Background: Cannabis sativa has garnered significant attention due to its complex phytochemistry and diverse pharmacological properties. Given the rising interest in medicinal cannabis, understanding its physicochemical properties is crucial for drug development, quality control, and abuse prevention. This study aimed to analyze its phytoconstituents, with a focus on the isolation and profiling of cannabinoids. Methods: Fresh C. sativa leaves were macerated in ethanol to obtain a crude extract, which underwent phytochemical screening to detect alkaloids, flavonoids, cardiac glycosides, terpenes, steroids, and resins. Thin-layer chromatography (TLC) was performed using a n-hexane/diethyl ether (8:2) ratio as the mobile phase to separate cannabinoids, with visualization under UV light. Column chromatography further purified the extract, and subsequent TLC confirmed cannabinoid-rich fractions. Hydrogen peroxide-modified TLC was employed to assess oxidation effects on cannabinoid stability. Results: Phytochemical screening confirmed the presence of alkaloids, flavonoids, terpenes, and resins, while saponins and tannins were absent. TLC analysis revealed distinct Rf values for tetrahydrocannabinol (THC = 0.94) and cannabidiol (CBD = 0.90), with color differentiation indicating successful separation and a more polar nature of CBD. Column chromatography yielded enriched fractions, validated by TLC. Hydrogen peroxide exposure altered Rf values of 0.78 to 0.8, suggesting oxidative degradation. The study identified THC and CBD as dominant markers, alongside minor cannabinoids, reinforcing C. sativa’s complex chemical profile. These findings give clues to further research into standardized extraction protocols and stability testing to optimize medicinal applications of the plant and its phytoconstituents. Conclusions: This study highlights the efficacy of TLC and column chromatography for cannabinoid isolation and profiling. The presence of THC, CBD, and other bioactive compounds underscores C. sativa’s dual therapeutic and psychoactive potential.

Karishma

Newcastle Disease Virus (NDV) constitutes a major constraint to the poultry production system in Nigeria. This study was carried out to investigate the seroprevalence of NDV antibodies in local chickens (Gallus domesticus) slaughtered in five different live bird markets (LBMs) in Kaduna metropolis, Nigeria. Three hundred blood samples were collected and screened for antibodies against NDV using Haemagglutination Inhibition (HI). An overall seroprevalence rate of 23% (95%:CI18.5-28.0) was recorded in this study. Seroprevalence based on different LBMs revealed a higher prevalence of 28.3% (95% : Cl 18.0-40.7) in Sabo market, followed by Sokoto road market 26.7% (Cl:16.7-38.9), Kawo market 18.3% (95% Cl: 10.0-29.6), Railway market 13.3% (Cl:6.4-23.5), and the lowest prevalence was recorded in central market 11.7% (Cl:5.2-21.7). The difference in seroprevalence among the LBMs was not statistically significant (p > 0.05). Higher seroprevalence of NDV antibodies in female birds 30.5 % (Cl: 24.1-37.6) was recorded compared to male 13.9% (Cl: 8.3-21.4). The study indicated that NDV is endemic in the population. LBMs location had no significant influence on the seroprevalence of NDV in the study area. The difference in seroprevalence between sexes was statistically significant (p < 0.05). Therefore, this study demonstrated the need for a regular strategic vaccination programme against NDV in local chickens in Kaduna metropolis.

Bitrus inuwa

Melioidosis is an infection that causes high morbidity and mortality. Predisposing risk factors include diabetes mellitus (DM) and immunocompromised state. We report a case of septic shock secondary to bacteremia caused by Burkholderia pseudomallei in a patient who is supposed to be previously healthy and subsequently diagnosed with DM and glucose-6-phosphate dehydrogenase (G6PD) deficiency. He completed 17 days of intravenous antibiotics followed by a 12-week course of oral trimethoprim/sulfamethoxazole. We postulate that G6PD deficiency could be a risk factor for melioidosis.

Karishma

Internet of Things (IoT) enhances the global connectivity to all the remote sensing devices. It enables the connectivity of communication and processing the real-time data that has been collected from an enormous number of connected sensing devices. There is an increase in the IoT technology that leads to various malicious attacks. It is more important to overcome the malicious attacks, mainly to stop attackers or intruders from taking all the control of devices. Ensuring the safety and accuracy of the sensing devices is a serious task. It is very much important to enabling the authenticity and integrity to obtain the safety of the devices. Dynamic tree chaining, Geometric star chaining and Onion encryption are the three solutions that has been proposed in this project for in order to enable authenticity and integrity with information hiding for secure communication. The simulation results are driven displays that the proposed system is very stable and much better than other existing solution in means of security, space and time.

Jebin bose s

In the modern world, Tuberculosis (TB) is regarded as a serious health issue with a high rate of mortality. TB can be cured completely by early diagnosis. For achieving this, one tool utilized is CXR (Chest X-rays) which is used to screen active TB. An enhanced deep learning (DL) model is implemented for automatic Tuberculosis detection. This work undergoes the phases like preprocessing, segmentation, feature extraction, and optimized classification. Initially, the CXR image is preprocessed and segmented using AFCM (Adaptive Fuzzy C means) clustering. Then, feature extraction and several features are extracted. Finally, these features are given to the DL classifier Deep Belief Network (DBN). To improve the classification accuracy and to optimize the DBN, a metaheuristic optimization Adaptive Monarch butterfly optimization (AMBO) algorithm is used. Here, the Deep Belief Network with Adaptive Monarch butterfly optimization (DBN-AMBO) is used for enhancing the accuracy, reducing the error function, and optimizing weighting parameters. The overall implementation is carried out on the Python platform. The overall performance evaluations of the DBN-AMBO were carried out on MC and SC datasets and compared over the other approaches on the basis of certain metrics.

Dr h shaheen

As we aware diabetes is not only one kind of symptomatic disease but its occurrence spread through the various metabolic channels and hence raises other disorders. The prolonged symptoms of diabetes also cause the complications of eyesight, Night blindness, kidney failure, and other autoimmuno dysfunction including sexual dysfunction. In those symptomatic diseases various drugs are used to treat the diabetes such as biosimilar therapy including use of insulin and insulin analogues, oral hypoglycaemic agents and various other complementary medicines. As herbal remedies i.e. M charantia Linn. (Bitter Gourd) are commonly known as fruit vegetables. The Leaves, Seeds, Roots, Fruits and the stem part of the plants are medicinally used in different diseases. It is most effectively used to treat the acidic condition of gastrointestinal tract. M.charantia is also called the oxygen radical scavenger, which takes part into metabolic pathway. Due to the oxygen radical scavenging activity of GSH it directly expedites the ROS neutralization and the repair of ROS-induced damage which is important to neutralize the acidic condition of gastrointestinal tract.The present investigation was carried out to study the characterization of present antidiabetic compound having different solvent extract of M.charantia in various solvent system. The overall conclusion suggested that the extracted compound shows the antidiabetic and diuretic properties. The total unknown protein concentration was 21.01 µg/mL which is similar with standard antidiabetic drug and the slope consists of 0.0314 with the line of intercept 0.081, which has been elaborated in results and conclusion.

Dr. wahul umesh b

Numerous initiatives to rely on new renewable energy sources, such solar electricity, have been sparked by the increased interest in global warming. With an increase in home photovoltaic (PV) panels that are available to the public, more precise calculations of energy generation are now possible. Segmenting satellite images offers a straightforward and inexpensive way to categorize solar panels..This work suggests a method for classifying and segmenting solar panels that combines the watershed algorithm with deep learning approaches. First, a Convolutional Neural Network (CNN) architecture with the ResNet, EfficientNet, and Inception architectures is used for classification. Through the fine-tuning of pre-trained networks on a heterogeneous dataset of solar panels, transfer learning improves performance. The categorization model recognizes solar panels in a variety of settings with accuracy, making maintenance and monitoring easier. After classification, the watershed method uses intensity gradients to precisely delineate solar panels from the background. Tasks like defect detection and layout optimization are made easier when deep learning-based classification and watershed segmentation are combined. The outcomes of the experiments show how well the suggested method performs in terms of segmenting and classifying solar panels under various circumstances. A flexible automated solar panel management solution is provided by the combination of deep learning and the watershed algorithm, which promotes increased sustainability and efficiency in solar energy systems.

Bakka arun kumar

Creativity is regarded as one of the most complex of human behaviors. It can be influenced by a wide array of social, developmental and educational experience that leads to creativity in different ways in a variety of fields (Runco & Sakamoto, 1999). Opinions about the origin of creativity vary, and none of them explains the creative process completely. Creativity can be seen as the following: a divine quality, serendipitous activity, ‘planned luck’, endurance and ‘method’ (Cook, 1998a: p.6). Petrowski (2000: p.305) stated that “creativity research belongs to the baby-boom generation, beginning in earnest when Guilford directed the American Psychological Association in his 1950 presidential address to focus on this important but neglected area”. The existence of creativity as a modern term emerged from the results of the pioneering efforts of Guilford (1950) and Torrance (1962, 1974). Guilford and Torrance were psychometric theorists and they attempted to measure creativity from a psychometric viewpoint (Sternberg, 2006).

Mukhles m. al-ababneh

The latest phase of capitalist expansion is called “globalisation”. That no state is an autarky but enjoys comparative advantage over others with certain resources and that free trade among these states would work for mutual benefit is the essence of it. Consequently, it advocates the minimization of the governmental intervention in economic affairs and encourages free play of market forces to foster economic development. The argument that this rationale is also applicable to higher education is increasingly gaining currency. But this paper attempts to problematise such a proposition and in contrary argues that this may prove inimical to national development. Education and especially higher education is considered to be one of the factors that help state to promoting national development. However, apologists of globalisation call for its commercialization and argue for the “withdrawal of the state” from this realm. This has only resulted in mystifying profound class inequalities within and without state. Higher education in India is not immune to this ideology in the guise of good economics. It is being structured in such a fashion since 1991 that it has been primarily coupled with the process of economic liberalization and privatization. International financial institutions like World Bank, IMF, GATT, GATS, etc are its votaries. Education was acknowledged as one of the key sectors to be traded. As a result, higher education as a “social good” is fast shifting to being a commodity in the market.

Dr gedam kamalakar

This study was conducted to optimize the integration of solar-photovoltaic-distributed energy resources (SPVDERs) within the Nigerian power system networks using an AI-based Particle Swarm Optimization (PSO) Algorithm. By employing a mixed research method, primary and secondary data were gathered to calculate flow analysis, NR method's equations, PSO's position update model, particle swarm optimizer algorithm, and application modeling including Solar-PV DER modeling. The AI-based PSO algorithm design was developed for optimizing SPV-DER integration in Nigerian power system networks, and key parameters and variables that needed consideration were identified. The study also established how the performance of the AI-based PSO algorithm could be evaluated and compared with other optimization techniques for SPV-DER integration within Nigerian power system networks. The study's results showed that voltage limits were within acceptable ranges, and solar power contributions were estimated at 880.10MW with 46,718 panels needed. The study concluded and recommended that investing in AI-powered tools for efficient power distribution; monitoring and resource optimization for sustainable energy sources would optimize performance and unleash Nigeria's sustainable energy potential.

Fxintegrity publishing

Self-medication of antibiotics is an irrational use of drugs, contributing to microbial resistance, increasing health care cost and higher mortality and morbidity. This study was aimed to assess self-medication with antibiotics without a medical prescription in the community of Libya. This is a cross-sectional study conducted from June to December, 2022 and the total number of participants was 200. The design of the study and sample size were modified according to the proficiency of pharmacists and the medical and non-medical population of Libya. The questionnaire was developed in English and Arabic language and was distributed through social media platforms. The questions were used after a thorough literature search and assessing the validity and reliability. The significant signs regarding reasons for the treatment by self-medication drugs of antibiotics, because of its various drugs of antibiotic by pharmacist (n = 80, 40.0%) and family (n = 90, 45.0%) compare with experience and physicians by used prescription was 13 (06.50%) and significant sings regarding by nasal congestion self-medication of various antibiotics (n = 100, 50.0%). This sign must be practiced based on a previous physician’s prescription. The antibiotics are often self-administered as patient feel that they will save money and time but this can lead to substantial adverse drug reaction, antibiotic resistance, treatment failure and drug-related toxicity. This study respondent's medical and non-medical public of Libya who should be relatively informed and educated about the risk of treatment by self-medication of antibiotics with the development of resistance.

Mediterranean journal of pharmacy and pharmaceutical sciences

Background: The significance of healthcare wastes (HCWs) consists in their hazardous component, which constitutes real danger to public health. In Nigeria, healthcare waste management (HCWM) has remained a problem yet to be properly recognized and so addressed. The study aimed to sensitise health workers and the public on the need for proper management of HCWs, considering the public health implications of not doing so. Methods: The waste management systems of ten healthcare facilities (HCFs) were assessed, using a modification of the WHO rapid assessment tool. In each HCF, segregated wastes were collected daily for ten days and quantified by weighing, using a spring balance. Results: Administratively, the HCWM system was poor in the ten HCFs (40.6%). 70% of them had satisfactory waste segregation, 81%, good waste treatment, and 26.7% adequate transportation methods for waste. None of the HCFs had budget allocation for HCWM, and 90% had inadequate storage facilities. Mean waste generation was 1.81 kg/day, 0.23 kg/patient/day, 0.16 kg/bed/day, and proportion of infectious wastes 16.8%. Correlation between the number of patients and proportion of infectious waste, was positive, strong and significant (r=0.80, p=0.01), and between bed occupancy rate and proportion of infectious waste, was positive too, but weak, and insignificant (r=0.34, p=0.34). Conclusions: In view of the identified weaknesses of the ten HCFs in HCWM, budget allocations for HCWM, improving waste storage facilities and transportation, with strengthening of waste segregation, collection, and treatment, would help to ensure adequate HCWM in the HCFs.

Emmanuel umegbolu

Work life balance of employees has become an important issue which discusses mainly about their carrer development and the family care, it is necessary to know how the employees balance the demand for their profession and also their domestic compulsions. Professional life is hat the aim to grow and earn respect in the workplace and the society they live-in. Personal life means taking care of family, spouse, children, health and spending the available leisure time effectively. According to work foundation, the term work-life balance is about individuals having a measure of control over when, where and how they work, leading them to be able to enjoy an optimal quality of life. It is defined as establishing a successful balance between working obligations and personal commitments. Work – life balance for teaching professional has become a challenge in recent years. Teachers work load demands their time both in the institution and also extends to their home. Teaching professionals need to focus on soft skills and life skills so that they should aim at producing good citizens for the country.

Dr.n.s.lissy

Scholars who apply artificial intelligence to political questions seek, most generally, to expand the scope and relevance of political model analysis. By incorporating the effects of variable human notions, traditions, and meanings, they seek to humanize political models. Most early applications of artificial intelligence in political science research address substantive issues pertaining to political decision making. Most of these works apply production-system technology to construct choice models in for eign-policy decision contexts. In recent years, political applications have begun to diver sify. Today, lively research efforts flourish in widely varied application areas, such as computational text analysis, logic programming, computer learning, and conflict sim ulation. The works reviewed here constitute the early steps of a nascent program of study. Much remains to be accomplished. Nevertheless, the efforts conducted thus far suggest many potentially fruitful research avenues. Youth are the most essential and promising segment of every country’s population. India has a larger advantage over other countries in terms of becoming a global leader because we effectively tap into the youth’s potential. Quality education is the only way to achieve this. With artificial intelligence’s potential growth in India, now is the ideal time to incorporate AI in education to reap its benefits and prepare India’s young for the future. Artificial intelligence has great potential in India. India’s AI technology has the potential to make it a world leader in artificial intelligence. In India, AI technology is used effectively in nearly every area, including agriculture, healthcare, education, infrastructure, transportation, retail, manufacturing, and

Dr gedam kamalakar

Mushrooms and fenugreek are widely used to reduce hyperglycemia, and fenugreek is also used as a culinary ingredient to enhance flavor and aroma. This study is aimed at investigating the underlying mechanisms of the hypoglycemic effects of mushrooms and fenugreek in a Type 2 diabetic rat model. Adenosine monophosphate (AMP)–activated protein kinase (AMPK) functions to reduce hyperglycemia through insulin-independent pathways and protects beta-cells. Diabetic model rats were administered standard diets supplemented with 5% oyster mushroom powder (mushroom-treated (MT) group) and 5% fenugreek seed powder (fenugreektreated (FT) group) for 8 weeks. The results showed improvements in both glycemic and lipid profiles, with both oyster mushroom and fenugreek enhancing the phosphorylation of AMPK in muscle tissue. However, no effect on insulin secretion was observed. These findings suggest that both substances reduce hyperglycemia through an insulin-independent pathway. In silico analysis of both mushroom and fenugreek seed extracts revealed bioactive compounds having a strong binding affinity to α-glucosidase, which suggests mushroom and fenugreek supplements might control postprandial blood glucose levels.

Arafat hassan razon

This research was carried out at SDS Harapan Jakarta. This research aims to unravel the implementation of character education’s values through thematic subject, specifically on Indonesian Language Content. This research uses qualitative descriptive approach to gather research data deeply and thoroughly regarding character education’s value. Data collection was done using interviews, observation, and documentation. Miles and Huberman method was used to analyze data collected with the process of data collection, condensation, data display, and data verification. Triangulation was used to verify the validity of the data. The result of this study revealed that 1) The implementation of character education values in the content of Indonesian Language learning in Class 3 is implemented through reading and writing activities that prioritize the five main values in education according to the Minister of Education and Culture. 2) There are still less-effective efforts to achieve learning objectives. 3) There is still a lack of learning innovations carried out to achieve learning goals. 4) No lesson plans that are not made routinely as a means of evaluating learning. 5) There is still a need for improvement in the application of character education in Indonesian content that is linked to students' real experiences, both through online and offline learning.

Educare: journal of primary education

Introduction: Mental illness is a global issue that affects various population groups, including university students. Gaining insights into students' perspectives on mental illness plays a vital role in fostering mental health awareness and combating stigma in educational environments Purpose: The present study aimed to investigate Vietnamese undergraduate students’ knowledge, perceptions, and attitudes of mental illness by focusing on the dimensions: (i) the level of knowledge students possess about the causes and manifestations of mental illness, and (ii) their attitudes towards individuals experiencing mental health problems. Methodology: Using a descriptive cross-sectional design, this study involved 350 undergraduate students from five universities in Ho Chi Minh City, Vietnam. Data collection was conducted between June and July 2024 and utilized the Perception Towards Persons with Mental Illness (PWMI) Scale adapted from previous studies. Data analysis was performed using the Statistical Package for Social Science software, version 25 (IBM SPSS, Chicago, IL, USA). Results: The results indicated that approximately 80.6% knew about mental illness, and 70.5% perceived mental illness as a common or quite common phenomenon in Vietnam. Regarding the etiology of mental illness, a significant majority identified "bad things happening to you" as a cause (73.3%), followed by substance abuse (51.4%) and brain disease (50.0%). The findings also revealed that, despite some positive perceptions and attitudes, many responses clustered around the neutral option, particularly for controversial or personal items. Conclusions: The findings of this study underscore the need for targeted educational interventions to foster more informed and compassionate attitudes towards individuals with mental illness among undergraduate students.

Le minh tien

In the teaching and learning process, teachers are required to be able to carry out their role to the fullest as a motivator and initiator in an effort to maintain and at the same time increase the enthusiasm of students to learn. Especially in the Covid-19 pandemic situation which requires educational institutions to carry out online learning. This study aims to discuss the teacher's role as a motivator and the teacher's role as an initiator in improving the quality of student learning in online learning at Madrasah Ibtidaiyah Ma'arif Condro Jember. This research uses qualitative research methods and the type of research is a case study. Data collection techniques using observation, interviews and documentation. The validity of the data using source triangulation and technical triangulation. Meanwhile, data analysis uses data condensation, data presentation and verification/conclusion. The results of this study indicate: 1) The teacher's role as a motivator in improving the quality of learning in online learning, namely: providing opportunities for students to play an active role in learning, providing reinforcement, praise or verbal appreciation, teachers listening to students' concerns and wishes to bond. good relationship between teachers and students. 2) The role of the teacher as an initiator in improving the quality of learning in online learning, namely: utilizing information and communication technology such as Whatsapp, Facebook, Google Meet and Google Form. Dalam proses belajar mengajar, guru dituntut untuk mampu melaksanakan perannya secara maksimal menjadi motivator dan inisiator dalam upaya menjaga dan sekaligus meningkatkan semangat belajar peserta didik. Terlebih dalam situasi pandemi Covid-19 yang menuntut lembaga pendidikan untuk melaksanakan pembelajaran secara Daring. Penelitian ini bertujuan untuk membahas tentang peran guru sebagai motivator dan peran guru sebagai inisiator dalam meningkatan kualitas belajar peserta didik pada pembelajaran daring di Madrasah Ibtidaiyah Ma’arif Condro Jember. Penelitian ini menggunakan metode penelitian kualitatif dan jenis penelitiannya adalah studi kasus. Teknik pengumpulan data menggunakan observasi, wawancara dan dokumentasi. Keabsahan data menggunakan triangulasi sumber dan triangulasi teknik. Sedangkan analisis data menggunakan kondensasi data, penyajian data dan verifikasi/kesimpulan. Hasil penelitian ini menunjukkan: 1) Peran guru sebagai motivator dalam meningkatkan kualitas belajar pada pembelajaran daring yaitu: memberikan kesempatan kepada peserta didik untuk berperan aktif dalam pembelajaran, memberikan penguatan, pujian atau apresiasi secara verbal, guru mendengarkan keresahan dan keinginan peserta didik agar terjalin ikatan yang baik antara guru dan peserta didik. 2) Peran guru sebagai inisiator dalam meningkatkan kualitas belajar pada pembelajaran daring yaitu: memanfaatkan teknologi informasi dan komunikasi seperti Whatsapp, Facebook, Google Meet dan Google Form.

Educare: journal of primary education

Various types of security attacks are normal in vehicular communication networks. The current study uses a support vector machine to implement a Point to Point Critical Path Monitoring (P2PCPM) based Denial of Service (DOS) Attack detection technique for Vehicular Communication Network (VCN) resource management. Greatest quality of P2PCPM is that it eliminates attacked nodes from the network for the smooth process of vehicular communication. This scheme works well in terms of accuracy as well as attack detection rate. The whole simulation is made and tried by utilizing MATLAB Software. Simulation result shows 99% accuracy in case of security attack detection as well as reduced training and testing error upto 2%. Experimental results indicate that this scheme has a great efficiency and works well up to 1000 nodes, which is the limitation of current implementation. In future, simulation test may be done for unlimited nodes using similar or other techniques of attack detection.

Vartika agarwal

Biological information processing networks rely on allosteric protein switches that dynamically interconvert biological signals. Construction of their artificial analogues is a central goal of synthetic biology and bioengineering. Receptor domain insertion is one of the leading methods for constructing chimeric protein switches. Here we present an in vitro expression-based platform for the analysis of chimeric protein libraries for which traditional cell survival or cytometric high throughput assays are not applicable. We utilise this platform to screen a focused library of chimeras between PQQ-glucose dehydrogenase and calmodulin. Using this approach, we identified 50 chimeras (approximately 23% of the library) that were activated by calmodulin-binding peptides. We analysed performance parameters of the active chimeras and demonstrated that their dynamic range and response times are anticorrelated, pointing to the existence of an inherent thermodynamic trade-off. We show that the structure of the ligand peptide affects both the response and activation kinetics of the biosensors suggesting that the structure of a ligand:receptor complex can influence the chimera's activation pathway. In order to understand the extent of structural changes in the reporter protein induced by the receptor domains, we have analysed one of the chimeric molecules by CD spectroscopy and hydrogen-deuterium exchange mass spectrometry. We concluded that subtle ligand-induced changes in the receptor domain propagated into the GDH domain and affected residues important for substrate and cofactor binding. Finally, we used one of the identified chimeras to construct a two-component rapamycin biosensor and demonstrated that core switch optimisation translated into improved biosensor performance.

Cagla ergun ayva