The total population of the world today has exceeded 7.8 billion. Population growth is considered to be the biggest problem in the world. Four people are born every second. Death is happening in the same proportion? No, people die every moment, even if they don't die in proportion to birth. An average of 56 million people dies each year in the world. That means, two people leave the world in every second!
Cancer is considered the second leading cause of death globally, accounting to the report of world Health organization, 9.6 million deaths, or one in six deaths, in 2018. Lung, prostate, stomach and liver cancer are the most common types of cancer in men, while breast, lung, and thyroid cancer are the most common among women. (According to the WHO Report)
Cancer is not a contagious disease. It is not yet known exactly why these normal cells turn into abnormal cells. Harmful chemicals, 'hormone' radioactivity, occupations, habits (smoking, tobacco use, alcohol, etc.), injury, reproduction and perverted sexual behavior, air and water pollution, food (e.g., high fat or high fat diet), various racial, living systemic, geographical and environmental influences, parasites and viruses are generally universally recognized causes of cancer.
Once upon a time it was thought that cancer means death. But with the advancement and progress of medical science and technology, these ideas are no longer true at all, nor are the treatment of cancer invincible. It is possible to cure many cancers very easily. All that is needed is timely diagnosis and treatment.
Prospect of these studies
Currently Chemotherapy and radiotherapy is the most common treatment for the cancer. But, chemotherapy and radiotherapy have much more side effect due to less specificity, side effect including hair loss, Damage to lung tissue, Heart problems, Kidney problems, Nerve damage, Risk of a second cancer Chemotherapy mainly affect both normal and cancer cell which grow and divide so fast in the body. such as during the formation of new blood cells in the bone marrow or the cells in the mouth, stomach, skin, hair and reproductive organs.
So, scientists are trying to development of many new tumor and anti-cancer drug for actual targeted sites to reduce this dangerous side effect. In the last two decades, Scientist are being used nano technology for the treatment of cancer. And it is good news that they get many advantages for the cancer treatment by using nano medicine technology such as good pharmacokinetics, precise targeting of tumor cells, reduction of side effects, and drug resistance. The nano technology for the cancer treatment including Lipid based nanoparticles (liposomes), Polymer/lipid-based nanoparticles and micelles, Carbon-based nanoparticles and EPR etc.

Employee retention is the dependent variable in the study that is influenced either positively or negatively by the independent variable represented by the term human resource management initiatives whose variables are: training and development, career development strategies, job satisfaction and compensation policies. Employee retention has a relationship with human resource management initiatives; if the HRM initiatives are good the retention rates will be high while if HRM initiatives are poor there will be high employee turnover. Kenya Airways workers are vitally important for the effective functioning of airline systems and networks. The general objective of this study was to find out the influence of human resource management initiatives on employee retention at Kenya airways. The specific objectives of the study were; to assess the influence of training programs on employee retention at Kenya airways, to examine the effect of career development strategies on employee retention at Kenya Airways, to establish the effect of job satisfaction on employee retention at Kenya Airways and to determine the effect of compensation policies on employee retention at Kenya airways. The theoretical framework of the study consisted of Herzberg Two Factor Theory, Role Behavior Theory, Reinforcement Theory and Job Embeddedness Theory. This research adopted a descriptive research design which was used to explain characteristics of the subject being studied .Stratified sampling technique ad simple random sampling was used to select sample size of 109 respondents from the target population of 1089 respondents in Kenya Airways. Primary data was collected by use of self-administered structured questionnaires which was distributed through the drop and pick method. The secondary data collected was used to identify gaps, formulate objectives, validate the findings and interpret the primary data collected in-order to get reliable results. The collected data was analyzed quantitatively and qualitatively. Descriptive and inferential statistics was done using Statistical Package for Social Sciences (SPSS) version 24 and specifically multiple regression models were used for answering the research questions. Set of data was described using percentage, mean standard deviation and coefficient of variation and presented using tables, charts and graphs. The hypothesis testing was done at 95% confidence level testing and hence all the null hypotheses were rejected since their significance level was less than 0.05 meaning that the alternative hypotheses were accepted. The study revealed that human resource management initiatives had a statistically significant effect on employee retention at Kenya Airways. Employee training had a statistically significant effect on employee retention at Kenya Airways. Career development had a statistically significant effect on employee retention at Kenya Airways. Job satisfaction had a statistically significant effect on employee retention at Kenya Airways. Compensation policies had a statistically significant effect on employee retention at Kenya Airways. The study recommended that Kenya Airways management should adopt human resource management initiatives so as to boost employee retention.

Objective: To estimate the prevalence and pattern of iron deficiency (ID) in heart failure (HF) patients with or without anemia.

Methods: This study is conducted at a tertiary care hospital of Tamil Nadu. It is a single-centre observational study. Patients included in the study were admitted to hospital with clinical diagnosis of HF based on validated clinical criteria. ID was diagnosed based on complete Iron profile, including serum ferritin, serum iron, transferrin saturation (TSAT) and total iron binding capacity. Anaemia was defined as haemoglobin (Hb) <13 g/dl for males and <12 g/dl for females, based on World Health Organization definition. Absolute ID was taken as serum ferritin < 100 mg/L and functional ID was defined as normal serum ferritin (100–300 mg/L) with low TSAT (<20%).

Results: A total of 120 patients of HF (62% males and 38% females) were studied. Most of the patients were of high-functional NYHA class (mean NYHA 2.84 + 0.95). ID was present in 74% patients with 45.7% patients having absolute and 28.3% patients having functional ID. Females were having significantly higher prevalence of ID than males (90.2% vs 66.6%; p = 0.002). Nearly one-fourth of the patients were having ID but without anaemia, signifying importance of workup of ID other than Hb. Conclusion: Our study highlights the neglected burden of ID in HF patients in India. This study suggests further large-scale studies to better characterize this easily treatable condition and considering routine testing in future Indian guidelines.

This review presents infrared thermography, its application in livestock production and its integration with machine learning algorithm to provide an end-to-end solution towards enhancedproductivity. Infrared thermography is a simple non-contact, non-invasive method to detect surface temperature radiated from an animal skin. Temperature data is used to generate images called thermograms which can be used for diagnosis of diseased and non-diseased conditions. Real time collection of thermal data has resulted in huge volume of data, which requires the use of machine learning algorithms to assist the farmers gain insights that could be used to make informed decisions. The potential of the integration of machine learning and infrared thermography in livestock production have been explored. The areas of application include identification of unique features of individual animals, real time tracking of animals and determining breathing patterns that could indicate stress and pain. With improved understanding of how machine learning algorithms can be integrated with infrared thermography, farmers can explore other areas of application of both infrared thermography and machine learning to improve health, welfare and productivity of livestock.