Unsupervised record matching with noisy and incomplete data

We consider the problem of duplicate detection in noisy and incomplete data: given a large data set in which each record has multiple entries (attributes), detect which distinct records refer to the same real world entity. This task is complicated by noise (such as misspellings) and missing data, which can lead to records being different, despite referring to the same entity. Our method consists of three main steps: creating a similarity score between records, grouping records together into "unique entities", and refining the groups. We compare various methods for creating similarity scores between noisy records, considering different combinations of string matching, term frequency-inverse document frequency methods, and n-gram techniques. In particular, we introduce a vectorized soft term frequency-inverse document frequency method, with an optional refinement step. We also discuss two methods to deal with missing data in computing similarity scores. We test our method on the Los Angeles Police Department Field Interview Card data set, the Cora Citation Matching data set, and two sets of restaurant review data. The results show that the methods that use words as the basic units are preferable to those that use 3-grams. Moreover, in some (but certainly not all) parameter ranges soft term frequency-inverse document frequency methods can outperform the standard term frequency-inverse document frequency method. The results also confirm that our method for automatically determining the number of groups typically works well in many cases and allows for accurate results in the absence of a priori knowledge of the number of unique entities in the data set

Biotransformation of Heavy Metals by Plant Growth Promoting Endophytic Bacteria: An Assessment

As a consequence of urbanization and industrialization, the environment is progressively polluted with heavy metals which is a problem of great concern. In plants it can create oxidative stress, ethylene production, chlorosis, Necrosis, stunted growth, inhibits various physiological processes, and decrease biomass. Due to their persistent and non-degradable nature, they enter the food chain leading to biomagnification and causing carcinogenic, mutagenic, and lethal effects on humans and animals. Bioremediation, phytoremediation, biotransformation, non-host inoculation, and other methods are used to treat heavy metals in the environment. Endophytic bacteria have gained attention for their potency to remove or immobilize heavy metals. Bacterial bioremediation is an effective and reliable technique to degrade, detoxify, mineralize, transform, or reduce the concentration of pollutants. This review helps in understanding the endophytic bacterial activity on bioremediation along with its plant growth-promoting properties

Climate-Resilient Crops for a Sustainable Future: The Promising Case of Minor Millets in Tamil Nadu Irrigated Modernization Project (TNIAMP)

This study integrated continuous data on the impact of the area and yield of minor millets in the sub-basins of Tamil Nadu and correlated it with the area and yield of minor millets in the sub-basins cultivated under the TNIAMProject. In this study, minor millet crops such as foxtail millet, ragi, finger millet, and varagu were introduced in fourteen sub-basins and their yield was carefully collected. This included all parts of Tamil Nadu. This study investigated the suitability of different sub-basins for crop diversification by exploring matching management practices with respective yield potentials. In this study, it was recorded that the yield was more than 3000 kg per acre in the sub-basins of Nagarai River, Lower Vellaru, Pambar River, Krishnagiri, Lower Bhavani, Varaha River, Cauvery River, and Lower Tamirabarani. This has also increased the area under cultivation in these sub-basins. The study found that the area and yield of minor millets in the sub-basins of Tamil Nadu have increased significantly under the TNIAMProject. This is attributed to the input subsidy and technological interventions provided under the project. The study recommends that the excess yield of minor millets caused by the TNIAMProject should be converted into value-added products and documented for sale in the respective areas. This will help to increase the income of farmers and promote the cultivation of minor millets

Assessment of CpTi surface properties after nitrogen ion implantation with various dose and energy

Nitrogen ion implantation is one of the surface modification techniques used for increasing corrosion resistance of commercially pure titanium (CpTi). The nitrogen ion implanted CpTi in various doses markedly changes the corrosion resistance. Still the effect of nitrogen ion implantation on the CpTi at different energies needs to be verified. This study uses different methods to assess the CpTi surface properties after nitrogen ion implantation in various doses and energy. Surface hardness of the CpTi increases with an increase of the dose and decreases with an increase of the energy. The precipitation of the TiN increases with an increase of the nitrogen dose, and no formation of the Ti2N phase clearly appears. Corrosion resistance of the CpTi specimens can be upgraded to some extent after their surfaces are modified, implanting nitrogen ions at 100 keV by increasing dose. The optimum surface properties of the implanted CpTi are analyzed to contribute to materials science technology