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crossed and your i s dotted. I say this because it can be extremely hard to get mistakes corrected after the closing has taken place, especially when the sellers have picked up stakes and left town without leaving a forwarding address. And when this happens, you are what is known in Marine Corps parlance as SOL! And while you are doing your pre-closing checks, be sure to take the time to sit down and double-check all loan, title transfer, and closing documents for: 1. Mistakes made in computing prorations. 2. Mistakes made in transposing numbers and letters. 3. Mistakes made in spelling and typing.

Researchers Steve Whittaker, David Frohlich, and Owen Daly-Jones found that informal communication in a physical workplace includes brief, unplanned, and frequent interactions without openings and closings. Conversations are left open and ongoing between face-to-face interactions.* Virtual replacements need to provide ways of reproducing this interaction when you re not geographically collocated with your teammates. Your communications processes and tools also need to take into account the potential disruptiveness of interruptions compared to their value. Using multi-channel, multi-platform, presence-aware communications can help ensure that you interrupt people at relatively more convenient times and that you are interrupted when it suits you rather than when you are pressing to get solo work done on a deadline.

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Attitudes are a learned orientation or predisposition to a given situation, person, object or idea resulting in a tendency to respond favourably or unfavourably. There are three main components to an attitude: the cognitive, affective and conative. The cognitive dimension refers to knowledge or information possessed about the fashion product, service, image, store or prices; the knowledge possessed by the consumer may not be accurate or complete, but it is what is believed to be the truth by the consumer. The affective dimension is concerned with consumer feelings about fashion marketing offerings and is measured in terms such as like and dislike or good and bad. The conative aspect provides the behavioural aspect of attitudes and is usually expressed in terms of an intention, or not, to buy within a speci ed time. Thus a consumer may know of a new range from Missonia and of the colours, prices and sizes available; the consumer may like the new range and moreover intends to purchase a new sweater within the next seven days. Fashion marketers are interested in consumer attitudes as they are seen to be closely linked to behaviour. A simple model of the link between attitudes and buying behaviour is shown in Figure 3.6. The model below oversimpli es matters somewhat as it is argued that sometimes attitudes emerge or become manifest after purchase. Other writers contend that liking may precede knowledge in certain

three values: 1. No congestion. 2. Delay build-up: meaning the delay of packets in the transport network is increasing. 3. Lost packets: meaning that a certain number of packets in the transport network are lost. Upon reception of a congestion indicator for a certain UE, the Node B can lower the bit rate of at least this particular user, such that the congestion situation is solved.

Motivated by technological factors, some authors have recently started to investigate the computational power of even less restrictive streaming models. Today s computing platforms are equipped with large and inexpensive disks highly optimized for sequential read/write access to data, and among the primitives that can ef ciently access data in a nonlocal fashion, sorting is perhaps the most optimized and well understood. These considerations have led to introduce the stream-sort model [3,61]. This model extends classical streaming in two ways: the ability to write intermediate temporary streams and the ability to reorder them at each pass for free. A stream-sort algorithm alternates streaming and sorting passes: a streaming pass, while reading data from the input stream and processing them in the working memory, produces items that are sequentially appended to an output stream; a sorting pass consists of reordering the input stream according to some (global) partial order and producing the sorted stream as output. Streams are pipelined in such a way that the output stream produced during pass i is used as input stream at pass i + 1. We will see in Section 8.3.4 that the combined use of intermediate temporary streams and of a sorting primitive yields enough power to solve ef ciently (within polylogarithmic passes and memory) a variety of graph problems that cannot be solved in classical streaming. Even without sorting, the model is powerful enough for achieving space passes trade-offs [25] for graph problems for which no sublinear memory algorithm is known in classical streaming.

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