Implementasi Program Wirausaha Baru Oleh Dinas Tenaga Kerja Dan Transmigrasi Dalam Mendukung Gerdu Kempling Kota Semarang Tahun 2014

The Government of Semarang through Local Regulation Number 4 of 2008 about poverty reduction in Semarang City which is an acceleration in poverty reduction efforts. The strategy called Gerdu Kempling (Integrated Health, Economy, Education, Infrastructure, and Environment ) and one of the program that is New Entrepreneur Program by Dinas Tenaga Kerja dan Transmigrasi Kota Semarang. This research was meant to find out how the implementation of New Entrepreneur Program by Dinas Tenaga Kerja Dan Transmigrasi that supports Gerdu Kempling Kota Semarang in 2014 and knowing the influence factors of this implementation. New Entrepreneur Program has been part of Gerdu Kempling starting in 2011. There are three locations in this research: Village of Bulusan, Ngadirgo and Padangsari. This research using qualitative descriptive research methods. The subject in this study consisted of eight (8) informants. The results showed that the implementation of New Entrepreneur Program are still less effective that is seen from the precision implementation aspects. The factors that influence the implementation such as the goals and basic of policy, resource policy, communication and implementation activities, the implementing agency characteristics, external conditions as well as the disposition of the implementor are still less optimal too. Based on these conclusions, the researcher recommend to the implementation agency and target of this program need high commitment and take maximal advantages for sustainable in order to achieve the purpose of this program

1 Pengaruh Mengkonsumsi Rebusan Daun Sirsak Terhadap Penurunan Nyeri Pada Penderita Gout Artritis Di Wilayah Kerja Puskesmas Pineleng

Gout artritis merupakan penyakit yang ditandai dengan nyeri yang terjadi berulang-ulang yang disebabkan adanya endapan kristal monosodium urat yang tertumpuk di dalam sendi sebagai akibat tingginya kadar asam urat di dalam darah. Mengkonsumsi rebusan daun sirsak (Anonna muricata) adalah salah satu jenis terapi nonfamakologi yang bertujuan untuk menurunkan tingkat nyeri pada penderita gout artritis karena senyawa yang terkandung dalam daun sirsak berfungsi sebagai analgetik yang mempu mengurangi nyeri gout.Tujuan penelitan ini adalah untuk menganalisis pengaruh mengkonsumsi rebusan daun sirsak terhadap penurunan nyeri pada penderita gout artritis di wilayah kerja Puskesmas Pineleng.Sampel diambil dengan menggunakan total sampling yaitu 34 orang yang memenuhi kriteria inklusi.Desain penelitian yang digunakan adalah Time Series Design dan data yang dikumpulkan dari responden menggunakan lembar observasi.Hasil penelitian uji Wilcoxon sign rank test pada hasil akhir didapatkan nilai p = 0,004 < α = 0,005 sehingga dapat diambil Kesimpulan bahwa hipotesis penelitian diterima, hal ini menunjukan bahwa ada pengaruh mengkonsumsi rebusan daun sirsak terhadap penurunan nyeri pada penderita gout artritis di wilayah kerja Puskesmas Pineleng.Saran untuk penelitian selanjutnya dapat menggunakan populasi yang lebih besar untuk hasil yang lebih akurat serta dapat mengembangkan penelitian tentang pengaruh mengkonsumsi rebusan daun sirsak terhadap variabel yang lain seperti penurunan tekanan darah pada penderita hipertensi

Genotype-driven identification of a molecular network predictive of advanced coronary calcium in ClinSeq® and Framingham Heart Study cohorts

Background: One goal of personalized medicine is leveraging the emerging tools of data science to guide medical decision-making. Achieving this using disparate data sources is most daunting for polygenic traits. To this end, we employed random forests (RFs) and neural networks (NNs) for predictive modeling of coronary artery calcium (CAC), which is an intermediate endo-phenotype of coronary artery disease (CAD). Methods: Model inputs were derived from advanced cases in the ClinSeq®; discovery cohort (n=16) and the FHS replication cohort (n=36) from 89th-99th CAC score percentile range, and age-matched controls (ClinSeq®; n=16, FHS n=36) with no detectable CAC (all subjects were Caucasian males). These inputs included clinical variables and genotypes of 56 single nucleotide polymorphisms (SNPs) ranked highest in terms of their nominal correlation with the advanced CAC state in the discovery cohort. Predictive performance was assessed by computing the areas under receiver operating characteristic curves (ROC-AUC). Results: RF models trained and tested with clinical variables generated ROC-AUC values of 0.69 and 0.61 in the discovery and replication cohorts, respectively. In contrast, in both cohorts, the set of SNPs derived from the discovery cohort were highly predictive (ROC-AUC ≥0.85) with no significant change in predictive performance upon integration of clinical and genotype variables. Using the 21 SNPs that produced optimal predictive performance in both cohorts, we developed NN models trained with ClinSeq®; data and tested with FHS data and obtained high predictive accuracy (ROC-AUC=0.80-0.85) with several topologies. Several CAD and “vascular aging" related biological processes were enriched in the network of genes constructed from the predictive SNPs. Conclusions: We identified a molecular network predictive of advanced coronary calcium using genotype data from ClinSeq®; and FHS cohorts. Our results illustrate that machine learning tools, which utilize complex interactions between disease predictors intrinsic to the pathogenesis of polygenic disorders, hold promise for deriving predictive disease models and networks. Electronic supplementary material The online version of this article (doi:10.1186/s12918-017-0474-5) contains supplementary material, which is available to authorized users

Operational Research: Methods and Applications

Throughout its history, Operational Research has evolved to include a variety of methods, models and algorithms that have been applied to a diverse and wide range of contexts. This encyclopedic article consists of two main sections: methods and applications. The first aims to summarise the up-to-date knowledge and provide an overview of the state-of-the-art methods and key developments in the various subdomains of the field. The second offers a wide-ranging list of areas where Operational Research has been applied. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. The entries within the methods and applications sections are presented in alphabetical order

Immunopathological signatures in multisystem inflammatory syndrome in children and pediatric COVID-19

: Pediatric Coronavirus Disease 2019 (pCOVID-19) is rarely severe; however, a minority of children infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) might develop multisystem inflammatory syndrome in children (MIS-C), with substantial morbidity. In this longitudinal multi-institutional study, we applied multi-omics (analysis of soluble biomarkers, proteomics, single-cell gene expression and immune repertoire analysis) to profile children with COVID-19 (n = 110) and MIS-C (n = 76), along with pediatric healthy controls (pHCs; n = 76). pCOVID-19 was characterized by robust type I interferon (IFN) responses, whereas prominent type II IFN-dependent and NF-κB-dependent signatures, matrisome activation and increased levels of circulating spike protein were detected in MIS-C, with no correlation with SARS-CoV-2 PCR status around the time of admission. Transient expansion of TRBV11-2 T cell clonotypes in MIS-C was associated with signatures of inflammation and T cell activation. The association of MIS-C with the combination of HLA A*02, B*35 and C*04 alleles suggests genetic susceptibility. MIS-C B cells showed higher mutation load than pCOVID-19 and pHC. These results identify distinct immunopathological signatures in pCOVID-19 and MIS-C that might help better define the pathophysiology of these disorders and guide therapy

Age- and region-specific hepatitis B prevalence in Turkey estimated using generalized linear mixed models: a systematic review

Toy M, Önder FO, Wörmann T, et al. Age- and region-specific hepatitis B prevalence in Turkey estimated using generalized linear mixed models: a systematic review. BMC infectious diseases. 2011;11(1): 337.BACKGROUND: To provide a clear picture of the current hepatitis B situation, the authors performed a systematic review to estimate the age- and region-specific prevalence of chronic hepatitis B (CHB) in Turkey. METHODS: A total of 339 studies with original data on the prevalence of hepatitis B surface antigen (HBsAg) in Turkey and published between 1999 and 2009 were identified through a search of electronic databases, by reviewing citations, and by writing to authors. After a critical assessment, the authors included 129 studies, divided into categories: 'age-specific'; 'region-specific'; and 'specific population group'. To account for the differences among the studies, a generalized linear mixed model was used to estimate the overall prevalence across all age groups and regions. For specific population groups, the authors calculated the weighted mean prevalence. RESULTS: The estimated overall population prevalence was 4.57, 95% confidence interval (CI): 3.58, 5.76, and the estimated total number of CHB cases was about 3.3 million. The outcomes of the age-specific groups varied from 2.84, (95% CI: 2.60, 3.10) for the 0-14-year olds to 6.36 (95% CI: 5.83, 6.90) in the 25-34-year-old group. CONCLUSION: There are large age-group and regional differences in CHB prevalence in Turkey, where CHB remains a serious health problem

Control-oriented modeling of discrete configuration molecular scale processes: Applications in polymer synthesis and thin film growth

The objective of this thesis is to propose modeling techniques that enable the design and optimization of material systems which require descriptions via molecular simulations. These kinds of systems are quite common in materials and engineering research. The first step in performing design and optimization tasks on such systems is the development of accurate simulation models from experimental data. In the first part of this thesis, we present a novel simulation model for the hyperbranched polymerization process of difunctional A2 oligomers, and B3 monomers. Unlike the previous models developed by other groups, our model is able to simulate the evolution of the polymer structure development under a wide range of synthesis routes, and in the presence of cyclization and endcapping reactions. Furthermore, our results are in agreement with the experimental data, and add insight into the underlying kinetic mechanisms of this polymerization process. The second major step in our work is the development of reduced order process models that are suitable for design and optimization tasks, using simulation data. We illustrate our approach on a stochastic simulation model of epitaxial thin film deposition process. Compared to the widely used approach called equation-free modeling, our method requires fewer assumptions about the dynamic system. The assumptions required in equation-free modeling include a wide separation between the time scales of low and high order moments describing the system state, and the accuracy of the time derivatives of system properties computed from molecular simulation data, despite the potentially large amount of fluctuations in stochastic simulations. Unlike the recent similar studies, our study also includes the analysis of prediction error which is important to evaluate the predictions of the reduced order model, compared to the high dimensional molecular simulations. Hence, we address two major issues in this thesis: development of simulation models from molecular experimental data, and derivation of reduced order models from molecular simulation data. These two aspects of modeling are both necessary to design and optimize processing conditions of materials for which continuum level descriptions are not available or accurate enough.Ph.D.Committee Chair: Gallivan, Martha A.; Committee Member: Hess, Dennis; Committee Member: Lee, Jay H.; Committee Member: Li, Mo; Committee Member: Ludovice, Pet