Demand for Foreign Exchange Reserves in India: A Co-integration Approach

Using cointegraion and vector error correction approach, we estimate India’s demand for foreign exchange reserves over the period 1983:1-2005:1. Our results establish that the ratio imports to GDP, the ratio of broad money to GDP,exchange rate flexibility and interest rate differential determine India’s long-run reserves demand function. Our empirical results show that reserve accumulation in India is highly sensitive to capital account vulnerability and less sensitive to its opportunity cost. The speed of adjustment coefficient of vector error correction model suggests that Reserve Bank of India has to engage in more active reserve management practices.foreign exchange reserves; capital account vulnerability; current account vulnerability; cointegration

ALBI and Child-Pugh Score in Predicting Mortality in Chronic Liver Disease Patients Secondary to Alcohol: A Retrospective Comparative Study

Background/Aims: The severity of liver dysfunction in chronic liver disease (CLD) is often estimated with Child-Pugh (CTP) classification or model for end-stage liver disease (MELD) score. The albumin-to-bilirubin (ALBI) score is a new model for assessing the severity of liver dysfunction, which is simple and more objective. In the present study, we aimed to retrospectively compare the performance of ALBI score with Child-Pugh score for predicting the mortality in patients with CLD. Material and methods: Data of patients with CLD, irrespective of etiology, were retrospectively reviewed. Child-Pugh score and ALBI score were calculated for the patients and results from receiver operating characteristic (ROC) curves were analyzed. Results: The study was conducted on 299 patients of CLD; age distribution was between 20 and 85 years with mean age of patients being 45.7 ± 10.94 years, sex ratio male: female 265:34 with mortality rate of 19.73%. The area under the curve (AUC) of ROC of ALBI and Child-Pugh were 0.586 and 0.549, respectively. Conclusion: Ability of ALBI score for predicting mortality was comparable with that of Child-Pugh score but Child-Pugh score of >10 had better performance of predicting mortality as compared to ALBI score

Rapid Bedside Ultrasonography and Its Correlation with Clinical Assessment in Management of Different Types of Shock in Paediatric Emergency Room

INTRODUCTION: Paediatric shock is one of the important cause of mortality and morbidity worldwide. Shock is defined as inability of cardiovascular system to provide adequate oxygen and nutrients to meet metabolic demands of vital organ. Hypovolemic shock due to acute gastroenteritis is the most common type in paediatric shock followed by septic shock. Cardiogenic and obstructive shock are less common in children. Still they are important because they are very difficult to diagnose in paediatric population. Mortality due to shock is reduced by early recognition. Ultrasound has a role in identification of reversible and undifferentiated shock. OBJECTIVE: 1. To study the bedside ultrasound (POCUS) findings in various types of shock in paediatric emergency room. 2. To compare the clinical signs with USG findings in fluid intolerant state during the shock management. STUDY DESIGN: Cross- Sectional study (Prospective descriptive). STUDY SETTING: All children admitted in Paediatric ER, Institute of Social Paediatrics, Govt Stanley Medical college with shock in the period June 2018 to May 2019. METHODOLOGY: All the patients with shock with the age 29 days of life to 12 years of age with shock were selected for the study . Shock patients with other co morbidities like known congenial heart disease, Chronic kidney disease, chronic liver disease, protein losing conditions causing hypoproteinemia, Severe Acute Malnutrition were excluded from the study. Short History obtained from the guardian regarding the cause of the shock, co morbid illness , previous treatment. Clinical assessment- Rapid cardio pulmonary assessment (PEMC Guidelines) done for the child. Categorization of type and severity of shock were done, followed by USG assessment by POCUS protocol. Parameters analysed were Heart-cardiac contractility, pericardial effusion, IVC- diameter, collapsibility, Aorta- diameter, IVC / aorta ratio, Free fluid in the peritoneal cavity, Free fluid in pleural cavity/pneumothorax and Lung parenchyma-diffuse lung rockets, multiple B profile comet tail artifact. Shock was managed according to PEMC guidelines. Child was reassessed clinically and ultrasonographically after every management. Till recovery from the shock, signs of fluid intolerance and after initiation of ionotrope. Children were followed by me throughout the hospital stay/upto death. STATISTICAL METHOD: Data was analysed using R software Version 3.6.1. All demographics, clinical, ultrasound measurements and types of shock were represented as frequency and percentages. The agreement between clinical parameters with the ultrasound parameters for fluid overloaded cases were assessed using Kappa agreement statistics. RESULTS: Among 103 cases, 64 cases (62%) were hypovolemic shock, 24 cases (23%) were septic shock, 9 cases (9%) were cardiogenic shock and 6 cases were obstructive shock during the initial assessment. 24 cases showed signs of fluid intolerance during shock management. USG findings 103 shock patients showed the following results: Hypovolemic Shock: Hyperdynamic LV (78.2%), IVC/ AORTA ratio decreased (91%), IVC collapsible (100%), Lungs A profile (100%). Septic Shock: Hyperdynamic LV (79.2%), IVC/AORTA ratio decreased (87.5%), IVC Collapsibility(100%), Lungs USG A profile(100%). Cardiogenic Shock: Hypodynamic LV (100%), IVC/ AORTA fullness (100%), IVC non collapsible (100%), Lungs USG B profile (67%). Obstructive Shock: Hyperdynamic LV (100%), RV Strain (84%), RV diastolic collapse (16%), pericardial effusion (16%). Lungs USG showed absent sliding sign / bar code sign in M mode (68%), loculated effusion (16%). CONCLUSION: USG findings in Hypovolemic & septic shock are similar in initial assessment. USG doesn’t help in differentiating the hypovolemic & septic shock. In obstructive & cardiogenic shock USG findings confirms the diagnosis. In fluid intolerant states during shock correction sudden increase in liver span had almost perfect agreement (0.833) with the increased IVC/Aorta ratio (IVC fullness) and IVC non-collapsibility

Association of serum iron studies in COVID associated mucormycosis with stage of the disease

Background: Mucormycosis is a rare and lethal invasive fungal infection caused by opportunist and ubiquitous fungi. India has reported surge in cases of post COVID 19 mucormycosis due to the increasing frequency of risk factors like corticosteroid therapy, uncontrolled diabetes, DKA, neutropenia and iron overload and hence warrants a detailed study to identify potential contributing factors. Aim of this study was to study the clinical profile of patients with CAM and to correlate serum iron studies with severity and extent of disease in CAM patients. Methods: This prospective crosssectional study was conducted on 75 patients with CAM admitted to Bowring Hospital, Bangalore. Detailed history with clinical evaluation and appropriate investigations done and data was analysed. Results: The mean age of the subjects was 48.19 with 52 males and 23 females. Among 75 patients 90.7% were unvaccinated against COVID, 62.7% had oxygen and steroid use, with diabetes mellitus as most common comorbidity. Rhino orbital-cerebral mucormycosis was the most common clinical presentation. Patients with stage 4 CAM had elevated levels of inflammatory markers LDH (292), D-dimer (457), CRP (74.64), mean serum iron (50.37) and TIBC (255.37). Case fatality rate was 12%. Conclusions: The results of this study revealed significant correlation between the clinical severity of CAM and higher mortality, with increased serum iron levels and inflammatory markers. Therefore patients with elevated levels of available serum iron are uniquely susceptible to mucormycosis infection, suggesting dysregulated iron metabolism in its pathogenesis

Demand for Foreign Exchange Reserves in India: A Co-integration Approach

Using cointegraion and vector error correction approach, we estimate India’s demand for foreign exchange reserves over the period 1983:1-2005:1. Our results establish that the ratio imports to GDP, the ratio of broad money to GDP,exchange rate flexibility and interest rate differential determine India’s long-run reserves demand function. Our empirical results show that reserve accumulation in India is highly sensitive to capital account vulnerability and less sensitive to its opportunity cost. The speed of adjustment coefficient of vector error correction model suggests that Reserve Bank of India has to engage in more active reserve management practices

Demand for Foreign Exchange Reserves in India: A Co-integration Approach

Using cointegraion and vector error correction approach, we estimate India’s demand for foreign exchange reserves over the period 1983:1-2005:1. Our results establish that the ratio imports to GDP, the ratio of broad money to GDP,exchange rate flexibility and interest rate differential determine India’s long-run reserves demand function. Our empirical results show that reserve accumulation in India is highly sensitive to capital account vulnerability and less sensitive to its opportunity cost. The speed of adjustment coefficient of vector error correction model suggests that Reserve Bank of India has to engage in more active reserve management practices

Wifi Infrastructure Security System from Vulnerable Attacks

Abstract Wi-Fi is a very popular wireless technology which is powerful core for the global digital infrastructure. A device connected using Wi-Fi can access the network resource such as the Internet via a wireless network access point. Recent discoveries and initiatives highlight a simple fact that the core is just as vulnerable as the edge. Wi-Fi can be less secure than wired connections because an intruder does not need a physical connection. Though security threats are imminent due to the open nature of communication, there are certain ways to protect the infrastructure of a network.In this paper, we examine the vulnerabilities of Wi-Fi network and this includes the intrusion detection in the security architecture of that network. We have shown such mechanism to solve arrival of intruders by Man-in -the-middle attack on a Wi-Fi network. Also, provide the steps to eliminate hackers from the Wi-Fi network and descriptions regarding the operations performed by different tools to avoid attackers from network. There are several holes in the wireless environment through which the attacks enter the network. In future those holes may be blocked completely by eliminating hackers from all attacks through which they enter. We also discuss a number of available solutions for controlling those threats

Internet of Things and Machine Learning Applications for Smart Precision Agriculture

Agriculture forms the major part of our Indian economy. In the current world, agriculture and irrigation are the essential and foremost sectors. It is a mandatory need to apply information and communication technology in our agricultural industries to aid agriculturalists and farmers to improve vice all stages of crop cultivation and post-harvest. It helps to enhance the country’s G.D.P. Agriculture needs to be assisted by modern automation to produce the maximum yield. The recent development in technology has a significant impact on agriculture. The evolutions of Machine Learning (ML) and the Internet of Things (IoT) have supported researchers to implement this automation in agriculture to support farmers. ML allows farmers to improve yield make use of effective land utilisation, the fruitfulness of the soil, level of water, mineral insufficiencies control pest, trim development and horticulture. Application of remote sensors like temperature, humidity, soil moisture, water level sensors and pH value will provide an idea to on active farming, which will show accuracy as well as practical agriculture to deal with challenges in the field. This advancement could empower agricultural management systems to handle farm data in an orchestrated manner and increase the agribusiness by formulating effective strategies. This paper highlights contribute to an overview of the modern technologies deployed to agriculture and suggests an outline of the current and potential applications, and discusses the challenges and possible solutions and implementations. Besides, it elucidates the problems, specific potential solutions, and future directions for the agriculture sector using Machine Learning and the Internet of things

Serum Phosphorus and Risk of Cardiovascular Disease, All-Cause Mortality, or Graft Failure in Kidney Transplant Recipients: An Ancillary Study of the FAVORIT Trial Cohort

Mild hyperphosphatemia is a putative risk factor for cardiovascular disease [CVD], loss of kidney function, and mortality. Very limited data are available from sizable multicenter kidney transplant recipient (KTR) cohorts assessing the potential relationships between serum phosphorus levels and the development of CVD outcomes, transplant failure, or all-cause mortality

Integration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function

In conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P = 5.6 × 10−9) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 × 10−4-2.2 × 10−7. Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in genera