The current study was conducted to explore the antiemetic activity of ten aromatic medicinal plants viz., Carissa carandus L. (fruits), Chichorium intybus L (flowers), Cinnamum tamala L (leaves), Curcuma caesia Roxb (rhizomes), Lallemantia royleana Benth (leaves), Matricaria chamomila L (flowers), Piper longum L (fruits), Piper methysticum G. Forst (fruits), Piper nigrum Linn. (fruits) and Syzygium aromaticum (Linn.) Merr. & Perry (flowering buds) was studied using a chick emetic model. The ethanol extracts of these plants were administered at 150 mg/kg body weight orally. Domperidone was given at 100 mg/kg as a reference drug. All the extracts decrease in retches induced by copper sulphate pentahydrate given orally at 50 mg/kg body weight and showed comparable antiemetic activity with domperidone. Compound targeted antiemetic activity is further suggested. Aromatic plants have tendency to relief from nausea. Alpinea offinarum,Zingiber officinale, Mentha piperita, Menthaspicata and Lavandula angustifola,are aromatic plants reported to possess antiemetic activity. So, presentinvestigation was done to evaluate more aromatic plantsregarding their antiemetic activity. Results of the antiemeticactivity of the ethanol extracts of Carissa carandus,Chichorium intybus, Cinnamum tamala, Curcuma caesia,Lallemantia royleana, Matricaria chamomila, Piper longum, Piper methysticum, Piper nigrum and Syzygium aromaticum are shown in the Table. All the extracts showed antiemeticactivity comparable with domperidone. The % inhibition was recorded as Carissa carandus (68.29), Chichorium intybus (73.86), Curcuma caesia (89.97), Cinnamum tamala (70.64), Lallemantia royleana (83.61), Matricaria chamomila (59.92), Piper longum (81.65), Piper methysticum (80.03), Piper nigrum (89.48) and Syzygium aromaticum (87.81). The highest % inhibition was shown by Curcuma caesia (89.97) and the lowest by Matricaria chamomila (59.92), whereas domperidone showed 80.18 % inhibition of emesis.

Dr. salman ahmed

This paper aims to explore the supporting and inhibiting factors in the effort to integrate character education in akidah akhlak subjects at MIN 11 Aceh Tenggara. This study uses a qualitative method with a narrative approach and data collection techniques of interview, observation, and documentation; then, the data is analyzed using the methods developed by Miles and Huberman, namely data reduction, data presentation, and data verification. This study shows that the supporting factor for integrating character education in aqidah moral learning at MIN 11 Aceh Tenggara is the availability of learning media in the form of focus and Madrasah residents who work together to supervise all students, both outside and inside the Madrasah environment. The inhibiting factors are the limitations of Madrasah infrastructure in the form of no mosque or prayer room, family support, and social media and games that have an influence on student character.

Educare: journal of primary education

Nowadays, the Internet of Things (IoT) has been used widely in our daily day to day life, starting from health care devices, hospital management appliances to a smart city. Most of the IoT devices have limited resources and limited storing capability. All the sensed information must have to be transmitted and to store in the cloud. To make a decision and for making analysis all the data stored in the cloud has to be retrieved. Making certain the credibility and security of the sensed information are much necessary and very important for the use of IoT devices. We tend to examine the proposed technique to be much secure than the existing one. In IoT, if the security is not ensured, then it may result in a variety of unsought issues. This survey resembles the overall safety aspects of IoT and debates the overall issues in the security of IoT.

Jebin bose s

The wet coating of anhydrous borax powders with stearic acid (SA) to reverse their inherent hydrophilic surface properties was investigated. The coating procedure was based on the results from a previous study that revealed that the stearic acid solution (2 wt. % SA) mixed for 60 minute at 750 rpm on the magnetic stirrer was sufficient for the surface modification of anhydrous borax. For the experiments, stearic acid powders were first dissolved in water at 80 °C. The mixture obtained by adding anhydrous borax powders to this solution was vigorously mixed on a magnetic stirrer to initiation and completion the surface modification. Each of these solutions was then filtered using a filter paper to separate the undissolved particles, and the residue on paper was dried at 50 °C for 48 h until constant weighing was obtained. Wettability has been accepted as a key parameter for success in wet coating treatment. This parameter gained via the experimental characterization technique was used for an evaluation of the powder properties. The degree of wettability of anhydrous borax powders was measured and compared both after their surfaces were coated with stearic acid and after they were treated with water for a certain period of time in an aqueous environment. The stearic acid coating made the powder hydrophobic and this property was highly preserved after washing.

Journal of characterization

Introduction: The prevalence of oral hygiene behaviors (OHB) is very low among school children in Ethiopia. However, the determinants of student's readiness/intention to perform those behaviors have been remained unstudied. Objective: This study aimed to identify the determinants of oral hygiene behavioral intention (OHBI) among preparatory school students based on the theory of planned behavior (TPB). Methods and materials: An institution-based cross-sectional study was conducted among 393 students. A 98-item self-administered questionnaire was used to evaluate oral hygiene knowledge (OHK), oral hygiene behavior (OHB), and OHBI based on TPB variables [attitude (ATT), subjective norms (SN) and perceived behavioral control (PBC)]. Descriptive statistics and structural equation modeling analysis (SEM) were employed to confirm relationships and associations among study variables. A p-value of less than 0.05 and a 95% confidence interval were used to declare statistical significance. Results: A total of 393 students were participated with a response rate of 97.5%. The mean age of the participants (54% females) was 18 (± 1.3) with an age range of 16 to 24. The TPB model was well fitted to the data and explained 66% of the variance in intention. ATT (β = 0.38; 95% CI, (0.21, 0.64)), SN (β = 0.33; 95% CI, (0.05, 0.83)) and PBC (β = 0.29; 95% CI, (0.13, 0.64)) were significant predictors of OHBI, where ATT was the strongest predictor of OHBI. Conclusion: The TPB model explained a large variance in the intention of students to improve their OHB. All TPB variables were significantly and positively linked to stronger intent, as the theory suggests. Furthermore, these results suggest that the model could provide a framework for oral hygiene promotion interventions in the study area. Indeed, these interventions should focus on changing the attitudes of students towards OHB, creation of positive social pressure, and enabling students to control OHB barriers.

Kegnie shitu

PKN Subject is on one of lesson implemented on SD, SMP and SMA to apply student characters and to form the student to understand and love home land also understand global life. The research background of the low student achievement on study still using lecture method, giving assignments, answer and guestion on PKN subject. The purposes of this research: 1.how student achievement on PKN subject before using word sguare model. 2. How student achievement on PKN subject after using calassroom action rescarch with quantitative approach. The sample is the students of class III MIS NU 2 Pontianak.in order to get the data, researcher using observation shett, measurement technique and documentation study.The result concluded: 1.the student achievement before using word square model the average is 53 ( good category ) with KKM > 70 as 5 or 25% and students with KKM < 70 as 15 students or 75%. 2. The student achievement after using word square on cycle 1 is 68,5 ( Better category) with KKM 55%. On the other hands, cycle 11 is 82,5 (Great category ) with KKM 90%. Mata pelajaran PKn salah satu pelajaran yang diterapkan mulai dari SD, SMP dan SMA dengan membekali karakter dan membentuk peserta didik cinta tanah air dan paham dalam kehidupan yang serba global. Rumusan penelitian ini; 1) Bagaimanan hasil belajar siswa pada mata pelajaran pendidikan kewarganegaraan sebelum menggunakan model pembelajaran word square kelas 3 MIS NU 2 Pontianak. 2) Bagaimana hasil belajar siswa pada mata pelajaran pendidikan kewarganegaraan setelah menggunakan model pembelajaran word square kelas 3 MIS NU 2 Pontianak. Metode dan jenis penelitian ini menggunakan jenis penelitian tindakan kelas dengan pendekatan kuantitatif.Subjek penelitian ini adalah siswa kelas III MIS NU 2 Pontianak. Untuk mendapatkan data peneliti menggunakan lembar observasi, teknik pengukuran dan studi dokumentasi. Hasil dari penelitian ini yaitu: 1) Hasil belajar siswa pada Mata Pelajaran PKn sebelum menggunakan model pembelajaran Word Square diperoleh nilai rata-rata sebesar 53 (kategori cukup) dengan siswa yang tuntas mencapai nilai KKM ? 70 sebanyak 5 atau 25% dan siswa yang tidak tuntas dengan nilai KKM ? 70 sebanyak 15 siswa atau 75%. 2) Hasil belajar siswa pada Mata Pelajaran PKn setelah menggunakan model pembelajaran Word Square pada siklus I sebesar 68,5 (kategori baik) dan siswa yang mencapai KKM sebesar 55%. Sedangkan pada siklus II sebesar 82,5 (kategori sangat baik) dan siswa yang mencapai KKM sebesar 90.

Educare: journal of primary education

Artificial Intelligence (AI) has emerged as a transformative force in the healthcare domain, revolutionizing various aspects of medical research, diagnostics, treatment, and patient care. This paper provides an overview of recent developments and applications of AI in healthcare, highlighting its potential to enhance efficiency, accuracy, and accessibility in medical practices. The integration of machine learning algorithms, natural language processing, and computer vision techniques has enabled AI systems to analyze vast amounts of medical data, support clinical decision-making, and personalize treatment plans. Additionally, AI-powered technologies play a crucial role in predictive analytics, early disease detection, and the optimization of healthcare workflows. Despite the promising advancements, challenges related to data privacy, ethical considerations, and regulatory frameworks need to be addressed to fully harness the benefits of AI in healthcare.

Dhruvitkumar talati

The present review shares an updated data on the botany, distribution, traditional medicinal uses, phytochemistry and pharmacology of Phaseolus lunatus L. All provided information was obtained through Google Scholar, Pubmed, Sci Finder, Scirus, Web of Science and library search.

Dr. salman ahmed

Currently, the use of internet-connected applications for storage by different organizations have rapidly increased with the vast need to store data, cybercrimes are also increasing and have affected large organizations and countries as a whole with highly sensitive information, countries like the United States of America, United Kingdom and Nigeria. Organizations generate a lot of information with the help of digitalization, these highly classified information are now stored in databases via the use of computer networks. Thus, allowing for attacks by cybercriminals and state-sponsored agents. Therefore, these organizations and countries spend more resources analyzing cybercrimes instead of preventing and detecting cybercrimes. The use of network forensics plays an important role in investigating cybercrimes; this is because most cybercrimes are committed via computer networks. This paper proposes a new approach to analyzing digital evidence in Nigeria using a proactive method of forensics with the help of deep learning algorithms - Convolutional Neural Networks (CNN) to proactively classify malicious packets from genuine packets and log them as they occur.

Dr. chandrashekhar uppin

The COVID-19 pandemic and related lock downs have accelerated the need for online and remote teaching within university settings. However, due to the abrupt nature of the pandemic, many academic staff were not prepared for this forced transition. This study aimed to understand how the pandemic affected academics at a New Zealand university, with regards to their transition to emergency remote teaching. Specifically, it explores the challenges as well as benefits academics experienced during this transition. Recommendations for future online learning are also made. Academic staff (N 67) at a New Zealand University completed an anonymous online survey. Quantitative data were analyzed statistically using descriptive and inferential statistics, while qualitative data were analyzed thematically. Major challenges experienced included miscommunication from the university, concerns about student access to technology, finding a quiet space to work, lack of digital competence skills, too much screen-time, managing work hours, and work/ life balance. Benefits included enhanced flexibility, enhanced teacher creativity, increasing autonomy of learners, and reduced commute time. Looking forward, academic staff desired future teaching to include blended learning and virtual immersion. New strategies of working remotely are being explored to facilitate teaching and learning while catering to the preferences and skills of both educators and students. Our findings honor the considerable agility of academic staff who sought to sustain and enhance excellence in remote education. At an institutional level our findings point to the need for staff to be supported by their institutions as they further refine their work within new-found spaces

Gwen erlam

Improving the agricultural productivity is an imminent need to meet the food requirement of constantly growing population rate. It can be gracefully satisfied if the farming process is integrated through technologies such as big data and IoT. The integration of agricultural processes with modern technologies has emerged as the smart agriculture technology. This research work is focused on proving the suitability of the big data analytics for smart agricultural processes in terms of increasing production and quality of yields with less resources and overhead. This research paper expounds the extensive review carried out on the related works in smart agricultural farming, challenges in implementing the smart farming technologies at large scale, followed by the conceptual framework model for the effective implementation of big data together with IoT devices in smart farming.

Dr h shaheen

The aim of the study was to explore the inhibition and modulation of calcium oxalate monohydrate crystals into calcium oxalate dihydrate by phytic acid. The study was carried out on glass slides using phytic acid (1 - 5%) solutions. All tested solutions inhibited the growth and modulated calcium oxalate monohydrate crystals. Donuts, rosettes and X-shape crystals of calcium oxalate monohydrate along with their defected forms were observed. The presence of calcium oxalate dihydrate crystals as elongated rods and tetragonal bipyramidal crystals revealed the modulated forms of calcium oxalate monohydrate. Smaller zones of nucleation are declared as general patterns of growth inhibition. This study gives valuable information about calcium oxalate crystals' inhibition and modulation patterns. Further studies are required to confirm the results of the present study.

Dr. salman ahmed

Since the WHO declared COVID-19 a pandemic on March 11, 2020, all countries worldwide have taken precautions to combat this pandemic, except for Yemen. The civil war and resulting humanitarian crises have diverted the attention of the Yemeni people and authorities away from COVID-19, potentially leading to the escalation of the pandemic. Following the initial denial, the internationally recognized government and the de facto authority of the Houthis acknowledged the first COVID-19 cases on March 11, 2020 and May 13, 2020, respectively. With only half of the Yemeni hospitals and medical facilities being fully operational, the authorities and humanitarian groups are working together to end the crisis. Due to paucity of information on the real number of cases in the country attributed to various reasons, no one can predict the future in this country, which will be most likely worse unless the civil war stops, and the humanitarian groups with the authorities need to work hard to strengthen the health system to prepare it for the current and all upcoming health crisis and pandemics.

Karishma

Avian leukosis virus is recognized as an important viral pathogen in the poultry industry, resulting in salient severe economic losses due to reduced production, uneven flock growth rates, reduced growth, and immunosuppression which predispose affected birds to other infections. This study examined the seroprevalence of avian leukosis virus (ALV) in local chickens (LC) in 5 different live bird markets (LBMs) in Kaduna Metropolis. A total of 276 sera were tested for ALV p27 antigen using enzyme-linked immunosorbent assay (ELISA). An overall seroprevalence of 28.3% (78/276) was recorded in the study. At the market level, the seroprevalence of 35% (21/60), 30% (18/60), 32% (16/50), 28.6% (16/56), and 14% (7/50) were recorded for Sabon Tasha, Central market, Railway station, Kawo and Sokoto Road LBMs respectively. With regards to sex, female LC showed a significantly higher prevalence of 30.5% (46/105) compared to male chickens 26.9% (46/171) with no significant difference (P > 0.05) observed. This study established the presence of antigen to ALV in local chickens sold in LBMs. We recommend surveillance and further studies on the isolation, molecular characterization and pathogenicity of ALV in the study area.

Bitrus inuwa

We present a series of large-eddy simulations to systematically investigate the impact of debris accumulation on the hydrodynamics and power production of a utility-scale marine hydrokinetic (MHK) turbine under various debris loads lodged on the upstream face of the turbine tower. The turbine blades are modeled using turbine resolving, actuator line, and actuator surface methods. Moreover, the influence of debris on the flow field is captured by directly resolving individual logs and employing a novel debris model. Analyzing the hydrodynamics effects of various debris accumulations, we show that an increase in the density of debris accumulation leads to more flow bypassing beneath the turbine blade. This, in turn, reduces the flow momentum that reaches the MHK blades at the lower depths, inducing significant fluctuation in power production. Further, it is shown that debris-induced turbulent fluctuations contribute to significant variability in the MHK turbine’s power production.

Hossein seyedzadeh

A major hallmark of Parkinson's disease is loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc). The pathophysiological mechanisms causing this relatively selective neurodegeneration are poorly understood, and thus experimental systems allowing to study dopaminergic neuron dysfunction are needed. Induced pluripotent stem cells (iPSCs) differentiated toward a dopaminergic neuronal phenotype offer a valuable source to generate human dopaminergic neurons. However, currently available protocols result in a highly variable yield of dopaminergic neurons depending on the source of hiPSCs. We have now developed a protocol based on HBA promoter-driven transient expression of transcription factors by means of adeno-associated viral (AAV) vectors, that allowed to generate very consistent numbers of dopaminergic neurons from four different human iPSC lines. We also demonstrate that AAV vectors expressing reporter genes from a neuron-specific hSyn1 promoter can serve as surrogate markers for maturation of hiPSC-derived dopaminergic neurons. Dopaminergic neurons differentiated by transcription factor expression showed aggravated neurodegeneration through α-synuclein overexpression, but were not sensitive to γ-synuclein overexpression, suggesting that these neurons are well suited to study neurodegeneration in the context of Parkinson’s disease.

Sameehan mahajani

This paper compares different optimizable machine learning classification models to predict eight types of anemia from complete blood count (CBC) data. For the research, we used a publicly available Kaggle dataset containing 1281 observations, 14 predictors, and the diagnosis as the categorical target variable with nine categories (eight types of anemia and the healthy category). First, we examined the dataset and observed the histograms of some of the predictors. We compared the values of predictors of observations with no anemia to the observations where any anemia was diagnosed. Next, we used MATLAB R2024a to train and test nine optimizable machine-learning classification models. These models were Ensemble, Tree, SVM, Efficient Linear, Neural Network, Kernel, KNN, Naïve Bayes, and the Discriminant. Bayesian optimization was used to optimize the hyperparameters of all these models. We used 90% of observations for training and 10% of observations for testing. During the training, 10-fold cross-validation was used to prevent overfitting. The results showed the best accuracy was reached with the Ensemble classification model using the bag ensemble method (validation accuracy: 99.22%, test accuracy: 100%). Finally, we inspected our best classification model in more detail. We calculated the permutation feature importance to determine the contribution of each predictor to the final model. The results showed 6–7 important predictors, while the most important feature was the amount of hemoglobin.

Ladislav végh

Neuroblastoma is the most prevalent extracranial solid tumor in pediatric patients, originating from sympathetic nervous system cells. Metastasis can be observed in approximately 70% of individuals after diagnosis, and the prognosis is poor. The current care methods used, which include surgical removal as well as radio and chemotherapy, are largely unsuccessful, with high mortality and relapse rates. Therefore, attempts have been made to incorporate natural compounds as new alternative treatments. Marine cyanobacteria are a vital source of physiologically active metabolites, which have recently received attention owing to their anticancer potential. This review addresses cyanobacterial peptides' anticancer efficacy against neuroblastoma. Numerous prospective studies have been carried out with marine peptides for pharmaceutical development, including research on anticancer potential. Marine peptides possess several advantages over proteins or antibodies, including small size, simple manufacturing, cell membrane crossing capabilities, minimal drug-drug interactions, minimal changes in blood-brain barrier (BBB) integrity, selective targeting, chemical and biological diversities, and effects on liver and kidney functions. We discussed the significance of cyanobacterial peptides in generating cytotoxic effects and their potential to prevent cancer cell proliferation via apoptosis, the activation of caspases, cell cycle arrest, sodium channel blocking, autophagy, and anti-metastasis behavior.

Dr. salman ahmed

Objective: This study was conducted to investigate traditional beliefs and practices of women regarding care of the mother and the infant during pregnancy, in childbirth, and in the postpartum period. Methods: This was a descriptive, cross-sectional study conducted at a public hospital in Istanbul. The data collected consisted of socio-demographic and obstetric characteristics, and responses to questions about some traditional customs regarding pregnancy, delivery, and the postpartum period. Results: In our research, some non-harmful cultural practices were found, such as the belief that to have a clever and beautiful baby the mother should eat fruit; that to have a healthy and peaceful pregnancy, the mother should not look upon ugly things; the mother should indulge her food cravings; and to have an easy birth, the mother should walk and focus on prayers. On the other hand, we also found beliefs that could be harmful, such as wiping the mouth of a baby with a date before breastfeeding, and practices believed to be protective that could cause harm, such as putting a knife under the baby’s bed, fastening a safety pin to the baby’s clothes, and for the mother and child to remain at home for 40 days. Conclusion: While non-harmful and beneficial practices related to maternal and infant health should be accepted and supported as a part of our cultural richness, practices that could be harmful should be prevented in pregnancy classes or with training upon hospital discharge

Reyhan aydin doğan

Indian Economy is the world's 06 th largest economy (2021 Nominal GDP) and 03 rd largest by purchasing power parity (2021 PPP). Salaried workers are a consistent group of tax paying citizens that give roughly 12% of overall revenue to a government through income tax. Due to which tax planning has assumed special importance for salaried individuals. All taxpayers in India have a variety of tax saving choices. These choices provide a variety of exclusions and deductions that help to reduce the total tax burden. Deductions are provided from Sections 80C through 80U, and qualifying taxpayers can claim them. Hence it is essential for the individual tax payer to know all their possible tax regulations and for tax compliance. It is totally legal and, in fact, a wise option when tax planning is done within the boundaries set by the relevant authorities. However the salaried individuals are not able to plan their taxes which results in opting for the wrong investment options. The objective of the study is to determine the level of awareness among the salaried individual on several tax planning methods offered on professional tax under the income tax act and to identify the factors influencing the tax planning behaviour of the salaried individuals..

Sabir mujawar