Volume 20 Issue 10 2025

Introduction: The concurrent presence of fibroadenosis and eczema in the same patient poses a therapeutic challenge. Conventional management of these conditions often provides only temporary relief and may involve multiple medications. Homoeopathy, through individualized prescriptions, offers a holistic approach that can address diverse complaints with a person tailored remedy. Case summary: A 19-year-old female presented with cyclical mastalgia and bilateral breast nodularity for 3 years, along with pruritic, scaly eczema on the right wrist for 6 months. Ultrasonography confirmed fibroadenosis with diffuse fibroglandular changes. Based on her totality of symptoms Conium maculatum 200C was prescribed as individualized remedy. Over 36 weeks, the patient experienced complete resolution of mastalgia and wrist eczema. Ultrasonography showed normalization of fibroglandular tissue, confirming radiological improvement. Photographic evidence demonstrated complete clearance of eczema. This case demonstrates that individualized homoeopathic prescription, Conium maculatum 200C, can effectively resolve multiple chronic complaints in the same patient. Clinical, imaging, and photographic evidence strengthen the role of individualized homoeopathy as a holistic therapeutic modality. Modified Naranjo Criteria for Homoeopathy scores +10/13 in this case, supporting the causal relationship between outcome and homoeopathic intervention when tailored to the patient's unique symptomatology

A modular coloring of a graph 𝐺 is a vertex coloring in which adjacent vertices may share the same color, provided that for every pair of adjacent vertices the sum of their color is distinct modulo𝑘,𝑘 ∈ 𝕫𝑘. The smallest integer 𝑘 for which 𝐺 admits such a 𝑘 - coloring is modular 𝑘– coloring andits called modular chromatic number. This paper constructs the extended snow graph 𝑆𝑇 𝛾(𝐺𝜇)for 𝜇, 𝛾 ≥ 3, and determines the modular chromatic number of the extended form 𝑆𝑇𝛾(𝐺𝜇), presenting bounds for their modular chromatic numbers.

The convergence of Artificial Intelligence (AI) and Machine Learning (ML) with electromagnetic (EM) applications has introduced revolutionary techniques in simulation, optimization, prediction, and realtime control across several fields of engineering. This paper investigates recent advancements in AI/ML methodologies applied to EM problems such as antenna design, radar signal processing, electromagnetic compatibility (EMC), inverse scattering, and metamaterials. A comparative analysis of traditional versus AIdriven EM techniques is presented. The methodology highlights supervised learning, neural networks, and reinforcement learning models used in EM applications. Case studies include neural-network-optimized microstrip antennas and machine learning for radar target classification. Results show improvements in accuracy, computational efficiency, and design innovation. The paper concludes with future challenges and research directions in combining AI with computational electromagnetics.

This study investigates the relationship between pulse time, suction flow rate, and dust density to enhance the cleaning efficiency of robotic vacuum cleaners used in indoor environments. Experimental tests were conducted to measure the impact of varying suction pressures and pulse durations on dust collection performance, supported by multiple linear regression analysis. The results revealed a strong positive correlation between dust density and cleaning effectiveness, with dust density emerging as the most significant predictor of performance. Flow rate was found to have a minor influence compared to dust concentration levels. The study provides quantitative insights into optimizing suction parameters for improved particle capture and energy efficiency. These findings establish a foundation for developing intelligent, sensor-based robotic vacuum systems capable of adaptive cleaning under dynamic environmental conditions.

Background: Recurrent pregnancy loss (RPL) and secondary infertility are significant reproductive challenges that can be attributed to hormonal, uterine, metabolic, and psychosomatic factors. Ayurveda approaches these conditions holistically, focusing on dosha balance, Agni (digestive/metabolic fire), and srotas (body channels). Case Presentation: A 29-year-old woman (G3P1A2L1D1) with a history of secondary infertility for 8 years presented with complaints of scanty menses, generalized weakness, acidity, and backache. Her reproductive history included two first-trimester miscarriages and one neonatal loss. Ayurvedic treatment was initiated with Shamana therapy, followed by Virechana Karma (therapeutic purgation), and post-detox Rasayana and Garbhasthapana formulations. Outcome: The patient conceived spontaneously within two months of completion of Panchakarma and Rasayana therapy, with no adverse events noted during the treatment. Conclusion: This case demonstrates the potential role of classical Ayurvedic interventions, including Shodhana and Rasayana therapies, in managing complex cases of secondary infertility and RPL. Integration of personalized Ayurvedic protocols may offer promising outcomes for such patients.

Food is one of the most vital basic needs for every living being and is more important for health and safety of human life. Food is the natural diet, and for good health and safety, it should be free from being adulterated. But due to more commercial practices prompted by profit motive, etc. food is adulterated by different adulterants. Adulteration reduces the vital important aspects of food necessary for health and safety. Not only this, even the colour of food may be changed. For example, Metanil yellow is used to intensify colour of turmeric. Such things are used to gain more profit and to reduce the price to compete in the market. Adulterants can cause different diseases like anaemia, brain damage, paralysis, stomach disorder, etc. Adulteration of food is often present in its most crude form as prohibited substances are either added partially or wholly. Food safety is one of most important subject to be considered for study and deal with at present very seriously as per Food safety and standard Act 2006 and necessary adjudication and prosecution is to be carried out as per law to deter the offenders from committing such acts. Assam is endowed with diverse Agro-climatic conditions which permit growing of wide range of horticultural crops. It accommodates various fruits, vegetables, flowers, spices, medicinal and aromatic plants, nut crops, tuber crops and also plantation crops. But most of products are being adulterated before and after they reach the markets and are purchased by the consumers for direct and ultimate consumption which affects their health and safety. Therefore, this practice of adulterating food and eatables stands before us, the present society, as a great threat and menace which demands preventive measures to be undertaken to eliminate it or at least minimize its ugly heads. This article aims to present a scenario of food adulteration with dreaded consequences and seek measures to remedy it. Further, it would make an enquiry about how AI-driven mechanisms could help to solve this problem besides the legal machinery put into operation as it is today under different provisions of legislation and the Constitution.

This study presents the comprehensive design and development of a robotic vacuum cleaner that integrates CAD modeling, CFD analysis, and intelligent navigation systems. The vacuum cleaner is equipped with a high-speed 18,000 RPM motor, ensuring powerful suction for effective cleaning performance. A multistage filtration system is incorporated to trap fine dust particles, thereby improving air quality and cleaning efficiency. The design utilizes advanced sensors that enable real-time detection of obstacles, allowing the robot to navigate smoothly through complex indoor environments without collisions or disruptions. Intelligent pathplanning algorithms enhance their autonomy, enabling them to adapt to dynamic surroundings and varying floor types. Computational Fluid Dynamics (CFD) analysis is employed to optimize airflow paths and internal pressure distribution, which significantly contributes to energy efficiency and improved dust intake. CAD tools assist in precise modeling and component placement, ensuring compactness and structural integrity. The overall development emphasizes energy efficiency, operational reliability, and ease of use. Simulation and testing confirm that the robotic vacuum cleaner performs effectively under diverse indoor conditions. The results support its potential for widespread use in smart homes, offering a reliable, autonomous cleaning solution that combines advanced engineering techniques with practical utility.

The hearing-impaired society in Tamil Nadu relies heavily on Tamil Sign Language (TSL) for communication, yet automatic TSL recognition is still a difficult task because of things like background clutter, signer unpredictability, occlusion, and variations in light. Although methods based on deep learning have shown promise, they frequently underperform in such real-world scenarios. The model achieved a 94% validation accuracy in the previous work when proposed an Enhanced ResNet-50 enhanced with a Convolutional Block Attention Module (CBAM). Building on this framework, the current work presents a unique framework that combines the CBAM-ResNet-50 backbone with ArcFace angular-margin loss. By optimizing inter-class separability and reducing intra-class variations, ArcFace improves the discriminability of learnt feature embeddings and resolves misclassification problems in visually identical gestures. Extensive tests show that the suggested CBAM+ArcFace architecture achieves 98% real-time recognition accuracy and 97% validation accuracy, setting a new standard for TSL recognition. These results highlight the framework's resilience and usefulness in creating assistive technology and real-time interpretation systems for the deaf community.

This study presents a comprehensive text analysis of 30 Google-indexed articles published in 2025 concerning U.S. President Donald Trump’s tariff policies. The analysis identifies tariffs as the most frequently used and thematically dominant term across the dataset, followed by US, trade, Trump, countries, goods, imports, and China. These terms collectively define the core thematic landscape of the media discourse. Network analysis reveals a structured hierarchy, with tariffs positioned as the central thematic anchor, holding the highest topic probability at 2.8%. The term US follows with a probability of 2.3% and exhibits a 99.98% semantic association with tariff, indicating a strong conceptual link between U.S. policy and tariff-related discussions. Trade also emerged as a key associated term, highlighting its significance in the broader narrative. Additional keywords such as forecast, impact, consumers, and China reflect concerns about economic consequences and international relations. Sentiment analysis further indicates that Trump’s tariff policies were generally portrayed negatively, with emphasis on potential harm to consumers, disruptions in trade, and global economic instability. Overall, the study offers insight into the key themes, relationships, and evaluative perspectives that characterized media coverage of Trump’s tariff policies in 2025.

This paper attempts to make a comparative study of spectatorship in Proscenium and Environmental theatre practices. Spectatorship in Proscenium theatre tradition has been historically held as passive and hierarchical, as the audiences are kept eternally in the dark, only to view the performance with absolute silence. Throughout the performance on the stage, their performance in the dark, lower area is confined to constant meaning production, revision, confirmation, and negation within the fixed time of performance. The only time the spectators get to reflect what they have watched is again never determined by them but by the performers with the use of intervals, act or scene divisions, set changes, lighting changes, costume changes and so on. So, the audience can never really share an equal theatrical space with the performer. The setting of the proscenium theatre hall also enforces an undemocratic homogeneity in theatre practice. The performers are the voice of the theatre whereas the audiences occupy the silence, the darkness of theatre. Multiple components happening on the stage generate meaning but in this generation what role do the audiences play? What is their contribution to theatre-making? Are they required only for enriching the box-office? How can the audience be involved in the process of performance? A reconstruction of the actor-audience relationship is necessary to democratize theatre. There are conventions in theatre history where the spectators have been brought physically close to the actors, although that hardly facilitated any active interaction between the two. In Schechner’s environmental theatre the performers and the spectators share a same theatrical space and engage in an active exchange of energies and feelings. In fact, in his theatre, the performance space is not a very sanctified hallowed space restricted or reserved only for the actors. The spectators are able to very much share the same space and move around various spaces along with the performers in the studio space. The line between the actor and the audience thins as both become performers. In fact, the entire space of an environmental theatre is full of only performers.

The integration of chemical engineering principles within food processing technology has transformed the global food industry by improving efficiency, safety, and sustainability. This systematic review explores the interdisciplinary link between chemical engineering and food processing, emphasizing the role of transport phenomena, thermodynamics, reaction kinetics, and process design in developing advanced food manufacturing systems. Key areas of focus include unit operations such as heat and mass transfer, mixing, drying, and membrane separation, which form the backbone of both chemical and food engineering processes. The review also highlights emerging technologies such as process modeling, automation, nanotechnology, and sustainable process intensification that bridge the two disciplines. By examining recent research trends, this paper identifies how chemical engineering approaches enhance product quality, resource utilization, and environmental performance in food systems. The findings underscore the necessity of a cross-disciplinary framework to drive innovation and achieve sustainable growth in the food processing sector.

Milk and dairy products are vital for human nutrition and are considered as the carrier of higher biological value proteins, calcium, essential fatty acids, amino acids and water-soluble vitamins. The present study aimed to develop a dietetic Rasmalai health mix enriched with sprouted millets and evaluate its microbiological, sensory and antioxidant properties. Given the rising demand for functional foods, the research focused on improving the nutritional profile of Rasmalai while maintaining sensory appeal and microbial analysis Microbial analysis was assessed through standard plate count, coliform, and yeast and mould count. Sensory evaluation was conducted using a 9-point hedonic scale. Antioxidant potential was determined using DPPH and ABTS•+ radical scavenging assays. Microbial assessment confirmed the hygienic quality of all samples of Rasmalai with sprouted millets showed SPC 6.67×10⁻⁶–3.02×10⁻⁶, coliform 3.12×10⁻¹–2.1×10⁻¹, yeast-mould 3.17×10⁻¹–1.32×10⁻¹, with reduced counts in T1-T3 versus control. Sensory evaluation indicated that T2 was the most preferred formulation, scoring highest in flavour (8.30) and texture (8.73). Antioxidant analysis revealed improved free radical scavenging activity, with T3 demonstrating the highest DPPH (56.4 mg/ml) and ABTS•+ (62.4 mg/ml) activity. Sprouted millet-enriched Rasmalai offers a nutritious, microbiologicallysafe, and sensory-appealing dessert. The study underscores the potential of sprouted millets in functional food innovation, aligning with modern dietary trends. Future research should explore different millet varieties, their impact on dairy desserts, and their health benefits.

The experimental findings indicate that the RCCI engine presents significant potential for reducing emissions and enhancing combustion characteristics relative to the conventional diesel combustion (CDC) engine. The RCCI mode demonstrated a reduced peak pressure rise rate, signifying more stable and regulated combustion. Substantial decreases in nitrogen oxides up to 95.66% and smoke opacity up to 73.04% were noted as a result of enhanced charge uniformity and reduced combustion temperatures. Nonetheless, carbon monoxide and hydrocarbon emissions escalated due to incomplete oxidation at reduced in-cylinder temperatures and oxygen concentrations, which can be alleviated with appropriate aftertreatment devices such catalytic converters. Despite observing slight cycle-to-cycle fluctuations, enhancing injection timing and combustion regulation can further augment stability. The study validates that RCCI combustion utilizing LPG-diesel fueling offers a viable approach for cleaner and more efficient internal combustion engines, appropriate for future low-emission transportation applications.

organic potato farming in East Kolkata Wetland area by zero tillage paddy straw mulching method has multidimensional approach towards sustainable practice of agriculture. Silty clay soil and seasonal delay with proportional increase of salinity are the potential threats of organic potato farming in this region. Paddy straw mulching method of potato farming has capability to convert these barriers into a favourable beneficiary environment. Paddy potato rotation of agricultural approach in this region can improve socio economic as well as healthy farming practice. Very limited involvement with minimum cost of investment can grow rapid interest in domestic farming with respect to the individual demand. Adoption of zero tillage paddy straw covering method in this region with a proper field experiment data can help to prepare protocol development for long term sustainable agricultural improvements. Thickness of paddy straw mulching is the major concept to adaptive soil and environmental condition towards friendly environment creation. Beneficiary microbial growth in root development region with supply of soil surface level nutrients highly depend on mulching thickness for the tuber development. Several cases are reported as having different levels of paddy straw layering in this method in different soil and environmental conditions. In this experiment designed to optimize paddy straw layering in naturally sewage treated auto recharged silty clay soil character of East Kolkata Wetland area.

The Protection of Children from Sexual Offences (POCSO) Act, 2012, is a major legal framework in India. It focuses on children and establishes Special Courts, confidentiality rules, and compensation options. However, its potential is limited by ongoing delays, lack of resources, and social barriers. The media and courts highlight issues such as delays, misuse, and inadequate infrastructure. Thus, the study attempts to explore how key administrative individuals—Child Welfare Committee chairpersons, District Child Protection Officers, Public Prosecutors, and judges who specialize in POCSO—understand and deal with these challenges. Through 25 detailed interviews (30–40 minutes each) and thematic analysis, this research identifies eight key themes, such as improved legal protections, misuse of the Act, procedural delays, compensation issues, social vulnerability, community-level confusion, psychological damage to survivors, and recommendations for reform. The findings reveal two realities. The Act does provide important protections, but delays, misuse, and weak institutional support diminish its effectiveness. Victimized girls often endure long-term trauma, worsened by poverty, low awareness of their rights, and dependence on informal settlements. Importantly, the discretion given to officials can be both beneficial and risky, as their decisions under pressure can shape case outcomes. The study emphasizes the need for policy change that considers street-level bureaucracy. This includes investing in training, establishing better oversight, providing traumainformed support, and raising community awareness to better connect the law's intent with real-life justice. Without these efforts, the idea of “justice” remains a goal rather than a reality.

The impact of pollution on freshwater resources has significant implications for public health and environmental sustainability. This study investigates the pollution levels of River Benue in Benue State, Nigeria, with the objective of evaluating its suitability for potable water supply. A comprehensive analysis was conducted using standard analytical techniques including titrimetry, gravimetry,potentiometry, and spectrophotometry to determine key physico-chemical parameters during both dry and rainy seasons. Results revealed seasonal variations in water quality indicators: total hardness ranged from 22.28 mg/L (dry season) to 41.87 mg/L (rainy season), while electrical conductivity measured 91.35 µS/cm in the rainy season and 54.10 µS/cm in the dry season. Total dissolved solids (TDS) were higher in the rainy season (76.02 mg/L) compared to the dry season (32.31 mg/L), indicating greater ionic presence during rainfall. Dissolved oxygen concentrations were 3.18 mg/L (rainy) and 3.72 mg/L (dry). Phosphate levels were 0.73 mg/L (rainy) and 0.85 mg/L (dry), while sodium concentrations were 2.78 mg/L and 2.95 mg/L, respectively. Calcium values were 1.57 mg/L (rainy) and 2.07 mg/L (dry). Chemical oxygen demand (COD) recorded 114.37 mg/L in the rainy season and 84.97 mg/L in the dry season. Biochemical oxygen demand (BOD) exceeded the World Health Organization (WHO) limits for drinking water, with values of 24.87 mg/L in rainy season and 25.63 mg/L in dry season). Elevated concentrations of heavy metals, including lead 0.00865 mg/L in dry season; 0.00281 mg/L in rainy season and copper 1.24 mg/L in dry season; 0.9734 mg/L in rainy season, poses potential health risks to aquatic life and communities relying on the river for domestic use. A Pearson Product Moment Correlation analysis yielded a coefficient (r) of 0.91, suggesting a strong positive correlation and relatively consistent water quality status across seasons. Furthermore, Artificial Neural Network (ANN) and MATLAB were employed to support the data analysis and predict pollution patterns. The integration of ANN techniques demonstrated high predictive accuracy, highlighting their effectiveness in water quality assessment and environmental monitoring.