Journal for ReAttach Therapy and Developmental Diversities (JRTDD)
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Development and Assessment of Orodispersible Tablets Utilizing Natural Superdisintegrant.
No full textThe current study aimed to develop Diltiazem HCl orodispersible tablets using banana powder as a superdisintegrant by direct compression technique. The powder mixture prepared for compression was evaluated for angle of repose, bulk density, Carr’s index, Hausner’s ratio. Post-compression evaluation of prepared tablet includes drug content, weight variation, thickness, hardness, friability, wetting time, water absorption ratio, disintegration test and in-vitro drug release studies. All parameter produced good results. The drug and excipients were found to be compatible during IR testing. The study reveals that formulation prepared by direct compression F6 exhibits highest dissolution using banana powder at an 8% concentration and showed faster drug release 96.37% over a 25 minute period, while tablet disintegration time was 36 seconds when compared to other formulation batches of Diltiazem HCl
The Weight Of Silence: ‘Trauma’ And Its Echoes In Selvadurai\u27s Selective Queer Narratives
No full textTrauma refers to a deeply distressing and disturbing experience that overwhelms an individual’s ability to cope and results in feelings of intense fear, helplessness, or horror, leading to the symptom of long-lasting anxiety, depression, post-traumatic stress disorder and other kind of psychological distress and making an individual question their identity, impacting their sense of self, their relationships, and their mental and emotional health. Queer theory is employed as a theoretical framework to emphasize that trauma is not solely an individual problem but rather a product of societal and cultural factors, including homophobia, transphobia, and heteronormativity. The concept of intersectionality recognizes that individuals can experience multiple forms of discrimination, and this is especially true for Queer individuals who face a unique set of challenges in society. The question of how Queers experience trauma requires examining power dynamics and the ways in which voices and experiences of such individuals are recognized and valued within society. Despite this, there has been limited research on the discussion on Trauma of a Queer individuals and its impact on their self and society. This research paper explores the confluence of queer theory and trauma theory, shedding light on how conventionalism and expectations related to gender and sexuality contribute to exclusive formation of identity of LGBTQ+ individuals against the heteronormative rhetoric while investigating the traces in Selvadurai’s writings. Secondly, it attempts to create space for Queer individuals to speak out and be heard, while also recognizing and addressing the structural barriers that limit their agency and power. Lastly, this research paper aims to highlight the ways in which experiences of trauma can be transformative and serve as a catalyst for change, leading to new and more inclusive understandings of gender and sexuality
A Comparative Study of Stress and Coping among Caregivers of Cancer Patients and Alcohol Dependence
No full textThe incidence and prevalence of cancer has been increasing in developing countries in the last few decades. Cancer is viewed increasingly as a chronic disease, with prolonged management and increased rates of survival, leading to long term care requirements of the patient. The act of caring for a sick patient is multifaceted. The caregiver needs to have dedicated time to take the patient for hospital appointments and care for disease and treatment related problems at home as well. Alcohol use disorders (AUD) are a significant risk factor for a range of adverse health outcomes, reducing the lifespan of those who drink by more than a decade. Dependent drinking is the most severe form of AUD, often characterized by increased tolerance to alcohol, impaired control over drinking, persistent drinking despite harmful consequences and physical withdrawal upon discontinuation. In India, the prevalence of dependent drinking among males aged 15 and over is estimated at 7%, a significantly higher prevalence than the average for the World Health Organization South East Asia Region (2.9%). Coping with such problems needs a lot of patience. Caregivers must give up their personal time to care for their family members. The aim is to study the stress and coping between caregivers of cancer patients and alcohol dependents. The sample consisted of 60 caregivers 30 each of cancer patients and alcohol dependents. The caregivers were residents of Bangalore City. With the consent of the caregivers, they were administered caregivers strain index and brief cope. A purposive sampling design was opted for the study. The mean, SD, and ‘t’ was computed using appropriate statistical measures. The result revealed that there was significant difference in stress and coping between the caregivers
Towards Quantum-Enhanced Cloud Platforms: Bridging Classical and Quantum Computing for Future Workloads
No full textThe rapid advancement of quantum computing technology presents an opportunity to revolutionize cloud computing platforms, enabling the execution of complex workloads that are beyond the reach of classical systems. This paper explores the potential of quantum-enhanced cloud platforms, focusing on bridging classical and quantum computing to support future workloads. We examine the integration of quantum processors with classical cloud infrastructure, highlighting the challenges and benefits of hybrid architectures that combine the strengths of both paradigms. Key topics include quantum resource management, quantum programming models, and the development of algorithms that leverage quantum speedup for optimization, machine learning, and data analysis. Additionally, we address the scalability, security, and interoperability concerns that must be overcome for effective deployment in real-world cloud environments. By offering insights into the convergence of classical and quantum computing, this paper provides a roadmap for the evolution of cloud platforms capable of supporting next-generation applications and workloads
Vitamin A And E Quantification Using Spectrophotometric Methods
Get PDF The study presents a detailed exploration of spectrophotometric methods for quantifying vitamins A and E. These vitamins play critical roles in human health, necessitating accurate and efficient analytical techniques for their measurement in various matrices like food products, pharmaceuticals, and biological samples. The research evaluates methods such as the Ferrozine-Fe(II) complex method, which leverages the antioxidant properties of vitamins A and E to facilitate metal ion reduction, and Raman spectroscopy, a more sophisticated approach used for precise analysis. Key findings indicate the Ferrozine-Fe(II) method is cost-effective, with sensitivity suitable for low concentrations of vitamins, while Raman spectroscopy provides advanced specificity and efficacy. The study highlights limitations like interference from other antioxidants and complex sample matrices, urging careful sample preparation. The work\u27s contributions include optimization of reaction conditions, offering a valuable tool for routine analysis in clinical and industrial settings. The research underscores the potential of spectrophotometry as a reliable and economical alternative to advanced techniques like HPLC, promoting its broader application in resource-limited environments
Impact Of Paid Advertising On Brand Awareness On Social Media Platforms
Get PDFIn the contemporary digital age, social media platforms have become essential elements of marketing strategies for enterprises. Among these strategies, paid advertising serves as an essential instrument for augmenting brand exposure and awareness. This study examines the influence of paid advertising on brand awareness across prominent social media platforms, emphasizing user perceptions, effectiveness, and engagement. A quantitative methodology was employed to collect data from 160 participants through structured questionnaires. The findings demonstrate that paid advertisements significantly influence brand recall, trust, and consumer engagement. Additionally, demographic factors such as age and employment have a significant impact on consumer responses to paid advertising. This information may aid businesses in developing more efficient and targeted social media strategies
Study and Incremental Research for Training and Development through Human Resource Enlargement
Get PDFThis research explores the impact of incremental training and development approaches on human resource expansion, focusing on the role of training programs in enhancing employees\u27 skills and performance. It evaluates the impact of skill enhancement techniques on workforce productivity, adaptability, job satisfaction, and organizational growth. The study provides insights into the effectiveness of continuous improvement strategies in HR development and emphasizes the importance of integrating learning modules with business objectives. With an emphasis on the changing trends in corporate learning and employee skill enhancement, this study explores the significance of training and development as a strategic instrument for HR expansion. It seeks to determine the most effective methods for long-term workforce development and examine how innovation and technology affect employee training. The study highlights the advantages of continuous learning in raising employee productivity, job happiness, and overall business performance, offering insightful information to HR experts, corporate trainers, and regulators. Nevertheless, the research is restricted to particular case studies and might not encompass all industry-specific variances. The introduction, literature review, research methodology, analysis and findings, and conclusion and recommendations make up the thesis\u27s five key chapters
Morphological and Biochemical Characterization of Synthesized TiO2 Nanoparticles for Enhanced Biotreatment of Pharmaceutical, Ayurvedic, and Culinary Wastewater
Get PDFThe rapid increase in pharmaceutical, Ayurvedic, and culinary wastewater production has led to growing environmental concerns, particularly in the context of wastewater treatment. These effluents are often rich in organic and inorganic pollutants, including biological oxygen demand (BOD), chemical oxygen demand (COD), color, trace metals, and oils, posing significant challenges for wastewater treatment. This study investigates the synthesis and characterization of titanium dioxide (TiO2) nanoparticles using plant extracts from Parthenium hysterophorus and Saccharum spontaneum. The green synthesis method, facilitated through spray drying, produced TiO2 nanoparticles with distinct morphological and biochemical properties that hold promise for biotreatment applications. The nanoparticles were characterized using Fourier Transform Infrared Spectroscopy (FTIR), X-Ray Diffraction (XRD), and Field Emission Scanning Electron Microscopy (FE-SEM), revealing functional groups, crystal phases (rutile and anatase), and nanoparticle morphology ranging from spherical to hexagonal with sizes between 72.9 nm and 190 nm. The study also demonstrates the potential of electrochemical coagulation (ECC) as an efficient biotreatment method for pharmaceutical, Ayurvedic, and culinary wastewater. The results suggest that TiO2 nanoparticles, synthesized through a green approach, could serve as effective agents in the treatment of wastewater from diverse sectors, offering a sustainable and eco-friendly alternative for environmental remediation
The Role of Machine Learning in Predictive Business Management
Get PDFThe integration of machine learning (ML) tools into business processes has significantly transformed decision-making and predictive management in organizations. This research explores the relationship between ML adoption and predictive business outcomes, focusing on key factors such as data quality, managerial support, employee competency, and technological infrastructure. Using a survey of 250 respondents from various industries, the study tests five hypotheses concerning the role of ML in decision-making processes. Findings reveal that higher data quality and availability, along with effective managerial support, significantly enhance the effectiveness of predictive decision-making. Additionally, employee competency in ML tools positively impacts business performance, and technological infrastructure plays a critical role in the success of ML-driven management practices. The study concludes by discussing the implications of these findings for organizations looking to adopt ML solutions, providing recommendations for fostering a supportive environment that includes training, infrastructure, and leadership commitment to drive success. Future research may explore the long-term effects of ML integration in diverse sectors and its impact on organizational culture and employee engagement.
 
Designing Cloud-Native AI Infrastructure: A Framework for High-Performance, Fault-Tolerant, and Compliant Machine Learning Pipelines
Get PDFBig Tech companies have spent the last decade designing scalable, elastic, and resilient cloud infrastructures to support their business applications. However, the emergence of machine learning as a service-area-in-silico and the urgent need for operationalizing compliance in highly regulated industries have required them to invest an additional effort in designing cloud-native infrastructures to support ML workloads. These infrastructures must provide the required elasticity and efficiency to support high-performance, fault-tolerant, blameless, and compliant ML pipelines. The principled redesign of cloud architectures to overcome the challenges of serving ML workloads at scale is essential for accelerating their maturity; however, it has yet to start in earnest. This paper contributes a framework to guide the design of cloud-native infrastructures for ML workloads that links high-level design requirements with architectural dimensions. The framework enables architecture teams to compose the design of cloud-native architectures for ML workloads by exposing the architectural trade-offs involved in configuring elasticity, performance, fault-tolerance, compliance, cost, and risk for ML workloads. We describe the design framework properties using concrete examples that optimize for elasticity, cost, and risk. Finally, we argue that the principled design of cloud architectures for ML workloads is paramount for accelerating their further adoption and maturity in enterprise environments