Edukasi asuransi kesehatan pada remaja pranikah desa donorojo, Kabupaten Magelang

Health checks before marriage are carried out to find out how the health condition of the prospective bride and groom. in preventing health problems in oneself, spouse and offspring in order to build a good and prosperous family. Health Insurance is a protection that should be owned when married, insurance provides benefits to free participants from the difficulty of providing cash data, health costs that can be monitored and the availability of health data with health insurance, families will get optimal care when sick or postpartum so that prospective fathers and mothers are not burdened with large medical expenses. Health insurance has several benefits for its users, namely as health savings, easing the burden and a comfortable and peaceful life. The types of health insurance are seen from the fund managers, namely the government and private fund managers (premi) managed by private companies. Keywords — Premarital Preparation; Insurance Health; BPJS;   Abstrak— Pemeriksaan kesehatan sebelum menikah dilakukan untuk mengetahui bagaimana kondisis kesehatan calon pengantin. dalam mencegah terjadinya masalah kesehatan pada diri sendiri, pasangan dan keturunan agar terbangun keluarga baik dan sejahtera. Asuransi Kesehatan merupakan perlindungan yang patut dimiliki ketika sudah berkeluarga, asuransi memberikan manfaat untuk membebaskan peserta dari kesulitan penyediaan data tunai, biaya kesehatan yang dapat diawasi dan tersedianya data kesehatan dengan adanya asuransi kesehatan, keluarga akan mendapatkan perawatan yang optimal ketika sakit maupun pasca melahirkan sehingga calon ayah dan ibu tidak terbebani dengan biaya pengobatan yang jumlahnya besar. Asuransi kesehatan terdapat beberapa manfaat bagi penggunanya yaitu sebagai tabungan kesehatan, Meringankan beban dan hidup yang nyaman dan tentram. Jenis-jenis asuransi kesehatan dilihat dari pengelola dana yaitu pemerintah dan swasta pengelola dana (premi) yang dikelola oleh perusahaan swasta Kata Kunci— Pranikah; Asuransi Kesehatan; BPJS;).

Interactive Effect of Learning Rate and Batch Size to Implement Transfer Learning for Brain Tumor Classification

For classifying brain tumors with small datasets, the knowledge-based transfer learning (KBTL) approach has performed very well in attaining an optimized classification model. However, its successful implementation is typically affected by different hyperparameters, specifically the learning rate (LR), batch size (BS), and their joint influence. In general, most of the existing research could not achieve the desired performance because the work addressed only one hyperparameter tuning. This study adopted a Cartesian product matrix-based approach, to interpret the effect of both hyperparameters and their interaction on the performance of models. To evaluate their impact, 56 two-tuple hyperparameters from the Cartesian product matrix were used as inputs to perform an extensive exercise, comprising 504 simulations for three cutting-edge architecture-based pre-trained Deep Learning (DL) models, ResNet18, ResNet50, and ResNet101. Additionally, the impact was also assessed by using three well-known optimizers (solvers): SGDM, Adam, and RMSProp. The performance assessment showed that the framework is an efficient framework to attain optimal values of two important hyperparameters (LR and BS) and consequently an optimized model with an accuracy of 99.56%. Further, our results showed that both hyperparameters have a significant impact individually as well as interactively, with a trade-off in between. Further, the evaluation space was extended by using the statistical ANOVA analysis to validate the main findings. F-test returned with p < 0.05, confirming that both hyperparameters not only have a significant impact on the model performance independently, but that there exists an interaction between the hyperparameters for a combination of their levels

Model-assisted metabolic engineering of Escherichia coli for long chain alkane and alcohol production

Biologically-derived hydrocarbons are considered to have great potential as next-generation biofuels owing to the similarity of their chemical properties to contemporary diesel and jet fuels. However, the low yield of these hydrocarbons in biotechnological production is a major obstacle for commercialization. Several genetic and process engineering approaches have been adopted to increase the yield of hydrocarbon, but a model driven approach has not been implemented so far. Here, we applied a constraint-based metabolic modeling approach in which a variable demand for alkane biosynthesis was imposed, and co-varying reactions were considered as potential targets for further engineering of an E. coli strain already expressing cyanobacterial enzymes towards higher chain alkane production. The reactions that co-varied with the imposed alkane production were found to be mainly associated with the pentose phosphate pathway (PPP) and the lower half of glycolysis. An optimal modeling solution was achieved by imposing increased flux through the reaction catalyzed by glucose-6-phosphate dehydrogenase (zwf) and iteratively removing 7 reactions from the network, leading to an alkane yield of 94.2% of the theoretical maximum conversion determined by in silico analysis at a given biomass rate. To validate the in silico findings, we first performed pathway optimization of the cyanobacterial enzymes in E. coli via different dosages of genes, promoting substrate channelling through protein fusion and inducing substantial equivalent protein expression, which led to a 36-fold increase in alka(e)ne production from 2.8 mg/L to 102 mg/L. Further, engineering of E. coli based on in silico findings, including biomass constraint, led to an increase in the alka(e)ne titer to 425 mg/L (major components being 249 mg/L pentadecane and 160 mg/L heptadecene), a 148.6-fold improvement over the initial strain, respectively; with a yield of 34.2% of the theoretical maximum. The impact of model-assisted engineering was also tested for the production of long chain fatty alcohol, another commercially important molecule sharing the same pathway while differing only at the terminal reaction, and a titer of 1506 mg/L was achieved with a yield of 86.4% of the theoretical maximum. Moreover, the model assisted engineered strains had produced 2.54 g/L and 12.5 g/L of long chain alkane and fatty alcohol, respectively, in the bioreactor under fed-batch cultivation condition. Our study demonstrated successful implementation of a combined in silico modeling approach along with the pathway and process optimization in achieving the highest reported titers of long chain hydrocarbons in E. coli

A genetic toolbox for metabolic engineering of Issatchenkia orientalis

The nonconventional yeast Issatchenkia orientalis can grow under highly acidic conditions and has been explored for production of various organic acids. However, its broader application is hampered by the lack of efficient genetic tools to enable sophisticated metabolic manipulations. We recently constructed an episomal plasmid based on the autonomously replicating sequence (ARS) from Saccharomyces cerevisiae (ScARS) in I. orientalis and developed a CRISPR/Cas9 system for multiplex gene deletions. Here we report three additional genetic tools including: (1) identification of a 0.8 kb centromere-like (CEN-L) sequence from the I. orientalis genome by using bioinformatics and functional screening; (2) discovery and characterization of a set of constitutive promoters and terminators under different culture conditions by using RNA-Seq analysis and a fluorescent reporter; and (3) development of a rapid and efficient in vivo DNA assembly method in I. orientalis, which exhibited ∼100% fidelity when assembling a 7 kb-plasmid from seven DNA fragments ranging from 0.7 kb to 1.7 kb. As proof of concept, we used these genetic tools to rapidly construct a functional xylose utilization pathway in I. orientalis

The Changing Landscape for Stroke\ua0Prevention in AF: Findings From the GLORIA-AF Registry Phase 2

Background GLORIA-AF (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients with Atrial Fibrillation) is a prospective, global registry program describing antithrombotic treatment patterns in patients with newly diagnosed nonvalvular atrial fibrillation at risk of stroke. Phase 2 began when dabigatran, the first non\u2013vitamin K antagonist oral anticoagulant (NOAC), became available. Objectives This study sought to describe phase 2 baseline data and compare these with the pre-NOAC era collected during phase&nbsp;1. Methods During phase 2, 15,641 consenting patients were enrolled (November 2011 to December 2014); 15,092 were eligible. This pre-specified cross-sectional analysis describes eligible patients\u2019 baseline characteristics. Atrial fibrillation&nbsp;disease characteristics, medical outcomes, and concomitant diseases and medications were collected. Data were analyzed using descriptive statistics. Results Of the total patients, 45.5% were female; median age was 71 (interquartile range: 64, 78) years. Patients were from Europe (47.1%), North America (22.5%), Asia (20.3%), Latin America (6.0%), and the Middle East/Africa (4.0%). Most had high stroke risk (CHA2DS2-VASc [Congestive heart failure, Hypertension, Age&nbsp; 6575 years, Diabetes mellitus, previous Stroke, Vascular disease, Age 65 to 74 years, Sex category] score&nbsp; 652; 86.1%); 13.9% had moderate risk (CHA2DS2-VASc&nbsp;= 1). Overall, 79.9% received oral anticoagulants, of whom 47.6% received NOAC and 32.3% vitamin K antagonists (VKA); 12.1% received antiplatelet agents; 7.8% received no antithrombotic treatment. For comparison, the proportion of phase 1 patients (of N&nbsp;= 1,063 all eligible) prescribed VKA was 32.8%, acetylsalicylic acid 41.7%, and no therapy 20.2%. In Europe in phase 2, treatment with NOAC was more common than VKA (52.3% and 37.8%, respectively); 6.0% of patients received antiplatelet treatment; and 3.8% received no antithrombotic treatment. In North America, 52.1%, 26.2%, and 14.0% of patients received NOAC, VKA, and antiplatelet drugs, respectively; 7.5% received no antithrombotic treatment. NOAC use was less common in Asia (27.7%), where 27.5% of patients received VKA, 25.0% antiplatelet drugs, and 19.8% no antithrombotic treatment. Conclusions The baseline data from GLORIA-AF phase 2 demonstrate that in newly diagnosed nonvalvular atrial fibrillation patients, NOAC have been highly adopted into practice, becoming more frequently prescribed than VKA in&nbsp;Europe and North America. Worldwide, however, a large proportion of patients remain undertreated, particularly in&nbsp;Asia&nbsp;and North America. (Global Registry on Long-Term Oral Antithrombotic Treatment in Patients With Atrial Fibrillation [GLORIA-AF]; NCT01468701

Mortality from gastrointestinal congenital anomalies at 264 hospitals in 74 low-income, middle-income, and high-income countries: a multicentre, international, prospective cohort study

Summary Background Congenital anomalies are the fifth leading cause of mortality in children younger than 5 years globally. Many gastrointestinal congenital anomalies are fatal without timely access to neonatal surgical care, but few studies have been done on these conditions in low-income and middle-income countries (LMICs). We compared outcomes of the seven most common gastrointestinal congenital anomalies in low-income, middle-income, and high-income countries globally, and identified factors associated with mortality. Methods We did a multicentre, international prospective cohort study of patients younger than 16 years, presenting to hospital for the first time with oesophageal atresia, congenital diaphragmatic hernia, intestinal atresia, gastroschisis, exomphalos, anorectal malformation, and Hirschsprung’s disease. Recruitment was of consecutive patients for a minimum of 1 month between October, 2018, and April, 2019. We collected data on patient demographics, clinical status, interventions, and outcomes using the REDCap platform. Patients were followed up for 30 days after primary intervention, or 30 days after admission if they did not receive an intervention. The primary outcome was all-cause, in-hospital mortality for all conditions combined and each condition individually, stratified by country income status. We did a complete case analysis. Findings We included 3849 patients with 3975 study conditions (560 with oesophageal atresia, 448 with congenital diaphragmatic hernia, 681 with intestinal atresia, 453 with gastroschisis, 325 with exomphalos, 991 with anorectal malformation, and 517 with Hirschsprung’s disease) from 264 hospitals (89 in high-income countries, 166 in middleincome countries, and nine in low-income countries) in 74 countries. Of the 3849 patients, 2231 (58·0%) were male. Median gestational age at birth was 38 weeks (IQR 36–39) and median bodyweight at presentation was 2·8 kg (2·3–3·3). Mortality among all patients was 37 (39·8%) of 93 in low-income countries, 583 (20·4%) of 2860 in middle-income countries, and 50 (5·6%) of 896 in high-income countries (p<0·0001 between all country income groups). Gastroschisis had the greatest difference in mortality between country income strata (nine [90·0%] of ten in lowincome countries, 97 [31·9%] of 304 in middle-income countries, and two [1·4%] of 139 in high-income countries; p≤0·0001 between all country income groups). Factors significantly associated with higher mortality for all patients combined included country income status (low-income vs high-income countries, risk ratio 2·78 [95% CI 1·88–4·11], p<0·0001; middle-income vs high-income countries, 2·11 [1·59–2·79], p<0·0001), sepsis at presentation (1·20 [1·04–1·40], p=0·016), higher American Society of Anesthesiologists (ASA) score at primary intervention (ASA 4–5 vs ASA 1–2, 1·82 [1·40–2·35], p<0·0001; ASA 3 vs ASA 1–2, 1·58, [1·30–1·92], p<0·0001]), surgical safety checklist not used (1·39 [1·02–1·90], p=0·035), and ventilation or parenteral nutrition unavailable when needed (ventilation 1·96, [1·41–2·71], p=0·0001; parenteral nutrition 1·35, [1·05–1·74], p=0·018). Administration of parenteral nutrition (0·61, [0·47–0·79], p=0·0002) and use of a peripherally inserted central catheter (0·65 [0·50–0·86], p=0·0024) or percutaneous central line (0·69 [0·48–1·00], p=0·049) were associated with lower mortality. Interpretation Unacceptable differences in mortality exist for gastrointestinal congenital anomalies between lowincome, middle-income, and high-income countries. Improving access to quality neonatal surgical care in LMICs will be vital to achieve Sustainable Development Goal 3.2 of ending preventable deaths in neonates and children younger than 5 years by 2030

Interactive Effect of Learning Rate and Batch Size to Implement Transfer Learning for Brain Tumor Classification

For classifying brain tumors with small datasets, the knowledge-based transfer learning (KBTL) approach has performed very well in attaining an optimized classification model. However, its successful implementation is typically affected by different hyperparameters, specifically the learning rate (LR), batch size (BS), and their joint influence. In general, most of the existing research could not achieve the desired performance because the work addressed only one hyperparameter tuning. This study adopted a Cartesian product matrix-based approach, to interpret the effect of both hyperparameters and their interaction on the performance of models. To evaluate their impact, 56 two-tuple hyperparameters from the Cartesian product matrix were used as inputs to perform an extensive exercise, comprising 504 simulations for three cutting-edge architecture-based pre-trained Deep Learning (DL) models, ResNet18, ResNet50, and ResNet101. Additionally, the impact was also assessed by using three well-known optimizers (solvers): SGDM, Adam, and RMSProp. The performance assessment showed that the framework is an efficient framework to attain optimal values of two important hyperparameters (LR and BS) and consequently an optimized model with an accuracy of 99.56%. Further, our results showed that both hyperparameters have a significant impact individually as well as interactively, with a trade-off in between. Further, the evaluation space was extended by using the statistical ANOVA analysis to validate the main findings. F-test returned with p < 0.05, confirming that both hyperparameters not only have a significant impact on the model performance independently, but that there exists an interaction between the hyperparameters for a combination of their levels

Mountain Gazelle Algorithm-Based Optimal Control Strategy for Improving LVRT Capability of Grid-Tied Wind Power Stations

The large-scale wind energy conversion systems (WECS) based on a doubly fed induction generator (DFIG) have recently gained attention due to their numerous economic and technological advantages. However, the rapid integration of WECS with standing power networks severely influenced the system&#x2019;s reliability and stability; also, the DFIG rotor circuit experiences a substantial overcurrent due to grid voltage fluctuations. Indeed, these problems emphasize the significance of a DFIG&#x2019;s low-voltage ride-through (LVRT) capacity in maintaining the stability of the electrical grid during voltage fluctuations. To solve these challenges simultaneously, this research employs a metaheuristic optimization technique to regulate a doubly fed induction generator&#x2019;s (DFIG) operation via a wind turbine (WT) system. The article proposes a novel Mountain Gazelle Optimizer (MGO) to optimize the proportional-integral (PI) controller gains for the DFIG system&#x2019;s active and reactive power control to enhance the LVRT capability of Wind turbines linked to the power grid. In the proposed scheme, LVRT improvement is proportional to undershoot or overshoot, settlement time, and steady-state inaccuracy of voltage responses. The proposed control method is implemented in MATLAB by a detailed model of 9MW wind turbine, and its performance is validated and compared with traditional optimization control approaches. The suggested MGO method&#x2019;s efficacy is demonstrated by the assessment and comparison to classic optimization-based PI controllers under various fault scenarios. The simulation results show that the optimized control method improved performance in terms of three-phase terminal voltage output responses, active power, reactive power demand to networks, and DC-Link voltage

Engineered Production of Short Chain Fatty Acid in <i>Escherichia coli</i> Using Fatty Acid Synthesis Pathway

<div><p>Short-chain fatty acids (SCFAs), such as butyric acid, have a broad range of applications in chemical and fuel industries. Worldwide demand of sustainable fuels and chemicals has encouraged researchers for microbial synthesis of SCFAs. In this study we compared three thioesterases, i.e., TesAT from <i>Anaerococcus tetradius</i>, TesBF from <i>Bryantella formatexigens</i> and TesBT from <i>Bacteroides thetaiotaomicron</i>, for production of SCFAs in <i>Escherichia coli</i> utilizing native fatty acid synthesis (FASII) pathway and modulated the genetic and bioprocess parameters to improve its yield and productivity. <i>E</i>. <i>coli</i> strain expressing <i>tesBT</i> gene yielded maximum butyric acid titer at 1.46 g L^-1, followed by <i>tesBF</i> at 0.85 g L^-1 and <i>tesAT</i> at 0.12 g L^-1. The titer of butyric acid varied significantly depending upon the plasmid copy number and strain genotype. The modulation of genetic factors that are known to influence long chain fatty acid production, such as deletion of the <i>fadD</i> and <i>fadE</i> that initiates the fatty acid degradation cycle and overexpression of <i>fadR</i> that is a global transcriptional activator of fatty acid biosynthesis and repressor of degradation cycle, did not improve the butyric acid titer significantly. Use of chemical inhibitor cerulenin, which restricts the fatty acid elongation cycle, increased the butyric acid titer by 1.7-fold in case of TesBF, while it had adverse impact in case of TesBT. <i>In vitro</i> enzyme assay indicated that cerulenin also inhibited short chain specific thioesterase, though inhibitory concentration varied according to the type of thioesterase used. Further process optimization followed by fed-batch cultivation under phosphorous limited condition led to production of 14.3 g L^-1 butyric acid and 17.5 g L^-1 total free fatty acid at 28% of theoretical yield. This study expands our understanding of SCFAs production in <i>E</i>. <i>coli</i> through FASII pathway and highlights role of genetic and process optimization to enhance the desired product.</p></div

A genetic toolbox for metabolic engineering of Issatchenkia orientalis.

The nonconventional yeast Issatchenkia orientalis can grow under highly acidic conditions and has been explored for production of various organic acids. However, its broader application is hampered by the lack of efficient genetic tools to enable sophisticated metabolic manipulations. We recently constructed an episomal plasmid based on the autonomously replicating sequence (ARS) from Saccharomyces cerevisiae (ScARS) in I. orientalis and developed a CRISPR/Cas9 system for multiplexed gene deletions. Here we report three additional genetic tools including: (1) identification of a 0.8&nbsp;kb centromere-like (CEN-L) sequence from the I. orientalis genome by using bioinformatics and functional screening; (2) discovery and characterization of a set of constitutive promoters and terminators under different culture conditions by using RNA-Seq analysis and a fluorescent reporter; and (3) development of a rapid and efficient in vivo DNA assembly method in I. orientalis, which exhibited ~100% fidelity when assembling a 7&nbsp;kb-plasmid from seven DNA fragments ranging from 0.7&nbsp;kb to 1.7&nbsp;kb. As proof of concept, we used these genetic tools to rapidly construct a functional xylose utilization pathway in I. orientalis