If you are thinking of breaking into the petite modeling industry and wondering if you should hundreds of doll ars on modeling school or classes you need to read this article. Here are few facts about modeling schools.

==>Modeling schools will not get you jobs. Clients who are hiring petite models do not care if you have been to modeling school or not. It does not quialify your for the job.

==>Modeling schools and classes teach mostly runway modeling techniques. This type of modeling is for the fashion industry, and if you are under 5 feet 9 inches there is a next to nothing chance that you will get work as a runway model.

==>Some modeling agencies or managers offer classes to boost their earnings. This is especially common in less populated areas where models are scarce and the agency does not earn much money. Be ware of agencies that offer these classes, they are doing so for their own financial gain. A reputable agency would never ask you to pay for classes.

==>You do not have to have a modeling to model for clients. You can get all the modeling practice you need by practicing poses in front of your mirror. A client is more interested in your looks and vibrant personality than they are in whether you've had modeling lessons or not.

Many times highschool and college students are approached by a "modleing scout" who offers them the opportunity to start their career as a model. Be ware of these people, jsut because they have a business card does not make them an agency who

can get you modeling jobs. These scouts are usually paid by modeling schools on a per student basis. For each student they convince to sign up for the modeling class they are paid a commission.

To get work from a reputable agent or modeling manager you need to find someone with a business license and who has connections with real life clients that are ready to pay models for work.

Many models in this industry end up doing tv or video modeling and you are considering this part of the industry you may need to look into acting classes.

Although modeling classes are not necissary for model work, if you plan to get speaking parts in the tv/video industry you may want to consider taking acting classes.

Acting classes are considered by many directors to be valid experience and they can make a difference in your modeling portfolio. Most of us are not born actors, so acting classes may be necissary to do the job the way a client wants it done if you have a speaking part.

So while modeling classes may be a waste of your time and money, some acting classes may be necissary if you choose to pursue this type of modeling. Many petite and average modles have an easire time in this industry becuse most of the time size is not a deciding factor. The ability to do the job well is more important. The industry is still competative, but if you have experience modeling in non speaking background parts it makes breaking into this sector much easier.

Modeling is an art to show your talent to the real world by using your expression, your presence of mind or by using your facial expression, by your dressing. Art of modeling used in various industries to promote their business idea to end level customer. There are so many type of modeling works available in the market and which attract the new age people to start career in modeling. There are lots of opportunities available for fashion modeling and commercial modeling. Equal demands are available for male models and female models around the world. There are so many factors to choose modeling as your career line

1) Your Looks

If you have a unique and glamour looks on your face and figure, your relative and friends always called you as a models or doll. If this is the thing then your face has quite unique light then other and has a charm to attract the attention of people on you. Modeling industries gives them a right platform to use their look for their career

2) Investment

To start any type of new business, people required a lots of continuous money inflow to run their business. Modeling is such a business that does not required investment of money. Models just have to pay to photographer for preparing attractive modeling portfolio. Once you have a very good portfolio or profile, you do not need any other investment. Having a personal website will add an extra benefit to your portfolio. Using your personal website, you can reach to all world famous modeling agency.

3) Part time career choice

Modeling is such a business that you can start working in it from your school days on a part time basis. Start career as teen models or child models gives more experience when you start working as young models. Modeling do not required everyday work or audition. You can take modeling as a part time career and able to earn good income from this. Participation in fashion show or runway modeling gives more income in short time.

4) Prestige

If your last desired is to become famous person or top celebrity then modeling is very fast and best way to achieve it. Top male and female models from all categories like Teen model, commercial model or glamour model.

So, if you thing that you have above quality or capability and just some dedication and right direction gives you bright career in modeling. As said, modeling is an art; it’s not a property or estate of anyone. All have the perfect place in each modeling work.

Voltage-gated Na+ channels play a fundamental role in the excitability of nerve and muscle cells. Defects in fast Na+ channel inactivation can cause hereditary muscle diseases with hyper- or hypoexcitability of the sarcolemma. To explore the kinetics and gating mechanisms of noninactivating muscle Na+ channels on a molecular level, we analyzed single channel currents from wild-type and five mutant Na+ channels. The mutations were localized in different protein regions which have been previously shown to be important for fast inactivation (D3-D4-linker, D3/S4-S5, D4/S4-S5, D4/S6) and exhibited distinct grades of defective fast inactivation with varying levels of persistent Na+ currents caused by late channel reopenings. Different gating schemes were fitted to the data using hidden Markov models with a correction for time interval omission and compared statistically. For all investigated channels including the wild-type, two open states were necessary to describe our data. Whereas one inactivated state was sufficient to fit the single channel behavior of wild-type channels, modeling the mutants with impaired fast inactivation revealed evidence for several inactivated states. We propose a single gating scheme with two open and three inactivated states to describe the behavior of all five examined mutants. This scheme provides a biological interpretation of the collected data, based on previous investigations in voltage-gated Na+ and K+ channels.

Voltage-gated Na+ channels are the basis for the initiation and conduction of action potentials in excitable cells. The channel's main α-subunit, containing the selectivity filter and the gating machinery of the channel, consists of four domains (D1-D4), each of which contains six transmembrane segments (S1-S6). The S4 segments contain positively charged amino acids constituting the so-called voltage sensors that can move relative to the rest of the protein upon voltage changes. Movement of the voltage sensors out of their resting position upon membrane depolarization leads to an opening of the gate, a process called activation. Conventionally, its reversal upon repolarization, when the channel is transferred back from the open to the closed state, is termed deactivation. During a maintained depolarization, wild-type (WT) Na+ channels, after a brief initial opening, are transferred to another nonconducting state within milliseconds, due to closure of a second gate, and remain closed. This process is called fast inactivation and the conformational state correspondingly, fast inactivated state. A part of the protein located between domains D3 and D4 on the intracellular side of the membrane is responsible for fast inactivation. It is believed that the inactivation gate consists of three-to-four hydrophobic amino acids (isoleucine-phenylalanine-methionine-(threonine), i.e., IFM(T); denoted IFM, thereafter) that might bind to a receptor site within the inner mouth of the pore, blocking the permeation pathway. Previous work revealed the cytoplasmic loops connecting the S4 and S5 segments and the intracellular parts of the S6 segments in D3 and D4 as primary candidates for forming an IFM binding site (1,2).

To deepen the understanding of the molecular mechanism of fast inactivation we performed single channel recordings for channels containing mutations in the regions critical for the fast inactivation process. Analysis of the macroscopic whole-cell currents showed an altered gating of the mutant channels, in particular a disrupted inactivation with a slowing of the current relaxation, the presence of more or less prominent noninactivating, persistent Na+ currents in a range of 3%-55% of the initial peak current and a 10-20 mV positive shift of steady-state inactivation ((3,4), A. Alekov and H. Lerche, unpublished.)

In contrast to macroscopic currents, single ion channel data contain information on the dwell times in different protein conformations and the correlations between them. Thus, they can give further insight into the channel kinetics. Most commonly, single ion channel currents are described by hidden Markov models. In these models, the switching between the different protein configurations, called states, is described by a Markov chain. The number of these states and the allowed transitions between them is comprised graphically in the gating scheme.

One approach to analyze the data has been introduced by Horn and Lange (5). The authors fitted given gating schemes to the idealized, noise-free time series. Since the inevitable anti-aliasing filter limits the time resolution of the recording system and since the idealization of the current records relies on heavy filtering, brief openings and closings are missed. Several methods to cope with these missed events have been proposed, which are mostly approximative (6-9). An exact solution to the problem of time interval omission has been given by Hawkes et al. (10), who derived recursion formulas for the resulting apparent open and apparent closed time distributions.

Human CYP27A1 is a mitochondrial cytochrome P450, which is principally found in the liver and plays important roles in the biological activation of vitamin D3 and in the biosynthesis of bile acids. We have applied a systematic analysis of hydrogen bonding patterns in 11 prokaryotic and mammalian CYP crystal structures to construct a homology-based model of CYP27A1. Docking of vitamin D3 structures into the active site of this model identified potential substrate contact residues in the F-helix, the β-3 sheet, and the β-5 sheet. Site-directed mutagenesis and expression in COS-1 cells confirmed that these positions affect enzymatic activity, in some cases shifting metabolism of 1α-hydroxyvitamin D3 to favor 25- or 27-hydroxylation. The results suggest that conserved hydrophobic residues in the β-5 hairpin help define the shape of the substrate binding cavity and that this structure interacts with Phe-248 in the F-helix. Mutations directed toward the β-3a strand suggested a possible heme-binding interaction centered on Asn-403 and a structural role for substrate contact residues Thr-402 and Ser-404.

Abbreviations used: CYP27A1, cytochrome P450 25-hydroxylase; CTX, cerebrotendinous xanthomatosis; CYP, cytochrome P450; CYP24A1, 1α,25-dihydroxyvitamin D3-inducible cytochrome P450 24-hydroxylase; CYP27B1, cytochrome P450 1α-hydroxylase; HPLC, high performance lic|uid chromatography; VDDR-1, vitamin D-dependent rickets-type I; 1α-OH-D^sub 3^, 1α-hydroxyvitamin D3; 1α,25-(OH)^sub 2^D^sub 3^, 1α,25-dihydroxyvitamin D3 25-OH-D^sub 3^, 25-hydroxyvitamin D3; RMSD, root mean-square deviation; congenital adrenal hyperplasia, CAH.

The use of vitamin D3 by the body is mediated through a series of mitochondrial cytochrome P450 enzyme reactions in which the parent vitamin is transformed sequentially by the hepatic 25-hydroxylase (CYP27A1) into 25-OH-D^sub 3^ and the renal 1α-hydroxylase (CYP27B1) into the active hormone, 1α,25-(OH)^sub 2^D^sub 3^. Subsequent catabolism in vitamin D target tissues by the 1α,25-(OH)^sub 2^D^sub 3^-inducible 24-hydroxylase (CYP24A1) produces the biliary excretory product calcitroic acid (1). The active hormone and its precursors are transported between tissues complexed to vitamin D-binding protein. In the nucleus of cells in vitamin D target tissues, 1α,25-(OH)^sub 2^D3 binds vitamin D receptor to transactivate, the expression of specific gene products affecting calcium homeostasis and the proliferation and differentiation of certain specialized cell types (2). Thus the structure of the vitamin D molecule helps define crucial interactions with at least five proteins, thereby influencing transport, activation, biological action, catabolism, pharmacokinetics, and the precise sequence of these events (3). However, research into the design of vitamin D prodrugs has shown that the activation sequence can be manipulated, and that a nonphysiological, 1α-hydroxylated vitamin D analog can be 25-hydroxylated and activated in a single cytochrome-mediated step (4).

The circulating level of 25-OH-D^sub 3^ is a measure of vitamin D status (5), but the CYP enzymes regulating its formation are still not completely defined. The best studied 25-hydroxylase, CYP27A1, is well conserved across species and is a bifunctional enzyme that also expresses 27-hydroxylase activity toward cholesterol and related sterols in two separate bile acid biosynthetic pathways (6). Despite being the affected target in cerebrotendinous xanthomatosis (CTX) (7,8), a lipid storage disorder characterized by the accumulation of abnormal metabolites of bile acid precursors (9), the only indication of vitamin D deficiency associated with the loss of CYP27A1 is an increased risk of osteoporosis and bone fractures and in low 25-OH-D^sub 3^ levels that fail to normalize with bile-acid replacement therapy (10). This suggests a redundant or compensatory 25-hydroxylase activity that is in agreement with one of the earliest studies of vitamin D 25-hydroxylation, which inferred the existence of a high specificity, low capacity (microsomal) enzyme and a low specificity, high capacity (mitochondrial) enzyme (11). Two of the candidates for the human microsomal 25-hydroxylase include CYP3A4, a hepatic drug metabolizing enzyme with broad substrate specificity (12,13), and CYP2R1, recently shown to have activity (14) and to be associated with a mild form of rickets (15). A similar microsomal 25-hydroxylase redundancy is seen in the rat enzymes CYP2J3 (16), CYP2R1, and CYP2C11 (17), the pig CYP2D25 (18), and the mouse CYP2R1 (19).

Since there are no crystal structures of mitochondrial cytochrome P450s, any model for CYP27A1 must be based upon one or more existing prokaryotic or microsomal CYP crystal structures. Although an important model of bovine mitochondrial CYP11A1 (side-chain cleavage enzyme, P450scc) (20) is available in the Protein Data Bank, there is disagreement concerning the existence of an ad hoc surface loop between the E- and F-helices hypothesized to mediate membrane binding in it since subsequent models of bovine CYP11A1 (21), human CYP11A1 (22), human CYP11B1 and CYP11B2 (23), and all cytochrome P450 crystal structures, including 14α-sterol demethylase (CYP51) from Mycobacterium tuberculosis (24,25) and the mammalian enzymes CYP2B4 (26), CYP2C5 (27,28), CYP2C8 (29), CYP2C9 (30), and CYP3A4 (31,32) show no evidence of this surface loop. Thus the quality of a previous model for CYP27A1 based on the original bovine model (7) remains in doubt.

Queueing networks and Markov chains are used to evaluate the performance and reliability of computer, communication, and manufacturing systems, but this seems to be the first book to cover both. Bolch (computer science, U. of Erlangen); Stefan Greiner, with a German company; Hermann de Meer (mathematics and computer science, U. of Passau); and Kishor S. Trivedi (electrical and computer engineering and computer science, Duke U.) offer a textbook for a graduate or advanced undergraduate course within a computer science and computer engineering curricula. It describes and compares a large set of numerical solution methods. The first edition was published in 1999.

The human epidermal growth factor receptor (HER/ErbB) system comprises the epidermal growth factor receptor (EGFR/HER1) and three other homologs, namely HERs 2-4. This receptor system plays a critical role in cell proliferation and differentiation and receptor overexpression has been associated with poor prognosis in cancers of the epithelium. Here, we examine the effect of coexpressing varying levels of HERs 1-3 on the receptor dimerization patterns using a detailed kinetic model for HER/ErbB dimerization and trafficking. Our results indicate that coexpression of EGFR with HER2 or HER3 biases signaling to the cell surface and retards signal downregulation. In addition, simultaneous coexpression of HERs 1-3 leads to an abundance of HER2-HER3 heterodimers, which are known to be potent inducers of cell growth and transformation. Our new approach to use parameter dependence analysis in experimental design reveals that measurements of HER3 phosphorylation and HER2 internalization ratio may prove to be especially useful for the estimation of critical model parameters. Further, we examine the effect of receptor dimerization patterns on biological response using a simple phenomenological model. Results indicate that coexpression of EGFR with HER2 and HER3 at low to moderate levels may enable cells to match the response of a high HER2 expresser.

The human epidermal growth factor receptor (HER/ErbB) system comprises the epidermal growth factor receptor (EGFR/HER1) and three other homologs, namely HERs 2-4. This receptor system plays a critical role in cell proliferation and differentiation and receptor overexpression has been associated with poor prognosis in cancers of the epithelium. Here, we examine the effect of coexpressing varying levels of HERs 1-3 on the receptor dimerization patterns using a detailed kinetic model for HER/ErbB dimerization and trafficking. Our results indicate that coexpression of EGFR with HER2 or HER3 biases signaling to the cell surface and retards signal downregulation. In addition, simultaneous coexpression of HERs 1-3 leads to an abundance of HER2-HER3 heterodimers, which are known to be potent inducers of cell growth and transformation. Our new approach to use parameter dependence analysis in experimental design reveals that measurements of HER3 phosphorylation and HER2 internalization ratio may prove to be especially useful for the estimation of critical model parameters. Further, we examine the effect of receptor dimerization patterns on biological response using a simple phenomenological model. Results indicate that coexpression of EGFR with HER2 and HER3 at low to moderate levels may enable cells to match the response of a high HER2 expresser.

The Integrated Modeling Environment (IME) is a software system that establishes a centralized Web-based interface for integrating people (who may be geographically dispersed), processes, and data involved in a common engineering project. The IME includes software tools for life-cycle management, configuration management, visualization, and collaboration. It enables organized, efficient communication of engineering analyses and the statuses thereof. Key functions performed by use of the IME include creation, further development, and management of modeling analyses over their entire life cycles; publishing model and analysis information for availability and reuse throughout the user community; and managing legacy information without regard to original formats, database organizations, or computing platforms. The use of the IME creates an archive of analysis results, plus documentation that identifies the assumptions and data elements used for each analysis. This archive is configured to enable reuse of previous analysis results, and tracing of types and versions of software used for each step of each analysis. The IME utilizes a customized version of a commercial product-life-cycle-management application program that provides rich capabilities for managing configurations, workflows, data, and access through a single Web-based environment.

Exact and approximate modeling of linear systems; a behavioral approach.

SIAM

2006

206 pages

$64.00

Paperback

Mathematical modeling and computation

QA402

The behavioral approach to mathematical modeling presented in this text requires models to be viewed as sets of possible outcomes rather than to be a priori bound to particular representations. The authors, who are all from Katholieke Universiteit Leuven, Belgium, discuss exact and approximate fitting of data by linear, bilinear and quadratic static models and linear dynamic models, a formulation that enables readers to select the most suitable representation for a particular purpose. The text presents exact subspace-type and approximate optimization-based identification methods, as well as representation-free problem formulations, an overview of solution approaches and software implementation.

The Information Systems undergraduate program at Cleveland State University (CSU) has adopted the Unified Modeling Language (UML) as the tool for defining a system model through out the development process. This paper discusses the revised CSU curriculum, the use of UML as a common tool to unify several aspects of system development and implementation, and the way in which this approach replaces traditional software development tools. In general, the current CSU curriculum matches the IS 2002 curriculum model in which the implementation of database systems is a continuation of the analysis and logical design course. At CSU, to simplify course scheduling issues, students may take either course first or both at the same time, compromising the IS 2002 suggested prerequisite structure. Our teaching approach to this academic scenario is presented, as is our teaching methodology. Several examples are shown, including the use of tools such as Rational Rose, MS-Access, and Oracle.

In 1998 the Information Systems curriculum at Cleveland State University (CSU) underwent a major renovation, based in large part on the IS '97 (Davis, 1997) model curriculum, and has recently undergone review based on the IS 2002 report (Gorgone et al., 2002). Our goal at CSU is to prepare our students to play an effective role in entry level information systems positions, and to give them a solid foundation that allows them continued career growth. The flexibility of the IS 2002 model curriculum fits well with that goal. The current structure of the CSU IS curriculum is shown in Figure 1 ; the diagram also shows how each of our courses compares with the corresponding IS 2002.X course model; for instance our Systems Analysis Methods (IST 321) closely matches the IS 2002.7 course suggested in (Gorgone et al., 2002).

In addition to business courses and general education courses, the Information Systems program requires students to take a core of eight computer-based courses and three elective courses. The core covers programming, systems analysis, database development, networks, and the relationship between information systems and business. Electives include subjects such as web site development, knowledge management, project management, advanced programming, emerging technologies, etc.

In addition to the fact that the CSU program does not include quite as many courses as the IS 2002 program, there are differences in course prerequisites, particularly those relating to the systems analysis and database implementation courses. Many of our students (possibly a majority) are part-time students, which means that they take a few courses each semester and cannot fit into any type of "lock-step" program. As a result, we try to avoid locking students into long chains of course prerequisites since doing so could extend their degree completion time by a year or more. One consequence of this situation is that for many of the courses beyond the first few semesters, we cannot control the order in which students take courses. In particular, we cannot predict whether students will take the systems analysis course before the database course or vice versa. Given this situation, we have structured each course so that, in addition to teaching about the courses main topic, we also show students how the topic fits into the system development process.

In the initial redesign of the program (circa Fall, 1998), we identified two goals to emphasize across the curriculum: (a) placing emphasis on problem solving strategies and critical thinking; and (b) identifying and using best-practice and state-of-the-art techniques in problem solving. At that time, our general approach to system development was structured, and except for obvious knowledge dependencies, we treated most courses as independent of each other.

Over the next few years (the early 2000's) it became clear that we should be teaching object-oriented systems development and several changes were made to the curriculum. First we adopted a third goal: (c) presenting the entire systems development effort in a common, uniform, and unambiguous framework. Today, IS courses embrace the object-oriented model, and traditional structured development tools such as entity-relationship diagrams, data flow diagrams, and structure charts (Ramakrishnan and Gehrke, 1998; Yourdon, 1989; Page-Jones, 1988) have been replaced by UML diagrams. This has proven to be highly beneficial for several reasons. The UML tool provides a single complete and extendable tool for representing the entire life cycle. Although mastering the whole range of UML diagrams may seem overwhelming for the novice student, by presenting different parts of UML in different courses we make the learning process manageable, and students respond well to learning about specific types of diagrams. More importantly, the repetition of the diagrams in different IS courses has a remarkable effect in helping students to understand, review, and accept the systems development effort as a continuous and complex process. Rather than associating UML diagrams with just analysis and design, they are exposed repeatedly to the same tool in different parts of the system life cycle.

In this article, we define five purposes of a data model and describe a typical data modeling problem. We then evaluate the Entity-Relationship and Unified Modeling Language data models against those five purposes in the context of the example problem. We find severe limitations with both data models. We conclude the article with a survey of the characteristics needed for a new data model.

A database is a model of the users' perceptions of the objects in their business environment. Databases succeed or fail on how well they match the users' perceptions. Database designs that do not support the user's perceptions will be judged to be "difficult to use" or "not really what I need." In some cases, database designs that conflict with the users' perceptions can be made usable by complicating the logic of application programs to transform the given database structure into the user-perceived application components. Such programs are needlessly expensive to develop and a nightmare to maintain.

For all but the simplest databases, it is too difficult to express the users' perceptions in terms of a particular database model such as the relational model. Instead, the users' perceptions are normally first expressed in terms of a data model, which is an abstraction of the users' view. Data models thus serve as an intermediary between the users' requirements on one hand and the DBMS database design. The data model is normally constructed during the requirements stage of a database project and is converted into a database design during the design stage.

We cannot overemphasize that the primary purpose of a data model is to describe and document the users' view of their world. A data model is not a tool for recording a database design. The primary purpose of a data model is not to define the tables that will appear in the database. A relational schemata is a representation of a DBMS storage definition, not of the users' perceptions. Unfortunately, the table model is not rich enough to represent the users' needs. Consequently, without a suitable data modeling facility, the developers contort the users' requirements into the relational schemata and in the process, lose many important requirements.

We believe that neither the existing versions of the entityrelationship model nor the UML data model are adequate for use as a data model for documenting user requirements. We believe that both have significant limitations and that either a new data model or a substantially extended version of E-R or UML is needed.

Our argument proceeds as follows: We begin by defining characteristics of a desirable data model. We then describe an example problem and demonstrate, in subsequent sections, how neither the E-R model nor UML adequately describes that example. We conclude with a description of what we believe are the minimum requirements for an appropriate data model.

1.1 Needed Characteristics of a Data Model

In our view, a data model should have the following characteristics:

1. Sufficiently robust to readily express the users' perceptions

2. As simple as possible

3. Independent of any physical database model

4. Utilize domains with inheritable properties

5. Readily support database migration

Let us now consider each of the criteria in turn.

1.2 Sufficiently Robust

The features and functions of a data model must be rich enough to support the users' perceptions of the objects in their world. Of course this means that a data model should represent the entities and their relationships, but additional features and functions should allow the modeling of many other semantic constructs as well.

Consider two examples. First, suppose the user wants to keep track of customers and indicates that those customers hve an Address that consists of Street, City, State, and Zip. Additionally, the user states that Address is not required, but that if any portion of the Address is provided, then all of the elements of address become required. Thus, in a data entry form, the user need not enter any part of address, but if the user enters a value for, say, City, then all of the attributes Street, State, and Zip become required.

A second example is more subtle. Suppose the same users states that each customer has a contact person. For each contact, the user wants to record Name, Email, and Phone. A customer must have at least one contact, but may have as many as 3. Name is required, and both Email and Phone are optional. The question then becomes, is a contact simply an attribute of a customer, or is a contact a separate thing, independent of customer that has a relationship to a customer? We will return to this question in a moment.

An easy way to visualize these requirements is to suppose that we have constructed a prototype customer form and we record the underlying structure of that form. Figure 1 shows such a form-based schematic. The dotted subscript notation indicates the minimum and maximum cardinalities of each attribute, respectively. The 1.1 subscript on Name means that exactly one value of Name is required and allowed. The 0.1 subscript on Description indicates that no value for Description is required, but that a maximum of one value is allowed.