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Optimizations of antioxidants-rich herbal tea formulation from selected medicinal plants for the enhancement of Psidium guajava tea
Get PDFHerbal teas are simple, effective, inexpensive, drugfree, and caffeine-free ways to enjoy the flavor and benefits of
herbs and spices, which are commonly consumed by people
since they are natural, harmless, and can assist in treating
or controlling various therapeutic illnesses. The purpose of
this study was to develop guava leaf-based herbal tea with
a combination of supporting and activating herbs such as
Cinnamomum zeylanicum (cinnamon) leaf and bark, Senna
auriculata (avaram senna) flower, Gymnema sylvestre (gurmar),
Ocimum tenuiflorum(holy basil) leaf, and Citrus limon (lemon)
leaf in order to improve guava tea. Herbal teas were prepared
using nine various combinations of the above-mentioned plant
materials along with guava tea for comparative purposes.
The extraction of tea was done by infusing tea bags, and
phytochemicals were screened with a standard procedure. Total
polyphenolic content (TPC) and total flavonoid content (TFC)
were determined using the Folin-Ciocalteu approach and the
aluminum chloride spectrophotometric method, respectively.
Total antioxidant capacity was determined by the ferric reducing antioxidant power (FRAP) assay, while radical scavenging
activity was determined by the 2,2-diphenyl-1-picrylhydrazyl
(DPPH) assay. The toxicity of developed tea bags was assessed
using a brine shrimp micro-well cytotoxicity assay. According
to the findings, all of the prepared herbal teas and guava tea are
rich in essential phytochemicals. Moreover, the combination of
guava leaf, cinnamon bark, cinnamon leaf, avaram senna flower,
gurmar leaf, holy basil leaf, and lemon leaf (35:20:1:1:1:1:1)
exhibited the highest TPC (2027.12 mg GAE/ml) and antioxidant capacity (82.33 mg ascorbic acid eq/ml). During sensory
evaluation, this composition was most preferred to guava tea
by the semi-trained panel, and it showed nontoxicity to brine
shrimp (LC50 values higher than 1000 mg/L). In conclusion,
even though guava tea has already been developed and proven
to have anti-diabetic and antioxidant properties, the herbal tea
formulation from seven medicinal plants showed the greatest
preference due to the highest TPC and highest antioxidant
capacity. Further studies are needed to determine the antidiabetic properties of developed herbal teas and compare the
anti-diabetic properties of guava tea
The impacts of poverty on secondary students’ education- a case study of t/ Kinniya al-aqsa national school
Get PDFகல்வி என்பது ஒரு தனிமனிதனில் ஆரம்பித்து சமூகத்தின்
பால் அதன் வெளியீட்டினைக் கொண்டு சேர்க்கும் ஒரு கருவியாகும். கல்வியின்
முக்கியத்துவம் அதிகம் பேசப்பட்டு வந்தாலும் அதனை பெற்றுக் கொள்வதில் பல
காரணிகள் தடையாகவுள்ளன. அதனடிப்படையில் கிண்ணியா கல்வி வலயத்தில்
அமைந்துள்ள பாடசாலையான திஃகிண்-அல் அக்ஸா தேசிய பாடசாலையில்
இடைநிலைப் பிரிவு மாணவர்களின் கல்வியில் வறுமை ஏற்படுத்தும் தாக்கங்களை
அடையாளப்படுத்துவதனை இவ்வாய்வு முதன்மை நோக்காகக் கொண்டுள்ளது.
பண்பு மற்றும் அளவுசார் முறையில் அமைந்த இவ்வாய்வானது முதலாம் மற்றும்
இரண்டாம் நிலைத் தரவுகளைக் கொண்டமைந்துள்ளது. முதலாம் நிலைத்
தரவுகளாக நேர்காணல்கள், கலந்துரையாடல்கள் மற்றும் அளவையியல்
வினாக்கொத்து என்பவற்றை உள்ளடக்கி அவை விபரிப்பு மற்றும் விளக்கப்
பகுப்பாய்வு முறையில் முன்வைக்கப்பட்டுள்ளது. ஆய்வின் பெறுபேறுகளை விளக்க
விரிதாள் துணை (MS Excel Sheet 2013) கொண்டு தரவுகள் பகுப்பாயப்பட்டு
அட்டவணைகளும் வரைபடங்களும் தயார்படுத்தப்பட்டுள்ளது. இரண்டாம் நிலைத்
தரவுகளாக ஆய்வுக் கட்டுரைகள், அறிக்கைகள், சஞ்சிகைகள், இணையத்தளத்
தகவல்கள் ஆகியன மிளாயப்பட்டு ஆய்வுக் கோட்பாட்டுக் கட்டமைப்பைப்
பெற்றுள்ளது. ஆய்வின் பிரதான கண்டறிதல்களாக: மாணவர்களின் கல்வி
நடவடிக்கைகளில் பெற்றோர் கவனம் செலுத்தாமை, தினசரி பாடசாலைக்கு
செல்வதில் மாணவர்கள் மத்தியில் விருப்பமின்மை, மேலதிக வகுப்புகளுக்கு
செல்வதில் சிக்கல்கள், மாணவர்கள் தொழிலுக்குச் செல்லுதலில் ஆர்வம் காட்டல், வளப்பற்றாக்குறை, பாடசாலை உபகரணங்கள் கொள்வனவு செய்வதில்
சிக்கல்கள், பாடசாலை வருகை குறைவும் பாடசாலை இடைவிலகல்களும், கல்வியில் பின்னடைவு போன்ற பிரச்சினைகளை கண்டுகொள்ள முடிகின்றது.
எனவே மாணவர்களின் கல்வியில் வறுமையானது எதிர்மறையான தாக்கத்தை
செலுத்தியுள்ளது என்பதை இவ்வாய்வு முடிவாகக் கொள்கிறது. குறித்த
பாடசாலையில் கல்வி பெறும் மாணவர்களின் பிரச்சினைகளை உரிய முறையில்
அணுகி அவர்களுக்கு உதவித் திட்டங்களை மேற்கொள்ளவும் மாணவர்களுக்கு
உண்டாகும் கல்வி சார்ந்த பிரச்சினைகளை நிவர்த்தி செய்வதற்கான
ஆலோசணைகள் மற்றும் பரிந்துரைகள் பற்றிய முன்மொழிவை தருவதாகவும்
எதிர்காலத்தில் இவ்விடயத்தில் ஆய்வு செய்பவர்களுக்கு இவ்வாய்வு
துணைபுரிவதாகவும் அமையும
rbcL nucleotide sequence-based phylogenetic analysis of Nepenthes distillatoria L.
Get PDFAmong carnivorous plant families, Nepenthaceae is a very peculiar family which has only one
genus, Nepenthes. In Sri Lanka, this genus is represented by a single endemic species;
Nepenthes distillatoria L. (1753). In that aspect, this plant has a key taxonomic value in Sri
Lankan flora. This study was intended to identify the phylogenetic position and to establish a
relationship between N. distillatoria and other selected carnivorous plant species of
Nepenthaceae using rbcL sequences. DNA was extracted from leaves of N. distillatoria and
subsequent PCR amplification of the rbcL region was performed. The amplified PCR products
were subjected to DNA sequencing. The rbcL sequence alignments were constructed using
MEGA v.7.0 and phylogenetic analyses were carried out under the Maximum Likelihood
method. This study mainly introduces the partial coding sequence of the rbcL gene of N.
distillatoria. The reconstructed phylogenetic tree based on the sequence results revealed that
N. ventricosa, N. merrilliana, N. khasiana, N. bellii, and N. fusca are closely related species to
N. distillatoria
Real-time sign language detection using deep learning model
Get PDFKey Effective communication between deaf and hearing individuals can be challenging
due to the lack of efficient sign-language recognition systems. To address this
challenge, a Deep Learning-Based Approach for Sign Language Detection using a
Convolutional Neural Network (CNN) is proposed. The model is trained and evaluated
on a standard sign language image dataset consisting of 7500 images belonging to 25
classes, with each class having 300 images. The dataset is split into training and testing
data in a ratio of 80:20, respectively, by randomly selecting images from the dataset.
The proposed approach achieves a remarkable accuracy of 94% in detecting sign
language gestures in real time. Machine learning algorithms through the image
classification method based on the CNN model and libraries such as TensorFlow,
Keras, and OpenCV with Python are used to develop the deep learning-based approach
for sign language detection. The video frame is labeled according to the sign language
gesture being performed by the person. The results of the research demonstrate the
effectiveness of deep learning-based approaches for sign language detection and
contribute to the development of more advanced and efficient sign language recognition
systems. This technology has the potential to significantly improve communication and
interactions between deaf and hearing individuals
Mass screening of rice mutant populations at low CO2 for identification of lowered photorespiration and respiration rates
Get PDFIdentifying rice (Oryza sativa) germplasm with improved efficiency of primary metabolism is of utmost importance in order to increase yields. One such approach can be attained through screening genetically diverse populations under altered environmental conditions. Growth or treatment under low carbon dioxide (CO2) concentrations can be used as a means of revealing altered leaf photorespiration, respiration and other metabolic variants
Smart doc: an ai driven disease prediction and consultant direction smart system
Get PDFNumerous developing nations, including Sri Lanka, struggle with healthcare challenges
stemming from insufficient personnel, a scarcity of modern medical equipment, and a
lack of contemporary hospitals in rural areas, contributing to elevated mortality rates in
remote regions. Addressing these issues, this paper proposes an innovative solution
through the development of an Android-based system. Specifically, a mobile expert
system has been designed and implemented to provide diagnoses for forty prevalent
diseases in Sri Lanka. The AI-powered Disease Prediction prototype provides early
illness detection during urgency. It employs symptom-based queries and can guess
possible illness when a person gets sick. For instance, if a person gets cough, he should
know some basic information related to the sickness and symptoms. If the cough is
mild, there is no need to go to doctor and waste money and time. Here, the person needs
to decide to meet a physician or not. This app enables users in this direction. The
mobile system utilizes Android operating system technology, which can be widely
adopted in Sri Lanka. Evaluation of the system involved user feedback, highlighting its
efficacy as a decision support tool for predicting and addressing common health issues
in the country. The Disease Prediction Android App, crafted using Android Studio,
exemplifies the application of Machine Learning in healthcare, enhancing disease
detection and prediction. This user-friendly app enables individuals to input symptoms
and facilitating early disease prediction. Leveraging the Naive Bayes algorithm, the
application swiftly and accurately identifies ailments based on user-provided
symptoms. In essence, this project underscores the potential of technology-driven
solutions to address healthcare challenges in developing nations, specifically in the
context of disease prediction
Investigating the role of gesture modalities and screen size in an AR 3D game
Get PDFIn pursuit of immersive Augmented Reality (AR) Games, gesture interaction is considered a promising mode. On the other hand, despite the considerable effect of screen size on user experience and usability in game contexts, the effect is still under-explored in AR game contexts. This, in turn, sparks a specific research interest in the interaction between gesture modalities and screen sizes in AR games. This work contributes to a controlled study investigating the effect of two different gesture modalities (touch and tilt) on varying screen sizes in a custom-made AR game. Competence, engagement, fatigue, and user preference were evaluated using the combined effect of gesture modalities and screen sizes. The results revealed that gesture modalities affect game competence and fatigue while they had no significant impact on user engagement. Further analysis has revealed that touch outperforms tilt for target-selection tasks like destroying enemies while tilt outperforms touch for path-following tasks like turning a character. However, no significant effect was found on screen size, contradicting past studies that suggested that screen size has an effect on engagement, fatigue, and performance. The findings of the study could be useful for AR game designers to further develop usable and engaging AR games
Prevalence of gestational diabetes mellitus and associated risk factors in pregnant mothers: a hospital-based study
Get PDFGestational Diabetes Mellitus (GDM) is a form of diabetes that can occur during
pregnancy and is a global public health issue. Women with GDM face elevated risks of
pregnancy and delivery complications, and they and their children are more likely to
develop type 2 diabetes later in life. This study aimed to identify and analyze the risk
factors linked to GDM. It involved constructing a binary logistic regression model to
assess the likelihood of developing GDM based on specific risk factors. This study was
conducted using 200 data was randomly selected from the medical record of pregnant
mothers who were admitted at the Ashraff Memorial Hospital Kalmunai between
January 2021 to December 2022. The statistical analysis was performed using statistical
software (Minitab 21) and P<0.05 was considered significance for all analyzes. Out of
the 200 pregnant mothers studied, it was found that 15.5% (with a 95% confidence
interval ranging from 10.8% to 21.3%) had GDM. The chi-square test revealed
significant associations between prevalence of GDM and factors such as the mother's
age, blood glucose levels, body mass index (BMI), and a family history of diabetes (all
with p-values less than 0.05). Additionally, a binary logistic regression model was
created to assess the relationship between dependent and independent variables. The
results indicated that factors like age, parity (number of children), platelet count (PLT),
and a family history of diabetes were significant predictors of GDM outcomes (all with
p-values less than 0.05). By utilizing this binary logistic regression model, healthcare
professionals can gain a better understanding of the risk factors associated with
gestational diabetes mellitus
Relationship between institutional investors’ ownership and public companies’ performance in Sri Lanka
No full textInstitutional investors have become important players and stakeholders in the
financial industry today. They have also become a major influence in the equity
market. They have a substantial global presence in both established and developing
markets. The growing amount of corporate equity they hold demonstrates their
growing significance in corporate governance. When making decisions in the past,
these investors avoided direct involvement and instead used the exit strategy, selling
their shares if they didn't like the decisions made by management (Bathalaal, 1994).
They are more emboldened to speak up when they disagree with management since
they used their right to vote during company meetings, and as a result, they are
actively taking part in corporate decision-making. They do this in an effort to
persuade senior executives to consider the long-term interests of shareholders
(Coffee, 1991). The purpose of the study is to look at the relationship between firm
performance and institutional ownership. The annual reports and financial statements
of 100 companies from thirteen industries that were listed on the Colombo Stock
Exchange in Sri Lanka between 2017 and 2019 were used to compile the desired
goals and the relevant data. The institutional investor’s ownership has been
investigated as an independent variable, along with company performance (Return on
Assets and Return on Equity) and firm size (control variable). This study employed
correlation and regression, and the results revealed a significant positive relationship
between firm size and performance, whereas ownership by institutional investors has
a significant negative association with the company's performance. The study's
conclusions suggest that it is wise to support the adoption of corporate governance
principles in Sri Lankan public firms in order to motivate institutions to boost their
investments and implement efficient monitoring, which might improve company
performance
Association between temperature and life table development of fall armyworm, spodoptera frugiperda (lepidoptera: noctuidae) under control condition
No full textFall armyworm (FAW), scientifically known as Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae), is an important polyphagous pest that causes significant yield losses in various crop plants. The critical role of ambient temperatures in shaping the biology, distribution and population dynamics of FAW highlights the importance of temperature in its life cycle. The aim of this study was to evaluate the effects of different temperature conditions on the growth and development of FAW. The FAW larvae were collected from infested fields and maintained under three different temperature regimes: 25 °C (T25), 30 °C (T30), and 35 °C (T35), all within a controlled photoperiod of 12:12 h, maintained in an incubators. Comprehensive life and fertility tables were created using growth parameters. Analysis of variance revealed statistically significant differences (p < 0.05) in the mean duration of each life stage across the different temperature conditions. Of note, the adult stage had a cumulative mortality of 95% at T35, 61% at T30, and 64% at T25. The net reproductive rate (Ro) was quantified as 132.17, while the average generation time (Tc) was the shortest at T30 (32.31). The daily finite rate of increase (λ) was 1.1702 females per female per day, with a population doubling time of 3.004 days. In parallel, the intrinsic rate of natural increase (rm) was recorded as 0.1511 females per female per day. Importantly, the hypothetical female population in the F2 generation showed a significant increase at T30 (17468.20). In conclusion, the results clearly highlight the superior influence of a temperature of 30 °C (T30) on the growth and development of FAW compared to the other temperature conditions tested. These results are of significant practical importance in the context of pest control modeling and predictive forecasting