Leveraging "The Wisdom of the Crowds" for Efficient Tagging and Retrieval of documents from the Historic Newspaper Archive

Computers may have defeated humans in chess and arithmetic, but there are many areas where the human mind still excels such as visual cognition and language processing (Comm. of ACM, Vol 52, No 3, March 2009). If one mind is good, it has been argued that several minds are likely to be superior in certain tasks than individuals and even experts. This project aims to leverage the wisdom of the crowds (von Ahn, 2008) to collaboratively tag historical newspaper articles in the holdings of the New York Public Library (NYPL). Patrons and scholars will be encouraged to generate custom tags for articles they read and use often; these will be integrated into a meta-data library and evaluated for their contribution to improving retrieval performance. The text in the newspaper articles along with user-generated tags will be subjected to statistical analysis and machine learning for automatic categorization

Chip Architecture for Data Sorting Using Recursive Algorithm

“This paper suggests a way to implement recursive algorithm on hardware with an example of sorting of numeric data. Every recursive call/return needs a mechanism to store/restore parameters, local variables and return addresses respectively. Also a control sequence is needed to control the flow of execution as in case of recursive call and recursive return. The number of states required for the execution of a recursion in hardware can be reduced compared with software. This paper describes all the details that are required to implement recursive algorithm in hardware. For implementation, all the entities are designed using VHDL and are synthesized, configured on Spartan-2 XC2S200-5PQ208.

Corporate Social Responsibility in the Global Apparel Industry: An Exploration of Indian Manufacturers’ Perceptions

In last few decades, corporate social responsibility (CSR) has marked its importance in scholarly research as evidenced by an increasing number of articles and journals dedicated to the topic (Dirnbach, 2008). This increase in popularity is in part the result of globalization and international trade (Jamali & Mirshak, 2006), as the era of globalization has meant that many apparel retailers do not own production factories, but have divested their manufacturing in favor of outsourced production. Availability of inexpensive labor and low production costs make developing countries attractive outsourcing locations. For this reason, India is emerging as one of the major players in the global apparel supply chain (Krishnamoorthy, 2006). The Indian textile and apparel manufacturing sector employs roughly 45 million people, making it the second largest provider of jobs in India after agriculture, and accounts for nearly 11% of the country’s total exports (Ministry of Textiles, 2012)

Surface To Surface Map Algorithm For Protein - Small Molecule Matching

Current methods for protein analysis are based on either sequence similarity or comparison of overall tertiary structure. These conserved primary sequences or 3-dimensional structures may imply similar functional characteristics. However, substrate or ligand binding sites usually reside on or near protein surface, so, similarly shaped surface regions could imply similar functions. Our current work includes development of an algorithm that would allow surface matching over specific regions on related proteins with an output equal to the match percentage between two proteins. Initial results indicate that we can successfully match a family of related active sites, and find their similarly shaped surface regions. This method of surface analysis could be extended to help us understand functional surface relationship between the proteins within which there is no relationship in sequence or overall structure

VAPC, an human endogenous inhibitor for hepatitis C virus (HCV) infection, is intrinsically unstructured but forms a "fuzzy complex" with HCV NS5B

10.1371/journal.pone.0040341PLoS ONE77

Placental biometry for prediction of small for gestational age fetuses in low resource setting

Background: Small for gestational age refers to foetuses with birth weight less than tenth centile for gestational age. Such foetuses are at increased risk of intrauterine fatal demise in comparison to others. Placenta plays a central role in supporting foetal growth. Researchers have emphasized on three dimensional sonographic placental volumetry as a predictor of SGA. This study focussed on role of two dimensional Ultrasonographic placental measurement in predicting SGA foetuses.Methods: Prospective study was conducted at Department of Obstetrics and Gynecology, Maulana Azad Medical College from November 2013 to February 2015. In singleton pregnancies at 18-22 weeks of gestation, placental biometry (in two dimensions) was performed. Maximal Placental Diameter (MaxPD) and Maximal Placental Thickness (MaxPT) in two orthogonal planes was recorded. Mean Placental Diameter (MPD) and Mean Placental Thickness (MPT) were calculated. At the time of delivery, as per the birth weight the neonate was classified into appropriate for gestational age (AGA)/ SGA/ large for gestational age (LGA). MPD and MPT were analyzed as predictors of SGA.Results: Both the MaxPDs and MPD were significantly smaller in SGA pregnancies (all with p ≤ 0.001). Similarly, both the MaxPTs (p = 0.006 and p = 0.001) and MPT (p = 0.000) were significantly smaller in SGA pregnancies. The ROC curve for combined placental biometry had the maximum area under the curve (0.805).Conclusions: Placental measurements taken in mid-gestation are a valuable predictor of SGA. Measurement of placental diameter and thickness is quick and simple. This approach should be explored in future to develop a predictive model for growth restricted foetuses