methodology, research results, and conclusion and policy implications. Based on the samples of 353 respondents working in small and mediumsized enterprises in Ho Chi Minh City, the research employs both qualitative and quantitative methods to find the answers for research questions. Group discussion, which yields final observed variables of the factors of organizational culture is used for qualitative method. Statistics, assessment of the reliability of Cronbach's Alpha scale, exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structural equation modeling (SEM) are used for quantitative procedure. The results show that mission, involvement and inconsistency in organizational culture positively affect the accounting information system of small and medium-sized firms in Vietnam. In addition, mission, involvement, adaptability and consistency in organizational culture are found to have positive impacts on the firm operational performance. Another finding of the study is that the accounting information system has a positive effect on operational performance of small and medium-sized firms in Vietnam.
ORCA: Enabling an Owner-Centric and Data-Driven Management Paradigm for Future Heterogeneous Edge-IoT Systems

Integrating the Internet of Things (IoT) and edge computing in Edge-IoT systems, converged with machine intelligence, has the potential to enable a wide range of applications in smart homes, factories, and cities. Edge-IoT can connect many diverse devices, and IoT asset owners can run heterogeneous IoT systems supported by various vendors or service providers (SPs), using either cloud or local edge computing (or both) for resource assistance. The existing methods typically manage the systems as separate vertical silos, or in a vendor-/SP-centric way, which suffers from significant challenges. In this article, we present a novel owner-centric management paradigm named ORCA to address the gaps left by the owner-centric paradigm and empower IoT asset owners to effectively identify and mitigate potential issues in their own network premises, regardless of vendors'/SPs' situations. ORCA aims to be scalable and extensible in assisting IoT owners to perform intelligent management through a behavior-oriented and data-driven approach. ORCA is an ongoing project, and the preliminary results indicate that it can significantly empower IoT system owners to better manage their IoT assets.
Learning and Engagement in the Flipped Classroom of Analytical Mathematics

Learning techniques have changed over time in order to try and improve student engagement across different subjects in higher education. Mathematics has dominantly adhered to certain learning methods that use a more conventional approach. Interactive and active learning in Mathematics tend to be more common in further education yet, university level Mathematics is more complex, heavy in content and poses more difficulty in applying active learning approaches as a passive approach of traditional lectures has always been applied. The issues of learning problems in mathematics is ignored and the lack of metacognitive awareness of mathematical thinking and problem-solving skills seem to persist despite differences amongst educators on an effective learning methodology. Following the reform movement in mathematics education in the mid 1980’s, resulting from the dissatisfaction of conventional approaches, recommending the restructuring of mathematical delivery marked the need for modifications in teaching methodology. Employing multiple models to deliver lessons may implement the changes needed to drive student engagement and satisfaction to improve the experience in learning mathematics. In order for these methods to become applicable and effective in students’ experiences in mathematical education, educators need to be encouraged to present active learning techniques so that students can begin to facilitate their own learning which can be done through introducing approaches specific to the individual such as student-centred approaches. Original Research Article Sofroniou; JESBS, 33(11): 93-111, 2020; Article no.JESBS. 64155 94 This paper evaluates the techniques used by mathematicians to deliver lessons and how it reflects on learning and engagement of students in comparison to the flipped classroom approach which inverts the common traditional lecture style used in classrooms. The flipped classroom model in this study is adopted to a topic from the university foundation level module, Analytical Mathematics, whereby results from the quantitative analysis undertaken show a decrease in the success of students’ performance suggesting a lesser impact on improved learning. With regards to engagement, observations from the qualitative analysis of the study highlight positive aspects of the flipped classroom model, specifically an optimistic engagement amongst peers.
The Development and Validation of the Emotional Literacy Skills Scale

Emotional literacy is the ability to understand, express and regulate emotions in social contexts. It emphasizes the ability to communicate with certain feeling words in interpersonal relationships. It stands as a bridge between the thoughts and emotions of school stakeholders, contributing to more effective learning, safer schools, and a democratic climate (O‟Hara, 2011). It is possible to teach emotions academically, even to make them a part of the curriculum (Antidote, 2003); however, it is essential to also see emotional literacy as a vital skill through the values of the school and the behaviors of teachers. Therefore, it is valuable to evaluate the emotions of teachers in the school environment. To do this, it was the aim of this study to develop a reliable and valid measurement tool -the Emotional Literacy Skills Scale (ELSS). The validity of the model was confirmed via exploratory factor analysis and confirmatory factor analysis. We found a Cronbach Alpha reliability coefficient of . 85. The findings showed that the Emotional Literacy Skills Scale is valid and reliable and formed by five factors: Motivation, empathy, self-regulation, emotional awareness, and social skills.