Diabetes Prediction: A Study of Various Classification based Data Mining Techniques

Data Mining is an integral part of KDD (Knowledge Discovery in Databases) process. It deals with discovering unknown patterns and knowledge hidden in data. Classification is a pivotal data mining technique with a very wide range of applications. Now a day’s diabetic has become a major disease which has almost crippled people across the globe. It is a medical condition that causes the metabolism to become dysfunctional and increases the blood sugar level in the body and it becomes a major concern for medical practitioner and people at large. An early diagnosis is the starting point for living well with diabetes. Classification Analysis on diabetic dataset is a part of this diagnosis process which can help to detect a diabetic patient from non-diabetic. In this paper classification algorithms are applied on the Pima Indian Diabetic Database which is collected from UCI Machine Learning Laboratory. Various classification algorithms which are Naïve Bayes Classifier, Logistic Regression, Decision Tree Classifier, Random Forest Classifier, Support Vector Classifier and XGBoost Classifier are analyzed and compared based on the accuracy delivered by the models

SENTIGRADE: A SENTIMENT BASED USER PROFILING STRATEGY FOR PERSONALISATION

Nowadays, the availability of folksonomy data is increased to make importance for user profiling approaches to provide results of the retrieval data or personalized recommendation. The approach is used for detecting the preferences for users and can be able to understand the interest of the user in a better way. In this approach, the incorporation of information with numerous data which depends upon sentiment is implemented using a framework SentiGrade by User Profiles (UP) and Resource Profiles (RP) for user Personalized Search (PS). From the folksonomy data, the discovery of User Preference (UsP) is presented by a rigorous probabilistic framework and relevance method are proposed for obtaining Sentiment-Based Personalized (SBP) ranking. According to the evaluation of the approach, the proposed SBP search is compared with the existing method and uses the two datasets namely, Movielens and FMRS databases. The experimental outcome of the research proved the effectiveness of the framework and works well when compared to the existing method. Through user study, the evaluation of approaches and developed systems are made which shows that considering information such as relevance and probabilistic data in Web Personalization (WP) systems can able to offer better recommendations and provide much effective personalization services to users

Monothia [22]pentaphyrin(2.0.1.1.0): A core modified isomer of Sapphyrin

A novel 22π-aromatic sapphyrin isomer endowed with acene moiety is designed and realized for the first time as its core-modified mono-thia analogue. This macrocycle exhibits absorption and emission in the near infrared region. It was diprotonated under strong acidic condition, then it binds anion like sapphyrin. It shows unusual coordination chemistry by acting as a neutral ligand to undergo large out-of-plane deformation to bind Pd (II) ion

Effect of Long Term Manuring on Soil Carbon Stock and Some Biological Properties under Rice – Rice Cropping System in an Inceptisol of Bhubaneswar, Odisha, India

This research was carried out to determine the effect of different manurial treatments on the quantity of carbon added to soil through stubble in rice-rice cropping system, organic carbon stock and its relation to biological properties in an Inceptisol of Bhubaneswar, Odisha. This has been contemplated in existing Long Term Fertilizer Experiment which is in progress since 1994 located in Central Research Station, OUAT with Rice-Rice cropping sequence. The experiment dealt with six treatments during the eighth crop cycle viz, 100% NPK, 100% NPK + FYM, 100% N, 100% NP, 100% NPK +Lime, control (no manuring) with 4 replications in a randomized block design. Both in the kharif and the rabi seasons, rice stubble with undisturbed roots was meticulously collected, processed, and tested for total carbon after rice harvest. The usual approach was followed when collecting and analyzing soil samples. Between 1223.5 and 2571.5 kg/ha of carbon and 2998.9 to 6330.85 kg/ha of total stubble were absorbed into the soil. After kharif and rabi, the surface carbon stock of the soil ranged from 7.41 to 12.50 Mg/ha and 7.14 to 11.76 Mg/ha, respectively. After kharif, the SOC of surface soil ranged between 3.48 and 6.51 g/kg and 3.35 and 6.13 g/kg. In 100% NPK+ FYM, the highest amounts of stubble, stubble carbon, and MBC were found. No manuring enhanced the BD (1.42 Mg/m3) but the addition of FYM and stubble decreased the BD (1.28 Mg/m3). MBC varied from 45.89 to 132.41 g of carbon per g of soil. The importance of subble addition in enhancing SOC was demonstrated by the significantly positive association between SOC and quantity of stubble addition (r = 0.85), carbon addition by stubble (r = 0.94), and carbon stock (r =0.91**). Similar to this, the MBC-SOC connection (r = 0.83**), which supported the contribution of SOC to collective formation. The strong positive link between SOC and MBC suggests that adding carbon helps to improve soil health, and rice straw is an excellent source of carbon. It needs to be suppressed in the soil

Poly- and Perfluoroalkyl Substances (PFAS): Do They Matter to Aquatic Ecosystems?

Poly- and perfluoroalkyl substances (PFASs) are a group of anthropogenic chemicals with an aliphatic fluorinated carbon chain. Due to their durability, bioaccumulation potential, and negative impacts on living organisms, these compounds have drawn lots of attention across the world. The negative impacts of PFASs on aquatic ecosystems are becoming a major concern due to their widespread use in increasing concentrations and constant leakage into the aquatic environment. Furthermore, by acting as agonists or antagonists, PFASs may alter the bioaccumulation and toxicity of certain substances. In many species, particularly aquatic organisms, PFASs can stay in the body and induce a variety of negative consequences, such as reproductive toxicity, oxidative stress, metabolic disruption, immunological toxicity, developmental toxicity, cellular damage and necrosis. PFAS bioaccumulation plays a significant role and has an impact on the composition of the intestinal microbiota, which is influenced by the kind of diet and is directly related to the host’s well-being. PFASs also act as endocrine disruptor chemicals (EDCs) which can change the endocrine system and result in dysbiosis of gut microbes and other health repercussions. In silico investigation and analysis also shows that PFASs are incorporated into the maturing oocytes during vitellogenesis and are bound to vitellogenin and other yolk proteins. The present review reveals that aquatic species, especially fishes, are negatively affected by exposure to emerging PFASs. Additionally, the effects of PFAS pollution on aquatic ecosystems were investigated by evaluating a number of characteristics, including extracellular polymeric substances (EPSs) and chlorophyll content as well as the diversity of the microorganisms in the biofilms. Therefore, this review will provide crucial information on the possible adverse effects of PFASs on fish growth, reproduction, gut microbial dysbiosis, and its potential endocrine disruption. This information aims to help the researchers and academicians work and come up with possible remedial measures to protect aquatic ecosystems as future works need to be focus on techno-economic assessment, life cycle assessment, and multi criteria decision analysis systems that screen PFAS-containing samples. New innovative methods requires further development to reach detection at the permissible regulatory limits