Efficacy, Safety and Steroid-sparing Effect of Topical Cyclosporine A 0.05% for Vernal Keratoconjunctivitis in Indian Children

Purpose: To evaluate the efficacy, safety, and steroid-sparing effect of topical cyclosporine A (Cs A) 0.05% in patients with moderate to severe steroid dependent vernal keratoconjunctivitis (VKC). Methods: A prospective, comparative, placebo controlled study was carried out on 68 VKC patients, with 34 patients treated with topical Cs A 0.05% and the remaining 34 with topical carboxymethyl cellulose 0.5% (placebo). Both groups also received topical loteprednol etabonate 0.5%. Symptom (itching, photophobia, tearing, and discharge) score, sign (tarsal and limbal papillae, corneal involvement, and conjunctival hyperemia) score, and drug score (steroid drop usage/day/eye) were recorded at baseline and each followup visit. The intraocular pressure (IOP) measurement and evaluation of any ocular side effects were carried out. Results: Significant reduction in symptom score and sign score was seen in both groups. Cs A group significantly showed more reduction in symptom (P < 0.0001 in all follow-up visits) and sign (P < 0.0001 in all follow-up visits) scores compared to the placebo group. At day 7, mean steroid usage reduced from 4 to 3.44 ± 0.5 and 3.79 ± 0.4 in Cs A and placebo groups, respectively (P < 0.0001). Steroid drops completely stopped in 21 patients at day 60 in the Cs A group compared to none in the placebo group. No significant rise in IOP or any side effects were noted in either group. Conclusion: Topical Cs A 0.05% is effective and safe in patients with moderate to severe VKC with good steroid-sparing effect

A Study on Formation of Hammer Transfer Stains in a Crime Scene

It is difficult to interpret hammer transfer strain in a crime scene. This paper lies in the argument that proper analysis of hammer transfer stains in crime scene may indicate the possibilities of proper incidence

The Intricacies Involved in the Analysis and Interpretation of Hammer Transfer Stain/s in a Crime Scene

Bloodstain Pattern analysis particularly deals with the reconstruction of dynamic bloodletting events from static bloodstain patterns. Bloodstain patterns often help to sequence events that might have occurred at a crime scene. It can also be used to draw inference about the position of the victim/s, perpetrator/s and bystander/s (if any) at the crime scene. This paper is aimed at intricate analysis/interpretation of transfer stains produced by blunt ended objects at a crime scene. By way of experiments performed within a laboratory setting this paper attempts at establishing that hammer transfer stain or possible weapon transfer stain at a crime scene does not indicate that that particular instrument has been used to murder the victim/s. Also when blood drips over hammer and when a hammer falls under gravity onto a blood pool, the stain patterns formed are particularly different. This particular information under certain circumstances could particularly contribute to sequencing of events at a crime scene. Again, different blunt ended objects were found to produce similar transfer stain patterns. Hence transfer stain patterns should be interpreted in coherence with other relevant circumstantial evidence at the crime scene

Artificial Intelligence Based Study on Analyzing of Habits and with History of Diseases of Patients for Prediction of Recurrence of Disease Due to COVID-19

A patient will visit physicians when he/she feels ill. This illness is not for COVID-19 but it is a general tendency of human being to visit doctor probably it cannot be controlled by general drug. When a patient comes to a doctor, the doctor examines him/her after knowing his/her problem. The physician always asks him/her about some questions related to him/her daily life. For example, if a young male patient comes to a doctor with a symptom of fever and cough, the first question doctor asked him that he has a habit of smoking. Then doctor asks him whether this type of symptom appeared often to him previously or not. If the answers of both questions are yes, then the first one is habit and the second one is that he may suffering from some serious disease or a disease due to the weather. The aim of this paper is to consider habit of the patient as well as he/she has been affected by a critical disease. This information is used to build a model that will predict whether there is any possibility of his/her being affected by COVID-19. This research work contributes to tackle the pandemic situation occurred due to Corona Virus Infectious Disease, 2019 (Covid-19). Outbreak of this disease happens based on numerous factors such as past health records and habits of patients. Health records include diabetes tendency, cardiovascular disease existence, pregnancy, asthma, hypertension, pneumonia; chronic renal disease may contribute to this disease occurrence. Past lifestyles such as tobacco, alcohol consumption may be analyzed. A deep learning based framework is investigated to verify the relationship between past health records, habits of patients and covid-19 occurrence. A stacked Gated Recurrent Unit (GRU) based model is proposed in this paper that identifies whether a patient can be infected by this disease or not. The proposed predictive system is compared against existing benchmark Machine Learning classifiers such as Support Vector Machine (SVM) and Decision Tree (DT)

Human Face Detection: Manual vs. Kohonen Self Organizing Map

In today's world it is very much important to maintain the security of information and its risks. The biometric-based techniques are very much useful in these problems. Among the several kinds of biometric-based technique, face detection is much complex and much more important. Due to the age and several other problems, a human face structure changes over time, again a human has lots of expressions. Sometimes due to the lighting condition or the variation of the angle of an input device, the pattern of a human face structure also changed. As a result, the face cannot be detected properly. In this paper, a method is proposed that can detect the human faces both automatically and manually very efficiently. In manual mode, a user can select the input faces referred by the system according to their choice. In automated mode, the system detected all possible face areas using the Kohonen Self-Organizing Feature Map technique. This method reduced the complex color image into a vector quantized image with desired colors. Then a color segmentation technique is used to detect the possible face skin areas from the vector quantized image. Then the Histogram Oriented Gradient technique used to detect the feature from the faces and K-Nearest Neighbor Classifier is used to compare both face images detected by the two modes. The automated method prosed better accuracy than the manual method

A Hypothesis is Placed to Justify the Extendibility of Recommender System/ Recommendation System into Social Life

Researchers still believe that the information filtering system/ collaborating system is a recommender system or a recommendation system. It is used to predict the "rating" or "preference" of a user to an item.  In other words, both predict rating or preference for an item or product on a specific platform. The aim of the paper is to extend the areas of the recommender system/recommendation systems. The basic task of the recommender system mainly is to predict or analyze items/product. If it is possible to include more products in the system, then obviously the system may be extended for other areas also. For example, Medicine is a product and doctors filter the particular medicine for the particular disease. In the medical diagnosis doctors prescribed a medicine and it a product. It depends on the disease of the user/patient so here doctor predicts a medicine or product just like an item is recommended in a recommender system. The main objective of the paper is to extend the Recommender System/Recommendation system in other fields so that the research works can be extended Social Science, Bio-medical Science and many other areas

Analysis of Stress, Anxiety and Depression of Children during COVID-19

Coronavirus is believed to have originated from a wet market in Wuhan, China, and has spread all over the world, resulting in a large number of hospitalizations and deaths. Social scientists are just beginning to understand its consequences on human behavior. One policy that public health officials put in place to help stop the spread of the virus were stay-at-home/shelter-in-place lockdown-style orders.Schools, Colleges and Universities across the country have now been shut down till now due to Covid-19. Some Governments in India impose lockdown to reduce the crises created by this unknown virus. It is now difficult to make final assessments by school, school leaving examinations and entrance tests for undergraduate and post-graduate courses. This disruption implies for students across the socio-economic spectrum, both in terms of learning outcomes, food and economic security. Here the aim is to discuss the implications of lockdown-induced in schools in both urban and rural areas in India. The whole world implemented a nationwide lockdown to curb the transmission of the virus.  A survey was over Five hundred families to complete a questionnaire with questions around symptoms of depression, anxiety, stress, and family affluence. The humans who do not have enough supplies to sustain the lockdown were most affected Families with affluence were found to be negatively correlated with stress, anxiety, and depression. Stress, anxiety, and depression more than others are seen in students and healthcare professionals. The main aim of the paper is to find out how symptoms of depression, anxiety and stress on parents due to COVID-19