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INTRAMURAL AEROMYCOLOGICAL STUDY OF GOVERNMENT ADIWASI GIRLS HOSTEL OF DESAIGANJ WADSA, DISTRICT-GADCHIROLI MAHARASHTRA
Get PDFThis study investigates the Intramural aeromycoflora of Government Adiwasi girlshostel of DesaiganjWadsa located in Gadchiroli District of Maharashtra state. The sampling was conducted from the different section of hostel, such as Girls room, Dining area, Kitchen. Air samples collected during February, 2023 to January, 2024 for a year at an interval of 15 days. Air sampling was done by two methods with the help of Hi Air Sampler (Mark ll), Hi Media Loboratories, India and simultaneous Exposure Petri plate method. For this study culture media Czapek’s Dox Agar (CDA) was utilized for Petri plate method and Rose Bengal Strips were used in air sampler. Fungal spores were collected from indoor air of different sections of hostel. Total 1312colonies were appeared from Feb-2023 to Jan-2024 by exposure petri plate method. Total6700 CFUs/m3were trapped by sampler method. The genera like Aspergillus, Alternaria, Cladosporium, Penicillium, Fusarium, Mucor, and Rhizopuswere reported in Adiwasi girl’s hostel. Seasonal variations revealed, higher fungal spore concentration and CFUs/m 3 during rainy season correlating with increased humidity and decreased temperature levels. Temperature, Humidity and Rainfall affect the growth of fungus
A SURVEY OF ETHNOMEDICINAL PLANTS USED BY LOCAL TRIBES OF AHERI AND BHAMRAGARH FOREST AREA OF GADCHIROLI DISTRICT IN MAHARASHTRA, INDIA
Get PDFAheri tahsil is located on the southern part of Gadchiroli district. Among the 12 tehsils, Aheri is the largest tehsil in the Gadchiroli district covering an area of 2282.70 km², while Desaiganj (Wadsa) is the smallest in the district, covering an area of 262.74 km². Chamorshi is the most populous whereas Bhamragad is the least populous tehsil in Gadchiroli district. A major portion of Aheri and Bhamragad areas are covered by forest and the ethnic group is Gond. The major local language is Gondi, however these people also know Marathi and Telugu as well. The current study covers both Aheri and Bhamragad tahsils. These tribals depend on forest resources for their daily needs including medicines. Usually they visit hakims (local doctor who prepare medicines from locally available plants only), for the treatment of any ailment
A PROOF-OF-CONCEPT DIGITAL LEAKY INTEGRATE-AND-FIRE NEURAL NETWORK - THE CAT DESIGN
Get PDFDigital neural networks are an alternative computing structure to the traditional von Neumann architecture and offer enhanced performance when many inputs need to be processed in parallel. This occurs in complex data sets or data sets composed of sensory (e.g. visual or auditory) information. Neural networks inspired by biological systems offer efficient solutions for real-time signal processing, pattern recognition, and neuromorphic computing. This paper presents a proof-of-concept digital implementation of a Leaky Integrate-and-Fire (LIF) neural network, designed and tested in hardware using FPGA-based digital logic. The proposed architecture, termed CAT Design, leverages a scalable and modular approach to implement LIF neurons with configurable parameters such as membrane potential decay, threshold-based firing, and synaptic weight adjustments. By employing efficient digital arithmetic and parallel processing techniques, the design achieves low-latency spike-based computation, making it suitable for energy-efficient neuromorphic applications. We evaluate the performance of the system in terms of computational efficiency, hardware resource utilization, and real-time processing capabilities. The results demonstrate the feasibility of implementing spiking neural networks in digital hardware, paving the way for future developments in brain-inspired computing systems.This paper presents the results from testing a small proof-of-concept digital neural network designed in VLSI hardware
Ritual Plants of Maharashtra: Documentation, Analysis, and Cultural Significance
Get PDFFestivals are integral to human culture, celebrating significant life events and spiritual occasions. Traditional festivals reflect cultural identity, fostering community and spirituality. Plants play a crucial role in these celebrations worldwide, symbolizing cultural heritage and the human-nature relationship. In India, their significance extends beyond practical use, yet research on their cultural importance remains limited.This study documents and statistically analyzes plant usage in 19 Indian festivals across different seasons. Food-related plants are central to many celebrations, with Haritalika showing the highest plant usage. Arecaceae and Poaceae are the most commonly used families, with key plants including nagli, coconut, mangoes, and nuts. Word cloud analysis highlights prominent plant-related festivals such as Gopalkala, Pola, Mangalagaur, and Diwali.A Chi-square test revealed a highly significant association between festivals and seasons (X² = 820, df = 72, p < 2.2e-16), confirmed by Cramér’s V (1) and the contingency coefficient (0.894). Flower and tree usage showed strong associations with Marathi and English months (Φ = 0.512 and Φ = 0.410, respectively). Flower (Φ = 0.412) and powder (Φ = 0.417) usage were significantly linked to festivals, highlighting their importance in religious and celebratory practices. Sentiment analysis assigned scores to plant-related phrases, indicating mild positivity for "food, worshipping" (0.4596) and neutrality for "prasad" and "decoration" (0.0000). Network analysis revealed distinct clusters of festivals and seasons, emphasizing shared cultural and temporal connections. Correspondence analysis biplots showed strong seasonal associations, with Gregorian calendar months exhibiting clearer temporal fixation than the Hindu lunar calendar.This study enhances understanding of the cultural significance of plants in festivals, reinforcing their role in biodiversity conservation and cultural heritage preservation
Data Mining and Artificial Intelligence in Digital Forensics
Get PDFThe artificial intelligence of the data integration they can used for extracting the information on the important steps in the area of digital forensics, because it seeks to improving on the precision and effectiveness of the law enforcement investigations. Current trials at time include huge and intricate information that are used for the challenging for the current scientific treatments to navigate. The aforementioned database they can use for the finding the fundamental patterns and anomalies by through using methods of data mining include as division and clustering. The artificial intelligence methods the opposite simplifies the procedure of analysis and greatly enhances the rate of processing and precision of detection. This becomes particularly relevant with the artificial training and deep neural networks in the deep learning techniques. The present research they can used for examines the way of these methods exist in the scientific instances include as analysing network traffic, identifying malware, and internal surveillance. The artificial intelligence to enhance on the forensic tools to be operate higher than traditional ones in the multiple significant domains, based on the in-depth review of the research and individual scenarios. The machine learning methods used for the great services shows increased antivirus recognition precision, better recognition of network intrusions, as well as effective treat from within detection. This current research contrast evaluation shows the significant improvements with regard to metrics include as identification costs, clarity, and recall that artificial intelligence systems have rendered feasible. The main investigation of the challenges and constraints they can used for the identifying digital forensics in the mining data, to accessing the needs of great data and the demand of computer power and moral concerns.The analysing on the result to be indicate the relevance of combining data mining techniques with modern AI techniques in the expert forensics efforts. The research studies they can use for the suppliers make resources in the advanced strategies, ensure the secure implementation via suitable instruction and develop moral standards. In the years to come, studies ought to focus on creating the solid structures for the ethical application of the AI in digital forensics, exploring novel development include as cloud based and block chain approaches and overcoming on the present barriers to technological challenges. The effectiveness and productivity of the inquiries into digital forensics potential in to substantially boosted by these technological advances
Artificial Intelligence (AI) in Financial Forecasting: A Data-Driven Approach to Risk Mitigation
Get PDFThe increasing complexity of financial markets has heightened the need for accurate and efficient forecasting techniques. Traditional financial forecasting models often struggle to capture market volatility, leading to suboptimal decision-making and increased financial risk. The effects of AI-powered predictive analytics on business planning, risk management, and financial forecasting are studied in this research.. Using a mixed-methods approach, data were collected from 350 finance professionals across major Indian financial hubs. The study employed statistical techniques, including ANOVA and correlation analysis, to measure the effectiveness of AI-driven forecasting models.The results indicate that AI implementation led to a 17% increase in forecast accuracy and a 22% reduction in forecasting errors, with significant improvements observed across multiple industries (p < 0.01). Furthermore, a strong positive correlation (r = 0.72) was found between AI adoption and enhanced risk management strategies, suggesting that AI not only improves financial prediction but also strengthens proactive risk mitigation measures. Corporate planners' qualitative observations showed that by offering real-time market trend and risk assessment, AI-driven analytics improves strategic decision-making.By proving its capacity to increase accuracy, efficiency, and risk management skills, this study adds to the increasing corpus of studies on artificial intelligence in financial forecasting. The findings suggest that firms adopting AI-based predictive analytics can achieve greater financial stability and resilience to market fluctuations. Future research should explore AI’s role in long-term financial sustainability and its impact on investment strategies in dynamic market environments
EVALUATION OF INSECTICIDAL POTENTIAL: A COMPARATIVE STUDY OF VACHA (Acorus calamus), APAMARGA (Achyranthes aspera), AND KEBUKA (Costus speciosa) EXTRACTS AGAINST PULSE BEETLE (Callosobruchus chinensis) IN STORED CHICKPEAS
Get PDFThis study investigates the insecticidal efficacy of Vacha (Acorus calamus), Apamarga (Achyranthes aspera), and Kebuka (Costus speciosus) extracts against the Pulse Beetle (Callosobruchus chinensis) in stored chickpeas (Cicer arietinum). Pulse Beetles are significant pests in stored legumes, causing extensive losses in seed quality and quantity. The objective was to evaluate the effectiveness of these plant-derived extracts as natural alternatives to chemical insecticides, aligning with the growing demand for eco-friendly pest management strategies. Key results indicated differential efficacy among the three plant extracts, with Acorus calamus showing the highest insecticidal activity, significantly reducing beetle infestation rates and seed damage. Achyranthes aspera demonstrated moderate effectiveness, while Costus speciosus) exhibited the least efficacy but still outperformed untreated controls. These findings were further discussed in the context of their active phytochemicals, such as alkaloids and essential oils, which disrupt the metabolic and reproductive systems of the pests. The study concludes that these botanical extracts are promising candidates for sustainable pest management. The novelty of this research lies in its comparative approach, highlighting the potential of traditional herbal knowledge in addressing modern agricultural challenges. This approach is particularly relevant in current times, where there is a pressing need to reduce the environmental and health impacts of synthetic pesticides while ensuring food security through effective pest control in stored grains
Correlation Between Palatal Rugae Patterns and Digital Fingerprints in the Bengali Population: A Forensic Study
Get PDFBackground: Human identification in forensic science is a critical process employed to establish the identity of individuals in criminal investigations, disaster victim identification, and legal proceedings. This process relies on a variety of scientific methods, including fingerprint analysis, DNA profiling, dental record evaluation, and facial recognition. Among these, fingerprint and DNA analysis are considered highly reliable due to their uniqueness and accuracy. Forensic anthropologists and odontologists also play a significant role by examining skeletal remains to determine age, sex, and ancestry. With advancements in technology, biometric identification and digital forensics have become integral in enhancing accuracy and efficiency.Aim: This study aims to evaluate the potential correlation between palatal rugae patterns and digital fingerprint types in individuals from the Bengali population.Materials and Methods:A total of 100 subjects (50 males and 50 females), aged 17–25 years, were recruited from Kusum Devi Sunderlal Dugar Jain Dental College and Hospital, Kolkata. Maxillary impressions were made using alginate, and the palatal rugae patterns were traced on dental stone casts. Only individuals without systemic diseases or prior orthodontic/prosthodontic treatment were included. Digital fingerprints were recorded using ink by rolling the thumb from the ulnar to radial side. Ethical clearance was obtained, and informed consent was secured from all participants
EFFECTIVENESS OF APPLYING GROWTH REGULATORS TO FINE-FIBER COTTON CULTIVATED UNDER DIFFERENT IRRIGATION REGIMES
Get PDFThe experiment established that when growing under an irrigation regime of 70-75-65%,using the stimulant Uzbiogumin and Immunoactive before sowing seeds and during the growingseason, compared to the control
Phytochemical Profile and Antioxidant Potential of Solanum torvum Swartz: An Integrated Review
Get PDFSolanum torvum Swartz, also known as turkey berry, is a medicinal herb in the Solanaceae family traditionallyused to treat infections, hypertension, and liver diseases. Due to increasing concerns about the safety ofsynthetic antioxidants, interest in plant-based alternatives has grown, and this turkey berry has garneredattention due to its impressive phytochemistry and strong antioxidant properties. This review covers the plant'staxonomy, modern ethnomedicine, phytochemical profile, and antioxidant activity, based on existingliterature. All parts of turkey berry (leaves, fruit, roots, and seeds) have been examined for antioxidant activitythrough extraction methods and various assays, including DPPH, FRAP, ABTS, hydrogen peroxide, nitricoxide, lipid peroxidation, and total antioxidant capacity. The plant contains several phytochemicals, such asalkaloids, flavonoids, phenolics, steroidal glycosides, saponins, and vitamins. It has long been used intraditional medicine to treat a range of health conditions, including ulcers, hypertension, diabetes, and cancer,and is known for its neuroprotective, immunomodulatory, hepatoprotective, antioxidant, and antimicrobialeffects. This review consolidates findings from 22 studies on S. torvum, all highlighting its significantantioxidant activity. In conclusion, turkey berry shows great potential as a natural source of antioxidants,aligning with its traditional medicinal uses. Further research should focus on isolating and characterizingphenolic and flavonoid compounds and validating these findings through clinical studies