Clinico haematological profile in beta Thalassemia trait
Introduction with Objectives: - The most common causes of microcytic hypochromic anemia in India are β Thalassemia & Iron deficiency anemia (IDA). β- Thalassemia is one of the most common single gene disorder in India with an overall prevalence of 3-4 %. Effective screening of β Thalassemia trait (βTT), decrease its incidence. Hb electrophoresis, serum iron profile & RBC indices are used to differentiate βTT from IDA .HbA2, red cell indices are observed as effective screening tests in βTT. Our main objective is to study the hemoglobin electrophoresis & RBC indices in β-Thalassemia Trait & to differentiate from IDA. Methodology: - A retrospective study of 50 patients (OP & IP) admitted in our KMC & hospital, Manipal was done. Study period was 1year (Aug 2015-Sep 2016). HbA2 level is studied by capillary zone electrophoresis method. Hb & red cell indices (MCV, MCH, RDW) were calculated. From red cell indices formulas –Mentzer (MI-cut off-13), Srivastava (SI-3.3), Shine & Lal(S&L-595), England & Frazer (E&F-1.39) were derived & serum iron profiles (Fe 2+, TIBC, Ferritin) was done to distinguish βTT from IDA. Vitamin B12 & folate assay was done . Sensitivity, specificity & Youden index were also calculated . Results:-All 50 pts were diagnosed as β-Thalassemia Trait (HbA2≥3.5 .Hb≤8gms/dl, MCV<60fL, MCH5x106/mm3, RDW>16%).Mean age group is 50yrs, M>F.3/50 cases (6%) shows ↑ HbF along with ↑HbA2.2/50 (4%) has ↑HbS .1 case shows IDA features with βTT. 49/50 (98%) cases of βTT showed-≤ cut off values of all index (MI,SI, S&LI ,E&FI). Serum iron profile was normal in 24/50 (48%), ↑ serum ferritin in 5/50 (10%).↑ vitamin B12 & folate levels seen in 9/50(18%).1 case showed ↓iron profile & ↑index. The MI is the most sensitive (>90%) & specific (>83%). Conclusion:-βTT & IDA are the M.C. causes of microcytic anemia. Hemogram parameters and RBC indices have significant role in βTT. HbA2, MCV & MI are the most sensitive tool to detect βTT.
Published by: Dr. Muthu Venkat T.
Author: Dr. Muthu Venkat T.
Paper ID: V6I4-1193
Paper Status: published
Published: July 15, 2020
Managing cross-cultural diversity in global scenario through HR strategies
International management has never been as significant as today. As the 21st Century has been tremendous growths in enterprise sectors many of the world’s largest firms are truly global and even their small counterparts increasingly participate in cross-border activities by- having customers, joint venture partner collaboration around the globe. The trend towards a single global economy is expanding the market and providing limitless opportunities for global business. Place of a job today consists of people who are diverse and unique in religion and culture, language, age gender and ability, education, interest and opinion, expectations as well. The cultural diversity of a company has cascading effects on the way its organization messages are restrained, collected, allocated, and perceived and how it is elucidated. Global workforces managing has increased pressure on human resource managers to identify and adopt the culture differences. To remain competitive, companies must have an understanding of HRM practices and cultural differences across the globe. The main motive of this study is to get a clear concept of cross-cultural management and to identify the reason, how HR mange to develop a multicultural workforce, the resultant challenges, and the way to manage effectively the diversified workforce in the international scenario.
Published by: Anisha Anil Hande
Author: Anisha Anil Hande
Paper ID: V6I4-1149
Paper Status: published
Published: July 15, 2020
A pre-experimental study to assess the effectiveness of a structured interventional program on knowledge regarding care of patients with chest tube drainage among staff nurses in IGMC and Hospital, Shimla, Himachal Pradesh
Introduction: A chest tube insertion is a surgical procedure to remove the air, blood, pus, lymph, and fluid from the pleural space by inserting a hollow, flexible drainage tube through the side of the chest in the pleural space. A chest tube is a widespread therapeutic intervention for patients admitted to medical and surgical care areas. It is associated with significant morbidity and mortality. Objectives: To assess the knowledge of staff nurses regarding the care of the patient with chest tube drainage, To evaluate the effectiveness of the structured interventional program on knowledge regarding care of the patient with chest tube drainage among staff nurses, to find out the association between pre-test scores of knowledge regarding care of the patient with chest tube drainage with selected socio-demographic variables. Methods: A quantitative one group pre-test and post-test design were conducted at IGMC and Hospital Shimla, Himachal Pradesh. A total of 40 staff nurses were selected by convenience sampling technique. The tool used for data collection was a structured knowledge questionnaire. A structured interventional program on care of patients with chest tube drainage with the use of ppt was administered. Results: The majority of the subjects 19(47.5%) fall in the age group between 26-30 years. With respect to education, 19(47.5) have done B.Sc nursing. 22 (55.0%) of the staff nurses had experienced between 2-3 years, and 34(85.0) of them belong to the Hindu religion. The majority had 20 (70%) average knowledge, 16 (40%) of staff nurses had poor knowledge and 4(10%) of them had good knowledge whereas after intervention majority 28(70%) of the subjects have good knowledge, 12(30%) of subjects has average knowledge and none of the subjects has poor knowledge regarding care of patients with chest tube drainage. The mean knowledge score in the pre-test was (16.6 ±7.98), in the post-test was (31.65±6.12) which indicates there is an increase in knowledge of the subjects. Conclusion: The study concluded that a structured interventional program on the care of the patient with chest tube drainage was found to be effective in increasing the knowledge of staff nurses. Staff nurses had a significant gain in knowledge regarding the care of patients with chest tube drainage.
Published by: Lovely, Sangeeta Sharma
Author: Lovely
Paper ID: V6I4-1196
Paper Status: published
Published: July 15, 2020
Behaviour of youth towards sustainable and fast fashion
Sustainable fashion is producing clothes, shoes, and accessories in environmentally and socio-economically sustainable manners with more sustainable patterns of consumption and use, which necessitate shifts in individual attitudes and behaviour. Sustainable clothing refers to fabrics derived from eco-friendly resources, such as sustainably grown crops or recycled materials and how these fabrics are made. Fashion is the second most polluting industry globally. The apparel and footwear industries together account for more than 8% of global carbon emissions, greater than all international airline flights and maritime shipping routes combined. On average a person consumes 11.4kg of apparel each year (Quantis 2018). It takes about 2,720 litres of water to produce just one cotton shirt – a number equivalent to what an average person drinks over three years (EJF). Nearly three-fifths or 60% of all clothing produced ends up in incinerators or landfills within a year of being made (McKinsey 2016). The total level of fashion waste is expected to be 148 million tons by 2030—equivalent to annual waste of 17.5 kg per capita across the planet. Textile dyeing is the second largest polluter of clean water globally, after agriculture. In such severe conditions, unawareness among consumer about sustainable fashion costs the environment. The main objectives of this study is to analyse whether the trend towards buying sustainable fashion really helping with climate crisis, or should one simply be buying less clothing? For the conservation of the environment, the sustainability of fashion is the utmost need in the present fastest growing world. This research is based on empirical study done with literature review and other secondary data sources. A combination of quantitative and qualitative research methodology approach has been adopted to understand ethical shopping.
Published by: Pragya Gargee
Author: Pragya Gargee
Paper ID: V6I4-1204
Paper Status: published
Published: July 15, 2020
Green Building: A Review
Green Building is a technology which has been developed and put forward in recent years, so as to lead our world towards economic, global as well as social sustainability. Green buildings are quite related to sustainable buildings and they are interchangeable. Green buildings are helpful considering several factors like reduction of carbon footprint, usage renewable energies, use of less energy,usage of smart materials and so on. In recent times, world is facing a major problem of drastic climate change. A major contributor to climate change is the construction industry. Buildings are responsible for an estimated 33% global greenhouse gas emission. Between 1971 and 2004, Carbon dioxide (CO2) grew 2.5% for commercial buildings and 1.7% for residential buildings. This puts the concept of green building in light. Government all around the globe have started to take this concept solemnly. Few organizations are in place for rating green buildings. LEED also known as Leadership in Energy and Environmental design is one of the leading organization. Green building rating system in India are Green Rating for Integrated Habitat Assessment (GRIHA), Indian Green Building Council (IGBC). These organizations rate the buildings on various factors like operation, cost, maintenance, etc. The intention of writing this paper is to acquaint everyone with green building.
Published by: Chetan Sonvane, Ompriya Kale
Author: Chetan Sonvane
Paper ID: V6I4-1154
Paper Status: published
Published: July 15, 2020
Detection of Cyberbullying using Machine Learning
Cyberbullying is a form of bullying in which technology is used as a medium to bully someone. As the new boom of the internet and other social media platforms are increasing, the number of users is also increasing and the main users of social media are mostly teens and young adults. As much as these social media platforms are used for getting new information and for entertainment, it is more prone for bullies to uses these networks as vulnerable to attacks against victims. Due to the increase in cyberbullying on victims, it is in need to develop a suitable method for the detection and prevention of cyberbullying. A growing body of work is emerging on automated approaches to cyberbullying detection. These approaches utilize machine learning and natural language processing techniques to identify the characteristics of a cyberbullying exchange and automatically detect cyberbullying by matching Textual data. The main objective of this project is to detect cyberbullying by matching both Image and Textual data. The test cases and are used to classify the dataset and detect the bullying. Machine learning techniques are used to efficiently predict and detect cyberbullying.
Published by: Sinchana C., Sinchana K, Pradyumna C S, Deepika S
Author: Sinchana C.
Paper ID: V6I4-1214
Paper Status: published
Published: July 13, 2020
