Protein topology of presenilin 1

Mutations in a gene encoding a multitransmembrane protein, termed presenilin 1 (PS1), are causative in the majority of early-onset cases of AD. To determine the topology of PS1, we utilized two strategies: first, we tested whether putative transmembranes are sufficient to export a protease-sensitive substrate across a lipid bilayer; and second, we examined the binding of antibodies to specific PS1 epitopes in cultured cells selectively permeabilized with the pore-forming toxin, streptolysin-O. We document that the "loop," N-terminal, and C-terminal domains of PS1 are oriented toward the cytoplasm.     

SVM for English semantic classification in parallel environment

Semantic analysis is very important and very helpful for many researches and many applications for a long time. SVM is a famous algorithm which is used in the researches and applications in many different fields. In this study, we propose a new model using a SVM algorithm with Hadoop Map (M)/Reduce (R) for English document-level emotional classification in the Cloudera parallel network environment. Cloudera is also a distributed system. Our English testing data set has 25,000 English documents, including 12,500 English positive reviews and 12,500 English negative reviews. Our English training data set has 90,000 English sentences, including 45,000 English positive sentences and 45,000 English negative sentences. Our new model is tested on the English testing data set and we achieve 63.7% accuracy of sentiment classification on this English testing data set.     

A decision tree using ID3 algorithm for English semantic analysis

Natural language processing has been studied for many years, and it has been applied to many researches and commercial applications. A new model is proposed in this paper, and is used in the English document-level emotional classification. In this survey, we proposed a new model by using an ID3 algorithm of a decision tree to classify semantics (positive, negative, and neutral) for the English documents. The semantic classification of our model is based on many rules which are generated by applying the ID3 algorithm to 115,000 English sentences of our English training data set. We test our new model on the English testing data set including 25,000 English documents, and achieve 63.6% accuracy of sentiment classification results.     

Comparison of methods for selecting personal protective equipment for arc flash hazards

In 1960, a large global chemical company began documenting and implementing requirements for preventing injuries from electric arc flash hazards, including appropriate personal protective equipment (PPE). Methods evolved from requiring a 100% natural fiber long-sleeve shirt for a specific task to a detailed analysis with multiple flame-resistant clothing options. This paper compares the PPE required by these methods, based on hazards analysis in more than 65 manufacturing and laboratory facilities. The total costs for the example company are estimated for each method.     

An overview of recommender systems in the healthy food domain

Recently, food recommender systems have received increasing attention due to their relevance for healthy living. Most existing studies on the food domain focus on recommendations that suggest proper food items for individual users on the basis of considering their preferences or health problems. These systems also provide functionalities to keep track of nutritional consumption as well as to persuade users to change their eating behavior in positive ways. Also, group recommendation functionalities are very useful in the food domain, especially when a group of users wants to have a dinner together at home or have a birthday party in a restaurant. Such scenarios create many challenges for food recommender systems since the preferences of all group members have to be taken into account in an adequate fashion. In this paper, we present an overview of recommendation techniques for individuals and groups in the healthy food domain. In addition, we analyze the existing state-of-the-art in food recommender systems and discuss research challenges related to the development of future food recommendation technologies.     

Benign and efficient preparation of thioethers by solvent-free S-alkylation of thiols with alkyl halides catalyzed by potassium fluoride on alumina

The preparation of thioethers by S-alkylation of various thiols with alkyl halides under solvent-free reaction conditions using potassium fluoride on alumina (KF/Al₂O₃) as a solid catalyst has been investigated in detail with respect to three different modes of reaction activation (ultrasound irradiation, microwave irradiation, and conventional heating) for obtaining maximum yield of the thioether. The importance of KF/Al₂O₃ as a particularly efficient catalyst was corroborated for all three modes of reaction activation, although the reaction time was found to be strongly dependent on the mode of activation. The yield of the thioethers was also found to depend on the amount of the solid catalyst relative to the equimolar amounts of the two reactants.