A general asymptotic scheme for inference under order restrictions

Limit distributions for the greatest convex minorant and its derivative are considered for a general class of stochastic processes including partial sum processes and empirical processes, for independent, weakly dependent and long range dependent data. The results are applied to isotonic regression, isotonic regression after kernel smoothing, estimation of convex regression functions, and estimation of monotone and convex density functions. Various pointwise limit distributions are obtained, and the rate of convergence depends on the self similarity properties and on the rate of convergence of the processes considered.Comment: Published at http://dx.doi.org/10.1214/009053606000000443 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Kompetensi Guru dalam Mengembangkan Pembelajaran Sejarah Berbasis Teknologi dan Informasi (IT) di SMA Assalaam Sukoharjo Tahun Ajaran 2017/2018

ABSTRAK Diany Tri Rahmawati. KOMPETENSI GURU DALAM MENGEMBANGKAN PEMBELAJARAN SEJARAH BERBASIS TEKNOLOGI DAN INFORMASI (IT) DI SMA ASSALAAM SUKOHARJO TAHUN AJARAN 2017/2018. Skripsi, Fakultas Keguruan dan Ilmu Pendidikan Universitas Sebelas Maret Surakarta, Desember, 2018. Tujuan dari penelitian ini untuk mendeskripsikan: (1) pemahaman guru sejarah terhadap pengembangan pembelajaran berbasis IT, (2) implementasi pengembangan pembelajaran berbasis IT dalam pembelajaran sejarah di SMA Assalaam Sukoharjo Tahun Ajaran 2017/2018, (3) upaya yang ditempuh untuk mengatasi hambatan dalam implementasi pengembangan pembelajaran berbasis IT dalam pembelajaran sejarah di SMA Assalaam Sukoharjo Tahun Ajaran 2017/2018. Bentuk penelitian ini adalah deskriptif kualitatif, yaitu suatu cara dalam meneliti suatu peristiwa dengan menghasilkan data-data deskriptif. Sumber data yang digunakan adalah tempat, peristiwa, informan, dan dokumen. Teknik pengumpulan data yang digunakan adalah observasi, wawancara, dan analisis dokumen.Teknik sampling yang digunakan adalah purposive sampling. Teknik validitas data yang digunakan adalah trianggulasi sumber dan trianggulasi metode. Teknik analisis data yang digunakan adalah teknik analisis interaktif, yaitu teknik analisis yang bergerak di antara tiga komponen yang meliputi reduksi data, penyajian data, dan penarikan kesimpulan. Berdasarkan hasil penelitian ini dapat diambil kesimpulan sebagai berikut: (1) Guru Sejarah di SMA Assalam Sukoharjo memahami bahwa pembelajaran berbasis IT adalah pembelajaran yang memanfaatkan piranti IT yang bertujuan untuk meningkatkan hasil belajar siswa. Guru memahami bahwa dalam pelajaran sejarah sangat tepat jika diajarkan dengan menggunakan pembelajaran berbasis IT, (2)Pengembangan pembelajaran sejarah berbasis IT di SMA Assalaam Sukoharjo terdiri dari tahap perencanaan, pelaksanaan dan evaluasi. Tahap perencanaan pembelajaran sejarah berbasis IT dimulai dengan penyusunan perangkat pembelajaran berupa RPP, PROTA, PROMES, dan SILABUS, tahap pelaksanaan pembelajaran sejarah berbasis IT diterapkan dengan guru menggunakan media pengajaran berbasis IT berupa slide powerpoint, penyajian gambar, dan pemutaran film dokumenter, tahap evaluasi pembelajaran sejarah berbasis IT dilaksanakan melalui penilaian sesuai dengan ketentuan penilaian pada Kurikulum 2013, yakni penilaian pada kompetensi dasar spiritual, sikap, pengetahuan dan keterampilan. Penilaian dilakukan dengan menggunakan aplikasi atau software penilaian khusus yang berbasis online atau SIAKAD (3) kendala yang ditemui dalam mengembangkan pembelajaran sejarah berbasis IT adalah kurangnya akses siswa terhadap internet dan lab komputer, upaya yang dilakukan untuk mengatasi kendala tersebut adalah dengan terus berusaha menambah fasilitas laboraturium komputer, dan pihak sekolah secara berkala mengadakan pelatihan untuk guru yang berkaitan dengan pengembangan berbasis IT, sehingga kemampuan dan keterampilan guru dapat terus bertambah. Kata kunci: kompetensi guru, pembelajaran berbasis IT, pembelajaran sejarah

Chemogenetic fingerprinting by analysis of cellular growth dynamics

<p>Abstract</p> <p>Background</p> <p>A fundamental goal in chemical biology is the elucidation of on- and off-target effects of drugs and biocides. To this aim chemogenetic screens that quantify drug induced changes in cellular fitness, typically taken as changes in composite growth, is commonly applied.</p> <p>Results</p> <p>Using the model organism <it>Saccharomyces cerevisiae </it>we here report that resolving cellular growth dynamics into its individual components, growth lag, growth rate and growth efficiency, increases the predictive power of chemogenetic screens. Both in terms of drug-drug and gene-drug interactions did the individual growth variables capture distinct and only partially overlapping aspects of cell physiology. In fact, the impact on cellular growth dynamics represented functionally distinct chemical fingerprints.</p> <p>Discussion</p> <p>Our findings suggest that the resolution and quantification of all facets of growth increases the informational and interpretational output of chemogenetic screening. Hence, by facilitating a physiologically more complete analysis of gene-drug and drug-drug interactions the here reported results may simplify the assignment of mode-of-action to orphan bioactive compounds.</p

Genetic Prediction of Future Type 2 Diabetes

BACKGROUND: Type 2 diabetes (T2D) is a multifactorial disease in which environmental triggers interact with genetic variants in the predisposition to the disease. A number of common variants have been associated with T2D but our knowledge of their ability to predict T2D prospectively is limited. METHODS AND FINDINGS: By using a Cox proportional hazard model, common variants in the PPARG (P12A), CAPN10 (SNP43 and 44), KCNJ11 (E23K), UCP2 (−866G>A), and IRS1 (G972R) genes were studied for their ability to predict T2D in 2,293 individuals participating in the Botnia study in Finland. After a median follow-up of 6 y, 132 (6%) persons developed T2D. The hazard ratio for risk of developing T2D was 1.7 (95% confidence interval [CI] 1.1–2.7) for the PPARG PP genotype, 1.5 (95% CI 1.0–2.2) for the CAPN10 SNP44 TT genotype, and 2.6 (95% CI 1.5–4.5) for the combination of PPARG and CAPN10 risk genotypes. In individuals with fasting plasma glucose ≥ 5.6 mmol/l and body mass index ≥ 30 kg/m(2), the hazard ratio increased to 21.2 (95% CI 8.7–51.4) for the combination of the PPARG PP and CAPN10 SNP43/44 GG/TT genotypes as compared to those with the low-risk genotypes with normal fasting plasma glucose and body mass index < 30 kg/m(2). CONCLUSION: We demonstrate in a large prospective study that variants in the PPARG and CAPN10 genes predict future T2D. Genetic testing might become a future approach to identify individuals at risk of developing T2D

Estimating a probability mass function with unknown labels

In the context of a species sampling problem, we discuss a nonparametric maximum likelihood estimator for the underlying probability mass function. The estimator is known in the computer science literature as the high profile estimator. We prove strong consistency and derive the rates of convergence, for an extended model version of the estimator. We also study a sieved estimator for which similar consistency results are derived. Numerical computation of the sieved estimator is of great interest for practical problems, such as forensic DNA analysis, and we present a computational algorithm based on the stochastic approximation of the expectation maximisation algorithm. As an interesting byproduct of the numerical analyses, we introduce an algorithm for bounded isotonic regression for which we also prove convergence

Common variants in HNF-1 alpha and risk of type 2 diabetes.

AIMS/HYPOTHESIS: Mutations in the hepatocyte nuclear factor 1-alpha gene (HNF-1alpha, now known as the transcription factor 1 gene [TCF1]) cause the most common monogenic form of diabetes, MODY3, but it is not known if common variants in HNF-1a are associated with decreased transcriptional activity or phenotypes related to type 2 diabetes, or whether they predict future type 2 diabetes. SUBJECTS AND METHODS: We studied the effect of four common polymorphisms (rs1920792, I27L, A98V and S487N) in and upstream of the HNF-1alpha gene on transcriptional activity in vitro, and their possible association with type 2 diabetes and insulin secretion in vivo. RESULTS: Certain combinations of the I27L and A98V polymorphisms in the HNF-1alpha gene showed decreased transcriptional activity on the target promoters glucose transporter 2 (now known as solute carrier family 2 [facilitated glucose transporter], member 2) and albumin in both HeLa and INS-1 cells. In vivo, these polymorphisms were associated with a modest but significant impairment in insulin secretion in response to oral glucose. Insulin secretion deteriorated over time in individuals carrying the V allele of the A98V polymorphism (n = 2,293; p = 0.003). In a new case-control (n = 1,511 and n = 2,225 respectively) data set, the I27L polymorphism was associated with increased risk of type 2 diabetes, odds ratio (OR) = 1.5 (p = 0.002; multiple logistic regression), particularly in elderly (age &gt; 60 years) and overweight (BMI &gt; 25 kg/m(2)) patients (OR = 2.3, p = 0.002). CONCLUSIONS/INTERPRETATION: This study provides in vitro and in vivo evidence that common variants in the MODY3 gene, HNF-1alpha, influence transcriptional activity and insulin secretion in vivo. These variants are associated with a modestly increased risk of late-onset type 2 diabetes in subsets of elderly overweight individuals