bluuebunny/crossref_metadata_2025 huggingface dataset:
Artificial Taste Perception of Tea Beverage Using Machine Learning
Authors: Patil Amruta Bajirao , Bachute Mrinal Rahul
Published: May 2024

Nowadays, an artificial perception of beverages is in high demand as
working hours increase, and people depend on readymade food and beverages. An
assurance of quality, safety, and edibility of food and drink products is essential both
for food producers and consumers. Assurance of unique beverage taste and consistent
taste uniformity creates a distinct identity in the market. India is the second largest tea
producer country in the world. Based on geographic location, the tea has a specific
flavor and aroma. Artificial Intelligence (AI) can contribute to the feature identification
and grading of tea species. The taste, aroma, and color are the three main attributes that
can be sensed with the help of E-tongue, E-nose and E-vision, and can be processed
further for automatic tea grading. The various potentiometric, voltammetric, Metal
Oxide Semiconductor (MOS) and acoustic sensors are available with Principal
Component Analysis (PCA). For tea analysis, various reviews are mentioned, like User
Experience (UX evaluation, literature review, bibliometric review, and patent review.
An in-depth analysis of artificial taste perception using machine learning has been
described in the chapter. The topic covered almost all possible approaches to the
artificial perception of tea with various interesting facts.
Significance of Evolutionary Artificial Intelligence: A Detailed Overview of the Concepts, Techniques, and Applications
Authors: Tripathi Ashish , Singh Rajnesh , Singh Arun Kumar , Gupta Pragati , Vats Siddharth , Singhal Manoj
Published: May 2024

An evolutionary algorithm (EA) is known as a subset of evolutionary
computation. It is inspired by natural evolution and applies natural phenomena to
search for the optimal solution. Its parallel search capability and randomized nature
enable it to be effective and unique in solving different real-world problems in
comparison to existing classical optimization algorithms. The evolutionary algorithm
applies biological techniques such as selection, reproduction, and mutation to solve
complex problems. It starts with a random population of candidate solutions and
applies biological techniques to every generation until feasible solutions are obtained.
The only fit solutionis intelligence (AI) simulation human intelligence in machines.
Machines are programmed enough to think like humans and imitate their actions. AI
based models are developed to provide new solutions to real-world problems. As realworld problems are very complex, the desired solutions for such problems are required
to be explored in complex, high-dimensional, and very large search spaces. In this
context, nature inspired and population based evolutionary techniques are the most
suitable approach to find the optimal solution. The nature-inspired evolutionary
techniques follow the natural phenomenon and these phenomenon helps to search for
the desired optimal solution when the direction of the search is allowed to survive and
continue to move in further generations to determine the optimal solution. Artificial not
known at the beginning. So, “Evolutionary Artificial Intelligence (EAI)” is the term
that presents the combination of human intelligence and natural phenomenon-based
solutions to real-world complex problems. This chapter covers an overview of
optimization techniques, artificial intelligence, and evolutionary computation in detail. A detailed discussion on evolutionary artificial intelligence, followed by applications of
evolutionary machine learning is also presented. After that, the significance of
evolutionary artificial intelligence in decision making has been discussed. Finally, the
conclusion has been given, which shows the summary of the chapter.
Automated Bird Species Identification using Audio Signal Processing and Neural Network
Authors: Bhor Samruddhi , Ganage Rutuja , Pathade Hrushikesh , Domb Omkar , Khedkar Shilpa
Published: May 2024

Many bird species are rare nowadays, and when they are found, they are
difficult to classify. As an example, in various scenarios, birds include different sizes,
forms, colors, and a person's viewpoint from different angles. Although domain
specialists can classify birds manually, with increasing volumes of data, this becomes a
tiresome and time-consuming procedure. Using our approach, we can reliably and
quickly identify bird species. It is now feasible to track the number of birds as well as
their activity using automated bird species recognition and machine learning
algorithms. Convolutional neural networks (CNN) were chosen above standard
classifiers such as SVM, Random Forest, and SMACPY. For this system, we used the
“BirdCLEF 2021” dataset from Kaggle. The input dataset will be preprocessed, which
will involve framing, silence removal, and reconstruction, which will be supplied as
input to a convolutional neural network, followed by CNN modification, testing, and
classification. To avoid overfitting, we add a dropout layer. Preprocessing includes
importing the Librosa library. MFCC is a program that extracts distinct characteristics
from audio files (Mel-Frequency-Cepstral-Coefficients). The MFCC summarizes the
frequency distribution over the window size, allowing for sound frequency and
temporal analysis. The result is then compared with respect to the pre-trained data, and
output is shown, and birds are classified based on their classes.
Application Using Machine Learning to Predict Child’s Health
Authors: Kolapate Saurabh , Jadhav Tejal , Mangaonkar Nikhita
Published: May 2024

Nowadays, modern technologies are applied in many different areas of
medical science. One such piece of technology that helps in the diagnosis of numerous
illnesses and infections is the expert system. The Medical Expert System was created to
assist doctors in making diagnoses and to make it easier for the public to recognize
disorders. To diagnose the user, it treats facts and symptoms as queries or inputs. This
suggests that a medical expert system makes a diagnosis based on information about
the patient and knowledge of the diseases. Designing an Expert System for disease
diagnosis in youngsters up to the age of 16 is the main goal of this project. Python,
Java, and Flask are all used as computer programming languages. The selected
symptoms supplied as the question will enable the expert system to correctly diagnose
these diseases. With this discovery, we think the creation of an expert system will be
advantageous for disease diagnosis in pediatric instances and will also become more
affordable. Multiple tests are necessary for the diagnosis of disorders in children
because the symptoms might occasionally be deceiving. In these situations, an expert
system can aid in identifying and treating the true issue. In addition to a prescription, it
can diagnose the illness and offer information.
Shifting from Red AI To Green AI
Authors: Shetty Samruddhi , Joshi Nirmala , Banubakode Abhijit
Published: May 2024

The 2020s may see amazing advances in AI, however, as far as the
foundation and proficient utilization of energy is concerned, we have not reached the
optimized level. As AI research advances, we should demand the best platform,
methodologies, and tools for building AI models. Organizations heavily rely on AI for
various activities today, with only 7% of businesses trying to discover the facts related
to the problem that a bigger carbon footprint is left by AI, with the training process for
several large AI models emitting as much as 626,000 pounds of carbon dioxide
equivalent to the lifetime carbon footprint of nearly 3640 iPhones. As we know,
algorithmic training is an endless process for AI-powered tools, as a result, growing
reliance on AI only speeds up the death of the immediate environment. The awareness
among the people about how AI can impact the sustainability of the environment in the
near future is not considered while developing the solution. Apart from big players in
the market, the cognizant of sustainable and responsible AI is still a big question mark.
The end user or the consumers should be aware of the services they use, whether they
are only accurate or efficient as well. The balance between both factors should be
maintained based on the context and requirement. The same is studied in the given
paper concerning the concept of Red AI and Green AI and how they should be
balanced considering the environmental sustainability factor.
Knowledge Representation in Artificial Intelligence - A Practical Approach
Authors: Bagal Vandana C. , Rane Archana L. , Bhattacharya Debam , Banubakode Abhijeet , Mahalle Vishwanath S.
Published: May 2024

In the realm of artificial intelligence, knowledge representation is a vital
aspect that enables effective information sharing and processing. Humans excel at
sharing trusted information, which is acquired through rigorous testing and validation,
resulting in what we commonly refer to as knowledge. The representation of
knowledge can take various forms, such as graphs, maps, or textual formats. With the
continuous evolution of the IT sector, the introduction of AI has simplified many tasks,
often surpassing human capabilities and effortlessly handling even the most basic
activities. However, understanding the concept of knowledge representation remains a
fundamental question. In this research paper, we delve into the basics of knowledge
representation to directly address this question. The understanding of knowledge
representation is best achieved by examining the role knowledge plays in specific case
studies or systems, which includes scientific reasoning and comprehension of the
world. By exploring the intricacies of knowledge representation, we aim to provide a
practical approach to its implementation in the field of artificial intelligence.
File Content-based Malware Classification
Authors: Deore Mahendra , Gosavi Chhaya S.
Published: May 2024

Malicious Software (MALWARE) is a serious threat to system security the
moment any electronic gadget or ‘Thing’ is connected to the World Wide Web
(WWW). The malware - stealthy software that is used to collect sensitive information
gains access to private systems and can disrupt device operation. Thus, malware acts
against the user requirement and is a threat to all operating systems (OS), but more to
Windows and Android systems, as those are the most widely used OS. Malware
developers try to invade the system by means of viruses, adware, spyware,
ransomware, botware, Trojans, etc. Developers try different anti-forensic techniques so
that malware cannot be detected or investigated. Malware developers typically play
‘peekaboo’ with the malware investigators. The result is that investigating such attacks
becomes more complex, and many times it fails because of immature forensics
methodology or a lack of appropriate tools. This chapter is the first step towards
analysing malware. The process started with malware dataset collection and
understanding the same. ML has two basic blocks, i.e., feature extraction and
classification. In the case of supervised learning, this feature plays a significant role.
This asks for understanding features and their effect on classification, which was a
major task. Two separate experimental processes were explored. The first one involved
extracting n-grams from the binary files using the kfNgram tool, and the second one
used a shell script to parse the assembly files for method calls to external API libraries.
Several supervised machine learning classifiers like Decision Trees, SVM, and Naive
Bayes were used to classify the malware family based on extracted features. We
proposed a method to classify malware into nine families as per the Kaggle dataset. It
analyses the n-gram of the malware file to generate the feature vector. Here, the value
of ’n’ in n-gram is selectable; presently, it is four. The objective was to extract highly
probable n-grams from the binary files after pre-processing, i.e., calculating the IG
parameter. The present threshold for selecting n-gram from the top-most lists is five
hundred. It has been observed that SVM and Decision trees provide accuracy on the
scale of 98%. Nevertheless, there are chances of improvement as there is a probability
of selecting irrelevant n-grams due to the sequential selection of n-grams. This method
is considered a starting point for malware classification.
Cyber Physical Systems in Autonomous and Unmanned Aerial Vehicles
Authors: Rajendran Sindhu , S. Shreya , Tengli Alaska , N. Ramavenkateswaran
Published: May 2024

In today’s world, the demand for autonomous and unmanned aerial vehicles
is rapidly growing with applications in many domains. These autonomous vehicles
have potential advantages like – a reduction in traffic deaths by 90%, a drop in harmful
emissions by 60%, an improvement in fuel economy by 10%, an increase in lane
capacity by 500%, a reduction in travel time by 40%, an increase in transportation
accessibility and a reduction in transportation costs. Similarly, UAVs have advantages
like- traffic monitoring, moving objects in seemingly dangerous environments, payload
delivery and surveillance. Cyber-Physical Systems (CPS) are combinations of
networking, computation and physical systems. The three interacting components of
CPS - communication, computation, control and their coupling effects are necessary for
improving the performance of the UAV network. Control mechanisms, performance
and safety of autonomous and unmanned aerial vehicles are the important factors to be
considered while designing them.The major concern for any fully or partially
autonomous system is safety, the other challenges faced are: mechanical failure,
communication bandwidth shortage, cyber-hacking, communication delay, etc. Various
designs are proposed and tested to overcome these challenges, few of them are: a
framework for software - ReMinds in addition to the extensions implemented in the
Dronology system; for Dronology, researchers have proposed and designed incubators
for safety-critical CPS. The chapter emphasizes the role of CPS in autonomous and
unmanned aerial vehicles, framework of CPS for UAVs, the challenges with respect to
CPS and is concluded with the state of art of the present autonomous vehicles.
Cyber-Physical Systems in HealthCare
Authors: Revathy M. , Rakseda keerthi A.S.
Published: May 2024

Cyber-Physical Systems (CPS) are being developed with the integration of
computational capabilities and communication with physical systems. Recent
technologies like WSN (Wireless Sensor Networks), Communication Networks, Cloud
Computing, Big Data, and many more use CPS. Applications include Smart Grid,
Healthcare, Transportation, and Smart Buildings. CPS has made a huge impact on
increasing the efficiency of medicines and life span in many developed countries. This
has drawn researchers and the government's interest in Medical Cyber-Physical
Systems (MCPS), especially during Covid times. Many models were developed during
the pandemic. One of them is a Machine Learning (ML) integrated X-ray device called
Covilearn. In this chapter, an introduction to CPS in health care, its current trends, and
a device called e-stocking has been discussed. It is being used to treat leg venous
insufficiency. The motive of the application of CPS is to reduce power consumption for
long-term usage. This system is based on a model-driven energy-aware approach.
There are three approaches - Mechanical, Software, and Communication. False alarm is
one of the major issues as it is a pressure on both patients and caretakers. A model
aimed at resolving this problem is proposed and discussed here. Also, the existing
challenges and prospective opportunities in the domain of CPS have been explored.
A Luminescent Pathway for Anti-Counterfeiting of Currency and Forensic Applications
Authors: Pradhan P.P.
Published: May 2024

Nowadays, issues regarding counterfeit and forensic applications are gradually increasing. For instance, banking, insurance sectors, the drug industry, and university degrees, including different expensive commercial products, are facing counterfeit hitches with fake products. Duplication of the products could be done by simple methods and the replicated product looks genuine that nobody could doubt. So, to prevent these kinds of offensive activities, latent security ink has a great advantage to write secret codes or symbols. Similarly, the effective identification of latent fingerprints in forensic science is crucial for investigations at the crime scene. Latent fingerprints are generally accomplished on many surfaces. However, extraction of these from porous, non-porous, and colored surfaces is not so easy. To resolve the issue, organic/inorganic dyes, pigments, and nano phosphor materials have been used conventionally, due to the characteristics of nano-size, variable colour emission, afterglow, and high chemical stability, which consent the fingerprint recognition on any type of surface for forensic applications. This comprehensive book chapter includes a brief introduction to luminescence, properties of lanthanides, and lanthanide complexes. Extensive literature survey including synthesis and application of lanthanide-based nano phosphors in the areas of anticounterfeit and latent fingerprint extractions. Amongst the numerous techniques, which have been developed to combat counterfeits, visualization of latent fingerprints, security ink, and printing, innovative luminescent materials have been broadly utilized for various applications not only due to high-throughput production, facile design and simple operation but also due to exceptional security properties. Moreover, this chapter provides a systematic comprehensive overview of the latest developments in Ln-doped luminescent materials, plasmonic nanomaterials, quantum dots (QDs) and metal-organic frameworks for their possible use in the above high in demand applications.
Rare-Earth Doped Materials for Optical Information Storage
Authors: Kamal C.S.
Published: May 2024

Nowadays, in this digital era, we are constantly bombarded with information. In recent years, researchers have paid a lot of attention to new information storage formats and storage methodologies. Optical information storage offers a number of benefits that make it a viable future alternative for information storage in comparison to magnetic media and semiconductor memory. Due to the inherent 4fn orbital and rich energy-level structures of rare-earth elements, research on rare-earth doped materials for optical information storage has propelled the development of state-of-the-art luminescent materials as information carriers in the 21st century by emitting polychromatic radiation covering the entire visible and near-infrared (NIR) spectral region when irradiated by NIR, visible, or ultraviolet (UV) light.
The Role of Rare Earths in Fluid Catalytic Cracking (FCC) Catalyst
Authors: Akah A.
Published: May 2024

Rare earth oxides enhance catalyst activity and prevent the loss of acid sites during the FCC unit operation, especially when feed with high metal content is used. This chapter reviews the effects of rare earth elements on the structure, activity, and stability of FCC catalysts. It also looks into the mechanism of catalyst deactivation by vanadium and how rare earths are used to combat this. The objective is to elucidate the interaction of vanadium species with the zeolite component of the FCC catalysts and to show the role of rare earth elements in countering the deleterious effects of vanadium. The recycle of spent FCC catalyst with a focus on rare earth element recovery is also outlined.
Electrocatalytic Hydrogen Production: Catalysts and Applications
Authors: Peng Xiang
Published: May 2024

The book presents the fundamental principles, materials, and strategies involved in the design and development of catalysts for electrocatalytic hydrogen production.
Modelo matemático aplicado al control del proceso de carbón en pulpa
Authors: Pérez-Matos Edgar Ademar
Published: May 2024

Las relaciones matemáticas obtenidas denotan la complejidad de la operación en la etapa del oro lixiviado y adsorbido en el carbón activado; puesto que en operaciones metalúrgicas reales ocurren pérdidas importantes de oro en solución. Así mismo en la operación de oro adsorbido, revela su alta cinética al inicio y tiende a disminuir al transcurrir tal proceso; llegando a obtener toda la carga de oro que pueda admitir el carbón, para luego mostrar su tendencia opuesta. Además, al ir variando la concentracion del carbón repercute en la operación de adsorción; es decir la cinética de oro adsorbido en el carbón disminuye en el tiempo; pero la operación tiene mayor cinética con más volumen de carbón durante la adsorción. Lo mencionado es posible al constituir su respectivo modelo matemático del oro en solución barren y oro cargado en el carbón; luego optimizando con Solver- herramienta Excel los dos parámetros como la capacidad de carga y la constante cinética del carbón activado, ambos ligados íntimamente al proceso; con la condición de obtener un menor error relativo y por consiguiente un mayor grado de confianza. Consiguiendo así asemejar el modelo matemático hacia lo real; prediciendo fehacientemente la operación de oro adsorbido en carbón, variando la velocidad de flujo en el proceso de adsorción.
The impact of information technology governance according to the COBIT on performance
Authors:   Finance and Investment Department, College of Business, Jouf University, Sakaka, Saudi Arabia, Mohamed Abdelwhab Musa Elgali , Alnor Nasareldeen Hamed Ahmed ,   Accounting Department, College of Business, Jouf University, Sakaka, Saudi Arabia, Mohammed Omer Alsir Alhassan ,   Accounting Department, Faculty of Economics and Administrative Sciences, Islamic University of Minnesota, Virginia, USA, Al-Matari Ebrahim Mohammed ,   Accounting Department, College of Business, Jouf University, Sakaka, Saudi Arabia,   Faculty of Commerce and Economics, Amran University, Amran, Yemen, Alhebri Adeeb ,   Accounting Program, Applied College, King Khalid University, Muhyle Assir, Saudi Arabia, Ahmed Afaf ,   Business Administration Program, Applied College, King Khalid University, Sarat Obeida, Saudi Arabia
Published: May 2024

This study aims to explore the relationship between the performance of banks and the governance of information technology as outlined by control objectives for information and related technologies (COBIT) standards. A survey questionnaire method was used to collect data, guided by a specific model to address the research objectives. Participants included employees from the Central Bank of Sudan and various commercial banks. Out of 280 distributed surveys, 240 were successfully returned and analyzed using the SPSS software to assess both measurement and structural models. The analysis revealed a positive and significant link between bank performance and several aspects: acquisition and implementation, support and delivery, monitoring and evaluation, and planning and organizing. This research contributes to the existing literature by specifically examining the performance of banks and information technology governance in the Middle Eastern context through COBIT, marking it as a distinctive empirical study in this field.
Pragmatic Functions of Emoticons in WeChat Messaging
Authors: Tang Jianing
Published: May 2024

With the development of social media and the updating of emoticons, people widely use emoticons to convey information and express emotions in instant messaging to achieve the purpose of communication. As a new research field, emoticons have attracted extensive attention of scholars in recent years. The previous studies mostly focus on motivation and influencing factors of emoticon usage from the perspective of communication. However, little research has been done on the study of linguistics. The author of this paper intends to explore the roles and pragmatic functions of emoticons in WeChat messaging through discourse analysis based on speech act theory. The study shows that emoticons compensate for the lack of information and eliminate ambiguity in online communication, and that different age groups have different understandings of emoticons. Hopefully the study on emoticons will help people systematically understand the roles and functions of emoticons, thus achieving interpersonal effective communication.
The Application of Reading Circles Model in English Reading Teaching in Senior Middle School
Authors: Ting-ting Wang
Published: May 2024

There are various input methods for language learning, among which reading is the most important one. English reading class in High school aims to cultivate students’ comprehensive literacy by guiding them to think independently and actively participate in reading activities. The new curriculum standard proposes that English reading teaching in high school should focus on strengthening the cultivation of English subject competence. Thus, the effect of the reading circle model on students’ English reading is consistent with the educational purposes required by the core literacy of the English subject. Therefore, the article tries to explore the effect of reading circle on improving secondary school students’ English reading ability.
A NEW RP-UPLC METHOD FOR THE SEPARATION AND SIMULTANEOUS QUANTIFICATION OF DORZOLAMIDE HCl AND TIMOLOL MALEATE
Authors: ELURU ASHA , BABU K. SURENDRA
Published: May 2024

Objective: This investigation demonstrates a stability-indicating and reliable “reverse-phase ultra-performance liquid chromatography” method to simultaneously quantify timolol maleate and dorzolamide HCl in the pharmaceutical dosage form.
Methods: Successful separation was accomplished using Phenyl column (100 mm x 2.1 mm, 1.7μm) with isocratic type of elution using mobile phase containing Acetonitrile+Ammonium Formate buffer (30:70), respectively with 0.2 ml/min flow rate. The wavelength sensor was attuned at 266 nm to quantify timolol maleate and dorzolamide HCl.
Results: Dorzolamide HCl and timolol maleate peaks were eluted with fine resolution at retention times 0.7 min and 1.5 min, respectively. In the 55.75-334.5 μg/ml and 6.25-37.5 μg/ml concentration ranges for dorzolamide HCl and timolol maleate, the calibration graphs were linear, with regression coefficients of 0.99997 and 0.99991, respectively. The suggested ultra-performance liquid chromatography approach has been shown as sensitive, precise, robust, accurate, specific and stability, indicating through the resolution of dorzolamide HCl and timolol maleate from its degradation-based compounds.
Conclusion: The established ultra-performance liquid chromatography technique was effectively extended to the evaluation of dorzolamide HCl and timolol Maleate in the pharmaceutical dosage form and the test results appeared satisfactory.
FORMULATION AND EVALUATION OF RED GINGER RHIZOME EXTRACT SOAP AS AN ANTIBACTERIAL
Authors: NURLENI NOVI , FIRDIAWAN ARIE , RENDOWATY AGNES , KURNIASARI RESTI
Published: May 2024

Objective: Current research work aimed to develop a formulation of red ginger into a stable soap preparation, effective as an antibacterial and safe for long-term use.
Methods: The maceration method was used to extract red ginger rhizome. In the formulation, there are variations in the concentration of the extract, where Formulation I (FI) 3%, Formulation II (FII) 5%, Formulation III (FIII) 7%, and Formulation IV (FIV) 0%. The evaluation of the preparation includes tests such as sensory evaluation, homogeneity, pH, viscosity and flow properties, density, foam height, and stability, as well as antibacterial activity using the agar diffusion method against Staphylococcus aureus ATCC 25932 and Escherichia coli ATCC 25922.
Results: The percentage of extract yield obtained was 2.38%. All three formulations of soap have shown good stability during the 28-day evaluation (significant>0.05), indicating no significant changes during storage, and the inhibitory power of Staphylococcus aureus ATCC 25923 bacteria in the three successive formulations was 9.03±0.4; 12.21±0.3; 15.26±0.4 (mm) respectively, while that of Escherichia coli ATCC 25922 was 6.01±0.6; 10.32±0.4; 12.58±0.6 (mm).
Conclusion: The evaluation results, all formulations have good stability during storage. The variation in concentration of red ginger extract will affect the inhibitory power against test bacteria. F III, with an extract content of 7% has better antibacterial activity compared to other formulations.
REVITALIZING THERAPEUTICS: DRUG REPURPOSING AS A COST-EFFECTIVE STRATEGY FOR DRUG DEVELOPMENT
Authors: MAKHIJANI SHIVANI
Published: May 2024

The process of developing new drugs is known for being drawn-out, expensive, risky, and having a high attrition rate. Drug repurposing has grown in favor recently as a practical way to speed up the development of new medicines while reducing the costs and time constraints associated with traditional drug research. The description of this study's pharmacological repurposing highlights its promise as a practical method to fill gaps in the market and revitalize treatment options. This review provides a full analysis of the ground-breaking tactic of repurposing medications, supported by numerous cases that demonstrate its revolutionary potential. We examine instances of repurposed drugs, such as thalidomide, sildenafil, and metformin, that have performed astoundingly well in a range of therapeutic settings despite being used outside of their original scope.
Overall, the paper's main goal-to study pharmacological repurposing as a potentially successful strategy for revitalizing treatments-is, succinctly summarized in this abstract. It highlights the potential benefits of this approach and how it might be used in the pharmaceutical industry's ongoing quest for more inexpensive and effective medicine development.
DEVELOPMENT OF MYCROCRYSTALLINE CELLULOSE ORIGINATE FROM SAGO (METROXYLON SAGU) STEM BARK BY HYDROLISIS METHODE USING NITRIC ACID
Authors: AKIB NUR ILLIYYIN , SRIWIDODO  , LUBIS ADRYAN FRISTIOHADY , SYNTIA SAMANI MERY DINA , FAHMI NUR AHMAD , ANDRIANI RINA , CHAERUNISAA ANIS YOHANA
Published: May 2024

Objective: Microcrystalline cellulose (MCC) is an essential excipient in tablet formulation. Mostly MCC was obtained from wooden conifer stem fiber, therefore environment issues had been came up. Alternative sources for MCC which offer friendly conifer wood need to be explored. This study aimed to isolate and determine the characteristics of MCC originated from Sago (Metroxylon sago Rottb.) stem fibers as an promising alternative of MCC.
Methods: MCC was prepared through pre-hydrolysis using an acetic acid solution, alkali heating using NaOH solution, and acid hydrolysis using nitric acid 0.3 N using three variations of heating temperature, namely 90, 95 and 100 °C. The characterization carried out were pharmaceutical grade, powder properties, FTIR analysis and powder morphology by SEM.
Results: The yields obtained were 66.02; 65.53 and 65.08%, respectively. The characteristics of the MCC sample based on pharmaceutical grade quality were white to yellowish white powder, odorless, tasteless, insoluble in: ether, 96% alcohol, HCl 2N and NaOH 1N. The pH of the MCC suspension were 5.07-5.12, while moisture content were 3.67-4.17%, with loss on drying value as much as 0.37-0.4%, and ash content 1-2.17%. The value of permanganate number were 0.09-0.11, Hausner factor was between 1.05-1.25, and angle of repose were between 11.4-24.8°.
Conclusion: Based on the results, it can be concluded that Sago is potent natural resource for MCC. The resulting MCC revealed physicochemical and characteristic of MCC, which almost similar to Avicel PH 102 as standard.
FORMULATION DEVELOPMENT AND IN VITRO PENETRATION TEST OF ETHOSOME OF CHROMOLAENA ODORATA LEAVES EXTRACT
Authors: RAHMI SOFIA , REVENY JULIA , ARIANTO ANAYANTI , SITORUS PANAL
Published: May 2024

Objective: This study aimed to develop and assess ethosome preparation using extracts derived from the leaves of Chromolaena odorata.
Methods: The study started by obtaining Chromolaena odorata leaf extracts. Furthermore, Ethosome formulations were produced using a thermal technique. Ethosome variants were created, each with distinct compositions: Formulation F1, containing 10 ml of ethanol without the extract; Formulation F2, consisting of 0.5 grams of the extract mixed with 10 ml of ethanol; Formulation F3, combining 1 gram of the extract with 20 ml of ethanol; and Formulation F4, incorporating 1.5 grams of the extract with 30 ml of ethanol. The ethosomal systems were thoroughly characterized using various analytical techniques, such as organoleptic analysis, quantification of particle dimensions, zeta potential evaluation, pH metric analysis, transmission electron microscopy (TEM) imaging, and in vitro permeability assessment using the Franz Diffusion Cell apparatus.
Results: The findings indicated that the optimized F4 formulation showed 161.2±32.0 nm particle size measurement and a+34.33±0.58 mV zeta potential. All formula possess a pH range of 4.5-6.5, within which the skin can acclimate to preparations. It is evident from all formulations that the pH decreased after the addition of the extract at an acidic pH of 4.11. Following the 12-week storage period, the pH of all treatments exhibited a modest reduction; however, it remained within the acceptable range for skin pH. Furthermore, the F4 formula also had a higher level of penetration activity.
Conclusion: The optimized ethosomal formulations of Chromolaena odorata have promising applications in enhancing the permeability and efficacy of plant-derived therapeutic agents.
BIOLOGICAL REACTIONS OF MACROPHAGES TO METAL OXIDE NANOPARTICLES
Authors: ZORAH MOHAMMED , ATIYAH HASSAN LAFTA , WATHTHAB ALI NOOR , MOHAMMED JAWAD RUAA K. , ZAYED FATIMAH H. , MUDHAFAR MUSTAFA , H. A. ALSAILAWI , RAHEEM SAIF AHMED
Published: May 2024

In our daily lives, nanomaterials are utilized extensively in paints, textiles, food goods, cosmetics, and medicine. Several investigations aim to deter investigations of the physiological effects in various cell types. The innate immune system's macrophages regulate a wide range of biological functions. Depending on the stimulus, macrophages can be activated toward pro- or anti-inflammatory (M1) phenotypes; however, polarization may change in conditions including cancer, autoimmune illnesses, and bacterial and viral infections. Metal oxide nanoparticles have recently gained significant interest due to their diverse range of unique features with applications in research and industry. The production and usage of nanomaterials will rise significantly as the nanotechnology business grows. As a result, testing the consequences of nanomaterial exposure in biological systems is critical. A comparative analysis is conducted on the toxicities of several metal oxide nanoparticles. The significance of biogenically generated metal oxide nanoparticles has been growing in recent years. However, more research is needed to thoroughly characterize the potential toxicity of these nanoparticles to ensure nanosafety and consider environmental views. To that end, nanotoxicology seeks to assess the toxicity of nanomaterials to physicochemical factors such as size and form. In this review, we focus on the biological reactions of macrophages to metal oxide nanoparticles. Because macrophages are the first cells to engage with nanoparticles when they enter the body, they can absorb them through various processes.
UTILIZATION RED DRAGON FRUIT PEEL (HYLOCEREUS POLYRHIZUS) ETHANOL EXTRACT IN ORAL THIN FILM STRIP AS A MOUTH FRESHENER
Authors: APRILIANI NABILA , LAILA LIA , PRASETYO BAYU EKO
Published: May 2024

Objective: The aim of this study was to formulate an oral thin film strip (OTFS) contained the red dragon fruit peel (RDFP) ethanol extract (Hylocereus polyrhizus) and evaluate the characteristic, stability and antibacterial activity against Streptococcus mutans (S. mutans).
Methods: The film was made using the solvent casting method by adding a variety of concentration ethanol extract of red dragon fruit peel (5%, 10%, and 15%). The films were evaluated in organoleptic test, weight, thickness, pH, disintegration time, folding endurance, stability test and antibacterial activity.
Results: The results showed that the film provided a distinctive color, aroma, and taste of the extract. The result of film evaluation had weight between 0.07-0.21 g, thickness between 0.10-0.20 mm, pH between 5.70-5.99, disintegration time between 34.99-49.13 s, and folding endurance between 321.00-812.83 times. The films were stable for 2 mo at a variety storage temperature (4±2 ℃, 28±2 ℃, and 40±2 ℃). The films showed antibacterial activity for 5%, 10% and 15% with the diameter of inhibition 8.5 mm, 10.8 mm, and 12.9 mm, respectively.
Conclusion: Ethanol extract of RDFP can be utilized as a mouth freshener film that is stable for 2 mo and has antibacterial activity against S. mutans.
QUANTITATIVE DETERMINATION OF SOME NON-STEROIDAL ANTI-INFLAMMATORY DRUGSAND THEIR ACID DISSOCIATION CONSTANTS BY DIRECT POTENTIOMETRY
Authors: MASLARSKA VANIA
Published: May 2024

Objective: A potentiometric titration method was applied to determine non-steroidal anti-inflammatory drugs. The quantitative analysis and the treatment of the primary data are based on a nonlinear regression procedure using commercial software. A general formula valid for every type of acid-base titration, derived before is used as a direct input.
Methods: Potentiometric titration of ibuprofen, flurbiprofen, and ketoprofen with sodium hydroxide solution (0.1 mol/l). The solutions of ibuprofen, flurbiprofen, and ketoprofen were prepared in solvent CH3OH: H2O (40:60%). The determination was carried out using a 713 Metrohm pH meter, equipped with Metrohm combined electrode ref. 6.0228.000 Pt1000 with temperature sensor and auto burette. The analysis was performed at ionic strength (I=0.2 mol/l KCl) and t = 25±0.2 °C.
Results: The discussed substances were analyzed using potentiometric titration with a standard sodium hydroxide solution (0.1 mol/l). The experimental data V, ml/E, mV and the conditions of these titrations were used as input in the Data Fit program fixing the following parameters Vo =100.0 ml; Ct (NaOH) = 0.1000 mol/l; S = 59.16 mV (corresponding to 25 °C theoretical value) and Kw = 1.2 10-14 (ionic strength 0.2 mol/l). The analytical results for ibuprofen, flurbiprofen and ketoprofen were determined with good accuracy (error+0.4 % foribuprofen+0.2 % for flurbiprofen and+0.2 % for ketoprofen) and precision (1 % for the three). The quantity and acid-base constants of ibuprofen, flurbiprofen, and ketoprofen were determined alone and in tablets. The validation of the method showed very good accuracy and precision.
Conclusion: The present approach can be successfully used in routine analysis of the study drugs in quality control laboratories.
IDENTIFICATION, SEPARATION, AND CHARACTERIZATION OF DEGRADATION PRODUCTS OF TRIAMCINOLONE HEXACETONIDE USING LC AND LC-MS/MS
Authors: SUNIL MAHAJAN BHAVNA , MINIYAR PANKAJ B.
Published: May 2024

Objective: The study aimed to separate the forced degradation products of Triamcinolone hexacetonide using HPLC and characterize the degradation product by LC-MS/MS fragmentation pattern.
Methods: Triamcinolone hexacetonide (THA) and its primary degradation products were identified using a liquid chromatography-mass spectrometry/Mass spectrometry (LC-MS/MS) approach. The degradation study was based on in-depth stress testing with acid, base, peroxide, heat, and light. A Zorbax SB C18 column and a greener mobile phase composed of methanol and 10 mmol ammonium acetate buffer in water at pH 3 were employed to accomplish separation and quantitation at a flow rate of 0.7 ml/min in an isocratic mode with a 239 nm detection wavelength.
Results: A major degradation product of the drug was obtained in acidic and alkaline stress conditions. The drug was found to be stable for all other stress conditions. The LC-MS/MS analysis results of the active pharmaceutical ingredient and resulting product after degradation were interpreted to identify the novel degradation product and fragments. The developed method was validated as per International Council for Harmonization (ICH) guidelines. The square root of the correlation coefficients, which indicated linearity for THA in 50 to 150 % of the workload, was 0.99. Method Precision assay was performed on six different preparations, percentage relative standard deviation (% RSD) of assay value is 0.17 % and system precision is 0.30 %. In accuracy, overall % RSD of 50 %, 100 %, and 150 % in triplicate is 0.95.
Conclusion: It is concluded that the drug is stable to all other stress conditions except for acidic and alkaline stress conditions and generates a novel degradation product. The developed LC (Liquid chromatography) method separates and identifies the degradation product.
IBUPROFEN INJECTABLE MICROEMULSION PREPARATION COATED BY CHITOSAN: FORMULATION, CHARACTERIZATION, IN VITRO PERFORMANCE, ANTI-INFLAMMATION ACTIVITY, AND HEMATOLOGY ASSESSMENT
Authors: UL HAFIZAH AULIA , SUGITA PURWANTININGSIH , KHOTIB MOHAMMAD , CAHYANINGSIH UMI , SADIAH SITI
Published: May 2024

Objective: This study aimed to develop, characterize, and conduct stability evaluations to ensure compliance with intravenous administration for microemulsion ibuprofen injection. In addition, hematology assessment and profile of drug release kinetics were analyzed.
Methods: The formulation process commenced by introducing various chitosan concentrations into microemulsion ibuprofen injection, following a method established in a previous study. Formulation parameters studied include particle size, polydispersity index (PDI), zeta potential, kinetic of drug release, anti-inflammation activity using the 1% carrageenin induction method, and hematology assessment.
Results: The results showed that the addition of 1% chitosan solution allowed for the development of the ideal microemulsion formula, with droplet size, zeta potential, and PDI of 19.37±0.32 nm,-1.53±0.12 mV, and 0.38±0.02, respectively. Kinetics of chitosan-coated ibuprofen microemulsion (MK) were governed by the squared root of time paradigm, suggesting that drug release proceeded by diffusion and was influenced by the carrier. Compared to the other groups, the paw injected with MK indicated a strong anti-inflammatory effect and did not differ significantly from the control group (p>0.05). However, Hematology analysis showed no statistically significant variations in leukocyte and erythrocyte profiles between the treatment and control groups (p>0.05).
Conclusion: MK met the criteria as an intravenous preparation based on the characteristics and safety.
RP-HPLC METHOD DEVELOPMENT AND VALIDATION FOR SIMULTANEOUS ESTIMATION OF CURCUMIN AND RESVERATROL IN NANO-MICELLE: DUAL DRUG DUAL FORM SIMULTANEOUS ESTIMATION
Authors: RAHAMAN SK MOSIUR , CHANDRA ATANU , BISWAS RANU
Published: May 2024

Objective: To develop a reverse-phase high-performance liquid chromatography (RP-HPLC) method for simultaneous estimation of conjugated form of Curcumin (CCMN) and free form of Resveratrol (RSV) in nano-micelle.
Methods: The conjugation of lipophilic CCMN and hydrophilic Chitosan (CHT) through succinyl linker produce amphipathic molecule that can self-assemble into RSV solution to form micelle. Here RSV exists in micelle core as free form and CCMN with micelle backbone as conjugated form. So it required to estimate conjugated drug and free drug simultaneously from nano-micelle. We developed a RP-HPLC method, utilized C18 column, follow flow rate of mobile phase 1.0 ml/min, which consist of acetonitrile with water (0.5% Ortho Phosphoric acid, pH 4.6) in the ratio of 1:1 for 20 min. Injection volume was 10μl and column temperature 25 ℃. Isosbestic detection of both drugs was at 254 nm.
Results: The retention time of RSV and CCMN were at 8.15 min and 11.41 min respectively, completely distinguished sharp peak of CCMN and RSV developed with resolution 7.360±0.117, wide range of linearity with correlation coefficient value (R2) of CCMN and RSV were 0.99987 and 0.99992 respectively and recovery value of CCMN and RSV were 100.041±0.22 % and 100.041±0.21 % respectively. The RSD (relative standard deviation) for accuracy, precision and robustness of the method was found to be less than 2%.
Conclusion: The develop method for simultaneous estimation of conjugated CCMN and free form of RSV in the nano-micelle formulation was consider to be accurate, precise, robust and sensitive.
AUTOMATION IN ANALYTICAL CHEMISTRY: THE ROLE OF AI IN CHROMATOGRAPHY
Authors: KALPANA DIVEKAR , PRASAD SHISHIR KUMAR
Published: May 2024

Artificial Intelligence (AI) has facilitated significant breakthroughs in drug discovery, the design of materials, and organic synthesis. The advancements in the latter group are especially remarkable due to the abilities of the latest computational methods (molecular design algorithms) that enable the exploration of extensive chemical spaces and enhance research in fields such as predicting molecule properties, designing molecules, retrosynthesis, predicting reaction conditions, and predicting reaction outcomes. A literary review was conducted following PRISMA guidelines. This study aimed to review existing data on the application of AI in separation chromatography. The evolution and utilization of AI in the pharmaceutical industry and its future aspects were articulated in this study. The utilization of AI can completely transform the field of chromatography analysis by facilitating expedited, more precise, and more effective data processing. By automating chromatography analysis, AI can enhance efficiency and minimize the potential for human mistakes. This advancement enables scientists to dedicate their efforts towards addressing intricate and demanding analytical issues. With the evolution of technology and the increasing adoption, we can anticipate more progress in chromatography analysis and analytical chemistry.
DEVELOPMENT, OPTIMIZATION AND IN VITRO CHARACTERIZATION OF HALOPERIDOL NANOCRYSTALS USING 32 FACTORIAL DESIGN
Authors: SARITHA DAMINENI , CHANDRA BOSE P. SUBHASH , OSMANI RIYAZ ALI M. , IRIVENTI PADMINI , KANNA SANDEEP , RAVI GUNDAWAR
Published: May 2024

Objective: The main aim of the present study was to improve the dissolution rate of Haloperidol nanocrystals and thereby increase their bioavailability. Haloperidol is a typical antipsychotic drug and it is used to treat schizophrenia as well as acute mania and mixed states associated with bipolar disorder. Haloperidol falls into the Biopharmaceutics Classification System (BCS-II) class of drugs (poorly soluble aqueous and highly permeable) and has poor bioavailability.
Methods: The present study involves the preparation and optimization of Haloperidol nanocrystals by the anti-solvent precipitation method using Polaxomer407 and polyvinyl pyrrolidone K30 (PVP K30). The prepared nanocrystals were evaluated for various parameters like particle size, zeta potential, % drug content, % yield, surface morphology, drug-excipient compatibility studies (Fourier-transform infrared spectroscopy (FT-IR) and Differential Scanning Calorimetry (DSC)), and in vitro dissolution studies.
Results: Nine preparations were done and the best preparation amongst them was selected for further studies. F7 preparation containingpolaxomer407 and PVP K30 was selected as optimized preparation based on their evaluation parameters. 32 factorial design was used in the preparation. The particle size of the F7 nanocrystals was 300.2±2.7 nm and the zeta potential-36.3±3.2 mV. The % yield was in the range of 63.62±0.3%-98.21±0.8 %. The drug content of various preparations was found to be in the range of 58.46±0.8%-93.54±0.5 %. In vitro dissolution studies showed the highest % drug release for F7(91.54±0.03%) in 10 h.
Conclusion: F7 preparation was found to be having acceptable characteristics and thus selected as optimized preparation.