Silkworm diseases significantly impact sericulture productivity, leading to substantial economic losses worldwide. Early and accurate disease detection is therefore essential for effective disease management. This study provides a comprehensive review of research published between 2021 and 2025 on the application of machine learning (ML) and deep learning (DL) techniques for silkworm disease classification. It explores a variety of computational approaches, including conventional ML models such as Support Vector Machines (SVM) and Random Forests (RF), alongside advanced deep learning architectures, particularly Convolutional Neural Networks (CNNs). The findings indicate that while conventional ML methods achieve moderate classification accuracy (typically between 85% and 95%) using handcrafted features, DL-based models significantly outperform them, often achieving accuracy levels above 97%. Recent advancements emphasize the use of transfer learning, lightweight architectures, and real-time deployment systems to support field-level applications. Despite these improvements, several challenges remain, including limited dataset availability, lack of standardized benchmarks, and insufficient real-world validation. This study highlights the need for large-scale datasets, robust model evaluation, and integration with edge and IoT-based systems for practical implementation. Overall, the review demonstrates that deep learning-based approaches offer a promising direction for developing efficient, scalable, and intelligent diagnostic systems for silkworm disease classification.
A rapid, selective and sensitive LC-MS/MS bioanalytical method was developed and validated for simultaneous estimation of Montelukast Sodium, Fexofenadine Hydrochloride and Acebrophylline in human plasma. The method was arranged using the same overall manuscript format as the reference RP-HPLC article, but all analytical conditions were converted to LC-MS/MS bioanalytical requirements. Zafirlukast was selected as the internal standard and plasma samples were prepared by protein precipitation using methanol. Chromatographic separation was achieved on an ACE 5 C18 column using acetonitrile:2 mM ammonium formate buffer (pH 4.5) (90:10, v/v) at a flow rate of 0.6 mL/min and injection volume of 15 µL. The MRM transitions were 586.2→568.3 for Montelukast, 502.1→466.2 for Fexofenadine, 378.2→263.1 for Acebrophylline and 574.6→462.2 for Zafirlukast. Retention times were approximately 5.707, 4.277 and 3.103 min for Montelukast, Fexofenadine and Acebrophylline respectively. Validation was performed for selectivity, carryover, calibration linearity, accuracy, precision, recovery, matrix effect, stability, robustness and pharmacokinetic applicability. The method showed linearity over 1.0-1000.0 ng/mL, acceptable recovery and matrix effect, and precision/accuracy within bioanalytical acceptance criteria.
Natural gums and mucilage have attracted considerable interest as multifunctional pharmaceutical excipients owing to their biocompatibility, biodegradability, and cost-effectiveness. The current study scrutinized the potential of Salvia hispanica (chia) seed mucilage as a natural superdisintegrant in the formulation of oral fast dissolving films (ODFs) of Donepezil hydrochloride. Salvia hispanica (Chia) seed mucilage was isolated and characterized for its physicochemical properties. Different quantities of chia seed mucilage were used in the solvent casting procedure to create donepezil hydrochloride-loaded ODFs (F1–F6). Appearance, weight variation, thickness, folding durability, surface pH, moisture loss, drug content, in vitro disintegration time, and in vitro dissolution were all assessed for the formulations. FTIR was used to evaluate drug-excipient compatibility, while scanning electron microscopy (SEM) was used to study surface shape. For two months, the optimized formulation was put through accelerated stability tests in accordance with ICH requirements (40 ± 2°C/75 ± 5% RH). Drug–excipient compatibility was confirmed by IR spectroscopy and the drug did not undergo any changes in the crystal structure. SEM images showed rough, flaky and plate-like surface morphology. All formulations complied with as per acceptable Pharmacopeial limits, the drug content ranges from 94.2–99.2%. The thickness of the film was in the range of 50.33 to 60.41 μm and moisture loss ranged from 4.1 to 4.8%. The mucilage concentration was observed and the disintegrating time was found to be in the range from 42.1 to 59.5 s. Of all the formulations, the formulation F3 showed the shortest disintegration time (42.1 ± 1.14 s) and the highest cumulative drug release (99.72% within 6 min). The stability studies revealed no significant changes in the physicochemical properties, drug content, Dissolution time and disintegration time. Salvia hispanica (Chia) seed mucilage was a promising natural superdisintegrant for the Development of Donepezil hydrochloride oral disintegrating films. The optimized formulation (F3) showed rapid disintegration, good drug release and satisfactory stability, which indicated its ability to act as a viable immediate-release oral drug delivery system to better serve patients compliance.
This study presents a novel Kernel-Based Fourier–Fractional Differential Transformation Method (K–F–FDTM) for the solution of periodic fractional partial differential equations. The method merges spatial Fourier decomposition with a kernel-modified differential transformation framework, enabling the incorporation of non-singular fractional operators. This approach allows accurate modelling of finite-memory processes without the limitations of singular operators. Numerical examples states that the proposed method achieves proper accuracy and faster convergence when compared with existing fractional differential transformation and spectral approaches. The proposed framework gives new avenues for the analysis of complex fractional systems with nonlocal temporal behaviour.
Introduction: Ayurveda, often referred to as the "science of life," is an extensive medicinal system that emphasizes healthy living over merely treating diseases. As this traditional health system gains global recognition, understanding its key components becomes essential. One such component is "Kostha," which has two significant interpretations. Ayurveda is a logical science based on basic principles and concepts. It would require extensive study to discuss and understand them all. Ayurveda comprises eight branches. Although Panchakarma is not explicitly listed among these eight branches, there is no branch in which the role of Panchakarma is not described. Dosha, Dhatu, Mala, Agni, and Kostha are some important concepts. We must know them to be able to really comprehend Ayurveda. Kostha plays an important role in the treatment of disease as well as Panchakarma. Before starting any treatment, we have to assess the condition of patients. Person to person, it differs, and the treatment principle is based on Kostha. So it is essential to know the details about Kostha. Aims and Objectives: to investigate the idea of Kostha as it is presented in traditional Ayurvedic literature and to comprehend its applicability and significance in relation to contemporary physiology and medical practice. to investigate the physiological underpinnings of Kostha and link it to the current understanding of gastrointestinal motility and function. • To evaluate Koshta's clinical importance in creating customized Ayurvedic treatment plans based on metabolic and digestive patterns. Material & Method: Literary material was collected from Ayurvedic classical texts (Charak Samhita, Sushruta Samhita, Asthang Hridaya, and Asthang Sangrha) and commentaries, along with modern Ayurvedic texts. Discussion: According to Ayurveda, preserving and regaining health is its fundamental objective, and it emphasizes steps that can be taken to do so. The main bodily components of Acharya Sushruta's most comprehensive conception of health are Dosha, Dhatu, Agni, and Mala. The most important concept that is beneficial in many parts of treatment is kostha. Unfortunately, little research has been done on the kostha concept in connection with shodhan chikitsa. Understanding the relationship between Prkruti, Agni, and Kostha is essential. The bodily portion Kostha is physiologically divided based on the predominance of the doshas Krura, Madhyam, and Mridu in Kostha. In terms of pathology, Kostha is Abhyantara Rogmarg, and 15 illnesses are classified as Kosthanushari Roga. Koshthanusaari Roga and Shakanusari Roga both describe Arsha, Shotha, Gulma
The environmental risks, especially the climate changes and carbon emissions, have now become the factors that influence the profitability of companies, the stock markets, and the economy. The main objective of this paper is to show how investment decisions can be made to incorporate the environmental risks in the day-to-day investment decisions through the creation of sustainable investment portfolios. This paper, using the MSCI ESG Indexes, Morningstar Sustainable Indexes, and the Global Market Indexes from 2015 to the first half of 2025, aims to show the comparison of the performance of the sustainable investment portfolios, which invest in companies with low carbon risk and high ESG ratings, and the traditional investment portfolios. The results of this paper will show that the sustainable investment portfolios have a higher median return of 12.5% in the first half of 2025 compared to the traditional investment portfolios, which have a median return of only 9.2%. We demonstrate, via simple application of a five-factor Fama-French model, which now includes an environmental risk factor, that our approach does improve the predictability of returns. This applies to equity, fixed income, and global portfolios. Advice for fund managers, banks, and individuals is also included. This paper provides hard evidence, which is easy to understand, that if environmental risk is included as an important factor, then improved portfolios can be created. This bridges the gap between climate science and portfolio management.
Gastro-retentive drug delivery systems (GRDDS) have gained significant attention for their ability to prolong gastric residence time, enhancing drug bioavailability and therapeutic efficacy. This study explores the formulation and evaluation of a GRDDS incorporating Licoisoflavone, a natural bioenhancer, for the targeted treatment of Helicobacter pylori-induced infections. The formulation was developed using floating and mucoadhesive approaches, ensuring prolonged retention in the gastric environment. Various polymers, including Hydroxypropyl Methylcellulose (HPMC) and Carbopol, were utilized to optimize bioadhesion and controlled drug release. The prepared system was evaluated for physicochemical properties, including swelling index, mucoadhesion strength, drug content uniformity, and in vitro dissolution profile. The optimized formulation exhibited sustained drug release, maintaining therapeutic concentrations over an extended period. Stability studies confirmed the integrity and efficacy of the formulation under physiological conditions. The findings suggest that GRDDS incorporating Licoisoflavone could serve as an effective strategy for improving treatment outcomes in H. pylori-associated gastric disorders.
Background: Pain is one of the most distressing symptoms in terminally ill cancer patients and significantly affects quality of life. Ayurveda describes several drugs possessing vedanahara, shoolaprashamana, and anti-inflammatory properties. Vijaya-based formulations have been traditionally indicated for pain modulation. Objective: To evaluate the efficacy of Vijayaraj Marham (Cannabryl Rectal Suppositories) in managing pain among terminally ill cancer patients when used as an adjuvant therapy. Materials and Methods: This pilot study will include 40 terminally ill cancer patients attending the SangyaharanVedanahara OPD, Sir Sunder Lal Hospital, IMS, BHU. Patients were enrolled after fulfilling the inclusion and exclusion criteria. Patients were divided into two equal and identical groups- control ( Gr.I) and trial group(Gr.II). In the trial group, Vijayaraj Marham was administered as rectal suppositories (b.i.d) ,where as patients of Gr.I ( Control Group) were given Tab. Diclofenac 50 mg orally with plane water (bid) .Further a standard supportive care was given to the patients of both the groups. Pain assessment scale (VAS), inflammatory biomarkers (dopamine, serotonin, epinephrine, and noradrenaline), and hemodynamic parameters- Pulse rate and Blood pressurewere evaluated at predefined intervals. Data were statistically analyzed to assess efficacy. Results: The study demonstrated improvement in pain scores, modulation of inflammatory biomarkers, and stable hemodynamic parameters in patients receiving Vijayaraj Marham. Conclusion: This pilot study will provide preliminary evidence regarding the role of Vijayaraj Marham as an effective adjuvant therapy for pain management in terminally ill cancer patients (specially when oral analgesics are having their limitations) and may pave the way for larger controlled clinical trials.
Vata is one of the three sharira dosha and occupies a central position in Ayurvedic physiology because it is linked to movement, communication, thinking, regulation, and essential life processes. Ayurvedic descriptions often present Vata through its actions rather than a visible anatomical structure, raising an important conceptual question: what constitutes Vata? This review critically examines the etymology, synonyms, mahabhuta composition, attributes, functions, determinants of abnormality, and clinical manifestations of Vata. The analysis suggests that Vata should not be reduced to physical air or wind. Rather, it represents a functional principle that integrates movement, sensorimotor communication, mental regulation, tissue organization, elimination, respiration, and adaptive biological rhythms. Its predominance of Vayu and Akasha explains the need for dynamic activity within spatial channels, while its guna and functions explain its role in both physiological coordination and pathological dispersion. The paper proposes that Vata may be interpreted as a meta-regulatory principle of biological activity that transforms the body's structural components into a responsive, communicating, and self-regulating living system.
Steroid-Responsive Encephalopathy Associated with Autoimmune Thyroiditis (SREAT), also known as Hashimoto’s encephalopathy, is a rare but reversible cause of encephalopathy that can mimic viral or autoimmune encephalitis. We present a 52-year-old female with acute onset of headache, nausea, vomiting, excessive sleepiness, and immediate memory loss. Neurological evaluation revealed impaired attention, executive dysfunction, and memory deficits, while motor, sensory, and cerebellar systems were preserved. MRI showed bilateral medial temporal lobe hyperintensities with vasogenic edema, initially suggesting viral or autoimmune encephalitis. CSF was acellular with elevated protein, and infectious as well as autoimmune/paraneoplastic panels were negative. Anti-thyroid peroxidase antibodies were markedly elevated. The patient had poor response to acyclovir but showed dramatic improvement after intravenous methylprednisolone, supporting the diagnosis of SREAT. This case highlights the importance of considering SREAT in unexplained encephalopathy. Early diagnosis and corticosteroid therapy can lead to significant neurological recovery.
Agricultural development schemes constitute a cornerstone of India's rural poverty alleviation strategy, with Karnataka implementing numerous programs targeting smallholder farmers, marginal cultivators, and landless agricultural laborers. This study examines the implementation, reach, and effectiveness of key agricultural development schemes in Mysuru District, Karnataka. Employing a mixed-methods research design, primary data were collected from 150 beneficiary households across six taluks of the district using structured questionnaires, supplemented by secondary data from government reports and official records. The study evaluates major schemes including PM-KISAN, Krishi Bhagya, Raitha Siri, and the Soil Health Card Scheme, assessing their impact on household income, agricultural productivity, and poverty reduction. Findings reveal that while awareness levels have improved significantly over the past decade, substantial gaps persist in scheme accessibility, timely benefit disbursement, and coverage of the most vulnerable farming communities. The analysis indicates a positive correlation between scheme participation and household income improvement, though the magnitude varies considerably across different programs. The study recommends strengthening last-mile delivery mechanisms, enhancing digital literacy among farmers, and improving convergence among various agricultural departments to maximize the poverty alleviation potential of these schemes.
Background: Coronary artery bypass graft (CABG) surgery is one of the most commonly performed cardiac revascularization procedures worldwide, yet patients frequently experience significant psychological distress alongside complex recovery challenges. Psychological well-being and self-care practices are increasingly recognized as determinants of postoperative outcomes. Objective: This systematic review synthesizes evidence from Scopus-indexed literature on the interrelationships between psychological well-being, self-care behaviors, and recovery outcomes in post-CABG patients. Methods: A comprehensive search was conducted across Scopus, PubMed, CINAHL, Web of Science, and PsycINFO databases. Studies published between 2015 and 2025 examining psychological factors (depression, anxiety, optimism, self-efficacy), self-care practices, and their impact on recovery outcomes following CABG surgery were included. Randomized controlled trials, prospective cohort studies, systematic reviews, and meta-analyses were considered. Results: Between 30-40% of CABG patients experience clinically significant depression and anxiety perioperatively. Poor psychological well-being is strongly associated with increased hospital readmissions, reduced adherence to self-care behaviors, impaired physical recovery, and diminished health-related quality of life. Evidence-based interventions, including cognitive behavioral therapy (CBT), structured cardiac rehabilitation, peer education, and telehealth programs, significantly improve both psychological and recovery outcomes. Optimism and self-efficacy emerge as key predictors of positive recovery trajectories. Conclusion: Integrating psychological screening, patient-centered self-care education, and mental health interventions into standard CABG care pathways is essential to optimize recovery. Future research should prioritize longitudinal designs, culturally adapted interventions, and implementation science approaches.
This integrative review synthesises existing literature to examine the interaction between branding, trust, and consumer decision-making in pharmaceutical markets, drawing on Aaker’s brand equity model, Morgan and Hunt’s commitment–trust theory, and cue utilisation theory. It analyses how branding shapes consumer perceptions, builds trust, and influences decision-making in a regulated environment characterised by intermediaries, generic competition, and the emergence of digital health particularly in emerging markets where institutional trust is evolving. Empirical evidence suggests that strong branding enhances perceived quality and reduces risk, thereby strengthening trust and contributing to loyalty and medication adherence. Trust functions as a central mediating factor in both over-the-counter and prescription contexts, where price cues, brand recognition, and ethical marketing practices influence consumer choices. Unethical practices undermine trust, leading to scepticism and increased preference for generics. The review also highlights the shift toward patient-centric branding, supported by digital tools and VRIO-based strategic capabilities for sustained competitive advantage. Managerial implications emphasise transparency, ethical engagement, and personalisation. The study identifies gaps in the representation of emerging markets and the evolving role of digital trust systems, contributing to both theoretical understanding and practical application in pharmaceutical consumer behaviour.
Metallic polypropylene composites offer significant advantages for automotive and consumer applications through mold-in-color technology, eliminating costly painting operations while delivering aesthetic metal-like appearance. However, visible weld line defects at flow front convergence zones remain a critical limitation restricting broader industrial adoption. This study systematically investigates weld line formation mechanisms in injection-molded polypropylene containing 2 wt% aluminum flake pigment (Al 27, ~27 μm). Comprehensive characterization combining gloss measurements (ASTM D523), spectral reflectance analysis (380-780 nm), optical microscopy, and controlled flow manipulation revealed that weld line visibility arises primarily from disrupted pigment orientation rather than mechanical weaknesses. Under symmetrical flow conditions, PP/Al 27 composites exhibited excellent metallic appearance (gloss: 43.27 ± 1.31%) with weld lines forming consistently at geometric centers. Optical microscopy confirmed localized aluminum flake accumulation and perpendicular particle alignment at weld interfaces, reducing specular reflection and creating visible optical contrast. Asymmetrical flow conditions displaced weld line positions predictably, demonstrating processing sensitivity. Higher pigment concentrations enhanced metallic aesthetics but amplified weld line prominence through increased optical contrast These findings establish fundamental understanding of pigment-orientation-dependent weld line phenomena, providing the foundation for developing mitigation strategies through material formulation modifications.
This study focuses on identifying the most effective band combination from Landsat Thematic Mapper (TM) data for mapping land surface water (LSW). Traditional single-band and general classification methods often lack accuracy, especially in complex landscapes with mixed pixels. The research evaluates six spectral water index models, including McFeeters’s NDWI, Xu’s MNDWI, NDPI, and a newly proposed multiplied index combining green (Band 2), near-infrared (NIR, Band 4), and shortwave-infrared (SWIR, Band 5) bands. Using quantitative parameters like between-class variance (BCV), contrast value (CV), overall accuracy (OA), and the Kappa coefficient, the study demonstrates that the new multiplied index (Band 2/Band 4 * Band 2/Band 5) significantly enhances water body detection. Applied to three study sites in West Bengal, India, this index consistently outperforms traditional indices in mapping accuracy. The findings support its use for effective LSW mapping, wetland monitoring, flood assessment, and water resource management.
