Challening Role of Nurses Essay Example | Topics and Well Written Essays - 2750 words

Challening Role of Nurses - Essay Example There are three different models of assessment in vogue of which Roper et al's model is adopted in the study. By also having a review of few published case studies, it is has been demonstrated that nurses are indispensable and they should conduct themselves in a responsible manner failing which the whole health care delivery system would collapse. one of the essential skills required of nurse clinicians is that of health assessment, including physical assessment. The nurses' role care of care starts from putting the patients and family members at ease on arrival and immediately beginning her health and physical assessment of the patient along with information provided by family members and past records of medical history. The Nurses should adopt a holistic approach as if they are one of the members of the community in delivering health care Nurses have a challenging role in the delivery of health care and are required to be skilled and knowledgeable clinicians; one of the essential skills required of nurse clinicians is that of health a... They undergo minimum three years of graduation like any other profession requires before they can practice as an indispensable link between doctors and patients. They are the first point of care in the absence of doctors and even in their presence. In fact nurse is a mini-doctor. Doctors look up on nurses as valuable source of information about the patients and expect them to fill the vacuum between the doctors and patients in their health care delivery to patients as the doctors can not be always be at the latter's bedside. Besides, Nursing and Midwifery Council (NMC), U.K. established in April 2002 has stipulated standards of proficiency for nurses which have come into force from 1 August 2004. Some of important standards of proficiency for nursing students prescribed by the NMC are that they should practice within legal and ethical limits keeping in view the patient's welfare, that they should not practice in a discriminatory manner between individuals and interest groups, that they should establish therapeutic relationships and withdraw from them appropriately, and that they should document the assessment of the patients systematically and accurately. (NMC) Health Assessment Basically an assessment of health involves collection of data and arriving at a judgement of status of a person's health, requirements, desires to serve as guide for future course of treatment.(Heath 2000) Nursing process starts with the said assessment. When the nurse meets the patient on being admitted to a hospital, visiting a clinic or at the patient's residence, she gathers information of the patient to decide on a care delivery. The assessment may be even conducted on day to day basis to monitor improvement

Reducing Violence in Society Essay Example for Free

Reducing Violence in Society Essay Finn’s that â€Å"we really understand the market only when we examine it within its [full] political, social, and cultural context† (p. 144). His use of the term the â€Å"moral ecology of markets† refers to his concept that markets involve complex interactions among a wide range of social factors that must be studied like an ecological system. Finn has identified four areas of morality:(1) government imposed constraints to markets that prevent market abuses, also they various opinions from left and right hinge on where fences should be built (2) the provision of essential goods and services to all persons, that means to redress distributional shortcomings of the market and balanced the demand and supply. (3) the morality of individuals and groups to restrain individual pursuit of self-interest by virtue. 4) the presence of civil society, in other worlds voluntary associations of individuals to achieve common goals. He suggests, is not between addressing these problems through totally free markets on the one hand, or some sort of centrally planned system on the other, since all real-world economic systems include some mix of markets and government involvement. Market systems provide some boundaries that limit or prohibit certain practices, and planned economies allow some decisions to be made by individuals. For all points of view from left to right, the assessment of justice will depend not only on the structure for markets themselves but also on the context of markets. Finn provides an economic defense of self-interest and market. Because he tried to believe that libertarians seek to defend markets without recourse to moral claims. However, they have failed eventually, because any defense of markets necessarily involves some moral claims, and indeed libertarians do accept some claims, though often implicitly. So that Finn proposes the â€Å"four problems of economic life†Ã¢â‚¬â€allocation, distribution, scale, and quality of relations—which all economic systems must address. The economic problems are interrelated, and attempts to solve on can have a beneficial or detrimental effects on the others. Begins with the â€Å"construction of fences† that defines the bounds of allowable market fences. They allow the established fences people are free to pursue their own interests. Simultaneously, USA people agree that current market fences are morally sufficient to prevent abuses. Since Finn argues that do acting on self-interest within the game is allowed. The executives should be responsible to shareholders and employees. It is not just corporation get profits as a main purpose, but also managers should consider others. For example a company had shortage, executives does not lay off its workers during a downturn in demand but rather reduces the wages and salaries of company employees, because everybody has right to pursue their self-interest. Employees also need to pay for their family or terrible life. Also, each person have desire to pursue self-interest in social and allow do acting within rules what they made, like the â€Å"construction of fences†, the multi-national corporation should obligate to treat all teams be fair. Finn’s arguments are not convincing. I do not think Finn’s account of self-interest promote mutual understanding. First, Finn’s account of self-interest fails to recognize that in most market exchanges neither the buyer nor the seller takes explicit account of his or her self-interest, nor the interest of others, but each simply â€Å"goes about his or her business. For example if I back to home and by the way go to supermarket to buy fruits and milk, I make calculations nor do I consider tradeoffs. I simply select the items, pay my bill, and head for home. I pursue my self-interest because I base my decision on factors such as convenience, bargains, but how often do â€Å"abuses† arise on account of self-interested behavior ? Second, Finn’s account of self-interest is that he seems to equate self-interested behavior with market behavior. A government officer might seek to enlarge his budget, or the number of workers reporting to him, so as to increase his salary.

Data Processing in Big Data Centres Cost Reduction Approach

Data Processing in Big Data Centres Cost Reduction Approach A Cost Reduction Approach for Data Processing in Big Data Centers R. Reni Hena Helan ABSTRACT- The tremendous development in cloud data processing leads to the high load on computation, storage and communication in the data storage centers, which influence the data center providers to spend a considerable expenditure in data processing. There are three features leading to this increased expenditure, ie., job allotment, data positioning and data movement. In this paper, these three features are taken into consideration and an approach for cost reduction for cloud data processing is proposed. I propose a Markov Chain Model to analyze the task completion considering the data transmission and its computation. Keywords: Markov Chain Model, Data Center, Cloud data, Data Positioning, Data Processing. INTRODUCTION In recent years, the outburst of data all over the world has led to the demand of data processing in the data storage centers. This demand further leads to the increase in the cost incurred in the computation and the communication resources. As predicted by Gartner, by 2015, 71% of the data storage center hardware utilization would be from the cloud data processing which will cross around $126.2 billion. So, it is of vital importance to analyze the cost reduction problem in cloud data processing in the data storage centers. Data Center resizing (DCR) has been proposed to reduce the cost involved in data processing by adjusting the number of activated servers through task placement[1]. The Cloud Data Service Architecture mainly consists of distributed file systems which is helpful in distributing the data and its copies all over the data centers for an efficient load balancing and high performance. Some studies focused on reducing the communication cost by taking steps to place data on the servers where the input data exist to solve the remote data loading problem. Even though there were many solutions proposed to solve the above issues, none of the solutions were helpful in providing a cost efficient big data processing due to few disadvantages. First one, being the wastage of resources for the data that is not often accessed. Second, being the transmission costs involved depending on the distances and the type of communication used between the data centers. Not all the data could be stored on the same server because of its high volume; it is a mandatory one to store few data into remote servers that would incur transmission cost. Transmission costs get increased proportionally with the number of communication links involved. To get rid of the above disadvantages, I consider the cost reduction for cloud data processing through a joint optimization approach of task placement and data positioning in the data centers. Every server may have only a few resources needed for each piece of data residing on it. The data will need more resources to carry out with its big data processing tasks. The main aim of this paper is to optimize the data positioning, task allocation, routing and DCR to minimize the overall computation cost involved. The contributions are briefed as follows, 1.This paper considers the cost reduction problem involved with the cloud data processing in the data centers by the joint optimization of data positioning, task allocation and routing. To explain the computation and the transmission involved with the data centers, the Markov Chain model has been used and the task completion time has been derived. 2. For cost reduction, three factors are taken into consideration. The first one is how to place data in servers and the second one is how to distribute the data and the third one is how to resize the data centers to achieve minimum cost operation. II. OTHER RELATED WORKS Cost Minimization in Server The data centers are distributed throughout the world to store huge volumes of data that are accessible to thousands of users. A data center consists of a large number of servers that consume much power. Few Million dollars were to be spent on electricity cost that is a rising problem leading to the increased operation cost. The best known mechanisms proposed that grabbed attention was the DCR that focused on energy management by the data centers. Liu et al.[2] examined the same issue by considering the delay with the network. Fan et. al [3] analyses on how much computing equipments can be hosted within a fixed power budget in a safer and an efficient manner. Data Management The main aspect of data management is the reliability and effective data positioning. Sathiamoorthy et al. [4] proposed a solution based on erasure codes that offered high reliability in comparison with the Reed-Solomon codes. Yazd et al[5] proposed a scheduling algorithm to improve energy efficiency in data centers considering the data locality properties. Data Placement Agarwal et al[6] gave a data placement approach for the geographically distributed cloud services by considering the bandwidth cost, data center capacity, etc. It analyzes the logs based on the data access types and the client locations. All the existing works either focus on the task allotment or on the data placement or on the data management. But this paper takes into consideration, the data positioning, the task allotment and the routing of data systematically. SYSTEM MODEL The geographically distributed data center topology is shown in Fig. 1. with all the data centers containing the same data are connected via switches. There are a set of data centers(D), and each data center d à Ã‚ µ D that consists of a set of servers Sd connected to the switch md à Ã‚ µ M having a local transmission cost of Cl . The local transmission cost Cl will be less than the data center transmission cost Cr. Le the whole system be modeled as a Graph denoted by G=(N,E) where, N is the vertex set that includes all the switches(M) and the servers(Sd) E is the edge set. The weight involved with the edges are represented as, w(u,v)= Cr , if u,v à Ã‚ µ M Cl, otherwise The data stored in geographically distributed data centers are divided into a set of chunks C. Each data chunk c à Ã‚ µ C has a size and its is normalized to the server storage capacity. For each chunk of data, there will be P copies available in the distributed system for the fault tolerance. ÃŽ »c be the average task arrival rate requesting for chunk c. Fig. 1. Data Center topology The task arrival in each server is considered as a Poisson Process. If the task is distributed to a data center where the data chunk does not reside, it will take some amount of time till the data chunk gets transferred to that data center. Each task should be replied with a response time of R. PROBLEM FORMULATION Data Placement and Task allocation constraints The binary variable ysc is used to refer to whether the data chunk c is placed on the server s. ysc takes the value 1 if the chunk c is placed in the server s and it takes the value 0 if the chunk c is not placed in the server s. In any distributed file system for each data, there are P copies of data chunks stored and the data stored in each server cannot go beyond the storage capacity. Any server is termed as an activated one(as), only if there are data chunks stored onto it or else tasks assigned to it. Data Loading Constraints For every data chunk c required by the server s, there are few external or internal data transmissions involved for which a routing procedure is devised. The Graph containing the servers and the switches is divided into three categories, 1. Source Nodes: These are the servers consisting of the data chunks 2. Relay Nodes : These nodes receive data from the source nodes and forward them to the  other nodes based on some routing technique. 3. Destination Nodes: These are the nodes that are receiving the data chunks. Each and every destination node will receive the data chunks only if does not have a copy of it. Cost Reduction The cost involved with the transmission of the data chunks could be minimized by choosing the parameters such as the ysc ,as , ÃŽ »c etc. PERFORMANCE EVALUATION The performance analysis of the joint optimization approach describes that the communication costs decreased if more tasks and data chunks were placed in the same data center. Further increase in the number of servers will not affect the data chunk distribution among them. Increased requests lead to more activated servers and more computation resources and the joint optimization approach tries to lower the server cost. This approach balances between the server cost and the communication cost. When the delay requirement is very small, many servers are activated to provide quality of service. And the server costs decrease as the delay constraints increases. CONCLUSION This paper explains the joint optimization approach of data positioning, task allotment and routing of  data to reduce the overall operational cost involved with the data centers that are geographically distributed. This approach reduced the computational complexity considerably. REFERENCES [1] L. Rao, X. Liu, L. Xie, and W. Liu , â€Å"Minimizing Electricity Cost: Optimization of Distributed Internet Data Centers in a Multi-Electricity –Market Environment,† in Proceedings of the 29th International Conference on Computer Communications (INFOCOM).IEEE,2010, pp. 1-9. [2] Z. Liu, M. Lin, A. Wierman, S.H. Low, and L.L. Andrew, â€Å"Greening Geographical Load Balancing ,†in Proceedings of International Conference on Measurement an Modeling of Computer Systems(SIGMETRICS. ACM, 2011,pp.233-244. [3] X. Fan, W. D. Weber, and L. A. Barroso, â€Å"Power Provisioning for a Warehouse-sized Computer,† in Proceedings of the 34th Annual International Symposium on Computer Architecture (ICA).ACM, 2007, pp.13-23. [4] M. Sathiamoorthy, M. Asteris, D. Papailiopoulos, A. G. Dimakis, R. Vadali, S. Chen, and D. Borthakur, â€Å"Xoring elephants: novel erasure codes for big data,† in Proceedings of the 39th International Conference on Very Large Data Bases, ser. PVLDB’13. VLDB Endowment, 2013, pp.325-336. [5] S. A. Yazd, S.Venkatesan, and N. Mittal, â€Å"Boosting energy efficiency with mirrored data block replication policy and energy scheduler,† SIGOPS Oper. Syst. Rev., vol.47, no.2, pp.33-40, 2013. [6] S. Agarwal, J. Dunagan, N. Jain, S. Saroiu, A. Wolman, and H. Bhogan, â€Å"Volley: Automated Data Placement for Geo-Distributed Cloud Services,† in the 7th USENIX Symposium on Networked Systems Design and Implementation (NSDI), 2010,pp.17-32. [7] S. Govindan, A. Sivasubramaniam, and B. Urgaonkar, â€Å"Benefits and Limitations of Tapping Into Stored Energy for Datacenters,† in Proceedings of the 38th Annual International Symposium on Computer Architecture (ISCA). ACM.,pp.341-352. [8] P. X. Gao, A. R. Curtis, B. Wong, and S. Keshav, â€Å"It’s Not Easy Being Green, â€Å" in Proceedings of the ACM Special Interest Group on Data Communication(SIGCOMM), ACM,2012.pp.211-222. [9] J. Cohen, B. Dolan, M. Dunlap, J. M. Hellerstein, and C. Welton, â€Å"Mad Skills : new analysis practices for big data,† Proc. VLDB Endow. Vol.2, no.2, pp. 1481-1492, 2009. [10] H. Sachnai, G. Tamir, and T. Tamir, â€Å"Minimal cost reconfiguration of data placement in a storage area network, â€Å"Theoretical Computer Science, vol. 460.pp.42-53, 2012.

Diabetes :: essays research papers

Diabetes (diabetes mellitus) Diabetes is a disease characterized by excessive urination. Diabetes mellitus is caused by insufficient insulin production or lack of responsiveness to insulin, resulting in hyperglycemia (high blood glucose levels). There are 2 primary types of diabetes mellitus, type I (insulin-dependent or juvenile-onset), which may be caused by an autoimmune response, and type II (non-insulin-dependent or adult-onset). Diabetes insipidus is typically due to hormonal dysregulation. Diabetes mellitus (DM) is a chronic metabolic disorder caused by an absolute or relative deficiency of insulin, an anabolic hormone. Insulin is produced in the pancreas by the beta cells of the islets of Langerhans. Absence, destruction, or loss of these cells causes an absolute deficiency of insulin, leading to type 1 diabetes (insulin-dependent diabetes mellitus [IDDM]). Most children with diabetes have IDDM and a lifetime dependence on exogenous insulin. Type 2 diabetes (non–insulin-dependent diabetes mellitus [NIDDM]) is a heterogeneous disorder. Patients with NIDDM have insulin resistance, and their beta cells lack the ability to overcome this resistance. Although this form of diabetes previously was uncommon in children, 20% or more of new patients with diabetes in childhood and adolescence now have NIDDM, a change associated with increased rates of obesity.   Ã‚  Ã‚  Ã‚  Ã‚   Insulin is essential to process carbohydrate, fat, and protein. Insulin reduces blood glucose levels by allowing glucose to enter muscle cells and fat cells and by stimulating the conversion of glucose to glycogen as a carbohydrate store. Insulin also inhibits the release of stored glucose from liver glycogen and slows the breakdown of fat to triglycerides, free fatty acids, and ketones. Additionally, insulin slows the breakdown of protein for glucose production. Hyperglycemia results when insulin deficiency leads to uninhibited gluconeogenesis and prevents the use and storage of circulating glucose. The kidneys cannot reabsorb the excess glucose load, causing glycosuria, osmotic diuresis, thirst, and dehydration. Increased fat and protein breakdown leads to ketone production and weight loss. Without insulin, a child with IDDM wastes away and eventually dies from diabetic ketoacidosis. Information on mortality rates is difficult to ascertain without complete national registers of childhood diabetes, although age-specific mortality probably is double that of the general population. Particularly at risk are children aged 1-4 years who may die with DKA at the time of diagnosis. Adolescents also are a high-risk group. Most deaths result from delayed diagnosis or neglected treatment and subsequent cerebral edema during treatment for DKA, although untreated hypoglycemia also causes some deaths.

Arguing for Drug Testing Policy

This memo is in response to your recent e-mail in regards to random drug testing. I believe that implementing this policy would be extremely beneficial to our company as a whole. This is for the following reasons: financial savings, workplace safety, and to maintain our reputation. Financial Savings It is important that we strive to maintain a safe and effective work environment for every single one of our employees.It is estimated that workplace accidents related to drugs have costs employers in the United States $75 to 100 billion dollars per year. Those who abuse are also six times more likely to file worker's compensation claim and use 16 times the amount of health benefits as their fellow employees who do not use drugs. (http://www. employmentdrugtesting. com/screening. html_) Not ensuring that our employees are drug-free could end up costing our company a great deal of money in the long run if an employee under the influence injures themself or nother employee while on the Job here at Life Support, Inc.One might argue that implementing this drug-testing policy would actually cost our company more money due to the cost of the drug tests. However, the cost of a drug test cannot compare to the higher cost of worker's compensation or lawsuits to this company that could potentially occur due to an employee under the influence while on the Job. Spending money on these drug tests is a preventative measure to keep our company from spending more money in the long run. Workplace Safety It is absolutely vital that Life Support, Inc. rovides an environment in which our employees come to work knowing that we value their safety. The facts and figures mentioned above suggest that employees under the influence of drugs are extremely likely to cause and produce accidents in the workplace. The drug users are not the only ones at risk. Employees under the influence of drugs are clearly not performing to the best of their ability; their impaired state can cause them to make careless mistakes or exercise poor Judgment that they normally would not if they were in a ober state of mind.This can cause injury not only to them, but their fellow co- workers. By â€Å"weeding out† the employees who choose to use drugs, we will be providing a safer place for our workers and also show them that we truly value their safety. Maintain Reputation It is important for Life Support, Inc. to maintain a reputable image. By not tolerating drug abuse by our employees we present ourselves as a company that really cares about their people and also the quality of their products. https://donemyessay.com/unit-5-review/Our products will continue o be made of impeccable quality and be held to the highest standards in the industry. Our clients and those who use our products will know that Life Support, Inc. is a name to be trusted. This kind of quality and standards will reduce any possible liability for any malfunctioning equipment. I urge you to consider the potential savings, workplace safety, and our reputation as you continue to make your decision in regards to this matter. As always, please feel free to contact me if I can be of any other assistance to you.

Symphonic Splendor essays

Symphonic Splendor essays The concert conducted October 6, 2002 at the Pensacola Saengar Theatre consisted of orchestral pieces composed by Richard Strauss and George Gerschwin. The show commenced with Strausss symphonic poem Don Juan, and continued to move on to Gershwins Concerto in F for piano and orchestra. The solo pianist for the piece was a man by the name of Christopher Taylor whom has earned much respect from other musicians and listeners over the years by displaying dedication and exquisite knowledge of the musical language. Taylor began his musical career at the young age of seven years as he began to learn piano theory. Although it is considered a late start by the man himself, his accomplishments and awards prove that he has acquired the skills needed to perform at a much higher standard than the average pianist. Christopher has recently graced the air with a sweet succession of tones in countries around the world including France, Korea, Spain, the Philippines, and the Caribbean. A membership to the American Pianists Association was granted to him in 2002 to compliment his previous awards such as the Irving Gilmore Young Artists Award, an Avery Fischer Career Grant, and a first place trophy from the William Kapell International Piano competition. In addition to Mr. Taylors career as a performer, he is currently holding the position of Assistant Professor of Piano at the University of Wisconsin in Madison so his techniques can be passed on to up and coming musicians. The list of things this man has done in his lifetime is extremely impressive to the extent that anyone can appreciate the time and effort he has spent on making beautiful, complex pieces of music history come alive. Richard Strauss, born in 1864, enjoyed early success as both conductor and composer. He developed the symphonic or tone-poem to an unrivalled level of expressiveness and after 1900 achieved great success wi...