Sense and Sensibility: A Novel of Moderation Essay -- Austen Sense Sen

  In her first published novel, Sense and Sensibility, Jane Austin brought to life the spirit of being young, in love and living in the eighteenth century. Her story revealed the heartaches and happiness shared by Elinor Dashwood, who represented sense and her sister Marianne, who stood for sensibility. Both sisters felt strongly for what they unknowingly stood for, but each needed to reach a middle ground to find true happiness. It was not until the end of the novel, through marriage, that Elinor and Marianne overcame their nature of having sense and sensibility. Although the title suggested a story of opposites, Sense and Sensibility was about moderation, and how it was applied to two individuals to create sincere joy. The Dashwood sisters were alike in many ways: they were both pretty, young and looking for a suitor. Their differences, however, far exceed their similarities. Marianne, the younger sister at seventeen, was described as "sensible and clever; but eager in every thing; her sorrows, her joys, could have no moderation. She was generous, amiable, interesting; she was everything but prudent" [sic] (p. 4). Elinor saw this with concern, for she "possessed a strength of understanding, and coolness of judgment, which qualified her, though only nineteen, to be the counsellor of her mother, and enabled her frequently to counteract, to the advantage of them all, that eagerness of mind in Mrs Dashwood which must generally have led to imprudence. She had an excellent heart; - her disposition was affectionate, and her feelings were strong; but she knew how to govern them" [sic] (p. 3). The sisters also had different ideas of what to look for in a husband. Elinor was never specific on what she looked for in a suitor; h... ...ndship, voluntarily to give her hand to another!" [sic] (p. 259). Marianne had overcome the passion she had possessed to find happiness, for she "found her own happiness . . . . [and] could never love by halves; and her whole heart became, in time, as much devoted to her husband, as it had once been to Willoughby" (p. 260). The novel Sense and Sensibility is a wonderful tale of two young sisters who were able to overcome their own personal trials to reach happiness. Elinor was able to show her passion for Edward, releasing a great burden of sadness off her shoulders, while Marianne overcame her passion of Willoughby to love another, her husband. Despite the suggestion of the title, the novel was focused on moderation, and the role it plays in creating happiness. Works Cited: Austen, Jane. Sense and Sensibility. New York: Barnes and Noble Inc., 1996.

Lydia Peelle †Mule Killers Essay

In this short story â€Å"Mule Killers† by Lydia Peele we meet three generations of a family, grandfather, father and son as well as the different women in the story. The story is told in present time by the son as a first person narrator, but almost everything in the story is a flashback of the father’s story about his youth. The story is constructed in parts; you get introduced to the lives of the father and the grandfather with no introduction of what has happened before, and then, the story jumps to the end in the present, without letting the reader know what has happened in between and what will probably happen after the story ends. The story takes place on a farm on the countryside near Nashville in the Southeast of United States. Though the story, you get an impression of an isolated society where the church is central and people has got quiet and ordinary lives while they work hard to make a living from their farms. The language in â€Å"Mule Killers† is observing, which we can see in the description of Eula: â€Å"(†¦)her hair swept up off her neck, thick purple-black and shining, the other girl’s hanging limply down, onion paper pale(†¦)† In the story we hear the father tell the son about the events that changed their lives: how he met the mother of his son and also had to give up on his dreams of love and how the lovestory of what should have been innocent turned out to be the thing that shaped his future. The tragic love story represents the way the farmland was changed in the future. Firstly, the shift from mules to tractors in the farming symbolises several things. For the grandfather, the shift to tractors and the following accident marks a new time that he does not accept and he does not take him. This we get an example of in this line: â€Å"you’re gonna see a future I can’t even stretch my mind around. Not any of it. I can’t even begin to imagine. † For the father, the loss of his mule Orphan, which was one of the things that he really cared about represents the end of his childhood. The mules is a symbol of the future and the killing of them is a bad sign for the future and also is the point of no return in this short story. The shift from child to grown-up is the main theme in this story, but also the fathers struggle to live up to his fathers ideals of what a man is, is an important aspect in the story. In his trying to be and act like a grown-up he supresses his fears and his sadness and also the things he love: music and the mules. So it’s like he cannot cultivate these interests any longer. Another important theme in the short story is time. During the story you get a feeling of time passing by. The father goes from being a young man to having a son, who is twice as old as the father was when the son was born, the farming changes and goes from using mulls to tractors.

A Data Warehouse Appliance Can Have a Huge Positive Impact on Businesses and Organizations Essay

Businesses and organizations of all sizes are becoming increasingly dependent on data analytics, and data warehouses or business analytic infrastructure has become a business critical application for many (if not most) companies. Indeed, these companies have always searched for better ways to understand their customers, and anticipate their needs. They have longed to improve the speed and accuracy of operational decision-making. Equally important as timeliness is the depth of the data analysis. Generally, the companies want to decipher all secrets hidden within the massive amounts of ever-increasing data. A data warehouse appliance, which is an integrated collection of hardware and software designed for a specific purpose typically involving the high throughput of data and analytic functions, can be used by organizations to optimize various areas of data processing. Its main intent is to supplant conventional business intelligence functions, such as warehousing, extract-transform-load (ETL), analysis and reporting. Due to its cost-effectiveness and efficiency, the data warehouse appliance has become an important segment of the data warehousing market. In this paper, I will examine the data warehouse appliances and describe its positive impact on business enterprises. Introduction Since introduced in the early 1990s, data warehouse (DW) has proven to be the key platform for strategic and tactical decision support systems in the competitive business environment today. See more: Analysis of Starbucks coffee company employees essay It has become a major technology for building data management infrastructure, and resulted in many benefits for various organizations, including providing â€Å"a single version of the truth, better data analysis and time savings for users, reductions in head count, facilitation of the development of new applications, better data, and support for customer-focused business strategies† (Rahman, 2007). The technology has become extremely important in an environment where increasing competition, unpredictable market fluctuations, and changing regulatory environments are putting pressure on business organizations. Data warehouses are also becoming the central repositories of organization/company information for data, which is obtained from a variety of operational data sources. Business applications will find data warehouses more beneficial and rely on them as the main source of information as they progress. These applications are able to perform all sorts of data analysis, with increasing customer demands for having the most up-to-date information available in data warehouses. Improving data freshness within short time frames is essential to meeting such demands. According to Hong et al, virtually all Fortune 1000 companies, today, have data warehouses, and many medium and small sized firms are developing them. The desire to improve decision-making and organizational performance is the fundamental business driver behind data warehouses. DW help managers easily discover problems and opportunities sooner, and widen the scope of their analysis. Hong also mentions that data warehouse is user-driven, meaning that users are allowed to be in control of the data and will have the responsibility of determining and finding the data they need. But however, the data warehouses have to be designed and evaluated from the user perspective in order to motivate users to be responsible for finding the data they need. Data warehouse is said to be â€Å"one of the most powerful decision-support tools to have emerged in the last decade† (Ramamurthy, 2008). They are developed by firms to help managers answer important business questions which require analytics including data slicing and dicing, pivoting, drill-downs, roll-ups and aggregations. And these analytics are best supported by online-analytical processing (OLAP) tools. A data warehouse appliance, which is the main topic of discussion in this research, is referred to as an integrated collection of hardware and software designed for specific purposes involving the high throughput of data and analytic functions. Data warehouse appliance has become an important segment of the data warehousing market, due to its cost-effectiveness and efficiency. A business or organization can use a data warehouse appliance to optimize various areas of data processing. In general, the main purpose of the DW appliance is to supplant conventional business intelligence (BI) functions including warehousing, extract, transform, load (ETL), analysis, and reporting. A data warehouse appliance can have a huge positive impact on a business enterprise. Large organizations are able to staff their data warehouse more efficiently, while assisting mid-level companies in solving business intelligence challenges. Data warehouse is fundamentally changing the way the businesses operate, as they are increasingly adopted across various companies. The purpose of this paper is to present the data warehouse appliances and how they impact businesses and organizations. In the next sections, I present a brief overview of data warehousing and the current state of BI, then I define and discuss DW appliances including its benefits, after which I describe the positive impact of DW appliances on businesses. Data Warehousing A data warehouse can basically be defined a subject-oriented, integrated, non-volatile, and time-variant collection of data in support of management’s decisions. Unlike the on-line transaction processing (OLTP) database systems, data warehouses are organized around subjects storing historical/summarized data for business requirement purposes. According to O’Brien and Marakas, a data warehouse is a central source of data which have been cleaned, transformed and cataloged so they are usable by managers/business professionals for data mining, online analytical processing, market research, and decision support. These stored data are usually extracted from various operational, external, and other database management system of an organization. DW can be sub-divided into data marts, holding subsets of data from the warehouse that focus on specific aspects, such as department, of a company. In general all data warehouse systems comprises of the following layers; data source, data extraction, staging area, ETL, data storage, data logic, data presentation, metadata, and system operations layer. But the four major components include the multi-dimensional database, ETL, OLAP, and metadata. The dimensional database applies the concept of standard star-schema including dimension and fact tables, hierarchies for drill-down, role models, aggregates and snow flaking. It optimizes database design for better performance. The ETL process involves the extraction, transformation and loading of data with appropriate ETL tools. Data integration is one of the most important aspects of data warehouse, whereby data is extracted from multiple heterogeneous source systems and placed in a staging area where it is cleaned, transformed, pruned, reformatted, standardized, combined, and summarized before loading into the warehouse. OLAP (online analytical processing) tool provides the front-end analytical capabilities including slice and dice, drill up, drill down, drill across, pivoting, and trend analysis across time. And metadata stores information (or data) about the data in the warehouse system. The components of a complete data warehouse architectural system are illustrated in Figure 1 below. Figure 1 An important characteristic about the data in a data warehouse is that they are static, unlike a typical database with constant changes. Once the data are gathered up, formatted for storage, and stored in the data warehouse, they will never change. The restriction is such that complex patterns or historical trends can be searched for, and analyzed, by queries. Data warehouses are also non-volatile in the sense that end-users cannot update the data directly, thereby being able to maintain a history of the data. A major use of the data warehouse databases is data mining, in which the data are analyzed to reveal hidden patterns and trends in historical business activity. Such analysis could be used to help managers make decisions about strategic changes in business operations in order to gain competitive advantages in the marketplace. Data warehousing is a relatively new technology that â€Å"brings the vision of an entirely new (customer-centric) way of conducting business to reality†, and can provide â€Å"environments promising a revolution in organizational creativity and innovation† (Ramamurthy, 2008). Ramamurthy also mentioned that data warehouse generally serves as an IT infrastructure technology, focused on data architecture, as it provides a foundation for integrating a diverse set of internal and external data sources, enabling enterprise-wide data access and sharing, enforcing data quality standards, providing answers to business questions, and promoting strategic thinking through CRM, data mining, and other front-end BI applications. Users of the data warehouses are from virtually every business unit, amongst which information systems, marketing and sales, finance, production and operations, are the heaviest users. Current State of Business Intelligence Business Intelligence are computer based techniques used in identifying, extracting and analyzing business data. Sales revenue by products, department, time, region or income are such examples. The BI technologies provide historical, current and predictive views of business operations. Some common functions of BI technologies include reporting, online analytical processing, analytics, data mining, text-mining and predictive analytics. As BI aims to support better business decision-making, they can also be referred to as a decision support system. BI applications often use data gathered from data warehouses or data marts, however, not all BI applications require a data warehouse. With sources from Wikipedia, business intelligence can be applied to business purposes in order to drive business value. Amongst these business purposes include measurement, analytics, reporting, collaboration, and knowledge management. BI is widely used today, mainly to describe analytic applications. According to Watson, BI is currently the top-most priority of many chief information officers. In a survey of 1,400 CIOs, from Gartner Group, it was discovered that BI projects were the number one technology priority for 2007. Watson further informs that the BI is a process which basically consists of two primary activities; â€Å"getting data in and getting data out†. Getting data in, also referred to as data ware housing, delivers limited value to a business enterprise. Organizations realize the full value of data from data warehouses only when users and applications access the data and use it to make decisions. Getting data out receives the most attention, as it consists of business users/applications accessing data from DW to perform enterprise reporting, OLAP, querying and analytics. The business intelligence framework is depicted in figure 2. Current BI infrastructure is a patchwork of hardware, software and storage that is growing ever more complex. Figure 2 – BI framework BI is continuing to evolve, and several recent developments are generating widespread interest, including real-time BI, business performance management, and pervasive BI. Data Warehousing Appliance A data warehouse is developed to support a broad range of organizational tasks. It can be referred to as an organized collection of large amounts of structured data, designed and intended to support decision making in organizations. The import of information and knowledge from a data warehouse is a complex process that requires understanding of the logical schema structure and the underlying business environment. According to Hinshaw, a data warehouse appliance, applied to business intelligence, â€Å"is a machine capable of retrieving valuable decision-aiding intelligence from terabytes of data in seconds or minutes versus hours or days†. The appliances represent the difference between decision-making using either stale data or the freshest information possible. With sources from Wikipedia, a more standard definition of the data warehouse appliance is an integrated collection of hardware and software designed for a specific purpose that typically involves the high throughput of data and analytic functions. It typically consists of integrated set of servers, operating systems, data storage facilities, database management systems (DBMS), and software that is pre-installed and pre-optimized for data warehousing. DW appliances provide solutions for the mid-to-large volume data warehouse market, offering low-cost performance usually on data volumes within the terabyte range. Due to its cost-effectiveness and efficiency, the data warehouse appliance has become a critical segment of the data warehousing market. A business or an organization can use a data warehouse appliance to optimize various areas of data processing. The main purpose of a DW appliance, in general, is to supplant conventional business intelligence functions, such as warehousing, extract, transform, load (ETL), analysis, and reporting. A true DW appliance is defined as one that does not require fine-tuning, indexing, partitioning, or aggregating, whereas, some other DW appliances use languages such as SQL to facilitate interaction with the appliance at a database request level. With reference to Wikipedia, most data warehouse appliance vendors use massive parallel processing (MPP) architectures to provide high query performance and platform scalability. The MPP architectures consist of independent processors or servers executing in parallel, implementing a â€Å"shared nothing architecture† which provides an effective way to combine multiple nodes within a highly parallel environment. A DW appliance is capable of deploying up to thousands of query processing nodes in one ppliance package, compared to traditional solutions where the cost and complexity of each additional node prevents a high level of hardware parallelism. Leveraging fully integrated data warehouse architecture, a data warehouse appliance can deliver a significant performance advantage, performing up to 100 times faster than general-purpose data warehousing systems. Maturation With reference to Hinshaw, data warehouse appliance is specifically designed for the streaming workload of business intelligence and is built based on commodity components. It integrates hardware, DBMS and storage into one opaque device and combines the best elements of SMP and massively parallel processing (MPP) approaches into one that allows a query to be processed in the best possible optimized way. A data warehouse appliance is fully compatible with existing BI applications, tools and data, through standard interfaces. It is simple to use and has an extremely low cost of ownership. The development of standardized interfaces, protocols and functionality is one of the most important trends in BI. In comparison to about a decade ago, there are a wealth of tools and applications using these standardized interfaces including MicroStrategy, Business Objects, Cognos, SAS and SPSS. And these are coupled with ETL tools having standardized interfaces such as Ab Initio, Ascential and Informatica. The appliances work seamlessly with these tools and other in-house applications. A data warehouse appliance is truly scalable. The bottlenecks are the speeds of the internal buses, internal networks, and disk transfer in BI, whereas in transactional workloads, scalability is limited primarily by CPU. Reliability, which is provided by the homogenous nature of an appliance – all parts of the system coming from a vendor, is also critical. A data warehouse appliance also provides simplicity for the administrators, in that it allows administrators spend a more productive time in troubleshooting complex database systems. And DBAs can be deployed to assist end users doing real-time BI. A data warehouse appliance offers the lowest cost of ownership as it has one source and one vendor, thereby reducing costs associated with support. Businesses and organizations will run more efficiently with the simple, efficient solution provided by a data warehouse appliance. Benefits Data warehouse appliances provide freedom to the business user. With patch-work systems, users are limited in the queries they can run due to the time required to run them. And with the time required to run a complex query reduced to seconds, users can not only run their old analysis with more iterations, but have the time to devise and run entirely new sets of analysis on granular data. With sources from Wikipedia, some researched benefits of DW appliance are briefly discussed as follows; Reduction in costs – As a data warehouse grows, the total cost of ownership of the data warehouse consists of initial entry costs, maintenance costs, and the cost of changing capacity. DW appliances offer low entry and maintenance cost. Parallel performance – DW appliances provide a compelling price/performance ratio. The vendors use several distribution and partitioning methods to provide parallel performance. With high performance on highly granular data, DW appliances can address analytics that could previously not meet performance requirements. Reduced Administration – DW appliances can provide a single vendor solution, taking ownership for optimizing the parts and software within the appliance, thereby eliminating the customer’s costs for integration and regression testing of the DBMS, OS and storage on a terabyte scale. DW appliance reduces administration via automated space-allocation, reduced index-maintenance and reduced tuning and performance analysis. Scalability – DW appliances scale for both capacity and performance. In massive parallel processing architectures, adding servers increases performance as well as capacity. Built-in high availability – Massive parallel processing DW appliance vendors provide built-in high availability via redundancy on components within the appliance. Warm-standby servers, dual networks, dual power-supplies, disk mirroring with fail-over and solutions for server failure are offered by many. Increasingly, business analytics are expected to be used to improve the current cycle, and DW appliances provide quick implementations without the need for regression and integration testing. Also, DW appliances provide solutions for many analytic application uses. Some of these applications include; enterprise data warehousing, super-sized sandboxes isolating power users with resource intensive queries, pilot projects, off-loading projects from the enterprise data warehouse, applications with specific performance or loading requirements, data marts that have outgrown their present environment, turnkey data warehouses, solutions for applications with high data growth and high performance requirements, and applications needing data warehouse encryption. Impact of Data Warehouse Appliances on Businesses and Organization Demand for data warehouse appliances is increasing, and businesses taking advantage of the benefits of this hardware range from a world-wide large-scale business to the smallest individual business. Data virtualization could be a useful partner to appliances, providing a single view of information across multiple appliances. Data virtualization is also useful because it provides a stable reporting layer during normal migration exercises, such as the circumstances during addition of data warehouse appliances to the information infrastructure. As businesses today continue to process extremely large volumes of data, there is always the need to keep data warehousing costs under control while ensuring a superior BI and application performance. Scalability, flexibility, and affordability are essential requirements for designing an infrastructure capable of supporting next-generation BI performance. When asked why the demand for data warehouse appliance is increasing, during an interview, Robert Eve (executive vice president of marketing for Composite Software Inc. ) stated that it is the confluence of three primary drivers at the macro level. The first is â€Å"the well-reported information explosion, and the technical challenges involved in making this information accessible in forms that business decision-makers can easily use†. Secondly, data warehouse appliances are more affordable and appealing, as the costs per terabyte and for support are coming down. And finally, recent advancements in analytics technology, notably in predictive analytics, promise to concur with the massive data volumes. Data warehouse appliances offer numerous advantages some of which are similar to benefits. Amongst the advantages include; more reporting and analytical capabilities – data warehouse appliance are able to handle bigger and more complex query workload, if it executes queries, Cost reductions – data warehouse appliance requires a minimal amount of tuning and optimization of the database server and database design. It is also able to run most queries with a quick speed, Flexibility – it will be easier to implement new user requests if less tuning and optimization is needed. With other database servers, a new query might lead to quite a number of technical changes, such as creating and dropping indexes, repartitioning tables, etc. Sometimes, decision is made not to implement the new request at all, due to the overwhelming work. The need for these additional technical changes is less with a data warehouse appliance. Data warehouse appliances helps support impressive BI deployments. With reference to Hinshaw, real world application examples of the positive impact of DW appliance on businesses are discussed. The rapid growth of call detail records, in the telecommunications industry, creates an imposing amount of data, which makes it difficult for companies to quickly and efficiently analyze customer and call plan information. And traditional approaches have been inefficient in processing queries on even a month’s data, seriously hampering an organization’s ability to perform trend analysis to reduce customer churn and generate timely reports. However, with a DW appliance, the telecom user can analyze customer activity down to the call detail record level over a full year’s worth of detailed data. Another industry where data warehouse appliances have begun to prove their worth, and are poised to play a bigger role in the future, is the retail. Hinshaw states that Brick-and-mortar and online retailers are capturing great amounts of customer transaction and supply chain information, creating a data explosion that threatens to overwhelm an average retail organization and its current IT infrastructure. But data warehouse appliances enable these retailers to manage and analyze the terabytes of information in near-real time. They are able to use the information to effectively forecast buying patterns, quickly generate targeted promotions and optimize their inventory and supply chain. Business intelligence remains the foundation for the success of decision making in any company. And BI, itself, relies on the underlying database architecture. Eve also presents other real world examples of positive business impact among a broad range of industries. A leading worldwide convenience foods business uses data warehouse appliances and analytic applications to acquire major business benefits in two specific areas. One of which the company optimizes its international network of delivery routes, making the system more efficient and ensuring timely delivery of its products. Secondly, it continuously refines its merchandizing mix daily, on a retail basis, in order to maximize sales and margins. Major League Baseball captures information about every pitch, at-bat, and fielding play within a data warehouse appliance, using this data to predict players’ future on-field performance. This can help teams to evaluate current and free-agent talent, refine coaching and development methods, and determine salaries, hence maximizing their wins. Also, a global freight, transportation, and logistics company uses data warehouse appliances to identify behavioral patterns that indicate potential dissatisfaction within its existing customer base. The customer care group then proactively takes steps to improve satisfaction before they lose their customers. Currently, smaller data warehouse appliance vendors seem to be focusing on adding functionality to their products in order to compete with the mega-vendors. However, it is anticipated that all appliance vendors will be impacted by the trend toward an inexpensive, high-performance, and scalable virtualized data warehouse implementations which use regular hardware and open source software. Conclusion In general, data warehouse appliance is a combination hardware and software product specifically designed for analytical processing. In a traditional data warehouse implementation, the database administrator can spend a significant amount of time tuning and putting structures around the data to get the database to perform well for large sets of users. But with a data warehouse appliance, it is the vendor who is responsible for simplifying the physical database design layer and making sure that the software is tuned for the hardware. In this research, a comprehensive examination/review of the data warehouse appliances, their benefits, and how they positively impact businesses and organizations, was presented. Based on this research, the negative impact of DW appliances on businesses are negligible compared to its positive impact. And there is an increasing demand for DW appliances. I believe that, in the near future, the DW appliances will become the sole platform for all business intelligence applications and requirements. I gained much knowledge and insights from researching this topic, and I intend to further my research on future impacts of DW appliance on businesses.

Environmental Influences On Human Behavior Essay

Eating disorder is a condition wherein an individual’s eating behavior of eating or not eating is influenced by a psychological impulse, instead of a physiological need. Individuals with eating disorders generally choose to ignore the signals their bodies send out that nourishment is needed for maintenance or that enough food has already been consumed. One general feature commonly observed in an individual with an eating disorder is abnormal weight, which may be either above or below the normal weight. Normal weight has been defined by the World Health Organization (WHO) as having a body mass index (BMI) of 18. 5 to 24. 9 kg/m2 (Deurenberg and Yap, 1999; Weisell, 2002). BMI is the ratio of an individual’s weight in kilograms (kg) to his heights in meters squared (m2). An individual with a BMI of 25 to 29 kg/m2 is classified as overweight, those with BMI greater than or equal to 30 kg/m2 are categorized as moderately obese, and people with BMI of 40 kg/m2 and above are identified as morbidly obese. Obesity was earlier considered as an imbalance between energy intake and energy expenditure. Today, obesity is regarded as a disease that is strongly influenced by genetic, physiologic and behavioral factors (Jequier and Tappy, 1999). The global estimate of overweight people is currently 1. 2 billion, of which at least 300 million are classified as obese. Obesity has been identified as a preventable health risk, but unfortunately, the mortality rate of this disease is still high, contributing to approximately 300,000 deaths each year in the United States alone. Since the cases of overweight and obesity are continually increasing without any preference to economic status of a country, health governing bodies have put in a significant effort to promote awareness of this disease and intervention programs that would teach the public of the risks of being overweight and/or obese. A major factor that influences such excessive weight gain is the poor lifestyle choices individuals make, in terms of their eating, exercising and physical activities. Binge eating is another eating disorder that is characterized by consuming huge amounts of food in order to achieve the strong feeling of being full. This disorder is generally involved with eating bouts even when an individual is not hungry. Anorexia nervosa is an eating disorder that is recognized in two forms- the restricting type and the binge-eating/purging types (APA, 1994). The restricting type of anorexia nervosa involves the absolute inhibition of food consumption and does not accompany any purging or binge-eating actions. The binge-eating type of anorexia nervosa is commonly characterized by cycles of binge-eating and purging. The classic symptom of anorexia nervosa is subjecting one’s self to a starvation condition, with the main goal of preventing or avoiding gaining weight or sensing that any fat is deposited in the body. The psychological angle with anorexia nervosa is that the individual perceives himself as overweight yet actually, their weight is already below normal. The extreme condition of anorexia nervosa usually involves death due to severe malnutrition. Bulimia nervosa is an eating disorder that is characterized by cycles of binge eating, purging and the employment of laxatives to remove any food that has been consumed (APA, 1994). Bulimia nervosa may be differentiated from anorexia nervosa through the feature that the individuals afflicted with this eating disorder typically have normal or above-average weights. In addition, individuals with anorexia nervosa can strongly inhibit their food intake, while individuals with bulimia nervosa find difficulty in avoiding food consumption. Bulimic individuals commonly carry a psychological feeling of guilt and shame of eating so much food, hence they try to appease themselves of their eating faults through purging and chemical elimination of the food they ate through the use of laxatives. They consider such activities as remedies or cleansing rituals so that they can immediately purify themselves of the disgrace they made from eating huge amounts of food. To date, the exact cause of bulimia remains unknown, yet there are theories that this eating disorder is strongly associated to depression and anxiety, however, a precise correlation of this cause still has to be investigated. Another theory involves the motivation of the bulimic individual to escape from reality, by treating for as a comfort instead of a source of energy and nutrition for their bodies. Childhood experiences may also possibly play a role in the cause of bulimia, because young children are often given different types of food in order to pacify them or to reward them for particular activities. Society may also play a role in bulimia, because the media strongly endorses that being thin is good, beautiful and acceptable. It has been suggested that eating disorders may be physiologically influenced by serotonin and norepinephrine. It has also been suggested that anorexia is more frequently observed in females in the Western world (Suematsu, 1986). Several theories have been proposed to explain the mechanism behind hunger and eating in overweight and obese individuals. The internal-external theory of Schachter (1971) states that hunger is influenced by external signals such as time, as shown in their experiments involving manipulation of clock rates and counting the consumption of crackers by the subjects. The research showed that faster ticking clocks that would reach meal times earlier would influence the subjects to eat earlier, while slower ticking close would influence subjects to eat later during the day. This theory strengthened the hypothesis that obese people tend to â€Å"feel† hungry based on the time of the day, and not based of the real sensation of hunger. The sensation of hungry in normal individuals is generally induced by internal signals such as an increased appetite or need to eat. The boundary theory of hunger considers the cognitive influence of hunger and satiety, wherein an individual determines the amount of food he should take in, as their limit or boundary (Hermand and Polivy, 1984). During diet regimes, the amount of food an individual eats is a little less than the set amount or boundary and in turn, the body physiologically adapts to the available sources of energy. In overweight and obese individuals, the boundary of food intake is significantly higher than an individual of normal weight. A third theory explaining the relation between excessive weight gain and eating is the set point theory, which is essentially based on the control of the hypothalamus on the body’s predetermined weight. Such set point of weight will be biologically maintained through the natural way, regardless of efforts to loss weight through diets and other weight loss regimens. A decreased intake of calories will not perturb the hypothalamus in its self-regulation of body weight. These theories are comparatively similar in terms of their goal of attempting to describe the mechanisms of obesity. The theories all emphasized that obesity is not influenced by a single factor, such as plain and simple overeating. These theories actually describe external influences of factors that result in overeating. In the external-internal theory identifies the time of the day as the major factor that triggers hunger. For the boundary theory, the individual himself, most probably with the cerebellum as the major organ, determines the amount of food he will eat. As for the set point theory, the hypothalamus controls the individual’s body weight. It is interesting to note that what the society has perceived as overweight is not really caused by a simple excessive hunger that stems from the need of the stomach to carry more food, but actually a more complex network involving the digestive system, the central nervous system and the immediate environment. Treatment for eating disorder often involves physical and psychological approaches. Psychotherapy serves as the main treatment for eating disorders, which often involves sessions with a therapist to discuss issues such as anxiety, depression, low self-esteem and body image concerns. The therapist generally emphasizes the relationship of one’s thoughts and eating activities, as well as teaching the patient that food is a source of nourishment and not a source of comfort or escape. Antidepressants may be prescribed to an individual with an eating disorder, to regulate the emotions of the depressed individual. The physician will also need to regularly check the physical vital signs of the patient, in order to monitor whether the patient is gaining weight and to determine whether any other complications may be present in the individual. Dieticians will design a well-balanced diet for an individual with an eating disorder, as well as educate the person of the nutritional value of every type of food that is consumed. The theories of hunger and eating disorders are based on the concept of primary motivation, which is mainly an interplay between psychology and the biological need to provide energy to the proper functioning of the human body. It is more complicated than the straightforward feeding mechanisms in other organisms because eating in the other species is singly influenced by the need to provide food for the normal physiology of the body. In human beings that have a more complex brain system due to evolution, we have acquired the additional capability to feed our minds, and even our souls, so to speak figuratively. It is important to individuals to understand that the mind is a powerful organ that can influence the actions and activities of the rest of the body but it is also more important to know that such choices of eating the right amount of food, as well as the right type of food, is a conscious and voluntary choice, and the consequences should be seriously considered.

Family and Unilever

2. 1 Macro Environment 2. 1. 1 Economy – Residential a) Economic -The policy of the Vietnamese industry is mutually agreed to build the economy of Vietnam following the trend of industrialization and modernization; giving priority to attract foreign investment, especially from transnational companies and multinationals such as Unilever to increase its budget. The domestic market (wholesale, retail, flow of goods, etc. ) has grown much more.And infrastructure in major cities, especially Ho Chi Minh City have been adequate investment, first on a par with other countries in the region. -Unilever Vietnam as the consumer goods market in this new, more â€Å"land† to business. -Economic growth of Vietnam is low possibility that high consumption of products. -Finance, Vietnam credit growth, the stock market is fragmented. In addition, telecommunications systems, communications, telephone charges, postal and Internet have the highest rates around the world.So, it the introducti on of the Internet in business is not possible for Unilever, although the company has repeatedly refers to this goal as a way to reach customers and promote your products successfully in industrialized countries. b) Population -In addition to the extended family model non-traditional married family. Also added and growing one share, and have major differences in consumer decision model extended family. -Distribution of population in Vietnam is very uneven.Rural population lives in 72%   Large-scale population of 86 million people (13th in the world), rising by about 1 million per year. $ Hardworking, eager to learn, is considered receptive knowledge, new technology. So promise quality human resources for Unilever   -Vietnam Educational level is relatively high, especially in urban areas. A lot of people graduating from high school and college †¦ compared to other countries; further intellectual labor in Vietnam better performance excellence in technology-so this is an abund ant human resources for the company. Vietnam has a young population structure and popular model extended family (including grandparents, uncles, etc. ) opportunities for Unilever because this is the company's target customers. -Population-planning policies of the government will make in the next few decades, young people will grow old and aging population structure is no longer an advantage for Unilever. In addition, the extended family in the middle (the most common family structure in Vietnam), the choice of buying a product, especially high-end products, generally considered very carefully.So, group consumption of personal care items (personal care) not as much as senior SSWD group (single, separate, widowed, divorced) in the capitalist countries. 2. 1. 2 Politics and law a) Political In the context of terrorism, war, epidemics, etc. Recently, the Vietnamese politics is considered stable and was selected as one of the safest destinations in Asia-Pacific own, and bring peace of mi nd to investors. Unilever-a world renowned company with strong financial background has decided to set up a branch in Vietnam – Unilever Vi? t Nam.We show that they also felt good political environment in our country's favorable conditions for long-term growth of the company. b) Legislation Legal system more complete, create favorable conditions for foreign companies such as Unilever to promote investment, business   Done still complain opinions (both excess and insufficient, inconsistent, overlapping   Our country's economy is on track to develop stronger, deeper integration into the world economy, thus modifying, perfecting the legal system that are consistent with international law is very same urgency. 2. . 3 Nature and technology a) Natural Vietnam is located in a relatively favorable position in the region, with a long coastline, many large seaports to facilitate the export of goods when Unilever began to focus on exports in the near future. Hot and humid tropical c limate is not suitable for some products originating from the parent company in Europe. Vietnam particularly rich source of medicinal raw materials for the production of consumer goods as well as research products. b) Technology -In terms of the country's technology still weak, so Unilever bring their echnology not only their most advanced   -The change in production technology at the plant is small, even if it was done in the branch Unilever in another markets. The only change when the demands of the competition. -Because Unilever consumer goods production has more or  «Technology » fairly stable   2. 1. 4 Culture and Society – Vietnam has a very diverse culture, rich and rich -Vietnam is a country of religious freedom to distribute, advertise products not subject to many constraints too strict as many other Asian countries. Vietnam state religion is Buddhism, traditional customs and rites bold Asians. Culture regions, provinces, districts and villages. 2. 2 Micro En vironment 2. 2. 1, customers Lipton target customers are elderly or middle-aged (30-50). They will be making decisions for the majority of problems in life, including the choice of the consumer to buy the product. â€Å"Many tea drinkers choose Lipton because it is really inexpensive and you can get it just about anywhere. It is surprising that more people do not drink tea, as they would longer, happier and healthier lives if they did† (Winslow 2006).Furthermore, some customers think that taking anti-oxidants are healthy, thus, customers drink a couple of gallons per week: â€Å"Tea makes you look younger too and gives you energy as well. 2. 2. 2 Competitors One of the major competitors for Lipton in the world ice tea market is Nestle Refreshment Company, maker of Nestea Ice Tea, well-known competitor for Lipton ice tea. Like Lipton-Unilever, Nestle Refreshment Company has forged agreement with another soda manufacturer, Coca Cola.

Autobiographical Incident Essay Example | Topics and Well Written Essays - 500 words

Autobiographical Incident - Essay Example Some are funny and some might be very serious to talk about. However, the changes brought by such incidents on life always depend upon the severity of the happening. Here I would like to describe a personal experience that has positively affected my life and thought. This incidence always helps me to remain optimistic in my approach and vision. During last New Year holidays, I was busy in shopping with my friends at Holiday Markets in New York City. These markets offer greatest hits for lots of gifts so we were having a great time buying little packages for our family. Later on, we enjoyed coffee and sandwiches. It was hustle and bustle all around. All the shops were glowing with beautiful lights that also brightened up the whole stuff present in the shops. Just finishing the shopping, we planned to go back with our tokens of love for our family. At that moment when I was walking down the stairs of the last shop, I noticed a person who was crossing the road. This guy was physically disabled. He had both the hand missing and had only one leg. It appeared that he had passed through a terrible accident earlier. It was disgusting looking at an incomplete guy who was young and might have many dreams that cannot be fulfilled because of his filthy condition. However what made me so surprised was a glow and a smile on his face even after such a terrible experience. His face had an unlimited peace. I was wondering as for how he could grin in spite of being in a miserable state. I was so confused at that moment and wished to know the hidden truth behind that peaceful smile. This wish compelled me to go and ask what happened to him and what made him so relaxed even after such a bad experience. I crossed the road and reached nearby. I asked the guy what made him so relaxed in such circumstances. He told that for him happiness is not a matter of external events but it always lies how we react towards odd situations. Our mental attitude plays a great role in real life.

LGBT clients Essay Example | Topics and Well Written Essays - 500 words

LGBT clients - Essay Example This is important considering language has a history of being used to oppress and discriminate the LGBT community. Moreover, every person has a right to live an entirely functioning and emotionally healthy life regardless his or her gender identity and expression. The importance of understanding the terminologies to use when addressing a LGBT client, does not only show respect but also contribute to LGBT client’s self acceptant and Council’s competence in handling LGBT clients. There are several advantages in understanding the language and terminologies as a LGBT councilor. The first advantage is that such knowledge help in creating a welcoming environment for the LGBT persons and people close to them by establishing a counseling space that affirms LGBT person’s identity (Burnes et al, 2009). For example, a councilor may intentionally have LGBT-positive magazine in his or her counseling office and waiting rooms. The second advantage could be acceptable language help achieve an open, informative and fruitful discussion with a client on their experience. By doing so the councilor is able to assist the client overcome any potential inbuilt negative attitudes of themselves and their loved ones. Third advantage is that constan t use of acceptable language ensures that the counselors’ own perception or knowledge about LGBT does not interfere with his or her work. Lastly, understanding the LGBT’s languages makes it possible to acknowledge the diversity among LGBT people. For example, LGBT persons from different race, age or religion will use different terminology to refer to the same thing. There are a number of terms that the LGBT persons generally prefer being referred to and those they term abusive. The firs term one should avoid when referring to LGBTs is homosexuals, instead, use words such as, gay people, lesbians, or gay man. This is because homosexual is a clinical term that tend to