machinery, mechanical appliances and electrical/electronic products (e.g. computers, cameras, lamps, refrigerators, washing machines) and Admirably clear, concise, down-to-earth, and powerful-unfortunately, these adjectives rarely describe legal writing, whether in the form of briefs, opinions, contracts, or statutes. In Legal Writing in Plain English, Bryan A. Garner provides lawyers, judges, paralegals, law students, and legal scholars sound advice and practical tools for improving their written work. The book encourages legal writers to challenge conventions and offers valuable insights into the writing process: how to organize ideas, create and refine prose, and improve editing skills. In essence, it teaches straight thinking--a skill inseparable from good writing. The examples provided are generic examples and may not apply to the specific substance you are viewing. A substance may have its use restricted to certain articles or products and therefore not all the examples may apply to the specific substance. Furthermore, some substances can be found in an article, but with unlikely exposure (e.g. inside a watch) or with very low concentrations considered not to pose risks to human health or the environment.

At least one company has indicated that the substance classification is affected by impurities or additives.Our impellers are manufactured to strict tolerances for optimal functionality unique MC97 rubber compound in many of our impellers

Minority position" - comes from data submitted by industry to ECHA, and indicates that the data submitted is not aligned. > 5% and < 50% of the data submitters have provided the concerns indicated at this "level". Minority position concerns are illustrated with a greyed out circle icon. The molecular structure is based on structures generated from information available in ECHA’s databases. If generated, an InChI string will also be generated and made available for searching. This information is only displayed if the substance is well-defined, its identity is not claimed confidential and there is sufficient information available in ECHA’s databases for ECHA’s algorithms to generate a molecular structure. Optimized to provide maximum life, especially for applications where the end user doesn’t run the engine on a regular basis: Toxic to Reproduction (R) – Recognised as toxic to reproduction: comes from a harmonised C&L classifying the substance as Carc. 1A or 1B and/or an entry in the Candidate list. Potentially toxic to reproduction: comes from a harmonised C&L classifying the substance as suspected toxic to reproduction Repr. 2. Broad agreement: comes from industry data where a majority of data submitters agree the substance is toxic to reproduction. Minority position: comes from industry data where a minority of data submitters indicate the substance is toxic to reproduction. More information about reproductive toxicity here.The ‘Substance identity’ section is calculated from substance identification information from all ECHA databases. The substance identifiers displayed in the InfoCard are the best available substance name, EC number, CAS number and/or the molecular and structural formulas. Random forest is an ensemble classifier based on the decision tree algorithm proposed by Breiman in 2001 ( Breiman, 2001). To solve regression or classification tasks, random forests construct many decision trees by extracting subsets from all the samples through the bootstrap technique and obtain the prediction result by voting on these decision trees. Random forests are widely used in bioinformatics because of their low computational overhead and ability of handling unbalanced data. indoor use in long-life materials with low release rate (e.g. flooring, furniture, toys, construction materials, curtains, foot-wear, leather products, paper and cardboard products, electronic equipment).