Research about online shopping Essay Example | Topics and Well Written Essays - 1750 words

Research about online shopping - Essay Example Adoption of this mode of shopping has been a function of multiple factors that the paper seeks to identify. Online shoppers are motivated by increased population in urban areas which makes shopping malls crowded, thus many people prefer ordering goods and services from home. Online shopping has numerous benefits that include convenience, price advantages and also times saving. Selection of goods from a variety and also access to a lot of information that may not be available in offline shopping is another force that motivates online shopping. Most online shoppers have a motive behind their decision to shop online. Large online retailers such as Amazon and eBay began online retailing in 1995 and have developed to accommodate shoppers from all over the world by integrating all the requirements stated above. The University of North Carolina (4) assert that online buying has been marred by problems such as insecurity, lack of privacy, longer waits periods and also no hands on-inspections that are usually more important in purchase decisions. A constellation of these forces act to stall the advancement of online shopping. To enhance online shopping, majority of online retailers are Search Engine Optimized to allow potential clients locate them using the search engines. SEO optimization is a key element in boosting online shopping since most new shoppers locate online shops by searching randomly over the search engines; therefore, making a shop visible is a major step towards encouraging online shopping since more potential clients can locate it. Harnessing customers is a major business requirement. Requirements for participation in online shopping There are several basic requirements for participation and the characteristics of online shopping. According to Luo, Sulin and Zhnag (1132), ease of access to the internet has led to massive changes in the way people shop. Unlike normal shopping sprees, transactions are conducted over the internet. This requirement has bee n boosted by the fact that the world is constantly increasing internet penetration and also the speeds. This makes online transactions faster and efficient. In china for example, most people opt to shop online due to congestion in the shopping malls that usually waste a lot of time. Online shopping is relatively cheap and thus becomes an appropriate avenue through which low income earners can access goods that are highly priced at shopping centers at a more affordable price. In addition, online shoppers have a chance to have their goods delivered to the door after purchase (Li 509). For one to shop online there must be an electronic means of payment. These means of payment are commonly referred to as third party payment systems. The payment systems form a platform through which the buyers and the sellers can exchange goods and make payments without being in physical presence (Luo and Sulin 1135). Such online payment systems include PayPal, Payoneer, Skrill, Alipay and Payza. Another requirement for shopping online is that one must poses a computer or any other electronic device that can access the internet. This follows that the user must be literate to use the gadgets. This requirement has been met in most countries through education. Access to information is vital in online shopping. 70% of online buyers are enthusiast youths who have access to more information about new releases of goods and services. In this regard, the first characteristic of

Essentials of Health Information Management Essay Example for Free

Essentials of Health Information Management Essay Source- oriented medical records are kept together by subject matters, such as data from all laboratory results. Progress notes are all kept together and are written in paragraph format; these entries are filed under a specific sectionalized area in the patient chart and are usually in chronological order. Many facilities use the chronological order because this is an easy way to locate the required documents. The major advantage is that information is organized together, which makes it easier to determine the assessment, treatment, and observations a particular department provided a patient. The major disadvantage is there is no possible way to quickly determine all of the patient problems or treatment that has been provided to the patient. Problem- oriented medical records are kept together by a problem number; with this a number is placed to each problem. This is the most traditional way that most physicians document his or her records. Progress notes are kept in a â€Å"SOAP format, which is S= subjective, O=objective, A= assessment, and P= plan of action.† (SOAP Notes, 2010) The problem oriented-medical records have four parts, which include a database, problem list, initial plan, and progress notes. The major advantage is the record format is the ease or progression through all the data. The data is organized into stratified sections, which is quicker to find information needed and allows for a more rapid review of multiple office vists over time. The major disadvantage is that this type of format requires additional training and commitment from the medical and professional staff. An integrated record is a combination of source- oriented and problem- oriented medical records. The records are arranged in a strict chronological order, regardless of the source of original information. This method keeps a good account of continual events as the events occur and this method makes it difficult to compare and coordinate the issues easily. References Farlex. (2011). The Free Dictionary. Retrieved from http://www.medical-dictonary.thefreedictionary.com SOAP Notes. (2010). Retrieved from http://www.maexample.com/soap-notes.htm

Association of Lipid Profile in Pregnancy with Pre-eclampsia

Association of Lipid Profile in Pregnancy with Pre-eclampsia Association of Lipid Profile in Pregnancy with Pre-eclampsia, Gestational Diabetes Mellitus and Preterm delivery Babita Ghodke*,1, Raghuram Puskuru2, Varshil Mehta3, Kunal Bhuta4 1Associate Professor, 2Senior Resident, 3Intern, 4Junior Resident Department of Medicine, MGM Medical College, Navi Mumbai, India. Abstract Introduction: During last two trimesters of pregnancy, glucose is spared (for the foetus) while the concentration of fatty acids in plasma increases which can create complications like Preeclampsia, Gestational diabetes mellitus and preterm delivery. Aim: To study the association of serum lipid levels during second and third trimester with the development of pregnancy associated diseases like preeclampsia, GDM and preterm. Methods and Materials: The present study was carried out at MGM Hospital, Navi Mumbai, India.   200 antenatal cases from October, 2012 to October 2014 were enrolled after taking an informed consent. Statistical analyses were performed using Statistical Package for Social Sciences (SPSS) version 20. All reported p-values are two-tailed, and confidence intervals were calculated at the 95% level. Results: In pre-eclamptic patients, the mean Systolic Blood Pressure was 151.40 mm/Hg and mean diastolic blood pressure was 74.03 mm/Hg in third trimester. In pre-eclamptic patients, the mean serum triglyceride levels in second trimester was 204.00 mg/dl while 243.20 md/dl in third trimester. In Gestational Diabetes Mellitus patients, the mean serum triglyceride was 214.33 mg/dl in second trimester while 230.50 mg/dl in third trimester. In patients with preterm, the mean triglycerides levels 212.83 mg/dl and 240.16 mg/dl in second and third trimester respectively. In pre-eclamptic patients the mean serum cholesterol levels in second trimester was 210 mg/dl, while in third trimester, it was 243.60 mg/dl. In GDM patients, the mean serum cholesterol was 223.50 mg/dl and 242.83 mg/dl in second and third trimester respectively. 213.33 mg/dl and 243.66 mg/dl were the means cholesterol levels in second and third trimester respectively in patients with preterm. Out of total 200 patients 168 had no complications, while 20 {10%} had preeclampsia, 6 {3%} had Gestational Diabetes Mellitus and 6 {3%} had preterm deliveries. Conclusion:An association between maternal early pregnancy triglyceridaemia, and the subsequent risk of pre-eclampsia, gestational diabetes and preterm deliveries was observed. Occurrence of Preeclampsia, Gestational Diabetes and Preterm deliveries cannot be predicted based on the values of Serum Cholesterol, HDL-Cholesterol, LDL-Cholesterol and VLDL-Cholesterol. Hence estimation of lipid profile is strongly recommended during pregnancy to prevent deleterious effect of hyperlipidaemia associated with pregnancy. Keywords: Lipid Profile, Gestational Diabetes Mellitus, Preterm, Preeclampsia, Pregnancy related disease. 1. Introduction Pregnancy is a physiological process which causes profound changes in the body. It leads to an increase in demands for metabolic fuels and also causes alteration in hormonal levels which may cause few changes in lipid profile during pregnancy [1]. During last two trimesters, glucose is spared (for the foetus) while the concentration of fatty acids in plasma increases which leads to Gestational Diabetes Mellitus (GDM) and Gestational Hypertension (GHTN) respectively. Freinkel had described this process as accelerated starvation, and facilitated anabolism [2]. GDM and GHTN can lead to peri and postpartum complications. Pregnancy is often also complicated with diseases which can hamper Cardio-Vascular System. GDM and GHTN are few of them which can develop type 2 diabetes and systemic hypertension in later part of life [3,4]. In our previous study, we showed that total cholesterol, triglycerides, LDL-cholesterol, VLDL-cholesterol increases in last two trimesters. The increase is even greater in third trimester, when compared to the second. However, HDL-Cholesterol levels are decreased in third trimester when compared to that of second. The study concluded that the estimation of lipid profile is highly recommended during pregnancy due to its association with high levels of triglycerides which may lead to Pre-eclampsia, GDM and preterm delivery [5]. The present study is a continuation of our previous study and here, it evaluates the clinical significance of the lipid profile level in pregnancy and its effect on the development of pregnancy induced diseases like GDM, pre-eclampsia and preterm. 2. Aim To study the association of serum lipid levels during second and third trimester with the development of pregnancy associated diseases like preeclampsia, GDM and preterm. 3. Material, Methods, Ethics, Statistical Analysis, Inclusion and Exclusion Criteria The present study is a continuation of our previous study and the material, methods, ethics, inclusion and exclusion criteria could be obtained from our previous study [5]. In brief, the present study was conducted at Mahatma Gandhi Mission Hospital, Navi Mumbai, India. A total of 200 pregnant local women were enrolled from October 2012 to 2014. Out of the 200 subjects, 10 developed GHTN in late third trimester which was detected after 32nd week during follow-up which were also included. The venous blood sample was collected from all subjects for measurement of lipid profile in the 16th week and 32nd week of gestation for analysis. All pregnant women with a singleton pregnancy with a gestational age of 13-28 weeks, irrespective of parity and gravida were included. Pregnant women in whom hypertension (HTN) was detected before 14 weeks and those with diseases or complications like chronic HTN, Diabetes, Renal Disorders and Thyroid Disorders, Obstetric and Foetal Complications (Hydrops foetalis, congenital foetal anomalies) were excluded. Statistical analyses were performed using Statistical Package for Social Sciences (SPSS) version 17.0. All reported P values are two-tailed, and confidence intervals were calculated at the 95% level. The data was presented using frequencies, percentages, descriptive statistics followed by charts and graphs. Level of significance was set at 5%. All p-values less than 0.05 were treated as significant. 4. Results The mean age of patients was 24.87 years with a SD of 2.7 years. The minimum age was 18 years and the maximum age was 30 years. 4.1 Blood Pressure The mean Systolic Blood Pressure (SBP) in second trimester was 117.03 mm/Hg with a SD of 10.33 mm/Hg. In third trimester, it was increased to 120.77 with a SD of 14.675. In pre-eclamptic patients, the mean SBP was 151.40 with a SD 6.05. (p =0.00) in third trimester. There was a highly significant statistical difference in the mean blood pressure values among normal and pre-eclamptic women in third trimester. The mean Diastolic Blood Pressure in our study in third trimester was 72.11 mm/Hg with a SD of 6.88 mm/Hg. In third trimester, the mean SBP was increased to 74.03 with a SD of 8.616. In pre-eclamptic patients the mean was 92.00 with a SD 2.59 (p =0.00). There was a highly significant statistical difference in the mean blood pressure values among normal and pre-eclamptic women in third trimester. Out of total 200 patients 168 had no complications, while 20 had preeclampsia, 6 had GDM and 6 had preterm deliveries. 4.2 Association of Triglycerides with Preeclampsia, GDM and Preterm The below table (figure 1) indicates the 95% confidence interval for triglyceride levels for patients with outcomes of Preeclampsia, GDM and Preterm. The mean triglyceride level in second trimester was 188.68 mg/dl with a standard deviation of 20.88 mg/dl. In third trimester, the mean triglyceride (TG) level was increased to 216.78 mg/dl with a standard deviation of 20.09 mg/dl [5]. In pre-eclamptic patients, the mean serum triglyceride levels in second trimester was 204.00 with a SD 18.904 (p =0.00), while in third trimester, the mean was 243.20 with a SD of 15.58 (p =0.00). There was significant statistical significance observed between serum triglyceride levels and pre-eclampsia in both second and third trimesters (figure 1). Outcome Trimester Mean N SD SEM 95 % CI Lower Bound Upper Bound Preeclampsia Second Trimester 204.00 20 18.90 4.23 195.71 212.29 Third Trimester 243.20 20 15.58 3.48 236.37 250.03 GDM Second Trimester 214.33 6 18.64 7.61 199.42 229.25 Third Trimester 230.50 6 17.03 6.95 216.88 244.12 Preterm Second Trimester 212.83 6 11.99 4.90 203.24 222.43 Third Trimester 240.17 6 7.73 3.16 233.98 246.35 Figure 1. Association of Triglycerides with Preeclampsia, GDM and Preterm 4.3 Association of Cholesterol with Preeclampsia, GDM and Preterm The below table (figure 2) indicates the 95% confidence interval for cholesterol levels for patients with outcomes of Eclampsia, GDM and Preterm. In pre eclamptic patients the mean serum cholesterol levels in second trimester was 210.75 with a SD 24.248 (p =0.320), in third trimester, the mean was 243.60 with a SD of 25.84 (p =0.826). There was no statistical significance observed between serum cholesterol and pre-eclampsia in both second and third trimesters. Compared to the normal value of 200mg/dl, cholesterol level is raised in normal pregnancy. In pre- eclamptic women cholesterol level is raised more than the values in normal pregnancy. Outcome Trimester N Mean SD SEM 95% CI Lower Bound Upper Bound Preeclampsia 2nd Trimester 20 210.75 24.25 5.42 199.401 222.10 3rd Trimester 20 243.60 25.85 5.78 231.50 255.69 GDM 2nd Trimester 6 223.50 25.16 10.27 197.09 249.90 3rd Trimester 6 242.83 27.14 11.08 214.35 271.31 Preterm 2nd Trimester 6 213.33 20.23 8.25 192.10 234.55 3rd Trimester 6 243.66 27.200 11.10 215.12 272.21 Figure 2. Association of Cholesterol with Preeclampsia, GDM and Preterm 4.4 Association of HDL Cholesterol with Preeclampsia, GDM and Preterm The below table (figure 3) indicates the 95% confidence interval for HDL cholesterol levels for patients with outcomes of Preeclampsia, GDM and Preterm. In third trimester, the mean serum HDL Cholesterol (HDL-C) level in normal patients was 42.78 with a SD of 4.31, in pre eclamptic patients the mean was 45.60 with a SD 4.12 Compared to the normal value of 40-60 mg/dl, HDL-Cholesterol level is within normal range in normal pregnancy. In pre-eclamptic women HDL-C level was higher than normal pregnancy but within normal range. In pre eclamptic patients the mean serum HDL Cholesterol levels in second trimester was 51.8 with a SD 5.8 (p =0.040), in third trimester, the mean was 45.60 with a SD of 4.1 (p =0.006). There was significant statistical significance observed between serum HDL -Cholesterol and pre-eclampsia in both second and third trimesters. Outcome Trimester N Mean SD SEM 95% CI Lower Bound Upper Bound Preeclampsia 2nd Trimester 20 51.80 5.84 1.30 49.06 54.53 3rd Trimester 20 45.60 4.12 .92 43.67 47.52 GDM 2nd Trimester 6 52.00 7.07 2.88 44.57 59.42 3rd Trimester 6 41.16 7.27 2.97 33.52 48.80 Preterm 2nd Trimester 6 49.00 6.13 2.50 42.56 55.43 3rd Trimester 6 45.50 4.03 1.64 41.26 49.73 Figure 3. Association of HDL Cholesterol with Preeclampsia, GDM and Preterm 4.5 Association of LDL Cholesterol with Preeclampsia, GDM and Preterm The below table (figure 4) indicates the 95% confidence interval for LDL cholesterol levels for patients with outcomes of Preeclampsia, GDM and Preterm. In third trimester, the mean serum LDL-Cholesterol level in normal patients was 137.80 with a SD of 13.67, in preeclamptic patients the mean was 137.80 with a SD 11.5.   Compared to the normal value of 130 mg/dl [5], triglyceride level is raised in normal pregnancy. In preeclamptic women LDL-C level was same as in normal pregnancy (figure 4). In preeclamptic patients the mean serum LDL-C levels in second trimester was 92.7 with a SD 18.2 (p =0.943), in third trimester, the mean was 137.8 with a SD of 11.5 (p =0.996). There was no significant statistical significance observed between serum LDL-C levels and pre-eclampsia in both second and third trimesters. Outcome Trimester N Mean SD SEM 95% CI Lower Bound Upper Bound Preeclampsia 2nd Trimester 20 92.70 18.22 4.07 84.17 101.23 3rd Trimester 20 137.80 11.59 2.59 132.37 143.22 GDM 2nd Trimester 6 96.83 31.39 12.81 63.89 129.77 3rd Trimester 6 150.16 9.88 4.03 139.79 160.54 Preterm 2nd Trimester 6 84.50 6.12 2.50 78.07 90.92 3rd Trimester 6 127.83 10.64 4.34 116.66 139.00 Figure 4. Association of LDL Cholesterol with Preeclampsia, GDM and Preterm 4.6 Association of VLDL Cholesterol with Eclampsia, GDM and Preterm The below table (figure 5) indicates the 95% confidence interval for VLDL cholesterol levels for patients with outcomes of Eclampsia, GDM and Preterm. In third trimester, the mean serum VLDL-Cholesterol (VLDL-C) level in normal patients was 35.88 with a SD of 6.5, in pre eclamptic patients the mean was 39.7 with a SD 7.1.   Compared to the normal value of 35 mg/dl [5], VLDL-C level is raised in normal pregnancy. In pre- eclamptic women VLDL-C level was increased more than that in normal pregnancy. In pre eclamptic patients the mean serum VLDL-C levels in second trimester was 30.9 with a SD 7.9 (p =0.93), in third trimester, the mean was 39.7 with a SD of 7.1 (p =0.016). There was no significant statistical significance observed between serum VLDL-C levels and pre-eclampsia in second trimester but significance was found in third trimesters. Outcome Trimester N Mean SD SEM 95% CI Lower Bound Upper Bound Eclampsia 2nd Trimester 20 30.95 7.93 1.77 27.23 34.66 3rd Trimester 20 39.70 7.11 1.59 36.36 43.03 GDM 2nd Trimester 6 27.16 6.01 2.45 20.85 33.47 3rd Trimester 6 34.00 5.65 2.30 28.06 39.93 Preterm 2nd Trimester 6 25.66 3.98 1.62 21.48 29.84 3rd Trimester 6 36.83 6.96 2.84 29.52 44.14 Figure 5. Association of VLDL Cholesterol with Eclampsia, GDM and Preterm 4.7 Mean values of lipid parameters with outcome in 2nd and 3rd trimester The mean values of Serum cholesterol, Serum TG, HDL-C, LDL-C, VLDL-C are given in figures 6 and 7. Trimester Outcome Serum Cholesterol {mg/dl} Serum Triglycerides {mg/dl} HDL-CHOLESTEROL {mg/dl} LDL-CHOLESTEROL {mg/dl} VLDL-CHOLESTEROL {mg/dl} Second Trimester Preeclampsia 210.75 204.00 51.80 92.70 30.95 GDM 223.50 214.33 52.00 96.83 27.16 Preterm 213.33 212.83 49.00 84.50 25.66 Third Trimester Preeclampsia 243.60 243.20 45.60 137.80 39.70 GDM 242.83 230.50 41.16 150.16 34.00 Preterm 243.66 240.16 45.50 127.83 36.83 Figure 6. Mean values of lipid parameters with outcome in 2nd and 3rd trimester Figure 7. Comparison of Lipid parameters between second and third trimester 4.9 Complications outcome distribution Out of total 200 patients 168 had no complications, while 20 {10%} had preeclampsia, 6 {3%} had Gestational Diabetes Mellitus and 6 {3%} had preterm deliveries (Figure 8). Complication No of Cases Percentage No Complication 168 84% Pre-eclampsia 20 10% GDM 6 3% Preterm 6 3% Total 200 100% Figure 8. Distribution according to Complications 5. Discussion Hypercholesterolemia is known to cause excessive lipid peroxidation and coexistent diminution in antioxidant activity which may result in an imbalance between peroxidases and antioxidants, leading to oxidative stress. Oxidative stress and elevated atherogenic index may lead to atherogenicity in Pre-eclampsia [6]. 5.1 Triglycerides In a study conducted by Arnon Wiznitzer et. al., to prove the association of lipid levels during gestation with preeclampsia and GDM in 9911 pregnant women, they observed that the composite endpoint (GDM or preeclampsia) occurred in 1209 women (12.2%). During the index pregnancy, GDM was diagnosed in 638 women (6.4%) while Preeclampsia was diagnosed in 625 pregnancies (6.3%) [7]. In a study by Lorentzen et al., it was observed that the mean triglyceride concentrations of pre-eclampsia patients were higher than normal pregnant women at 16-18 weeks [8]. Later, a large prospective cohort study conducted in Norway by Clausen et al. (2001) also demonstrated that women with triglycerides above 212 mg/dL (2.4 mmol/L) had a five-fold increased risk (95% CI 1.1-23.1) of early onset pre-eclampsia (onset before 34 weeks) compared with those with triglycerides levels 133 mg/dL [9]. A study done by S. Niromanesh et. al., to compare the outcomes of forty five pregnant women who had high TG levels (>195 mg/dl) with 135 pregnant women having TG levels [10]. In a study done by Kandimalla et. al., comprising 156 pregnant women attending antenatal clinic visits were included prior to 20 weeks and were analysed for lipid levels. 102 participants were followed until delivery and were monitored for pre-eclampsia. They reported that mean triglyceride levels were found significantly higher in the pre-eclampsia group. Women with triglycerides above 130 mg/dL had increased risk of pre-eclampsia compared with those with triglycerides levels of 91 mg/dL or less [11]. In the present study, compared to the normal value of 150 mg/dl [12], during second trimester, the 95% CI for triglyceride level with Preeclampsia was between 195.71 and 212.29, the 95% CI for triglyceride level with outcome GDM was between 199.42 and 229.25; while the 95 % CI for triglyceride with preterm outcome was between 203.24 and 222.43. Hence, we can conclude that triglyceride level of more than 195 mg/dl during second trimester can lead to complications like Preeclampsia, and triglycerides greater than 199.42mg/dl lead to GDM and levels above 203.24mg/dl lead to Preterm delivery. During third trimester, the 95% CI for triglyceride level with Preeclampsia was between 236.37 250.03, the 95% CI for triglyceride level with outcome GDM was between 216.88 244.12 and the 95 % CI for triglyceride with preterm outcome was between 233.98 and 246.35. Hence, we can conclude that triglyceride level of more than 236 mg/dl during second trimester can lead to complications like Preeclamps ia, triglyceride level of more than 216.88 mg/dl leads to GDM and triglyceride level of more than 233.98mg/dl leads to Preterm delivery (figure 1). Our findings correlate with the findings of a study done by Kandimalla et. al [11]. 5.2 Cholesterol

Twelfth Night Essays -- Literary Analysis, Shakespeare

In Shakespeare’s play, Twelfth Night or What you Will, the characters are involved in a plot complete with trickery, disguise, and love. Each character is defined not by his or her gender or true identity, but by the role they are forced to take because of the complicated situation that arises. Unlike their gender, the speech the characters give an insight to their true personalities. In the Twelfth Night, the character Duke Orsino uses flowery and over-dramatic language, long poetic sentence structure, and melodramatic metaphors to display his overemotional romantic nature despite the different emotions in his various speeches. Duke Orsino’s repeated usage of poetical verse and poetic devices to describe his woes from love set him apart from other character. By using deep metaphorical language and flowing poetic structure, Shakespeare conveys Orsino’s melodramatic nature. In Orsino’s first speech, he takes a complicated and metaphorical approach to explain his love for Olivia instead of directly stating his desires. Instead of using prose, Orsino speaks in blank verse which is significantly fancier and floral in language. He says, â€Å"If music be the food of love, play on; /Give me excess of it, that, surfeiting, /The appetite may sicken, and so die† (1.1 3-5) to compare his love for Olivia to his love of music. Orsino wants the â€Å"excess of it†, so that he can become bored of music and therefore his love for Olivia. This also shows that he is excessively wordy throughout his speech and often prolongs sentences with repetitive phrases such as â€Å"†¦,pla y on/Give me excess of it, that, surfeiting† (1.1.3-4) and â€Å"†¦may sicken, and so die† (1.1.5) that have the same meaning. His long-winded language illustrates the dramatic quality... ...ve./To spite a raven’s heart within a dove† (5.1.130-131), to finally summarize his long speech. Orsino uses metaphors to compare the lamb to Viola and the dove to Olivia. Viola is the gentle lamb that Orsino claims he will sacrifice in order to attain revenge against Olivia, a deceivingly beautiful dove with a dark heart. By using a metaphor to end his speech, Orsino exits with a more dramatic and profound flair than if he directly stated his plans to kill Viola. Despite the anger in the speech in Act 5, Orsino uses similar poetic techniques such as metaphors, repetition, and flowery language to convey his dramatic nature. These techniques often convolute the original meaning of Orsino’s words because of the metaphorical structure. It is however the same traits that put him aside other characters in the play and make Orsino memorable to the audience.

Payroll Basics in Sap

Payroll Basics (PY-XX-BS)  PurposeThe Payroll is based on an international payroll driver. This payroll driver was modified for each country. The country-specific payroll drivers take the statutory and administrative regulations of a country into account. Since the payroll driver has a modular structure, you can use the Customizing functions to quickly modify the payroll procedure to meet the particular requirements of your enterprise. Process FlowWhen you access Payroll, the payroll driver calls the accompanying payroll schema, which consists of a sequence of functions.For each activity, the individual functions import data from internal tables and payroll relevant files. Payroll is then performed as follows:ResultAfter the payroll run, you can transfer the payroll results to Financial Accounting, or perform evaluations and create lists and statistics. **************************************************************************************************************Payroll Driver  De finitionProgram you use to run payroll.StructureFor each Payroll country version there is a country-specific payroll driver with the technical name RPCALCx0 or HxxCALC0: * For programs with the technical name RPCALCx0, the x is replaced with a country indicator, for example, D for Germany, F for France, or X for â€Å"Other countries†. * For programs with the technical name HxxCALC0, the xx is replaced with the ISO code of the respective country, for example MX for Mexico, or ID for Indonesia.The program RPCALCX0 (Payroll driver international) contains no data about tax and social insurance regulations for net remuneration calculation. The other payroll drivers contain this data. IntegrationA relevant country-specific personnel calculation schema, in which personnel caclulation rules and functions are stored, contain the steps that a payroll driver should perform during payroll. All data is stored in internal tables and saved in payroll-relevant files. *********************** *******************************************************Payroll Schema  DefinitionThe payroll schema contains calculation rules to be used by the payroll driver during payroll. SAP has developed country-specific schemas which are based on schema X000. With country-specific reports, the first character in the name refers to the country indicator (for example, D for Germany, F for France). StructureA schema consists of the following parts: * Initialization The system performs the following steps: * Updates the databases * Imports equired infotypes * Gross calculation of pay The system performs the following steps: * Processes basic data and time data * Queries off-cycle payroll runs * Reads payroll account of the last period accounted * Processes time data and calculates the individual gross values * Performs factoring * Net calculation of pay The system performs the following steps: * Calculates net remuneration * Performs bank transfersIntegrationAll data is stored in internal tabl es and saved in files with a cluster structure. ***************************************************************************************************************Payroll Relevant Files  DefinitionPayroll files contain data for payroll and payroll results. StructureThe system requires the following files for payroll: * Pnnnn (nnnn = number of the infotype) The Pnnnn files contain data that has been entered in the respective infotypes for an employee. * PCL1 The PCL1 file contains primary information, in other words, data from the master data and time recording systems. PCL2 The PCL2 file contains secondary information, in other words, derived data and all generated schemas. IntegrationWhen you start payroll, the system imports the relevant master data from the Pnnn files (for example, basic pay and tax class) and imports the time data from the PCL1 file to the IT table. The system imports the payroll results from the previous month from table ORT (for example, to form averages). The s ystem processes this data and saves the payroll results and generated schemas in the PLC2 file. *****************************************************************************************************Internal Tables for Payroll  DefinitionTables that are used for storing data during the payroll run. UseWithin Payroll, data is processed in internal tables that the system fills and reads during the payroll run. The system also changes the data in these tables during the payroll run. The results of processing are then available for other steps. The read and change access to these tables is enabled using functions that are executed in a personnel calculation schema and using operations that are executed in personnel calculation rules.StructureThe following are some of the tables used in all country versions for Payroll:Internal Tables for Payroll Table| Short text| Description| WPBP| Work Place/Basic Pay| Table WPBP is filled by the infotypes Actions (0000), Organizational Assignment (00 01), Planned Working Time (0007), Basic Pay (0008), and Cost Distribution (0027). It contains important organizational and payment-relevant data, and different partial period parameters. For more information on table WBPB, see Payment-Relevant Information in the Payroll Result. | RT| Results Table| Table RT contains the result wage types of the current period for which payroll is run.Data is transferred from table IT to table RT using the operation ADDWTE. | CRT| Cumulative Results Table| Table CRT contains the cumulations of wage types in table RT over a certain time period. | BT| Payment Information| Every entry in the Bank Transactions table (BT) of an employee, corresponds to a payment that was created in a payroll period for this employee. However, the employee is not necessarily the payment recipient of all payments. For more information on table BT, see Payment-Relevant Information in the Payroll Result. C0| Cost Distribution| Table C0 contains global information about the co st distribution for wage types. Certain costs can be distributed to other cost centers than the master cost center. The information is taken from the Cost Distribution infotype (0027). | C1| Cost Assignment from Different Infotypes| Table C1 contains information about the individual cost assignment for individual wage types. You can use the infotype Recurring Payments/Deductions (0014) and Additional Payments (0015) to assign the wage types to a cost center that is different to the employee's master cost center. V0| Variable Assignment| Table V0 contains various additional information about the wage types. | GRT| Output Table from Gross Part| Table GRT is table RT according to the gross amount in a split payroll schema. | ARRRS| Arrears| Table ARRRS contains deductions that could not be taken and so are transferred to the following period. | DDNTK| Deductions not taken| Table DDNTK contains deductions that could not be taken in the current period. | ACCR| Month End Accruals| Table A CCR contains special information on a posting period assignment for month end accruals. BENTAB| Benefits| Table BENTAB contains cumulations for certain benefits plans. | FUND| Financing| Table FUND contains information about fund commitments. This information is taken from HR Funds and Position Management. | AVERAGE| Frozen Averages| Table AVERAGE contains information about frozen averages. | MODIF| Modifiers| Table MODIF contains various modifiers that can be used as additional keys for access to Customizing tables. The system sets the modifiers in payroll with the function MOD (Determine Employee Groupings) and operation MODIF (Set Employee Groupings). VERSION| Information on Creation| Table VERSION contains creation data for the payroll result, for example the Release and payroll program. | PCL2| Update Information PCL2| Table PCL2 contains information about the last change access to a payroll result. | VERSC| Payroll Status Information| Table VERSC contains organizational inform ation about the payroll result. | STATUS| Status Indicator| Table STATUS contains eight different status indicators. | The system exports the data in these tables at the end of payroll processing in cluster tables in table PCL2 (RP cluster 2) using function EXPRT.The cluster tables are in a country-specific cluster, for example RD (Payroll result, Germany), on the database. In this way, the data is available for other processing steps, for example, evaluation. Other internal tables are not exported after the payroll run but are deleted, since they are only required during the payroll run. Internal tables for Payroll that are not exported Table| Short text| Description| IT| Input Table| During the payroll run table IT is filled with data that is to be processed. Data is transferred to table RT using operation ADDWTE.Table IT must be empty by the end of the payroll run or the personnel number is rejected. This is checked with the personnel calculation rule X070 (Cancel, if table is no t empty). | OT| Output Table| Table OT only exists temporarily during processing. If a personnel calculation rule is called using the PIT function, a loop is performed for wage types from table IT. The results are written to table OT using the operation ADDWT. At the end of the loop, table IT is restructured from table OT. | DT| Difference Table| Table DT is used to transfer retroactive accounting differences within retroactive chains. ORT| Old Results Table| Table ORT is table RT from the last payroll result (usually from the previous payroll period). Tables LRT and VORT are also formed from table ORT. | LRT| Last Results Table| Table LRT is table RT from the last payroll result (usually from the previous payroll period). It is formed from table ORT but only contains the wage types that are relevant to the current period and required often. This is controlled using personnel calculation rule X006, which reads processing class 06. | VORT| Summarized ORT| Table VORT is a version of t able ORT in which certain splits are eliminated. |

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