Chemoselective Formation of Unsymmetrically Substituted Ethers from Catalytic Reductive Coupling of Aldehydes and Ketones with Alcohols in Aqueous Solution

A well-defined cationic Ru–H complex catalyzes reductive etherification of aldehydes and ketones with alcohols. The catalytic method employs environmentally benign water as the solvent and cheaply available molecular hydrogen as the reducing agent to afford unsymmetrical ethers in a highly chemoselective manner

Scope and Mechanistic Analysis for Chemoselective Hydrogenolysis of Carbonyl Compounds Catalyzed by a Cationic Ruthenium Hydride Complex with a Tunable Phenol Ligand

A cationic ruthenium hydride complex, [(C6H6)(PCy3)(CO)RuH]+BF4– (1), with a phenol ligand was found to exhibit high catalytic activity for the hydrogenolysis of carbonyl compounds to yield the corresponding aliphatic products. The catalytic method showed exceptionally high chemoselectivity toward the carbonyl reduction over alkene hydrogenation. Kinetic and spectroscopic studies revealed a strong electronic influence of the phenol ligand on the catalyst activity. The Hammett plot of the hydrogenolysis of 4-methoxyacetophenone displayed two opposite linear slopes for the catalytic system 1/p-X-C6H4OH (ρ = −3.3 for X = OMe, t-Bu, Et, and Me; ρ = +1.5 for X = F, Cl, and CF3). A normal deuterium isotope effect was observed for the hydrogenolysis reaction catalyzed by 1/p-X-C6H4OH with an electron-releasing group (kH/kD = 1.7–2.5; X = OMe, Et), whereas an inverse isotope effect was measured for 1/p-X-C6H4OH with an electron-withdrawing group (kH/kD = 0.6–0.7; X = Cl, CF3). The empirical rate law was determined from the hydrogenolysis of 4-methoxyacetophenone: rate = kobsd[Ru][ketone][H2]−1 for the reaction catalyzed by 1/p-OMe-C6H4OH, and rate = kobsd[Ru][ketone][H2]0 for the reaction catalyzed by 1/p-CF3-C6H4OH. Catalytically relevant dinuclear ruthenium hydride and hydroxo complexes were synthesized, and their structures were established by X-ray crystallography. Two distinct mechanistic pathways are presented for the hydrogenolysis reaction on the basis of these kinetic and spectroscopic data

Knowledge Era: Knowledge Management in Multinational Company – Role of KM in Project Management Scenario

Human society passed various stages like hunting and gathering society, peasant society, Industrial society and post- industrial society. Post – industrial society is recognized as ‘Knowledge Society’. Knowledge is more valuable product than any other goods in knowledge society. Today information is in the finger tips with the advent of Information and Communication Technology (ICT). Information gathering, storage and dissemination are the basic features of knowledge society. Due to the crucial role of knowledge 21st century is recognized as ‘Knowledge Era’. Information gathering, storage and dissemination to the right people are the central poles of Knowledge Era. Knowledge management is widening its area and it is one of the key task in multinational companies. Project Management has been growing as a discipline for decades. From basic task of planning to modern complexity management, it has evolved with the society. Today, project management is integrated in many companies and governmental organisms with strategy, via the portfolio or program management, and with the other departments, like manufacturing, human resources, legal and financial. It is a question of managing multiple products, multiple projects with interrelated resources from one or many companies, under the multiple constraints of the customers, the legal environment and the financial and market objectives. This paper presents the results of study into Knowledge Management (KM) performed at one of the multinational company called Perot Systems Consulting and Application Solutions (CAS) India (Bangalore and Noida). Keywords: Knowledge Era, Knowledge Management, Project Management, Knowledge Creatio

P2DM-RGCD: PPDM Centric Classification Rule Generation Scheme

In present day applications the approach of data mining and associated privacy preservation plays a significant role for ensuring optimal mining function. The approach of privacy preserving data mining (PPDM) emphasizes on ensuring security of private information of the participants. On the contrary majority of present mining applications employ the vertically partitioned data for mining utilities. In such scenario when the overall rule is divided among participants, some of the parties remain with fewer rules sets and thus the classification accuracy achieved by them always remain questionable. On the other hand, the consideration of private information associated with any part will violate the approach of PPDM. Therefore, in order to eliminate such situations and to provide a facility of rule regeneration in this paper, a highly robust and efficient rule regeneration scheme has been proposed ensures optimal classification accuracy without using any critical user information for rule generation. The proposed system developed a rule generation function called cumulative dot product (P2DM-RGCD) rule regeneration scheme. The developed algorithm generates two possible optimal rule generation and update functions based on cumulative updates and dot product. The proposed system has exhibited optimal response in terms of higher classification accuracy, minimum information loss and optimal training efficiency

SWAT: Spatial Structure Within and Among Tokens

Modeling visual data as tokens (i.e., image patches) using attention mechanisms, feed-forward networks or convolutions has been highly effective in recent years. Such methods usually have a common pipeline: a tokenization method, followed by a set of layers/blocks for information mixing, both within and among tokens. When image patches are converted into tokens, they are often flattened, discarding the spatial structure within each patch. As a result, any processing that follows (eg: multi-head self-attention) may fail to recover and/or benefit from such information. In this paper, we argue that models can have significant gains when spatial structure is preserved during tokenization, and is explicitly used during the mixing stage. We propose two key contributions: (1) Structure-aware Tokenization and, (2) Structure-aware Mixing, both of which can be combined with existing models with minimal effort. We introduce a family of models (SWAT), showing improvements over the likes of DeiT, MLP-Mixer and Swin Transformer, across multiple benchmarks including ImageNet classification and ADE20K segmentation. Our code and models will be released online

PERCEPTION AND USAGE OF HEALTH INFORMATION SOURCES AND SERVICES AMONG THE URBAN COMMUNITY USERS OF PUBLIC LIBRARIES: A CASE STUDY OF BHADRAVATHI

The study examined the perception and usage of health information sources and services by the urban community users of public libraries. The study investigated 110 users from two public libraries in Bhadravathi. Findings revealed that majority of the users not enrolling library membership. 44.54% of users were visit library daily and large numbers of respondents were get health information through newspaper followed by television, advertisements and pamphlet/brochures. Education and sports were the most frequently preferred topics by the users. Arogya column published by Prajavani Kannada newspaper was most preferred newspaper column for getting health information by the users followed by VK Health column published by Vijaya Karnataka was stood in 2nd position to get health information by the users. Most of the users preferred Sudha, Gruhashobha and Taranga magazines to get health information. Stimulatingly, large number of the users frequently listen health related programs in Radio. The study also revealed that most of the users were aware about H1N1, DPT, Polio, BCG, TT, AIDS Control, 108 Arogya Kavacha, Malaria Cholera Dengue, Family Planning, Chicken Gunya district health programs of Karnataka state

Email Classification Using Adaptive Ontologies Learning

Email is a way of communication for the today’s internet world, private and government sector or public sector all are used email for communication with their clients. They can freely send number of mail to their client without disturbing them. Now a day email communication is also a way of advertising, some mail is also spam, lots of social mails are there. Categorization and handling lots of email is an important task for the researches, as they all are working in this field by using the Natural language processing and ontology extraction process. User get frustrated for handling lots of mails and reading those for finding there is any important mail, sometime user delete lots of mail without reading and in that case may be some important mail which contain the important information may be about meeting, seminar etc. is also deleted. For avoiding these scenarios here auto updation of schedule calendar procedure is proposed by the author. Concept extraction and clustering of concept is done based on fuzzy logic, similar mail pattern is grouped in a same cluster if similarity is less than threshold value a new cluster is defined for that. From the extracted concept author establish the relationship between them and generate the result. Computation overhead is also calculated for different set of mails and finds that it takes very less time in computing large email data set