Faktor-Faktor Yang Mempengaruhi Pengungkapan Tanggung Jawab Sosial

Penelitian ini bertujuan untuk menentukan faktor-faktor yang mempengaruhi luasnya tingkat pengungkapan tanggung jawab sosial Perusahaan (Corporate Social Responsibility) dengan menguji pengaruh ukuran Perusahaan, profitabilitas, leverage, kepemilikan insti­tusional, ukuran dewan komisaris, ukuran dewan direksi, dan ukuran komite audit. Sampel yang digunakan adalah Perusahaan sektor pertambangan terdaftar di Bursa Efek Indonesia selama 2010-2012. Data diperoleh dari laporan keuangan auditan dan laporan tahunan serta laporan keberlanjutan (sustainability report) jika ada. Penelitian ini menggunakan pendekatan kuantitatif dengan analisis regresi linear berganda. Penelitian ini menunjukkan bahwa ukuran Perusahaan dan komite audit memiliki pengaruh positif terhadap peng­ungkapan tanggung jawab sosial. Tidak ditemukan bukti pengaruh profitabilitas, leverage, kepemilikan institusional, ukuran dewan komisaris, dan ukuran dewan direksi terhadap terhadap pengungkapan tanggung jawab sosial

The Last April

<p>Parameter settings of virtual datasets.</p

Current eigenmodes and dephasing in nanoscopic quantum networks

Using the nonequilibrium Keldysh Green’s function formalism, we show that the nonequilibrium charge transport in nanoscopic quantum networks takes place via current eigenmodes that possess characteristic spatial patterns.We identify the microscopic relation between the current patterns and the network’s electronic structure and topology and demonstrate that these patterns can be selected via gating or constrictions, providing new venues for manipulating charge transport at the nanoscale. Finally, decreasing the dephasing time leads to a smooth evolution of the current patterns from those of a ballistic quantum network to those of a classical resistor network

New Manufacturing Route to Picoxystrobin

A new and efficient manufacturing technology is disclosed in the present work for the preparation of picoxystrobin in which all of the intermediates can be used directly in the next step of the process without purification

Video_1_Reverse-sequence endoscopic nipple-sparing mastectomy with immediate implant-based breast reconstruction: an improvement of conventional minimal access breast surgery.mov

BackgroundOur center proposes a new technique that effectively provides space to broaden the surgical field of view and overcomes the limitations of endoscopy-assisted nipple-sparing mastectomy (E-NSM) by changing the dissection sequence and combining it with air inflation. The purpose of this study was to compare the clinical outcomes of the new technique designated “reverse-sequence endoscopic nipple-sparing mastectomy (R-E-NSM) with subpectoral breast reconstruction (SBR)“ and the conventional E-NSM (C-E-NSM) with SBR.MethodAll patients undergoing E-NSM with SBR at our breast center between April 2017 and December 2022 were included in this study. The cohort was divided into the C-E-NSM group and the R-E-NSM group. The operation time, anesthesia time, medical cost, complications, cosmetic outcomes, and oncological safety were compared.ResultsTwenty-six and seventy-nine consecutive patients were included in the C-E-NSM and R-E-NSM groups, with average ages of 36.9 ± 7.0 years and 39.7 ± 8.4 years (P=0.128). Patients in the R-E-NSM group had significantly shorter operation time (204.6 ± 59.2 vs. 318.9 ± 75.5 minutes, pConclusionR-E-NSM improves cosmetic outcomes and efficiency of C-E-NSM, reduces medical costs, and has a trend of lower surgical complications while maintaining the safety of oncology. It is a safe and feasible option for oncological procedures that deserves to be promoted and widely adopted in practice.</p

Results of four methods on the analysis of the SNP set from the GWAS study.

a<p>We extract the 1st PC to analyze.</p

Weighted SNP Set Analysis in Genome-Wide Association Study

<div><p>Genome-wide association studies (GWAS) are popular for identifying genetic variants which are associated with disease risk. Many approaches have been proposed to test multiple single nucleotide polymorphisms (SNPs) in a region simultaneously which considering disadvantages of methods in single locus association analysis. Kernel machine based SNP set analysis is more powerful than single locus analysis, which borrows information from SNPs correlated with causal or tag SNPs. Four types of kernel machine functions and principal component based approach (PCA) were also compared. However, given the loss of power caused by low minor allele frequencies (MAF), we conducted an extension work on PCA and used a new method called weighted PCA (wPCA). Comparative analysis was performed for weighted principal component analysis (wPCA), logistic kernel machine based test (LKM) and principal component analysis (PCA) based on SNP set in the case of different minor allele frequencies (MAF) and linkage disequilibrium (LD) structures. We also applied the three methods to analyze two SNP sets extracted from a real GWAS dataset of non-small cell lung cancer in Han Chinese population. Simulation results show that when the MAF of the causal SNP is low, weighted principal component and weighted IBS are more powerful than PCA and other kernel machine functions at different LD structures and different numbers of causal SNPs. Application of the three methods to a real GWAS dataset indicates that wPCA and wIBS have better performance than the linear kernel, IBS kernel and PCA.</p></div

Test of Power for LKM, PCA and wPCA in Scenarios B3–B8.

<p>Test of Power for LKM, PCA and wPCA in Scenarios B3–B8.</p

Empirical type I error rates for LKM, PCA and wPCA in Scenarios B1.

<p>Empirical type I error rates for LKM, PCA and wPCA in Scenarios B1.</p

Parameter settings of the <i>CLPTM1L</i> gene.

<p>Parameter settings of the <i>CLPTM1L</i> gene.</p