Volume 12 | Issue 5 |

 Abstract

Background: Research on COVID-19 acute phase reactants is still important today since it helps with early diagnosis, determining the severity of the illness, and assessing the efficacy of treatment. Critical information about the course and prognosis of the disease can be gained by analyzing the inflammatory response using acute phase reactants such as serum amyloid Acute phase proteins and C-reactive protein. Severe outcomes in COVID-19 individuals have been associated with higher acute phase reactants, lymphopenia, and neutrophil counts. By keeping an eye on these indicators, medical staff can enhance patient care, more efficiently use resources, and possibly even identify patients who are more likely to experience difficulties. All of these things can lead to better clinical outcomes and public health initiatives. Method: The study analyzed data from 200 hospitalized COVID-19 patients at an academic tertiary care hospital between August 2020 and June 2022. It focused on investigating various blood parameters, including C-reactive protein, ferritin, lactate dehydrogenase, erythrocyte sedimentation rate (ESR), procalcitonin, and albumin. Inclusion criteria comprised patients with positive COVID-19 RT-PCR results and complete lab records, while exclusion criteria included negative RT-PCR results, incomplete records, hospital stays less than one week, and patient transfers. Result: In our study of 200 hospitalized COVID-19 patients, C-reactive protein (CRP) levels were elevated in 179 (89.5%) patients, with 147 (90.74%) in wards and 32 (84.21%) in ICU. Procalcitonin levels were elevated in 51 (51.51%) patients overall, with 29 (40.85%) in wards and 22 (78.57%) in ICU. Ferritin levels were elevated in 94 (46.5%) patients, with 65 (40.12%) in wards and 28 (73.69%) in ICU. Elevated lactate dehydrogenase (LDH) was found in 110 (55%) patients, with 83 (51.23%) in wards and 27 (71.05%) in ICU. Erythrocyte sedimentation rate (ESR) was high in 128 (64%) patients, with 102 (62.96%) in wards and 26 (68.42%) in ICU. Decreased albumin levels were observed in 44 patients, with 24 (14.82%) in wards and 20 (52.63%) in ICU. Conclusion: Acute phase reactants like CRP, procalcitonin, ferritin, LDH, ESR, and albumin significantly influence COVID-19 progression, severity, and prognosis. Elevated CRP, procalcitonin, ferritin, LDH, ESR, and decreased albumin levels are strongly linked to disease severity and mortality. ICU patients exhibit more pronounced alterations in these markers compared to ward patients, aiding in severity prediction. Increased alterations in acute phase reactants are observed in deceased patients versus recovered ones, facilitating progression and prognosis prediction. Testing for these markers upon hospital admission in suspected or confirmed COVID-19 cases offers valuable prognostic insights. Utilizing acute phase reactants as predictive measures can enhance clinical management in COVID-19 patients. Keywords: COVID 19; Acute phase reactants; ICU; C Reactive Protein; Ferritin; Procalcitonin; LDH; ESR

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

COVID 19; Acute phase reactants; ICU; C Reactive Protein; Ferritin; Procalcitonin; LDH; ESR

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Inventory Management have significant influence in Aromatic Industry. The paper briefly discusses the impact of inventory management in the manufacturing company. The paper, with an aim of understanding the potential and practical implications of inventory management techniques and tools in the organization. Through a comprehensive review and analysis of existing literature, this paper examines various inventory management techniques and inventory optimization models. The study employees both descriptive and analytical approaches. The statistical tool considered to measure the significance is chi-square test method will be employed to test the significance.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Inventory management, inventory management techniques, turnover ratio

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This project entails the development of a robust data pipeline for OLX data leveraging Python. The pipeline employs web scraping techniques or OLX APIs for data extraction, followed by meticulous data transformation in Python to ensure data integrity and relevance. The processed data is stored in a chosen repository, utilizing Python libraries and frameworks for seamless integration. Automation and scheduling are implemented using Python-scripts. The pipeline incorporates error-handling mechanisms, and data quality checks are enforced throughout the process. The Python-based pipeline not only provides an efficient and scalable solution for handling OLX data but also facilitates easy integration with popular analytics tools, empowering users to derive actionable insights for strategic decision-making. The OLX Data Pipeline ensures a systematic and efficient processing of JSON-encoded data, laying the groundwork for insightful analytics and informed decision-making based on the structured information within OLX listings.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Data Pipeline, OLX, Python, Web Scraping, APIs, Data Extraction, Data Transformation,Data Integrity,Data Relevance,Data Storage, Repository, Integration ,Automation, Scheduling, Error Handling, Data Quality, Analytics Tools, Scalability, Efficiency, JSON-Encoding, Structured Data Processing, Decision-Making

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Introduction: Shareera is composed of Dosha, Dhatu and Mala. Dhatus are the entities which supports our body and helps in performing proper physiological functions. Asthi is one among the Sapta Dhatu, which mainly involves in Shareera Dharana function. Asthi Dhatu is located in its Srotas as well as in the whole body. Moolasthana of Asthivaha Srotas is Meda and Jaghana. Aims and Objectives: To understand the Asthi Dhatu and Asthivaha Srotas and its possible physiological interpretations. Materials and Method: Literature searches were conducted using classical text in Ayurveda, contemporary books, articles and many others. Discussion and conclusion: Asthi Dhatu plays a vital role in maintaining the physical integrity of the body. The possible interpretation of the Moolasthana of Asthivaha Srotas can be understood as fat or bone marrow adipose tissue and pelvic bone.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Asthi, Asthi Dhatu, Asthivaha Srotas

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

A smart plant monitoring system is designed to provide comprehensive monitoring and management of plants in various environments, such as agriculture, horticulture, or indoor gardening. This system leverages advanced technologies like Internet of Things (IoT), sensors, data analytics, and machine learning to optimize plant growth, conserve resources, and enhance productivity. Here's a detailed abstract outlining the components and functionalities of such a system: Sensor Network: The backbone of the smart plant monitoring system is a network of sensors deployed within the plant environment. These sensors measure various parameters critical to plant health and growth, including soil moisture, temperature, humidity, light intensity, pH levels, and nutrient levels. Data Acquisition and Transmission: Sensor data is collected at regular intervals and transmitted to a central control system or cloud platform using wireless communication protocols such as Wi-Fi, Bluetooth, or LoRaWAN. This ensures real-time monitoring and enables remote access to the data from anywhere with an internet connection. Data Processing and Analysis: Upon receiving the sensor data, the system processes it using data analytics techniques to derive meaningful insights. Machine learning algorithms may be employed to analyze historical data patterns, predict future trends, detect anomalies, and recommend optimal plant care strategies. Monitoring and Control: The system provides users with a user-friendly interface, typically accessible through a web or mobile application, to monitor the status of their plants in real- time. Users can view sensor readings, receive alerts for abnormal conditions such as water scarcity or pest infestation, and remotely control connected devices like irrigation systems or grow lights. Automation: Smart plant monitoring systems often incorporate automation features to streamline plant care tasks. For example, based on predefined thresholds and algorithms, the system can automatically adjust watering schedules, regulate environmental conditions, and administer nutrient supplements, reducing manual intervention and ensuring consistent plant care. Integration with External Systems: To enhance functionality and interoperability, the smart plant monitoring system may integrate with external systems and databases. This could include weather forecasting services, soil databases, plant databases, and agricultural advisory platforms, enriching the analysis and recommendations provided to users.Scalability and Customization: The system is designed to be scalable to accommodate varying plant sizes and cultivation setups, from small home gardens to large-scale agricultural operations. Additionally, users may have the flexibility to customize settings and preferences according to their specific plant species, growth stage, and environmental conditions. Benefits: By continuously monitoring and optimizing plant conditions, a smart plant monitoring system offers several benefits, including improved crop yields, resource efficiency (such as water and energy conservation), reduced labor costs, early detection of diseases and pests, and overall sustainability in agriculture and gardening practices .In summary, a smart plant monitoring system integrates sensor technology, data analytics, and automation to revolutionize plant care, enabling users to cultivate healthier plants with greater efficiency and precision.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Internet of Things, machine learning, data analytics.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

DiffNet is an advanced model that improves recommendation systems. It takes into account the impact of social networks on user preferences by simulating how they influence each other over time. By incorporating characteristics and interests, DiffNet produces embeddings that reflect a user's changing interests. This method greatly increases recommendation accuracy; it performs 13% better than any other current model. It represents a promising move towards more personalized and efficient recommendations in online platforms. In a social recommendation system, there are users and items. Users express their preferences by interacting with items, such as watching a movie or buying something.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

"Dynamic Social Recommendation Systems: Fusing Customer Networks with AI Dynamics for Enhanced Personalized Item Recommendations in Real-Time"

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Skin lesions affect millions of individuals globally, presenting challenges in diagnosis due to their similar symptoms. This study aims to gather and analyzethe use of machine learning (ML) in skin lesion research, aiming to spur the development of automated systems for skin disease diagnosis. Several skin image datasets have been created to aid dermatologists in clinical diagnosis, leading to the development of automated diagnosis systems utilizing image segmentation and classification techniques. This paper provides an overview of the essential steps in skin lesion diagnosis. It reviews the applications of ML methods, including traditional ML and deep learning (DL), in skin disease recognition, highlighting their contributions, methodologies, and outcomes. Such analysis supports the ongoing advancement of reliable and efficient computer-aided skin disease diagnosis systems. With further re-search, these automatic skin diagnosis studies are expected to be integrated into real clinical settings in the near future.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

skin image segmentation,skin lesion classification,machine laerning , deep learning

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

The banking industry has majorly evolved in the past ten years. The rise of fin-tech services has brought about significant amount of changes in the daily banking scenario. The introduction of digital banking has disrupted the traditional banking landscape in the country by posing threats to established banks for adapting the changes. This global evolution had the maximum impact on Indian millennials (born between 1980 and 1995) since that part of the population had largely experienced traditional banking. This paper aims to examine the impact of the changing financial technologies in the banking industry pertaining to Indian millennials. A sample size of approximately 120 people was taken via Google form to conduct this study.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

"Impact of Fin-tech on the banking industry- A study of Indian millenial"

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In line with the advancement of our understanding of pain mechanisms, there has been a growing emphasis on the creation of novel drug delivery systems that can offer patients individualized treatments without compromising the effectiveness of analgesics. Acute pain serves as a warning, but chronic pain is a syndrome that necessitates careful selection of highly bioavailable analgesic medications for longterm treatment. Topical drugs are designed to address these issues by providing a stable plasma level, allowing for gradual delivery of the active ingredient, and having a high safety profile. The most popular medications' topical formulations for the treatment of pain are reviewed here, along with new research findings. Tension headaches are one symptom of the stress of modern living. Since ancient times, there has been a strong need for cosmetics; however, these days, the emphasis is primarily on derived cosmetic items. In addition to cosmetics, skin care products are also preferred because of their convenient application. Of all dermal medication delivery treatments, pain balm formulations by provide the fastest local effect. Menthol is a naturally occurring, plant-derived cyclic terpene alcohol that has been used for therapeutic purposes since ancient times. It is widely used in dermatology, where it is commonly found in topical preparations for anti-pruritic, antibacterial, analgesic, and cooling purposes. Although menthol is widely used, the mechanism by which it produces the same chilly feeling has just lately come to light.The Identification of the TRPM 8 receptor provided an explanation for the feeling of low temperature. Despite the fact that"this receptor was discovered nearly five years ago, many dermatologists are still unaware of menthol's true target.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

evaluation of herbal pain balm, dermatology is ubiquitous, Castor oil, Mentha oil, Eugenol (clove), Camphor, Rose oil, Bees wax.

  License

Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In contemporary society, a considerable number of individuals view relocating in pursuit of improved living conditions as an optimal choice. Presently, the employment of migrant workers has become a contentious issue in various Indian states, where workers are compelled to migrate from their hometowns due to a lack of economic development, insufficient agricultural land, caste discrimination, limited job opportunities, low wages, mounting debts, and dire family financial situations. Recently, Tiruppur has witnessed a surge in the influx of migrant workers arriving from different parts of India, particularly to work in the textile industry. Despite the significant employment of migrant workers in the textile sector, the industry falls short in providing them with adequate facilities, job security, and appropriate working conditions. A valuable avenue for research lies in understanding the factors motivating individuals in the Tiruppur region to leave their homes and families in pursuit of better employment opportunities. The investigation will primarily focus on utilizing Cramer's model to explore socio-economic issues and challenges within the textile industry that impact migrant workers.

Licence: creative commons attribution 4.0

  License

Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Migrants, Challenges, health conditions, socio-economic, low wages

  License

Creative Commons Attribution 4.0 and The Open Definition