Help Desk Support Ticket and Issue Management

IT companies require methodical approaches to handle the growing volume of customer-reported software issues and service requests. An enormous backlog of unresolved issues has the potential to drastically raise software development and maintenance expenses. An         IT company therefore need a clearly defined customer support model. It acts as a link between the client and the business from beginning to end. The support industry also used this to track and record any procedures and solutions used to close tickets. With the Helpdesk Ticketing System, you can use an online platform to solve questions in a web-based environment. To ensure seamless and efficient operation, the user can submit tickets for even the smallest questions. Both within the company and remotely, the ticketing tool is usable. which can be accessed by anyone in organization or end user

Fine-Grained Session Recommendations in E-commerce using Deep Reinforcement Learning

Sustaining users' interest and keeping them engaged in the platform is very important for the success of an e-commerce business. A session encompasses different activities of a user between logging into the platform and logging out or making a purchase. User activities in a session can be classified into two groups: Known Intent and Unknown intent. Known intent activity pertains to the session where the intent of a user to browse/purchase a specific product can be easily captured. Whereas in unknown intent activity, the intent of the user is not known. For example, consider the scenario where a user enters the session to casually browse the products over the platform, similar to the window shopping experience in the offline setting. While recommending similar products is essential in the former, accurately understanding the intent and recommending interesting products is essential in the latter setting in order to retain a user. In this work, we focus primarily on the unknown intent setting where our objective is to recommend a sequence of products to a user in a session to sustain their interest, keep them engaged and possibly drive them towards purchase. We formulate this problem in the framework of the Markov Decision Process (MDP), a popular mathematical framework for sequential decision making and solve it using Deep Reinforcement Learning (DRL) techniques. However, training the next product recommendation is difficult in the RL paradigm due to large variance in browse/purchase behavior of the users. Therefore, we break the problem down into predicting various product attributes, where a pattern/trend can be identified and exploited to build accurate models. We show that the DRL agent provides better performance compared to a greedy strategy

Revolutionizing Drug Design with Artificial Intelligence: A Comprehensive Review of Techniques, Applications, and Case Studies

Introduction: Artificial intelligence (AI) has the potential to revolutionize drug design and discovery by significantly reducing the time and costs involved in developing new drugs. This literature review aims to explore the use of AI in drug design, focusing on virtual screening, de novo drug design, and prediction of ADME properties. Objective: The objective of this review is to provide an overview of the AI techniques used in drug design and their applications in virtual screening, de novo drug design, and prediction of ADME properties. The review also aims to summarize the advantages and limitations of these approaches and present case studies and examples showcasing their use in drug design. Methodology: A comprehensive search of academic databases was conducted, and 11 relevant articles were selected for inclusion in this review. The selected articles were analyzed to identify the AI techniques used in drug design, their applications, advantages, and limitations. Case studies and examples were also examined to demonstrate the efficacy of AI in drug design. Results: AI techniques such as machine learning, deep learning, and reinforcement learning have been successfully used in virtual screening, de novo drug design, and prediction of ADME properties. Virtual screening involves the use of AI algorithms to identify promising compounds for further testing, while de novo drug design involves the generation of novel compounds using AI techniques. Prediction of ADME properties involves the use of AI to predict the absorption, distribution, metabolism, and excretion of drug candidates. The case studies and examples presented in this review demonstrate the potential of AI to accelerate drug design and discovery. Conclusion: AI has the potential to revolutionize drug design and discovery by significantly reducing the time and costs involved in developing new drugs. Virtual screening, de novo drug design, and prediction of ADME properties are among the most promising applications of AI in drug design. However, further research is needed to fully explore the potential of AI in drug design and overcome some of the limitations of current approaches. Keywords: Artificial Intelligence; Drug Design; Virtual Screening; De Novo Drug Design; ADME Predictio

Study of Anaemia in children and current update

Anaemia in children is a major public health problem throughout the biosphere. It is estimated that at least one-third of the populace has been at one-time anemic. It is often multifactorial, iron deficiency being the most frequent etiology and reasons like malaria endemicity, poor nutrition including micronutrient deficiency, haemoglobinopathies, frequent bacterial infections and high parasitic infestations have been given for these high prevalence rates. Chronic Anaemia may impair growth, cardiac function and cognitive development in infants but other consequences are rather poorly explored more thoroughly. Chronic disorders and iron deficiency were the most common causes of Anaemia. Anaemia was frequently diagnosed in this series of elderly patients. Partly treatable nutritional deficiencies, such as iron or folate deficiency, were identified as possible causes. A complex and heterogeneous interplay of chronic inflammation, functional iron deficiency, and renal impairment was identified in a large proportion of patients. Measures directed at prevention and control of anemia, include increased coverage of supplementation and fortification programs are strongly recommended

Micro-satellite based diversity estimation of Local hill fowl (Uttara fowl): A unique poultry strain of Uttarakhand

Nainital and Pithoragarh districts of Uttarakhand in Himalayan region have 2 types of poultry populations. Uttara fowl is reared under backyard system. But no information is available in the literature of Uttara fowl. The aim of the study was to analyze the genetic diversity in Local hill fowl of Uttarakhand (Uttara Fowl) using panel of micro-satellite markers recommended by FAO. The 50 blood samples were collected from randomly selected Uttara fowl. A total of 25 micro-satellite loci were used for this study. All the analyzed 25 loci were polymorphic and a total of 158 alleles were observed in the present study of Uttara Fowl. The observed and expected heterozygosity ranged from 0.292 (LEI-155) to 0.729 (LEI-90) and from 0.414 (MCW–250) to 0.838 (MCW-228) in Uttara fowl, respectively. Wright’s fixation index (Fis) values among loci ranged from –0.085 (for LEI-90) to 0.747(MCW-84). The mean Fis for 25 microsatellite loci was estimated 0.168. Deviation from Hardy-Weinberg equilibrium was observed in Uttara fowl in the commercial cross. The overall population heterozygote deficiency was 0.168. The existence of sufficient genetic diversity within Local hill fowls, estimated through molecular markers analysis would further aid in a conservation scheme, enabling the planning of new strategies for the improvement of in situ conservation schemes

Evaluation and comparison of the constitutive expression levels of Toll-like receptors 2, 3 and 7 in the peripheral blood mononuclear cells of Tharparkar and crossbred cattle

Aim: This study was undertaken to assess the differential expression levels of toll-like receptors (TLRs) 2, 3 and 7 in peripheral blood mononuclear cells (PBMCs) isolated from Tharparkar and Crossbred cattle belonging to different regions of India. Materials and Methods: PBMCs were isolated from blood samples of Tharparkar cattle from Indian Veterinary Research Institute (IVRI) farm (n=30); Suratgarh farm (n=61); Jaipur farm (n=8) and cross breed cattle from Jaipur (n=47). RNA was isolated from PBMCs and cDNA was synthesized using random hexamers. The expression profiles of TLR 2, 3 and 7 were estimated by real-time PCR and normalized to the expression of β-actin. Results: PBMCs of Tharparkar cattle from Suratgarh, exhibited a significantly higher (p<0.05) constitutive expression levels of TLR2, TLR3 and TLR7 genes as compared to Tharparkar cattle from IVRI or Jaipur as well as the crossbred cattle from Jaipur. PBMCs of crossbred cattle from Jaipur showed higher expression profiles of all the TLRs than Tharparkar cattle from Jaipur and IVRI. Conclusion: Our study indicates, expression levels of TLR2, TLR3 and TLR7 are significantly higher for Tharparkar cattle from Suratgarh than the cattle from Jaipur and IVRI and crossbred cattle from Jaipur. However, crossbred cattle from Jaipur showed higher basal expression levels of all the three TLRs than Tharparkar cattle from Jaipur and IVRI. Results also indicate that PBMCs of Tharparkar cattle show a regional variation in the expression pattern of TLRs

Use of a mouth stick appliance to rehabilitate a quadriplegic patient

This article describes a clinical case report of a young male with a clinical condition of quadriplegia. The patient was functionally handicapped as his arms and hands were underdeveloped, weak and completely disfigured. The article describes the clinical and laboratory procedure of fabricating a simple and inexpensive device which will use the patient’s dentition to perform daily work. The requirements of such a mouthstick appliance have been mentioned and the necessary care that has to be taken during design of such an appliance has been outlined. The patient was highly satisfied with the result and was able to improve his lifestyle by writing, painting and even type with the appliance. The patient’s confidence and social acceptance grew tremendously after using the mouthstick appliance

Improving Structural Integrity of a Centrifugal Compressor Impeller by Blading Optimization

Three-dimensional blading features of impellers like sweep and lean improve the aerodynamic performance of centrifugal compressors, especially in terms of pressure ratio, stall margin and efficiency. But, these blade geometrical features often impose challenges on mechanical design and structural integrity of the impeller. Modern small gas turbine engines demand high-work input impellers rotating at very high speeds, making the structural design even more difficult. The present study deals with improving the structural integrity of a centrifugal impeller of a compressor stage designed for 42,000 rpm and power input of 1200 kW. The baseline design of the impeller, arrived using an advanced three-dimensional design software, met the aerodynamic performance requirements but failed to satisfy structurally. Higher backward lean present in the blade was found to be contributing to severe bending stresses and deformation. Hence, three different impellers, with modified thickness, lean angle and wrap angle distributions, were designed. These designs were subjected to 3D CFD and FEM analysis. Structural analysis was carried out to study stresses and deformations for all configurations, followed by pre-stressed modal analysis to predict their natural frequencies and corresponding mode shapes. The design with modified wrap angle distribution not only met the aerodynamic requirements but also satisfied structural requirements. This paper elaborates the design evolution of the centrifugal impeller from the baseline design to a more structurally stable one