Australian ICT Framework and Mobile Device Management Essay

Australian ICT Framework and Mobile Device Management - Essay Example The legal frameworks aid reliability in the procurement processes of service provision in all the different Australian governments, i.e. the federal, state and territorial governments. This also helps in underpinning enterprise architecture in the entire Australian government (Saha, 2009). The current ICT infrastructure in Australia requires improvement to help achieve the creation of a whole-of-government Australian Public Service (APS) ICT career structure, which entails training and development programs for information technology professionals. ICT improvement also helps in developing and maintaining an information technology whole-of-government strategic workforce plan. ICT policies and frameworks help in the effective management of government and private data, and the protection of the government data from unauthorized accesses and misuse (Hart & Diane, 2007). The need for ICT legal framework and policies is to regulate the different types of governments, and create an easier wa y to monitor them. Every Australian is entitled to freedom of information access as per the Freedom of Information Act 1982, which guides the legislative basis of the release of government information. However, some of the information needs privacy and confidentiality, and hence demands protection. This ensures that the unauthorized access of information is reduced, whereby the necessary precautions are applied to strictly allow for classified information access to authorized or accredited personnel only. The main principles of the Australian enterprise ICT framework and policies is the need to know, which is applied to all official information, and the need to protect government information. This ensures the proper information access platforms and protects the divulgement of information within the government or from a foreign government. There is the enhancement of legal proceedings through privileged information access to legal professionals in the justice and legal system of the government (Hart & Diane, 2007). The presence of information technology Acts and policies provides the necessary foundation and benchmarks for the Australian governments to facilitate the smooth functioning of the country’s ICT sector. There are whole-of-government ICT policy frameworks guided by the Financial Management and Accountability Act (FMA) of 1997. The ICT Customization and Bespoke Development policy outlines compliance requirements for FMA Act agencies, and strengthens government arrangements for ICT Customization and Bespoke development. The Australian government has the legal enterprise ICT framework for enhancing and ensuring e-security. There is the core Cyber Security Requirement Policy for ICT driven proposals that requires agencies to access and address cyber security risks, and ensure that all businesses prepared through ICT-based proposals comply with the Australian government’s Cyber Security policies. This is aimed at achieving core cyber security for the smooth running of agencies and the government at large, through a smooth and safe flow and storage of information (Saha, 2009). The ICT Strategic Workforce plan is a core policy that entails the current expertise and capabilities of the APS ICT workforce, and the agency capabilities required in the delivery of government priorities. It guides the shift of ICT short term objectives and factors into medium and long term goals. There is also the Opt-Out policy for the whole-of-government ICT arrangements that has changed the opt-in self approvement by agencies into the

Length of stay in pediatric intensive care unit

Length of stay in pediatric intensive care unit 1.1 Scope of Review The following review of the past work done in the area of intensive care unit (ICU) length of stay is divided into two parts. The first part covers the studies done on the PICU length of stay while the second part delves into the literature of ICU length of stay. 1.2 Studies of Length of Stay in Pediatric Intensive Care Unit Ruttimann Pollack (1996) investigated the relationship of length of pediatric intensive care unit (PICU) stay to severity of illness and other potentially relevant factors available within the first 24 hours after admission. A median and geometric mean length of PICU stay of 2.0 and 1.9 days respectively, and the upper 95th percentile at 12 days were found. To prevent undue influence of outliers, all patients staying longer than 12 days were considered long-stay patients (4.1% of the total sample) and were excluded from the model-building process. In the LOS prediction model, variables found to be significantly associated (p Table 1.1: Log-logistic regression model for length of stay Variable Regression coefficient SE Adjusted LOS ratio 95% CI PRISM score* 0.6386 0.0407 5 1.28 1.25-1.33 10 1.63 1.54-1.74 15 1.80 1.67-1.94 20 1.98 1.82-2.16 25 1.62 1.53-1.72 30 1.29 1.25-1.33 40 1.38 1.33-1.44 50 1.06 1.06-1.07 Primary diagnoses CNS diseases -0.1682 0.0267 0.85 0.80-0.89 Neoplastic diseases 0.2324 0.0579 1.26 1.13-1.41 Drug overdoses -0.1758 0.0383 0.84 0.77-0.90 Inguinal hernia -0.3270 0.1344 0.72 0.55-0.94 Asthma -0.1135 0.0527 0.89 0.80-0.99 Pneumonia 0.2350 0.0475 1.26 1.15-1.39 CNS infections 0.4966 0.0555 1.64 1.47-1.83 Respiratory diseases ÃÆ'- PRISMà ¢Ã¢â€š ¬Ã‚   0.1257 0.0579 1.67 1.49-1.87 Head trauma ÃÆ'- PRISMà ¢Ã¢â€š ¬Ã‚   0.1710 0.0611 1.73 1.53-1.94 Diabetes ÃÆ'- PRISMà ¢Ã¢â€š ¬Ã‚   -0.3332 0.0666 1.23 1.08-1.40 Admission conditions Postoperative 0.1267 0.0243 1.14 1.08-1.19 Inpatient 0.2358 0.0271 1.27 1.20-1.33 Previous ICU admission 0.1562 0.0521 1.17 1.06-1.29 Therapy Mechanical ventilation 0.4900 0.0258 1.63 1.55-1.72 Intercept -0.0191 0.0278 Scale 2.5602 0.0295 Log partial likelihood = -5487.2; global chi-square value = 1601.9; df = 15; p CI, Confidence interval; CNS, Central nervous system *LOS ratios computed relative to PRISM score = 0. à ¢Ã¢â€š ¬Ã‚  LOS ratios computed for an interaction with PRISM score = 6.42 (sample average). Source: Modified from Ruttimann Pollack (1996). In the same study, Ruttimann Pollack (1996) noted the ratio of observed to predicted LOS varied among PICUs from 0.83 to 1.25. The PICU factors associated (p Table 1.2: Effect of PICU characteristics on length of stay Variable Regression coefficient SE Adjusted LOS ratio 95% CI p* Intensivist -0.1208 0.0189 0.89 0.85-0.92 0.0001 Coordination -0.0513 0.0190 0.95 0.92-0.99 0.0071 Residents -0.0586 0.0200 0.94 0.91-0.98 0.0033 ln (PICU/hospital beds) à ¢Ã¢â€š ¬Ã‚   0.0459 0.0170 1.03 1.01-1.06 0.0068 CI, Confidence interval. *2 ÃÆ'- ln (likelihood ratio) test. à ¢Ã¢â€š ¬Ã‚  LOS ratio and 95% CIs computed for and increase of PICU/hospital bed ratio by a factor of 2. Source: Modified from Ruttimann Pollack (1996). Development of a new LOS prediction model was necessary due to the availability of a newly updated pediatric severity-of-illness assessment system, PRISM III-24 (Pediatric risk of mortality, version III, 24-hour assessment). Ruttimann et al. (1998) have then fitted a generalized linear regression model (inverse Gaussian) to the observed LOS data with the log link function. In the new LOS prediction model, variables found to be significantly associated (p Table 1.3: Generalized linear regression model (inverse Gaussian) for length of stay (n = 9558) Variable Length of stay ratio 95% Confidence interval p Valueà ¢Ã¢â€š ¬Ã‚   PRISM III-24 à ¢Ã¢â€š ¬Ã‚ ¡ à ¢Ã¢â€š ¬Ã‚ ¡ 0.0001 (PRISM III-24) °Ã‚ °2 à ¢Ã¢â€š ¬Ã‚ ¡ à ¢Ã¢â€š ¬Ã‚ ¡ 0.0001 Primary diagnoses CNS infections 1.41 1.28-1.56 0.0001 Neoplastic diseases 1.22 1.13-1.31 0.0001 Asthma 0.91 0.85-0.96 0.0045 Pneumonia 1.50 1.40-1.61 0.0001 Drug overdoses 0.74 0.70-0.79 0.0001 CV nonoperative 1.22 1.14-1.32 0.0001 CV operative 0.89 0.83-0.95 0.0006 Diabetes 0.74 0.67-0.81 0.0001 Admission specifications Postoperative 0.92 0.88-0.96 0.0004 Inpatient 1.17 1.13-1.22 0.0001 Previous ICU admission 1.26 1.15-1.38 0.0001 Therapy Mechanical ventilation 1.68 1.60-1.77 0.0001 Model intercept ( ± SEM) = 1.423  ± 0.021 days CNS, Central nervous system; CV, cardiovascular system.  °Effect of the variable after adjusting for the effects of all other variables in the model. à ¢Ã¢â€š ¬Ã‚  Log-likelihood ratio compared with the chi-squared distribution with 1 degree of freedom. à ¢Ã¢â€š ¬Ã‚ ¡See Fig.2 (pg 82, Ruttimann et al. 1998). Model fit: Scaled deviance = 9558 (chi-square with 9543 degrees of freedom, p >0.45). Observed versus predicted length of stay, mean ( ± SEM) in: training sample (n = 9,558): 2.351( ± 0.032) versus 2.360( ± 0.011), p >0.64; test sample (n = 1,100): 2.461( ± 0.069) versus 2.419( ± 0.035), p >0.49. Source: Modified from Ruttimann et al. (1998). Ruttimann et al. (1998) have also assessed the PICU efficiency with the new LOS prediction model and validation of the assessment by an efficiency measure based on daily use of intensive care unit-specific therapies (based on the criterion whether on each day a patient used at least one therapy that is best delivered in the ICU). PICU efficiency was computed as either the ratio of the observed efficient days or the days accounted for by the predictor variables to the total care days, and the agreement was assessed by Spearmans rank correlation analysis. PICU efficiency comparisons for both the predictor-based and therapy-based methods are nearly equivalent. Ruttimann and colleagues (1998) acknowledged the advantage of predictor-based efficiency as it can be computed from admission day data only. It was of researchers utmost interest to study the extended LOSs as well. Long-stay patients (LSPs) in the PICU were later being examined by Marcin et al. (2001). As explained previously, LSPs were defined as patients having a length of stay greater than 95th percentile (>12 days). In the study, the clinical profiles and relative resource use of LSPs were determined and a prediction model was developed to identify LSPs for early quality and cost saving interventions. To create a predictive algorithm, logistic regression analysis was used to determine clinical characteristics, available within the first 24 hours after admission that were associated with LSPs. Marcin and colleagues (2001) noted that, Long-stay patients in the PICU consume a disproportionate amount of health care resources and have higher mortality rates than short-stay patients. Multivariate analysis of the study identified predictive factors of long-stay as: age Table 1.4: Significant independent variables from the logistic regression analysis Variable Odds Ratio 95% CI p Value Age 1.77 1.42-2.20 Previous ICU admission 2.18 1.52-3.11 Emergency admission 1.67 1.28-2.19 CPR before admission 0.59 0.37-0.96 0.032 Admitted from another ICU or IMU 2.28 1.13-4.58 0.020 Chronic TPN 3.09 1.39-6.92 0.006 Chronic tracheostomy 2.23 1.41-3.52 0.001 Pneumonia 2.73 2.03-3.68 Other respiratory disorder 2.33 1.64-3.32 Acquired cardiac disease 3.07 2.01-4.67 Having never been discharged from hospital 2.27 1.12-4.59 0.020 Ventilator 4.59 3.60-5.86 Intracranial catheter 2.78 1.76-4.41 PRISM III-24 score between 10 and 33 2.99 2.35-3.81 CI, confidence interval; ICU, intensive care unit; CPR, Cardiopulmonary resuscitation; IMU, intermediate care unit; TPN, total parenteral nutrition; PRISM, Pediatric Risk of Mortality. Source: Modified from Marcin et al. (2001). In a case study carried out by Kapadia et al. (2000) in a childrens hospital in the Texas Medical Center in Houston, discrete time Markov processes was applied to study the course of stay in a PICU as the patients move back and forth between the severity of illness states. To study the dynamics of the movement of patients in PICU, PRISM scores representing the intensity of illness were utilized. The study modeled the flow of patients as a discrete time Markov process. Rather than describing by a string of services and scores, the course of treatment and length of stay in the intensive care was described as a sequence of Low, Medium and High severity of illness. The resulted Markovian model appeared to fit the data well. The models were expected to provide information of how the current severity of illness is likely to change over time and how long the child is likely to stay in the PICU. The use of a Markovian approach allowed estimation of the time spent by patients in different se verity of illness states during the PICU stay, for the purposes of quality monitoring and resource allocation. 1.2 Studies of Length of Stay in Intensive Care Unit According to Gruenberg et al. (2006), institutional, medical, social and psychological factors collectively affect the length of stay (LOS) in the intensive care unit (ICU). Institutional factors include geographic location, resources, organizational structure, and leadership. In term of medical factors, specific medical interventions, specific clinical laboratory values, and the type and severity of patients illnesses were found to be related to length of stay in the ICU. Social factors such as lack of quality communication between patients families and physicians or other healthcare personnel, and conflict between patients families and hospital staff have resulted in prolonged ICU and hospital stays. Anxiety and depression experienced by a patients family members are psychological characteristics that contribute to inadequate decision making and extended ICU stays. In order to examine the impact of prolonged stay in the intensive care unit (ICU) on resource utilization, Arabi and colleagues (2002) carried out a prospective study to determine the influence of certain factors as possible predictors of prolonged stay in an adult medical/surgical ICU in a tertiary-care teaching hospital. Prolonged ICU stay was defined as length of stay >14 days. The data analyzed included the demographics and the clinical profile of each new admission. Besides, two means were used to assess severity of illness: the Acute Physiology and Chronic Health Evaluation (APACHE) II score (Knaus et al., 1985, as cited in Arabi et al., 2002) and the Simplified Acute Physiology Score (SAPS) II (Le Gall et al., 1993, as cited in Arabi et al., 2002). The study has identified predictors found to be significantly associated with prolonged ICU stay: non-elective admissions, readmissions, respiratory or trauma-related reasons for admission, and first 24-hour evidence of infection, oliguria, coagulopathy, and the need for mechanical ventilation or vasopressor therapy had significant association with prolonged ICU stay (Table 2.5 2.6). It was also found that mean APACHE II and SAPS II were slightly higher in patients with prolonged stay. Arabi et al. (2002) concluded that patients with prolonged ICU stay form a small proportion of ICU patients, yet they consume a significant share of the ICU resources. Nevertheless, the outcome of this group of patients is comparable to that of shorter stay patients. The predictors identified in the study were expected to be used in targeting this group to improve resource utilization and efficiency of ICU care. Table 1.5: Demographic and clinical profile of patients in the study group [all values shown are n (%), except where indicated otherwise] All (n = 947) ICU length of stay p value à ¢Ã¢â‚¬ °Ã‚ ¤ 14 days (n = 843) >14 days (n = 104) Age (years) ¹ 12-44 391 (41.3) 349 (41.4) 42 (40.4) NS 45-64 309 (32.6) 274 (32.5) 35 (33.7) NS à ¢Ã¢â‚¬ °Ã‚ ¥65 247 (26.1) 220 (26.1) 27 (26.0) NS Gender Male 591 (62.4) 518 (61.4) 73 (70.2) NS Female 356 (37.6) 325 (38.6) 31 (29.8) NS Type of admission Elective 169 (17.8) 164 (19.5) 5 (4.8) Non-elective 778 (82.2) 679 (80.5) 99 (95.2) Severity of illness APACHE II score (mean  ± SD) 19  ± 9 19  ± 9 21  ± 8 0.016 SAPS II score (mean  ± SD) 38  ± 20 37  ± 20 43  ± 16 0.003 Tracheostomy 113 (11.9) 52 (6.2) 61 (58.7) ICU mortality 193 (20.4) 173 (20.5) 20 (19.2) NS NS, not significant.  ¹Because of rounding, some of the percentages may not add up to 100% exactly. Source: Modified from Arabi et al. (2002). Table 1.6: Possible predictors for prolonged stay and the associated odds ratio No. of patients (%) ORs for prolonged stay p value (n = 947) OR 95% CI Non-elective admission 778 (82.8) 4.7 1.9-11.7 Readmission 79 (8.3) 2.1 1.1-3.8 0.02 Main reason for admission Surgical Trauma 171 (18.1) 2.1 1.4-3.4 Non-trauma surgical 231 (24.4) 0.3 0.1-0.5 Medical Cardiovascular 212 (22.4) 1.0 0.6-1.6 NS Respiratory 159 (16.8) 2.2 1.4-3.6 Neurologic 36 (3.8) 0.5 0.1-2.0 NS Other 138 (14.6) 0.51 0.25-1.05 NS First 24-hour data Coagulopathy 345 (36.4) 1.5 1.0-2.3 0.05

Leif Erikson: How He Discovered America Essay -- Leif Erikson

Many people think that Christopher Columbus was the first European to set foot in America, but this conventional belief is wrong; Leif Erikson, a Norse explorer set foot in Newfoundland almost 500 years before Columbus was even born. This paper will cover everything about Leif Erikson’s life including his grandfather’s banishment from Norway, and Leif’s father’s exile from Iceland. Leif Erikson’s early life, his family, and his visit to Norway to serve under the king. The first recorded European to see North America, Bjarni Herjà ³lfsson, and Leif Erikson’s voyage to America. This paper is also going to talk about Leif Erikson’s brother, Thorvald Erikson’s voyage to Vinland because his tale is interesting. Near the end of this research paper, it will have a paragraph on Leif Erikson’s later life. Finally at the end of this paper it is going to talk about the unknown reason why no other Europeans sailed to Vinland, and Le if’s impact on modern day North America. Leif Erikson’s grandfather, Thorvald Asvaldsson slaughtered a man in Jà ¦ren, Norway in 960 CE. This was the age of the Vikings, but Thorvald was still banished from the land (Mandia, n.d.). So he brought his ten year old son Erik, later to be named as Erik the Red because of his scarlet hair, to Drangar in northwestern Iceland on a farm with rather appalling soil (Where is Vinland?, n.d.). Leif Erikson, son of Erik the Red, and grandson of Thorvald Asvaldsson, was born around 970 CE, in Iceland (Where is Vinland?). It was a convention of norse culture that children did not grow up with their families, instead Leif grew up with a man named Thyrker, practically a foster father to Leif. Thyrker was born in Germany, but he was brought to Iceland because Erik the Red captured h... ... http://www2.sunysuffolk.edu/mandias/lia/vikings_during_mwp.html Ryne, L. (n.d.). Leif Erikson. Retrieved March 11, 2014, from Great Norwegians website: http://www.mnc.net/norway/Erikson.htm Skrà ¥mm, Y. (2004, August 14). Leif Ericsson. Retrieved March 24, 2014, from The Viking Network website: http://viking.no/e/people/leif/e-leiv.htm Soniak, M. (2013, January 23). He Could Have Discovered America, but He Wanted to See His Parents. mental_floss, Retrieved from http://mentalfloss.com/article/33584/he-could-have-discovered-amErika-he-want d-see-his-parents Weitemier, K. A. (n.d.). Leif Erikson. Retrieved March 11, 2014, from Great Norwegians website: http://www.mnc.net/norway/LeifErikson.htm Where is Vinland? (n.d.). Retrieved March 31, 2014, from Canadian Mysteries website: http://www.canadianmysteries.ca/sites/vinland/home/indexen.html

Dumex Web Site

The Danone Dumex Web site located at is the online presence of Dumex (Malaysia) Sdn. Bhd.. , a Malaysian health food company operating since 1958. The Web site serves as a company brochure and features company news, the company's products, tips on various health-related topics like nutrition, advice, and child development, as well as health news and recipes. Strengths The site is presented in a clutter free way. It's easy to see what the whole site has to offer, so the user does not get lost.The content also allows for returning visitors, or visitors who go back to the site for updates and new information. The New This Month, and Featured This Month section, not only encourages returning visitors, it also highlights the things that they haven't seen since their last visit, so that they won't have to go through material they've seen before. Also, the site can be navigated easily. The menu bar at the left side of the page points the user to various areas of the Web site, from news, to recipes, to the company's products, to medical advice, etc.It's all there, near each other. The site encourages more user participation and interactivity with its contests. It provides the user with a meaningful experience by featuring user photographs, writings, experiences and advise. On the company side, it allows them to build a reputation and image of being an expert on health issues. By featuring health experts' advice and opinion, along with health-related news, they are positioning themselves in a way that they can be trusted with one's health. The site also offers a display case for all their products.Content-wise, the site features news and information that is valued highly by its target market. Since the product is for babies and pregnant mothers, their content is geared towards issues related to pregnancy and children. This makes it a one-stop resource for their customers, further consolidating their brand and company image. Weakness As a healthcare-related Web site, th e site should include language warning users that the site might have insufficient advice and implores users to seek further medical attention or to see their doctor.The disclaimer would put the user's best interest in mind specially if he's really sick, or have a condition that might need individual care. An example is the site's pregnancy teaser on the home page which says â€Å"Pregnant? Don't forget to exercise†. Colette Bouchez at WebMD writes that although exercise during pregnancy is not only recommended, it also have certain benefits for both mother and baby, the mother should be aware of some warning signs like vaginal discharges and bleeding, and stop exercising. This caution is not on the Dumex home page.As such, it is highly probable that while material on the site might have been checked and is reliable, it might adversely affect some people who follows medical, nutritional advise without consulting their doctors. Also, while the site has its products online, the re is no way to order their products on the site. * * * As a consumer, I need to be sure of what I'm purchasing. It has to give me value for my money. It has to deliver its promises. For me, I want to be an informed consumer, price is only secondary.Web sites like Dumex provides me with the necessary information that I would not normally see in other forms of advertisements. A good Web site should let me know about the product, for me to know its benefits, potential threats and how it fares against the competition. And I don't have to leave home to do it, it's all, literally, at the tips of my fingers. Aside from information, good product Web sites offer their customers other related information. That would keep me informed of the things I need to be aware of.In the case of Dumex, it also tells me how their products would fit my needs. Lastly, Web sites offer the convenience of purchasing at home, which would give me more time to do other more important things, and other perks like avoiding the long lines at the supermarket or horrendous traffic. Effects of IT Employment. Information technology makes it easier to do the tasks that would have been more difficult and time consuming without it, a prime example of which is the use of the word processor instead of the manual typewriter.According to Michael Handel at the SRI Institute, however, automation using I. T. may lead to unemployment. If you have computers that run certain processes or monitor certain activities running, then you don't need to hire somebody to do that for you (Handel, 2003). Privacy and Individuality. Information technology is also changing the way we live. With the advent of social networking sites like Friendster, Myspace and countless of others, it has been easier to find new friends and maintain relationships and contact (Dwyer, 2007) .IT, while making it easier to buy products and services and have them delivered to your doorstep without leaving your home, like a book from Amazon. Com, also raised privacy issues like hackers gaining access to your credit card information, or personal data. Even one's behavior patterns on the World Wide Web, like the sites being accessed, and the amount of time being spent on a particular site can be monitored. Co-workers, hackers, and family members may have their own personal motivation now have access to illicit computer programs to get such information from one's computer.(Rittenhouse, 2004). Computer Crimes. Computer crimes are on the rise and it may involved the unauthorized use of a computer (stealing passwords, or accessing another's computer via a backdoor program); spreading malicious computer programs like trojan, virii and worms; or an online version of stalking and harassment. The underlying premise is that computer crimes are done by people who lack respect for property and privacy of other people (Standler, 2002). Ironically, computer crimes are also being battled via I. T.Various Web sites have come up with online p rivacy tools, virus detection and deletion programs, tips on how to detect illicit computer activities, among others. Societal Solutions. One of the most widespread and easily-seen effect of I. T. on society is the way people get their news nowadays. Before, people have to rely on rumors and the next morning's papers, and eventually, the evening broadcast and breaking news on T. V. The thing is, people have to wait before they get the news. Now, all they have to do is to log on to various news Web sites to get the latest happenings, on a wider variety of topics.They can get news from Somalia, or news on the latest Britney happening. The problem with this is that there tends to be a lot of wrong news coming from unverified sources. An example of which comes from the the Virginia Polytech Institute and State University shooting a year ago. At that time, many students, checked out sites on the Internet, like Fark. Com, Facebook. Com and other social networking sites to get information on the shooting. But then, it happened that one unnamed student became suspected as the gunman when his own Facebook. Com profile showed pictures of him and his gun collection.The student became the subject of death threats, and hate campaign, until news came out that the real gunman was shot dead and the unnamed student's identity was verified (IDG News Service, 2007). Health Issues. Speaking of misinformation, the World Wide Web is full of it. While the Web has made it easier to obtain information on various topics like what to do when you're pregnant, how to make bombs, how to cook the best lambchops, it would be wise to check the reliability of the information presented first. Make sure that the site, or the writer of the article is authoritative on the subject matter.Take special care when it comes to one's health. As in the case of Dumex's Web site, take all information presented there with a grain of salt and a word of caution. While healthcare advice is plentiful on the Web, it might be best to consult one's physician if you're sick. Leslie Teach at Emory University puts it succinctly when she says that previously health-related videos, books, brochures were tediously edited and reviewed before released to the public, and that's not happening with Web sites. Health improvement, disease prevention, and information about diseases are the primary health-related information that are being accessed.Teach gives a number of criterion for evaluating health-related Web sites, including: ? a clearly stated purpose of the site; ? no evident bias; ? the site is not a disguised advertisement; ? all aspects of the subject are adequately taken up; ? the site provides accurate information, with documented sources. * * * Information technology is here to stay. In fact, the widespread and pervasiveness of this technology has made so many profound effects on our daily lives that it has become a part of our culture, and our psyche. As with other advances, it has its drawb acks.But the simple truth is, the benefits outweighs the dangers. And the disadvantages can be easily fought, with a little awareness, knowledge and a critical mind, one can be safe. References Bouchez, Colette. (2007). Exercise During Pregnancy: Myth Vs. Fact. WebMD. Com. Retrieved on 18 April 2008. Danone Dumex Web page. (2008). Retrieved on 18 April 2008. Dwyer, Cathy. (2007). Digital Relationships in the MySpace Generation: Results From aQualitative Study. Proceedings of the 40th Hawaii International Conference on System Sciences – 2007. Retrieved on 16 April 2008. Handel, Michael J. (2003). Complex Picture of Information Technology and Employment Emerges. SRI International. Retrieved on 18 April 2008. Rittenhouse, David. (2004). Information Technology Abuse — Privacy Issues. Retrieved on18 April 2008. Standler, Ronald. (2002). Computer Crime. Retrieved on 18 April 2008. Teach, Leslie. Evaluating Health-related Web Sites. Emory University. Retrieved on 18 Apr il 2008. Virginia Tech shooting shows benefits, pitfalls of social networking sites. (2007). IDG News Service. Retrieved on 19 April 2008.

Finding True Compassion Essay

In human society, man is surrounded by those less privileged, those in a state of desperation. In her piece â€Å"On Compassion†, Barbara Ascher describes brief scenes that capture the basis of transaction between the helpless and those in a position to give help, arguing that the only way society can achieve true compassion is by truly identifying with the suffering of others. Ascher observes the world around her as a member of society, describing encounters between those in a place of misery and those in normal walks of life. As she observes the â€Å"grinning man† on the street corner and the old man who smelled of â€Å"cigarettes and urine†, she distinguishes herself from her fellow human beings. Ascher notices these people, while others â€Å"look away† and â€Å"daydream a bit†, making her stand out as someone who can acknowledge and understand those in times of hardship. Because Ascher writes as someone who can identify with adversity, she succeeds in persuading society as a whole to embrace compassion through understanding. Ascher draws a strict line between those suffering and those privileged in her piece to specifically isolate her audience. At the very beginning of her essay, Ascher describes a group of pedestrians assembled at a street corner, intent on ignoring the haggard homeless man before them. A man â€Å"lifts and lowers the shiny toe of his right shoe, watching the light reflect† – doing anything to avoid confronting the â€Å"grinning man† in any way. Later in her piece, Ascher describes â€Å"ladies in high-heeled shoes† and how they â€Å"pick their way through poverty and madness†, hoping to escape the torment experienced by those around them. Ascher accuses these people as being the flawed majority of a compassionless society, exposing how they actively attempt to ignore and push past the living adversity that walks the streets around them. The â€Å"troublesome presence is removed from the awareness of the electorate†, but Ascher tries to persuade these people to do the exact opposite; by letting in the hardship they also grow to grasp compassion. Ascher describes scenarios in which she questions whether or not acts of â€Å"compassion† are simply facades that hide misguided motives. The woman who protects herself and her child by â€Å"bearing the dollar like a cross† obviously acts out of fear, attempting to ward off the unwanted presence of the homeless man. Ascher uses rhetorical questions to challenge the woman’s motives, inquiring â€Å"was it fear or compassion that motivated the gift? † Ascher also questions the motives of the coffee shop owner, asking if pity, care or compassion compelled her decision to feed the homeless man day after day. Ascher takes up an extremely accusatory tone, directly exposing the mayor of New York City’s misguided motives behind the â€Å"involuntary hospitalization† of the homeless in his city. Ascher questions the grounds upon which these people act to enforce her argument that humanity must learn to identify with the â€Å"rags with voices† to become truly compassionate. Ascher exposes the flaws in society’s acts of â€Å"compassion†, reminding everyday men and women that their tendency to fear and distance themselves from the helpless only proves to hinder their capacity for compassion. As people walk through the Greek tragedy that is life, the only way to truly brighten the stage is to embrace the darkness that afflicts other â€Å"players†, hoping to shed the pure light of compassion.