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Land is an asset in today’s era of development. A patch of land’s management must be planned so that its utilization can be done proportionally and professionally. The Special Region of Yogyakarta, namely Gunung Kidul Regency, has yet to have a reliable base map with high accuracy for each patch of land within its area, which results in the hampering of land use due to the lack of spatial information available. The lack of clear status and spatial information is felt by UPN “Veteran” Yogyakarta that has several patches of land in Gunung Kidul Regency, namely Kuwon Kidul, Pacarejo, Semanu, Gunung Kidul Regency. This research will create a base map scaled to 1:500 accompanied with information about height differences of said area and a recommended planning area considering three different aspects: geology, environment, and agriculture. The creation of a topographic map is useful for construction planning that will be conducted in the area. During this research, the topographic measurement and data processing were done in 11 days on field. The topographic measurement and data processing were conducted through five stages: initial survey, GNSS measurement, detail measurement, and data processing using software to produce a topographic map. The map result and measurement on field using Total Station showed that UPN “Veteran” Yogyakarta does not have a level surface and has good data density.

Pada setiap tahun pemerintah selalu menaikkan upah minimum kota maupun provinsi, ketentuan kenaikan upah minimum ini didasarkan pada UU Ketenagakerjaan No. 13 Tahun 2003, penentuan upah minimum ini bertujuan untuk memenuhi kebutuhan hidup yang layak bagi masyarakat. Masing-masing Kota/Kabupaten memiliki upah minimumnya tersendiri. Kenaikan upah minimum berdasarkan pertumbuhan ekonomi dan inflasi. Namun, pertumbuhan upah minimum ini membuat masyarakat merasa upah yang diberikan oleh pemerintah jawa timur hal ini dibuktikan dengan aksi unjuk rasa yang dilakukan oleh serikat buruh pada tanggal 20 November 2019 di depan Kantor Gubernur Jawa Timur jalan Pahlawan Surabaya. Saat ini hanya ada metode penelitian survei yang meneliti mengenai survei biaya hidup dan kenaikan Upah Minimum Kota yang dilakukan oleh BPS (Badan Pusat Statistik). Penulis bertujuan membuat Sistem Informasi Geografis yang menampilkan UMK dan biaya kebutuhan hidup berdasarkan kategori Kota dan Kabupaten. Sehingga dengan adanya Sistem Informasi Geografis ini, pengguna dalam hal ini masyarakat dengan mudah dapat melihat data berdasarkan grafis dari peta Kabupatan dan Kota di Provinsi Jawa Timur, dalam Sistem Informasi Geografis tersebut sehingga dengan melihat data peta yang ditampilkan didalam Sistem Informasi Geografis. Hasil pengujian Fungsional 100% sudah berjalan sesuai dengan kebutuhan aplikasi. Hasil pengujian fungsional pada perangkat Desktop menunjukkan hasil 100 % sesuai. Hasil pengujian fungsional pada perangkat mobile menunjukkan hasil 100 % dibuktikan dengan tata letak tampilan yang sesuai. Kata Kunci : UMK, SBH, WebGIS, Leaflet, Jawa Timur, SIG, GeoJSON

Discrimination statistics describe the ability of a survival model to assign higher risks to individuals who experience earlier events: examples are Harrell's C-index and Royston and Sauerbrei's D, which we call the D-index. Prognostic covariates whose distributions are controlled by the study design (e.g. age and sex) influence discrimination and can make it difficult to compare model discrimination between studies. Although covariate adjustment is a standard procedure for quantifying disease-risk factor associations, there are no covariate adjustment methods for discrimination statistics in censored survival data.To develop extensions of the C-index and D-index that describe the prognostic ability of a model adjusted for one or more covariate(s).We define a covariate-adjusted C-index and D-index for censored survival data, propose several estimators, and investigate their performance in simulation studies and in data from a large individual participant data meta-analysis, the Emerging Risk Factors Collaboration.The proposed methods perform well in simulations. In the Emerging Risk Factors Collaboration data, the age-adjusted C-index and D-index were substantially smaller than unadjusted values. The study-specific standard deviation of baseline age was strongly associated with the unadjusted C-index and D-index but not significantly associated with the age-adjusted indices.The proposed estimators improve meta-analysis comparisons, are easy to implement and give a more meaningful clinical interpretation.? 2014 The Author. Biometrical Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Many abstracts of diagnostic accuracy studies are currently insufficiently informative. We extended the STARD (Standards for Reporting Diagnostic Accuracy) statement by developing a list of essential items that authors should consider when reporting diagnostic accuracy studies in journal or conference abstracts. After a literature review of published guidance for reporting biomedical studies, we identified 39 items potentially relevant to report in an abstract. We then selected essential items through a two round web based survey among the 85 members of the STARD Group, followed by discussions within an executive committee. Seventy three STARD Group members responded (86%), with 100% completion rate. STARD for Abstracts is a list of 11 quintessential items, to be reported in every abstract of a diagnostic accuracy study. We provide examples of complete reporting, and developed template text for writing informative abstracts.

AIMSTo critically evaluate the clinical implications of the use of non-fasting rather than fasting lipid profiles and to provide guidance for the laboratory reporting of abnormal non-fasting or fasting lipid profiles.METHODS AND RESULTSExtensive observational data, in which random non-fasting lipid profiles have been compared with those determined under fasting conditions, indicate that the maximal mean changes at 1–6 h after habitual meals are not clinically significant [+0.3 mmol/L (26 mg/dL) for triglycerides; −0.2 mmol/L (8 mg/dL) for total cholesterol; −0.2 mmol/L (8 mg/dL) for LDL cholesterol; +0.2 mmol/L (8 mg/dL) for calculated remnant cholesterol; −0.2 mmol/L (8 mg/dL) for calculated non-HDL cholesterol]; concentrations of HDL cholesterol, apolipoprotein A1, apolipoprotein B, and lipoprotein(a) are not affected by fasting/non-fasting status. In addition, non-fasting and fasting concentrations vary similarly over time and are comparable in the prediction of cardiovascular disease. To improve patient compliance with lipid testing, we therefore recommend the routine use of non-fasting lipid profiles, whereas fasting sampling may be considered when non-fasting triglycerides are >5 mmol/L (440 mg/dL). For non-fasting samples, laboratory reports should flag abnormal concentrations as triglycerides ≥2 mmol/L (175 mg/dL), total cholesterol ≥5 mmol/L (190 mg/dL), LDL cholesterol ≥3 mmol/L (115 mg/dL), calculated remnant cholesterol ≥0.9 mmol/L (35 mg/dL), calculated non-HDL cholesterol ≥3.9 mmol/L (150 mg/dL), HDL cholesterol ≤1 mmol/L (40 mg/dL), apolipoprotein A1 ≤1.25 g/L (125 mg/dL), apolipoprotein B ≥1.0 g/L (100 mg/dL), and lipoprotein(a) ≥50 mg/dL (80th percentile); for fasting samples, abnormal concentrations correspond to triglycerides ≥1.7 mmol/L (150 mg/dL). Life-threatening concentrations require separate referral for the risk of pancreatitis when triglycerides are >10 mmol/L (880 mg/dL), for homozygous familial hypercholesterolemia when LDL cholesterol is >13 mmol/L (500 mg/dL), for heterozygous familial hypercholesterolemia when LDL cholesterol is >5 mmol/L (190 mg/dL), and for very high cardiovascular risk when lipoprotein(a) >150 mg/dL (99th percentile).CONCLUSIONSWe recommend that non-fasting blood samples be routinely used for the assessment of plasma lipid profiles. Laboratory reports should flag abnormal values on the basis of desirable concentration cutpoints. Non-fasting and fasting measurements should be complementary but not mutually exclusive.

Aims To critically evaluate the clinical implications of the use of non-fasting rather than fasting lipid profiles and to provide guidance for the laboratory reporting of abnormal non-fasting or fasting lipid profiles. Methods and results Extensive observational data, in which random non-fasting lipid profiles have been compared with those determined under fasting conditions, indicate that the maximal mean changes at 1–6 h after habitual meals are not clinically significant [+0.3 mmol/L (26 mg/dL) for triglycerides; −0.2 mmol/L (8 mg/dL) for total cholesterol; −0.2 mmol/L (8 mg/dL) for LDL cholesterol; +0.2 mmol/L (8 mg/dL) for calculated remnant cholesterol; −0.2 mmol/L (8 mg/dL) for calculated non-HDL cholesterol]; concentrations of HDL cholesterol, apolipoprotein A1, apolipoprotein B, and lipoprotein(a) are not affected by fasting/non-fasting status. In addition, non-fasting and fasting concentrations vary similarly over time and are comparable in the prediction of cardiovascular disease. To improve patient compliance with lipid testing, we therefore recommend the routine use of non-fasting lipid profiles, while fasting sampling may be considered when non-fasting triglycerides >5 mmol/L (440 mg/dL). For non-fasting samples, laboratory reports should flag abnormal concentrations as triglycerides ≥2 mmol/L (175 mg/dL), total cholesterol ≥5 mmol/L (190 mg/dL), LDL cholesterol ≥3 mmol/L (115 mg/dL), calculated remnant cholesterol ≥0.9 mmol/L (35 mg/dL), calculated non-HDL cholesterol ≥3.9 mmol/L (150 mg/dL), HDL cholesterol ≤1 mmol/L (40 mg/dL), apolipoprotein A1 ≤1.25 g/L (125 mg/dL), apolipoprotein B ≥1.0 g/L (100 mg/dL), and lipoprotein(a) ≥50 mg/dL (80th percentile); for fasting samples, abnormal concentrations correspond to triglycerides ≥1.7 mmol/L (150 mg/dL). Life-threatening concentrations require separate referral when triglycerides >10 mmol/L (880 mg/dL) for the risk of pancreatitis, LDL cholesterol >13 mmol/L (500 mg/dL) for homozygous familial hypercholesterolaemia, LDL cholesterol >5 mmol/L (190 mg/dL) for heterozygous familial hypercholesterolaemia, and lipoprotein(a) >150 mg/dL (99th percentile) for very high cardiovascular risk. Conclusion We recommend that non-fasting blood samples be routinely used for the assessment of plasma lipid profiles. Laboratory reports should flag abnormal values on the basis of desirable concentration cut-points. Non-fasting and fasting measurements should be complementary but not mutually exclusive., published version, peerReviewed

Incomplete reporting has been identified as a major source of avoidable waste in biomedical research. Essential information is often not provided in study reports, impeding the identification, critical appraisal, and replication of studies. To improve the quality of reporting of diagnostic accuracy studies, the Standards for Reporting of Diagnostic Accuracy Studies (STARD) statement was developed. Here we present STARD 2015, an updated list of 30 essential items that should be included in every report of a diagnostic accuracy study. This update incorporates recent evidence about sources of bias and variability in diagnostic accuracy and is intended to facilitate the use of STARD. As such, STARD 2015 may help to improve completeness and transparency in reporting of diagnostic accuracy studies.

This paper was presented at the 4th Micro and Nano Flows Conference (MNF2014), which was held at University College, London, UK. The conference was organised by Brunel University and supported by the Italian Union of Thermofluiddynamics, IPEM, the Process Intensification Network, the Institution of Mechanical Engineers, the Heat Transfer Society, HEXAG - the Heat Exchange Action Group, and the Energy Institute, ASME Press, LCN London Centre for Nanotechnology, UCL University College London, UCL Engineering, the International NanoScience Community, www.nanopaprika.eu. The various flow regimes prevalent during gold-palladium catalyzed benzyl alcohol oxidation in a micro-packed bed reactor and their influence on reaction performance are identified. The reaction is studied in a 300μm deep x 600μm wide silicon-glass micro-structured reactor packed with 65μm catalyst particles at a temperature of 120°C, pressure of 1 bar (g), using pure oxygen and neat benzyl alcohol as the feed. Significant improvement in the conversion and selectivity to the main product, benzaldehyde, is observed with increasing gas flowrate and decreasing liquid flowrate, which coincides with a change in the flow pattern from “liquid-dominated slug” (segregated regions of liquid and gas slugs) to “gas-continuous trickle” (thin film coated catalyst particles with gas flowing through the voids). The latter flow regime results in enhanced external mass transfer due to an increase in the available interfacial area and shorter diffusional distances. Results show selectivity up to 81% at a catalyst space time of 76 gcatgalc(-1).s, outperforming a conventional batch laboratory reactor.

C-reactive protein is an acute phase protein and an established marker for detection, risk stratification, and monitoring of infections and inflammatory and necrotic processes. Because C-reactive protein is sensitive but not specific, its values must be interpreted in the clinical context. In patients with acute myocardial infarction (AMI), C-reactive protein increases within 4–6 h of symptoms, peaks 2–4 days later, and returns to baseline after 7–10 days.1 C-reactive protein has gained interest recently as a marker for risk stratification in acute coronary syndrome (ACS) when measured by high-sensitivity C-reactive protein assays. These assays have greater analytical sensitivity and reliably measure C-reactive protein concentrations within the reference range with low imprecision (5–10%).2 Because of evidence that atherosclerosis is an inflammatory disease, high-sensitivity C-reactive protein can be used as a biomarker of risk in primary prevention and in patients with known cardiovascular disease.3 The aim of this review is to evaluate the use of C-reactive protein in patients with acute coronary disease. C-reactive protein is a non-specific first-line host defence mechanism.4 With stimulation by cytokines (e.g. interleukins and tumour necrosis factor-alpha), C-reactive protein synthesis in hepatocytes occurs within 4–6 h. Concentrations can rise 1000-fold or more over 24–48 h. C-reactive protein has been detected in atherosclerotic plaques; its possible role in atherosclerogenesis is summarized in Figure 1 , but is still a matter of debate.5 Genetic variants account for 35–40% of the variability in high-sensitivity C-reactive protein.6 Figure 1 Possible pathophysiological effects of C-reactive protein in atherosclerosis. Aggregated C-reactive protein selectively binds LDL and VLDL in serum, thereby potentially participating in the mechanisms involved in plaque formation and destabilization, and shows some of the key properties of antibodies and may contribute to immune responses by activation of antigen presenting cells. Procoagulant effects have been reported in vitro as …