Search

The Indian banking sector has arisen together as the strongest drivers of India’s economic growth. The Indian banking system has made outstanding advancement in the foregoing couple of periods, even during the days when the rest of the world was floundering with financial meltdown. Moment, all the banks face the matter of non-performing assets whether it's public sector bank or private sector bank. Unfortunately, the Covid-19 has stopped economic activity across multifold sectors and hypercritically affected the banking sector. This paper is aimed towards the review of on non-performing assets in Indian banking sector. According to RBI (Reserve Bank of India), for any asset on which the interest remains un-payable for a period of 90days,the asset becomes non-performing. Fast forward to 2021 digital lending has become a reality and preferred route for the vast majority of Indian for its speed and convenience, many player are available for providing MSME financing such as Lending kart, Aye Finance, Kreditbee

In the USA, the third leading cause of a large bowel obstruction in adults is volvulus with torsion occurring commonly in the sigmoid and the cecum. Transverse colonic volvulus is exceedingly rare and specific involvement of the splenic flexure is even more uncommon. In the present report, we discuss a Veteran octogenarian who presented with a long-standing history of constipation, but then developed an acute abdomen from a large bowel obstruction. At laparotomy, he had a double closed loop obstruction with volvulus of the splenic flexure. The colon at the splenic flexure was ischemic with patchy areas of necrosis, but no perforation. He underwent a subtotal colectomy with an ileostomy. This case illustrates the need for prompt intervention of this unusual entity. Current trends in the incidence, management, morbidity and mortality are discussed.

Background: Sexual dysfunctions (SDs) are common and lead to psychological distress and impair quality of life (QOL). However, little attention has been paid to explore SD in severe mental illnesses (SMIs). Hence, this study aimed to evaluate the occurrence of SD and its impact on the QOL in persons suffering from schizophrenia, bipolar disorder, and depression and compare it with healthy controls. Materials and Methods: In this cross-sectional study, 79 clinically stable patients and 50 healthy controls underwent evaluation for SD on the Arizona Sexual Experience Scale, and their QOL was measured using the WHO QOL-BREF scale. Chi-square test was used for the categorical variables, whereas comparison of continuous variables was done by t-test with post hoc corrections. Results: Compared to healthy controls, patients with depression had significantly higher rates of SD in the domain of obtaining penile erection (P = 0.019), ability to reach orgasm (P = 0.03), and satisfaction from orgasm (P = 0.01). Patients with schizophrenia had higher rates of problems in achieving arousal (P < 0.01), penile erection (P = 0.03), and satisfaction from orgasm (P = 0.03), whereas those with bipolar disorder only differed significantly on the domain of ability to reach orgasm (P = 0.03). However, patients fared better than the controls on various domains of QOL (except social domain). Conclusion: A significant number of patients with SMI suffer from SD. Hence, it should be made a routine practice to evaluate and address the problem of SDs in patients with SMI.

This chapter starts with why to choose ML. It covers various types of supervised and unsupervised machine learning algorithms with python code. Various performance measures are also to measure the performance of various algorithms are explained, and popular ML platforms are covered in the chapter.

This chapter examines the evolution of cloud computing and how the history of computing has swung between remote and local computers. It uses NIST definition to examine five essential features of any cloud computing service. Then the three service models of Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) are examined. Furthermore, we look into the deployment models of private, community, public, and hybrid clouds. Next, we will study the value-added chain of various cloud stakeholders, including their pain points. Lastly, a case will be made for conducting AI and ML in cloud. It will include a workflow for creating an ML model, with some real-life examples. We wrap up this chapter by looking at the future trends that include targeted hardware.

In this chapter, we will start by examining traditional information security and aspects of confidentiality, integrity, and access control. We will look at ways to protect data at rest, during transit, and in use. Then the security concerns arising out of cloud operating models will be examined. We will present seven recommended security practices to protect data in the cloud. Lastly, role of ML for cybersecurity will be investigated.

In this chapter, we focus on the practical aspects in machine learning. Framework for data preparation techniques is looked into. Various practical aspects for implementation of machine learning are discussed, like preprocessing, dimension reduction techniques, feature engineering, and methods for feature selection. We wrap up the chapter by looking into the techniques for dealing with imbalanced data.

Machine learning is a latest buzzword floating around everywhere. It is one of the most interesting sub-fields of computer science. In this chapter, we will introduce the basic concept of machine learning. We will cover various paradigms of learning and applications of machine learning. Next, we will cover the justification of using machine learning and various tasks where machine learning is used. In the end, we discuss about various tools used.

We start this chapter by revisiting the history of AI and its current limitations. In response, emergence of AI hardware accelerators will be studied, starting with GPUs. Next, we will study the use of FPGAs, ASICs, TPUs, VPUs, and a massive wafer scale AI engine. Several examples and products will be presented wrapping up with an ecosystem example.

This is chapter to examine the practical aspects of running data analytics in a Public Cloud with several real-life examples. We will discuss three major public Cloud Service Providers (CSPs), namely Amazon’s AWS, Google’s GCP, and MS Azure with their key ML-related offerings. A popular framework of MapReduce with an introduction of Hadoop will be examined. Lastly, practical examples of cloud-based AI and ML services will be presented. We will wrap up the chapter with future possibilities of using reinforced learning.

In this chapter, we introduce the concept of deep learning, and various deep learning architectures are covered. Difference between machine learning and deep learning is discussed. Justification for using DL is covered. Popular software and platform for deep learning are explored.

BackgroundIn the United States, the third leading cause of a large bowel obstruction (LBO) is colonic volvulus with torsion occurring most commonly in the sigmoid and the cecum. Transverse colonic volvulus (TCV) is exceedingly rare and specific involvement of the splenic flexure (SFV) is even less common. The present analysis was undertaken to interrogate current trends in presentation, management, and outcomes of TCV.MethodsIn the present report, the world literature was reviewed for the past 90 years (1932 to 2021). We conducted a systematic review to identify all cases of TCV following the PRISMA guidelines.ResultsWe identified 317 cases of TCV. This included SFV (n = 75), TCV in pediatric patients (n = 63), TCV in pregnant patients (n = 8), and TCV associated with other pathology such as Chilaiditi’s syndrome (n = 11). Compared to sigmoid and cecal volvulus, TCV was rare (.94%). It affected slightly more women (54%) than men, commonly in their third decade of life (37.7 ± 23.8). The clinical presentation and diagnostic imaging were consistent with LBO. Compared to sigmoid volvulus, there was a limited role for conservative management and colonoscopic decompression was less effective. The most common operation was segmental resection (25%). Mortality was (20%) commonly because of cardiopulmonary complications and affected more women (63%). The average age of this cohort was 55.7±24.6 years old.DiscussionOur review showed that TCV is an uncommon surgical entity. The diagnosis is likely to be made at laparotomy. Prompt recognition is paramount in preventing ischemia necrosis and perforation. Compared to sigmoid and cecal volvulus, the mortality for TCV remains high.

Population Based Training (PBT) is a recent approach that jointly optimizes neural network weights and hyperparameters which periodically copies weights of the best performers and mutates hyperparameters during training. Previous PBT implementations have been synchronized glass-box systems. We propose a general, black-box PBT framework that distributes many asynchronous "trials" (a small number of training steps with warm-starting) across a cluster, coordinated by the PBT controller. The black-box design does not make assumptions on model architectures, loss functions or training procedures. Our system supports dynamic hyperparameter schedules to optimize both differentiable and non-differentiable metrics. We apply our system to train a state-of-the-art WaveNet generative model for human voice synthesis. We show that our PBT system achieves better accuracy, less sensitivity and faster convergence compared to existing methods, given the same computational resource., 9 pages

We describe a software package called VPLanet that simulates fundamental aspects of planetary system evolution over Gyr timescales, with a focus on investigating habitable worlds. In this initial release, eleven physics modules are included that model internal, atmospheric, rotational, orbital, stellar, and galactic processes. Many of these modules can be coupled simultaneously to simulate the evolution of terrestrial planets, gaseous planets, and stars. The code is validated by reproducing a selection of observations and past results. VPLanet is written in C and designed so that the user can choose the physics modules to apply to an individual object at runtime without recompiling, i.e., a single executable can simulate the diverse phenomena that are relevant to a wide range of planetary and stellar systems. This feature is enabled by matrices and vectors of function pointers that are dynamically allocated and populated based on user input. The speed and modularity of VPLanet enables large parameter sweeps and the versatility to add/remove physical phenomena to assess their importance. VPLanet is publicly available from a repository that contains extensive documentation, numerous examples, Python scripts for plotting and data management, and infrastructure for community input and future development., Comment: 75 pages, 34 figures, 10 tables, accepted to the Proceedings of the Astronomical Society of the Pacific. Source code, documentation, and examples available at https://github.com/VirtualPlanetaryLaboratory/vplanet

Background: Suicide being a global health issue, the attitudes and beliefs of the healthcare professionals towards these attempters have significant effect on the outcome of the treatment. Objectives: Aim of the study was to assess the attitude of nursing students towards patients with suicide attempt. Materials and Methods: The study had a cross sectional design of 284 nursing students who were randomly recruited from the two institutions. Suicide opinion Questionnaire was administered. Results: Most were young single females, from rural locality, who were pursuing either BSc Nursing or GNM courses. Very few had previous exposure to suicide prevention training programmes. More than half of the students showed favourable attitude towards patients with suicidal attempt. Majority of students showed favourable attitudes for more than half of the attitudinal statements giving importance to the mental illness, disturbed family life, and depression and risk factors for suicide attempt. Unfavourable and uncertain attitude was noticed for a few of the statements. Conclusions: The nursing students showed favourable attitude towards patients with suicide attempts. More educational and training programs are therefore needed in these students for improving the uncertain and unfavourable responses to a few of these attitudes for better management of these patients.

Background: Managing patients with suicide attempts effectively requires overcoming barriers to their care. The attitudes and beliefs of the healthcare professionals have significant effect on the outcome of the treatment and implementation of the preventive strategies. Objectives: Aim of the study was to assess the attitude of nursing students toward suicide prevention. Materials and Methods: The study had a cross sectional design of 284 nursing students who were randomly recruited from the two institutions. Attitude toward suicide prevention scale was administered. Results: Most were young single females, from rural locality, who were pursuing either BSc Nursing or GNM courses. Very few had previous exposure to suicide prevention training programmes. Nearly half of the students showed favourable attitude towards patients with suicidal attempt, considering it as their responsibility and their efforts as rewarding. Nearly half students also showed empathy towards these patients not considering the attempts as just attention seeking ones. Nearly one third were uncertain whether the patients reveal their plans of attempt and whether the suicide prevention measures were draining of the resources. Half of the subjects showed pessimism towards modifying the risk factors of unemployment and poverty. Conclusions: Only half of the nursing students showed favourable attitude working with patients with suicide attempts. More educational and training programs on suicide prevention are therefore needed in these students for better prevention and management of these patients.