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In a one-way analysis-of-variance (ANOVA) model, the number of pairwise comparisons can become large even with a moderate number of groups. Motivated by this, we consider a regime with a growing number of groups and prove that, when testing pairwise comparisons, the Benjamini-Hochberg (BH) procedure can asymptotically control false discoveries, despite the fact that the involved t-statistics do not exhibit the well-known positive dependence structure required for exact false discovery rate (FDR) control. Following Tukey's perspective that the difference between the means of any two groups cannot be exactly zero, our main result provides control over the directional false discovery rate and directional false discovery proportion. A key technical contribution of our work is demonstrating that the dependence among the t-statistics is sufficiently weak to establish the convergence result typically required for asymptotic FDR control. Our analysis does not rely on conventional assumptions such as normality, variance homogeneity, or a balanced design, thereby offering a theoretical foundation for applications in more general settings. [ABSTRACT FROM AUTHOR]

Co-inertia analysis (CIA) is a multivariate analysis method that assesses relationships and trends in two sets of data. It has been effectively employed in the integrative analysis of high-dimensional multi-omics datasets. Recently, penalized CIA methods have been introduced to enhance the interpretability by inducing sparsity in the loading vectors. However, challenges persist in ensuring that non-zero elements in the estimated vector genuinely represent significant features. To address these challenges, we propose a penalized CIA method that controls the false discovery rate (FDR) using sorted l-1 penalized estimation (SLOPE). This approach allows for simultaneous FDR control and sparsity induction in the estimated vectors. Extensive simulation studies demonstrate the performance compared to the existing CIA method. Additionally, we apply our methods to the integrative analysis of NCI60 data to show its effectiveness in real-world scenarios. [ABSTRACT FROM AUTHOR]

A transfer learning for the large‐scale Gaussian graphical models (GGMs) is considered in a distributed architecture for fitting these target and auxiliary studies scattered across multiple sites. A distributed transfer learning algorithm, DisPower‐Trans‐CLIME, is proposed to learn the target GGMs by incorporating the data from similar and related auxiliary studies. The algorithm is communication efficient via the distributed power method for matrix decomposition. We show that DisPower‐Trans‐CLIME has a fast convergence rate comparable to the centred Trans‐CLIME algorithm. A debiased DisPower‐Trans‐CLIME is constructed and is proved to be element‐wise asymptotically normal for statistical inference. Thus, a multiple testing procedure is developed to detect edge of GGMs with false discovery rate (FDR) control. Extensive simulation experiments have been conducted to demonstrate superior numerical performance of our proposed learning algorithm on estimation and edge detection. It is also applied to infer the regional connection networks in brain regions of interest (ROIs) based on a target hospital site by leveraging the graph from multiple other hospital sites for autism spectrum disorder. We observe that the degrees of regional connectivity in the right brain are balanced, while the ones of the left brain region are extremely uneven because of the presence of multiple strong connections. However, the specific association, between the degrees of connectivity of these regions and ASD disease, is unknown. [ABSTRACT FROM AUTHOR]

Taking into account the local dependence structure in large-scale multiple testing is expected to improve both the efficiency of the testing procedure and the interpretability of scientific findings. The hidden Markov model (HMM), as an effective model to describe the sequential dependence, has been successfully applied to large-scale multiple testing with local correlations. However, in many applications, the first-order Markov chain is not flexible enough to capture the complexity of local correlations. To address this issue, this paper proposes a novel multiple testing procedure that uses a higher-order Markov chain to better characterize local correlations among tests. The proposed procedure is validated by theoretical results and simulation studies, which show that it outperforms its competitors in terms of power. Finally, a real data analysis is presented to demonstrate the favorable performance of the proposed procedure. [ABSTRACT FROM AUTHOR]

This study examines the effect of Financing To Deposit Ratio (FDR), Non-Performing Financing (NPF), and Good Corporate Governance (GCG) on the Profitability (ROA) of Islamic commercial banks listed on the Financial Services Authority for the period 2017-2023. The independent variables used are NPF, FDR, and GCG which are proxied by the ratio of the number of independent commissioners and the number of commissioners and the frequency of Sharia Supervisory Board meetings. The dependent variable used is the return on assets (ROA). The results of this study indicate that Non-Performing Financing (NPF) has an effect on profitability (ROA), while Financing To Deposit Ratio (FDR), Independent Board of Commissioners (DKI), and Sharia Supervisory Board (DPS) have no significant effect on the profitability of Islamic commercial banks. [ABSTRACT FROM AUTHOR]

This study aims to examine the effect of NPF, FDR, and GCG on the profitability of Islamic commercial banks. The data used is secondary data in the form of annual financial reports from 17 Islamic Commercial Banks in Indonesia registered with the Financial Services Authority for the period 2018-2022 so 69 observation data were obtained. The independent variables used are NPF, FDR, and GCG which are proxied by the number of boards of directors and the frequency of board meetings. At the same time, the dependent variable used is return on assets (ROA). The results of this study indicate that FDR has an effect on the profitability of Islamic commercial banks, while NPF, the board of directors, and the board of commissioners have no significant effect on the profitability of Islamic commercial banks. [ABSTRACT FROM AUTHOR]

The frequency‐domain reflection (FDR) has been demonstrated to be a trustworthy technique in solving the defect location of power cable by field experiments. However, the location spectrum of the FDR requires manual window smoothing and can be disturbed by spurious peaks. Aiming at these shortcomings of FDR, a new method of cable defect location based on Burg power spectral (BPS) is introduced in this paper. The idea of this method is to use linear difference variance to fit the distribution of reflection coefficient spectrum and build an auto‐regressive (AR) model. The Burg algorithm is employed to estimate the coefficients model and calculate the power distribution of the AR model. Then, the cable defects will be located by BPS with high precision and resolution. In this method, the fast Fourier transform (FFT) with windowed function is replaced by an AR model without windowed function. This suppressed the impact of spurious peaks or spectrum leakage in FFT on the localization defects, and the localization resolution is higher. Finally, we validate the feasibility and effectiveness of BPS through experiments conducted on a 500 m laboratory cable and a 9.6 km submarine cable. [ABSTRACT FROM AUTHOR]

ABSTRACT Currently in wheat breeding, genome wide association studies (GWAS) have successfully revealed the genetic basis of complex traits such as nitrogen use efficiency (NUE) and its biological processes. In the GWAS model, thresholding is common strategy to indicate deviation of expected range of p‐value(s), and it can be used to find the distribution of true positive associations under or over of test statistics. Therefore, the threshold plays a critical role to identify reliable and significant associations in wide genome, while the proportion of false positive results is relatively low. The problem of multiple comparisons arises when a statistical analysis involves multiple simultaneous statistical tests, each of them has the potential to be a discovery. There are several ways to address this problem, including the family‐wise error rate and false discovery rate (FDR), raw and adjusted p‐value(s), consideration of threshold coherence and consonance, and the properties of proportional hypothesis tests in the threshold definition. We encountered some limitations in the definition of FDR threshold, particularly in the upper bounds of linear and nonlinear approaches. We emphasize that empirical null distributions based on permutation test can be useful when the assumption of linear or parametric FDR approaches do not hold. Nevertheless, we believe that it is necessary to utilize modern statistical optimization techniques to evaluate the stability and performance of our results and to select significant FDR threshold. By incorporating the neural network algorithm, it is possible to improve the reliability of FDR threshold and increase the probability of identifying true genetic associations while minimizing the risk of false positives in GWAS results.

Purpose: This research aims to analyze the role of Islamic Corporate Governance (ICG) in mediating and moderating the influence of financing to deposit ratio (FDR) on the level of non-performing financing (NPF) of Islamic banks in Indonesia. Method: This research uses panel data from 7 Islamic banks in Indonesia during the 2016-2021 period. Samples were taken using judgment sampling techniques. The analytical method used is panel regression with a fixed effect model and uses SPSS software. Results: The research results show that there is no evidence that the financing to deposit ratio has a negative and significant effect on ICG. On the other hand, ICG has a negative and significant effect on NPF, and the financing to deposit ratio also does not have a positive and significant effect on NPF. Apart from that, the research results also show that ICG is not proven to mediate the negative influence of financing to deposit ratio on NPF. On the other hand, the moderating effect of ICG on the relationship between FDR and NPF is proven to have an impact. FDR has a significant influence on NPF. Implications: The implication of this study is that Islamic banks in Indonesia need to improve ICG practices as an internal control mechanism to reduce the risk of non-performing financing and improve financial performance. Novelty: This research uses two models of the role of Islamic Corporate Governance (ICG) in mediating and moderating the influence of the Financing to Deposit Ratio (FDR) variable on Non-Performing Financing (NPF).

The need to select mediators from a high dimensional data source, such as neuroimaging data and genetic data, arises in much scientific research. In this work, we formulate a multiple-hypothesis testing framework for mediator selection from a high-dimensional candidate set, and propose a method, which extends the recent development in false discovery rate (FDR)-controlled variable selection with knockoff to select mediators with FDR control. We show that the proposed method and algorithm achieved finite sample FDR control. We present extensive simulation results to demonstrate the power and finite sample performance compared with the existing method. Lastly, we demonstrate the method for analyzing the Adolescent Brain Cognitive Development (ABCD) study, in which the proposed method selects several resting-state functional magnetic resonance imaging connectivity markers as mediators for the relationship between adverse childhood events and the crystallized composite score in the NIH toolbox. [ABSTRACT FROM AUTHOR]

Abstract The frequency‐domain reflection (FDR) has been demonstrated to be a trustworthy technique in solving the defect location of power cable by field experiments. However, the location spectrum of the FDR requires manual window smoothing and can be disturbed by spurious peaks. Aiming at these shortcomings of FDR, a new method of cable defect location based on Burg power spectral (BPS) is introduced in this paper. The idea of this method is to use linear difference variance to fit the distribution of reflection coefficient spectrum and build an auto‐regressive (AR) model. The Burg algorithm is employed to estimate the coefficients model and calculate the power distribution of the AR model. Then, the cable defects will be located by BPS with high precision and resolution. In this method, the fast Fourier transform (FFT) with windowed function is replaced by an AR model without windowed function. This suppressed the impact of spurious peaks or spectrum leakage in FFT on the localization defects, and the localization resolution is higher. Finally, we validate the feasibility and effectiveness of BPS through experiments conducted on a 500 m laboratory cable and a 9.6 km submarine cable.

Interpretability and stability are two important characteristics required for the application of high dimensional data in statistics. Although the former has been favored by many existing forecasting methods to some extent, the latter in the sense of controlling the fraction of wrongly discovered features is still largely underdeveloped. Under the accelerated failure time model, this paper introduces a controlled variable selection method with the general framework of Model-X knockoffs to tackle high dimensional data. We provide theoretical justifications on the asymptotic false discovery rate (FDR) control. The proposed method has attracted significant interest due to its strong control of the FDR while preserving predictive power. Several simulation examples are conducted to assess the finite sample performance with desired interpretability and stability. A real data example from Acute Myeloid Leukemia study is analyzed to demonstrate the utility of the proposed method in practice. [ABSTRACT FROM AUTHOR]

Large-scale multiple testing is common in the statistical analysis of high-dimensional data. Conventional multiple testing procedures usually implicitly assumed that the tests are independent. However, this assumption is rarely established in many practical applications, particularly in "high-throughput" data analysis. Incorporating dependence structure information among tests can improve statistical power and interpretability of discoveries. In this paper, we propose a new large-scale dependent multiple testing procedure based on the hidden semi-Markov model (HSMM), which characterizes local correlations among tests using a semi-Markov process instead of a first-order Markov chain. Our novel approach allows for the number of consecutive null hypotheses to follow any reasonable distribution, enabling a more accurate description of complex local correlations. We show that the proposed procedure minimizes the marginal false non-discovery rate (mFNR) at the same marginal false discovery rate (mFDR) level. To reduce the computational complexity of the HSMM, we make use of the hidden Markov model (HMM) with an expanded state space to approximate it. We provide a forward-backward algorithm and an expectation-maximization (EM) algorithm for implementing the proposed procedure. Finally, we demonstrate the superior performance of the SMLIS procedure through extensive simulations and a real data analysis. [ABSTRACT FROM AUTHOR]

Fetal sex affects fetal and maternal health outcomes in pregnancy, but this connection remains poorly understood. As the placenta is the route of fetomaternal communication and derives from the fetal genome, placental gene expression sex differences may explain these outcomes. We utilized next generation sequencing to study the normal human placenta in both sexes in first and third trimester to generate a normative transcriptome based on sex and gestation. We analyzed 124 first trimester (T1, 59 female and 65 male) and 43 third trimester (T3, 18 female and 25 male) samples for sex differences within each trimester and sex-specific gestational differences. Placenta shows more significant sexual dimorphism in T1, with 94 T1 and 26 T3 differentially expressed genes (DEGs). The sex chromosomes contributed 60.6% of DEGs in T1 and 80.8% of DEGs in T3, excluding X/Y pseudoautosomal regions. There were 6 DEGs from the pseudoautosomal regions, only significant in T1 and all upregulated in males. The distribution of DEGs on the X chromosome suggests genes on Xp (the short arm) may be particularly important in placental sex differences. Dosage compensation analysis of X/Y homolog genes shows expression is primarily contributed by the X chromosome. In sex-specific analyses of first versus third trimester, there were 2815 DEGs common to both sexes upregulated in T1, and 3263 common DEGs upregulated in T3. There were 7 female-exclusive DEGs upregulated in T1, 15 female-exclusive DEGs upregulated in T3, 10 male-exclusive DEGs upregulated in T1, and 20 male-exclusive DEGs upregulated in T3. This is the largest cohort of placentas across gestation from healthy pregnancies defining the normative sex dimorphic gene expression and sex common, sex specific and sex exclusive gene expression across gestation. The first trimester has the most sexually dimorphic transcripts, and the majority were upregulated in females compared to males in both trimesters. The short arm of the X chromosome and the pseudoautosomal region is particularly critical in defining sex differences in the first trimester placenta. As pregnancy is a dynamic state, sex specific DEGs across gestation may contribute to sex dimorphic changes in overall outcomes. • Fetal and maternal health outcomes due to the placenta are sexually dimorphic, therefore sequencing was performed. • Sex differences were more prevalent in first trimester, and derived mostly from sex chromosomes. • Genes common to both sexes were identified, as well as genes exclusive to each sex. • This is the largest normative placenta transcriptome atlas stratified by sex across gestation. • Genes identified may account for changes during placentation or overall outcomes based on sex. [ABSTRACT FROM AUTHOR]

The article explores the particular segment of official American-Soviet relations at the beginning of the German-Soviet war, which concerned the issue of no religious freedom in the USSR and the influence of President Roosevelt's administration on its impact. The chronological boundaries of the study are the period from the German attack on the USSR on June 22, 1941 to December 1941, when a number of important events took place: the Soviet counteroffensive began near Moscow (December 5, 1941), Japan attacked the base of the US Pacific Fleet in Pearl Harbor (December 7, 1941), Germany and Italy declared war on the USA (December 11, 1941). The article attempts to trace the facts concerning the official relations between the United States of America and the Soviet Union regarding religious freedom during the most critical period of the German-Soviet war. The author analyzes official statements and documents, correspondence of diplomatic representatives, as well as memories of representatives of the highest state leadership, who were direct participants in the studied events, in order to highlight the state of interaction regarding issues of religious freedom. The article clarifies how the issue of religious freedom influenced the formation of the alliance between the two states, taking into account the historical context of restrictions on religious practice in the USSR and the active support of the right to religious freedom as part of American foreign policy. The study indicates that the issue of religious freedom concerned not only the moral dimension of relations between the two states, but was also a tool of diplomatic influence that depended on the US public opinion. The article is designed to show the complex nature of American-Soviet relations in the second half of 1941, emphasizing the role of ideological compromises in international politics and the importance of the issue of religious freedom as an element of diplomatic relations between the USA and the USSR. The results of the study show that religious issues could shape international relations during global conflicts and influence political decisions at the highest level. The author claims that taking into account the religious aspect in interstate relations can open up new opportunities for diplomacy and promote better mutual understanding between countries. [ABSTRACT FROM AUTHOR]

In Indonesia, the government encourages converting conventional regional development banks into sharia regional development banks. Such banks should become the driving force and the stimulator of a sharia ecosystem in the region, especially to support the development of regional economic potentials and to become a prosperous and peaceful country. This study aims to analyze the financial performance of regional development banks that have become sharia regional development banks to identify their ability to continue to provide economic growth in the region. Considering the results of previous studies, the authors conduct a comparative analysis of the financial performance of regional development banks that have converted to sharia banks using the following variables: return on assets (ROA), return on equity (ROE), loan-to-deposit ratio (LDR) / financing-to-deposit ratio (FDR), net interest margin (NIM) / net operating margin (NOM) and ratio of operating expenses to operating income (BOPO). The analysis aims to determine whether there is a significant difference in the financial performance between conventional and sharia regional development banks. The population in this study is the regional development bank, with a sample of 3 banks that have converted into sharia banks (Bank Aceh Shariah, Bank NTB Shariah, and Bank Riau Kepri Shariah). The study uses secondary bank data from quarterly financial reports on the banks’ websites. The independent sample t-test is used to test the performance of conventional and sharia banks. The study results indicate no significant differences in the financial performance of regional development banks as measured using the financial ratio indicators ROA, ROE, and LDR. However, there are significant differences in measurements using the NIM and BOPO ratio indicators. Although the financial performance of sharia banks is still lower than that of conventional banks, they are showing an upward trend.

Several decades ago, the 1998 financial crisis in ASEAN developing countries had a limited impact on the performance of sharia banking due to its adherence to principles of transparency and fairness in its operations, allowing it to sustain growth under various conditions. This study examines the effect of CAR, ROA, and FDR on the efficiency of Islamic banking in developing countries, specifically the United Arab Emirates, Malaysia, Kuwait, and Qatar. Employing quantitative methods and panel data regression analysis, the findings reveal that CAR does not have a significant individual effect on Sharia banking efficiency, whereas FDR and ROA significantly enhance banking efficiency. This research contributes valuable insights into the role of these financial ratios in shaping the efficiency of Islamic banks in developing countries, providing practical implications for policymakers and banking professionals aiming to improve sharia banking performance.

The IL-17A inhibitor secukinumab is efficacious for the treatment of psoriasis. To better understand its mechanism of action, we investigated its impact on psoriatic lesions from 15 patients with moderate-to-severe plaque psoriasis undergoing secukinumab treatment. We characterized the longitudinal transcriptomic changes of whole lesional skin tissue as well as cutaneous CD4+ and CD8+ T effector cells and CD4+ T regulatory cells across 12 weeks of treatment. Secukinumab was clinically effective and reduced disease-associated overexpression of IL17A , IL17F, IL23A, IL23R, and IFNG in whole tissue as soon as 2 weeks after initiation of treatment. IL17A overexpression in T-cell subsets, primarily CD8+ T cells, was also reduced. Although secukinumab treatment resolved 89‒97% of psoriasis-associated expression differences in bulk tissue and T-cell subsets by week 12 of treatment, we observed expression differences involved in IFN signaling and metallothionein synthesis that remained unresolved at this time point as well as potential treatment-associated expression differences involved in IL-15 signaling. These changes were accompanied by shifts in broader immune cell composition on the basis of deconvolution of RNA-sequencing data. In conclusion, our study reveals several phenotypic and cellular changes within the lesion that underlie clinical improvement from secukinumab.

Bank Muamalat sebagai bank syariah tertua di Indonesia menjadi perhatian khusus dalam hal kinerja usahanya. Performa yang baik dapat menjaga aktivitas bisnis Bank Muamalat. Salah satu penilaian performa yang digunakan untuk menilai bank adalah FDR (Finance to Deposit Ratio). Penelitian ini dilakukan untuk melakukan pembuktian proyeksi terhadap FDR Bank muamalat mulai dari tahun 2019 – 2021. Kemudian penelitian ini menggambarkan nilai tren bank muamalat dari tahun 2019 – 2022. Penelitian ini menggunakan metode analisis deskriptif kuantitiatif dengan menggunakan data sekunder yaitu laporan keuangan Bank Muamalat tahun 2019 – 2022. Hasil dari penelitian ini adalah FDR Bank Muamalat dari tahun 2019 – 2022 menempati peringkat 1 sesuai dengan SE dari Bank Indonesia, nilai FDR Proyeksi tidak ada yang sesuai dengan nilai FDR aktual dari Bank Muamalat, Proyeksi tren nilai FDR yang disampaikan Lubis et al (2022) memiliki kemiripan yaitu tren menurun mulai dari tahun 2019 – 2021 dan nilai Tendensi FDR mulai memberikan tren positif pada tahun 2022.

This research aims to analyze the influence of return on assets (ROA), non-performing financing (NPF), and financing-to-deposit ratio (FDR) on murabahah financing at Islamic Commercial Banks (ICB). This quantitative research uses secondary data from the annual Islamic Banking Statistics (IBS) report published by the Financial Services Authority (FSA) for 2015-2021. The population and sample in this study consisted of all ICBs in Indonesia registered with the FSA, namely 15. The sampling technique used saturated samples. Meanwhile, the data used is the overall financial condition of ICB in the research year consisting of 12 months x 7 periods = 84 data. The data analysis technique uses the partial least square-structural equation model (PLS-SEM). The research results show that ROA does not influence murabahah financing, while NPF and FDR influence murabahah financing negatively and significantly. The implications of this research complement the existing theory, and practically, it can be a reference for Islamic banks in increasing ROA, reducing NPF, and increasing FDR through third-party funds so that murabahah financing can increase and more people are helped.

This study shows vertical profiles and spatial distribution of upper‐air icing frequency over the tropical Americas. We estimated the in‐flight icing (IFI) over Colombia using the Current Icing Product‐sonde‐A algorithm over two data sets: (1) vertical soundings of temperature and relative humidity and surface station data taken at 12 Coordinated Universal Time or UTC (07 Local Time or LT) on five sites and (2) ERA5 at 00, 06, 12 and 18 UTC (19, 01, 07 and 13 LT). In either case, icing was defined for IFI values exceeding 0.01. Results show that icing tends to occur between 550 and 300 hPa (4.5 and 8.6 km altitude), with a maximum at 500–550 hPa and monotonically decreasing to zero until reaching 300 hPa. Aeronautic reports were used to evaluate the total column IFI and a layer‐based IFI detection with a probability of detection of 87% and 71%, respectively. The annual cycle of IFI is modulated by the meridional migration of the Intertropical Convergence Zone (ITCZ) with a bimodal distribution with peaks during the rainiest seasons. Spatially, IFI hotspots are found in the Pacific, the Andes Mountains and the Amazonia regions of Colombia; the northern Colombia Caribbean region show lower IFI frequency with a relative maximum collocated over the Sierra Nevada de Santa Marta mountains. The IFI exhibits a strong diurnal cycle with a high between night‐time to early morning and a low around noon. [ABSTRACT FROM AUTHOR]

In Indonesia, the government encourages converting conventional regional development banks into sharia regional development banks. Such banks should become the driving force and the stimulator of a sharia ecosystem in the region, especially to support the development of regional economic potentials and to become a prosperous and peaceful country. This study aims to analyze the financial performance of regional development banks that have become sharia regional development banks to identify their ability to continue to provide economic growth in the region. Considering the results of previous studies, the authors conduct a comparative analysis of the financial performance of regional development banks that have converted to sharia banks using the following variables: return on assets (ROA), return on equity (ROE), loan-to-deposit ratio (LDR) / financing-to-deposit ratio (FDR), net interest margin (NIM) / net operating margin (NOM) and ratio of operating expenses to operating income (BOPO). The analysis aims to determine whether there is a significant difference in the financial performance between conventional and sharia regional development banks. The population in this study is the regional development bank, with a sample of 3 banks that have converted into sharia banks (Bank Aceh Shariah, Bank NTB Shariah, and Bank Riau Kepri Shariah). The study uses secondary bank data from quarterly financial reports on the banks' websites. The independent sample t-test is used to test the performance of conventional and sharia banks. The study results indicate no significant differences in the financial performance of regional development banks as measured using the financial ratio indicators ROA, ROE, and LDR. However, there are significant differences in measurements using the NIM and BOPO ratio indicators. Although the financial performance of sharia banks is still lower than that of conventional banks, they are showing an upward trend. [ABSTRACT FROM AUTHOR]

【Objective】 Soil moisture sensors have been increasingly used in different fields to measure soil water content at high temporal resolution, but its reliability depends on many factors. In this paper, we investigate the effect of soil salinity on their accuracy. 【Method】 The laboratory experiment was conducted at the Irrigation Test Station of the First Division of Xinjiang Alaer Corps. FDR and TDR sensors were used in the experiment. We compared five salinity treatments: 2, 3, 5, 7, 9 mS/cm; the soil moisture was adjusted to the field capacity followed by natural evaporation. The absolute error (AE), relative error (RE) and standard deviation (SD) were used to evaluate the accuracy and consistency of the sensors. 【Result】 Soil moisture and salinity both affected accuracy and consistency of the sensors. Without calibration, the accuracy of the CSF11 and ML2x sensors was high and measurements were consistent, while the EC-5 and TDR305H sensors were less accurate and consistent due to the combined influence of soil salinity and moisture. Calibration significantly improved the accuracy and consistence of all four sensors. 【Conclusion】 Considering accuracy and consistency, the expensive ML2x sensors worked best when salt content does not exceed 9 mS/cm. The less expensive CSF11 sensors also worked well when soil salt is low. The EC-5 sensors can measure soil moisture reasonably well for soil with moderate and high salinity. When the soil moisture is less than 20 cm3/cm3, TDR305H sensors is accurate and reliable.

The Covid-19 pandemic has become a major obstacle for sharia-based banks in maintaining their profitability without having to take out additional loans. The aim of this study is to investigate the impact of financial performance, as measured by OCR, CAR, FDR, and NPF proxies, on profitability by considering the Financial Leverage variable as a moderating factor in Sharia Commercial Banks. The population in this study includes all Sharia Commercial Banks that publish financial reports to the Financial Services Authority (OJK) for the 2018-2022 period. The sample obtained included 12 Sharia commercial banks that met the criteria based on. Data analysis used multiple linear regression methods for the fixed-effect model (FEM) selection panel data. The findings indicate that OCR and NPF have a significant Return on Assets (ROA), while CAR and FDR do not have a significant effect on ROA. In addition, through the Moderated Regression Analysis (MRA) test, it was found that DER acts as a moderating variable that influences the relationship between CAR, FDR, and NPF on ROA but does not influence the relationship between OCR and ROA. This research proves that financial leverage by considering debt can be an indicator for measuring financial performance towards profitability.

This study aims to empirically prove the effect of third party funds, capital adequacy ratio and financing to deposit ratio on profitability with non-performing financing as a moderating variable in the Islamic people's financing bank (BPRS) Bhakti Sumekar Sumenep. The sample in this research is quarterly financial reports and the data used are 40 companies' quarterly financial reports with data analysis method using multiple linear regression. The results of the study show that DPK, FDR and NPF have no effect on the profitability of the Islamic people's financing bank (BPRS) Bhakti Sumekar Sumenep. While CAR has an effect on ROA. The results of the analysis on the moderating variable show that NPF is not able to moderate the effect of DPK, CAR and FDR on ROA. [ABSTRACT FROM AUTHOR]

This research aims to examine the impact of bank-specific and macroeconomic factors on profitability (ROA and ROE) in BPRS in Indonesia and the role of FDR as an intervening variable. This research uses analytical techniques Partial Least Square Structural Equation Model (PLS-SEM). The population was obtained from BPRS data recorded by OJK during 2017-2021. The total of sample are 154 BPRS through purposive sampling. The results showed that bank-specific factors through the DER variable did not affect profitability, BOPO negatively affected profitability, and NOM affected profitability. While macroeconomic factors through the GDP-Prov and Unemp variables do not affect profitability. Furthermore, the FDR affects ROA and does not affect ROE. then bank-specific factors through the DER variable have a positive FDR, BOPO negatively affect FDR, and NOM does not affects FDR. Meanwhile, macroeconomic factors through GDP-Prov did not affect FDR and Unemp negatively affected FDR. FDR does not mediate the affect of DER, BOPO, NOM, GDP-Prov and Unemp on profitability. The conclution is in Partially, not all variables affect profitability and there is no mediating role of the FDR variable between bank-specific and macroeconomic factors on profitability.

This study aims to analyze and show the effect of return on equity (ROE), financing to deposit ratio (FDR), company size, size of the Islamic supervisory board (ISB), and company age on the disclosure of Islamic social reporting (ISR) in Islamic commercial banks (ICB) in the period 2018-2020. This quantitative study uses secondary data, namely annual reports of ICB. The population of this study is ICB registered with the financial services authority (FSA) in 2018-2020, totalling 14 ICB. The sampling technique uses a purposive sampling method so that 12 samples. Data analysis technique using multiple linear regression method with panel data. The results show that ROE, FDR, company size and age significantly affect ISR disclosure. Meanwhile, the size of the Islamic supervisory board does not affect ISR disclosure. Simultaneously ROE, FDR, firm size, size of the Sharia supervisory board, and firm age significantly affect ISR disclosure. This research can complement the existing theory and can be a reference for ICB management to improve the disclosure of social responsibility for the better.

Murabahah financing is the most preferred financing option among customers due to its low risk and its versatility for working capital, consumption, or investment purposes. However, there is a phenomenon observed in BTPN Shariah where the increase in Murabahah financing is not accompanied by a rise in profits. Furthermore, the lack of profit increase is suspected to be due to the low Financing to Debt Ratio (FDR). This research aims to understand how Murabahah financing and FDR influence the profitability of Islamic banks, with Non-Performing Financing (NPF) acting as a moderator. The research sample includes quarterly reports from BTPN Shariah for the period 2015-2022, using purposive sampling techniques. The study utilizes SPSS 25 for analysis, including multiple linear regression,and Moderating Regression Analysis (MRA). The test results indicate that Murabahah financing, when considered individually, has an impact on profitability, whereas the Financing to Debt Ratio does not affect profitability. When both Murabahah financing and FDR are considered together, they collectively influence profitability with a percentage of 71.2% before moderation by NPF. The MRA results suggest that Non-Performing Financing is unable to moderate the impact of the two independent variables, namely Murabahah financing and FDR, on profitability.

This manuscript reviews some recent and popular error control methods for tree structured hypothesis testing. We review a common setting/definition for hypotheses arranged in a tree structure and we discuss two common Type I errors present in multiple testing: family wise error rates (FWERs) and false discovery rate (FDR). We also contrast these methods with a recent development designed to control the false selection rate (FSR). We discuss the algorithms used to implement these error controls and the strategies used to navigate tree structures in light of these errors. We highlight the assumptions necessary in these strategies, summarize the available R software packages to implement these approaches, and show them at work on an example. This article is categorized under:Data: Types and Structure > Image and Spatial DataApplications of Computational Statistics > Genomics/Proteomics/GeneticsData: Types and Structure > Microarrays [ABSTRACT FROM AUTHOR]

Background & Aims:A DNA methylation (DNAm) signature derived from 353 CpG sites (the Horvath clock) has been proposed as an epigenetic measure of chronological and biological age. This epigenetic signature is accelerated in diverse tissue types in various disorders, including non-alcoholic steatohepatitis, and is associated with mortality. Here, we assayed whole blood DNAm to explore age acceleration in patients with primary sclerosing cholangitis (PSC). Methods:Using the MethylationEPIC BeadChip (850K) array, DNAm signatures in whole blood were analyzed in 36 patients with PSC enrolled in a 96-week trial of simtuzumab (Ishak F0-1, n = 13; F5-6, n = 23). Age acceleration was calculated as the difference between DNAm age and chronological age. Comparisons between patients with high and low age acceleration (≥ vs. < the median) were made and Cox regression evaluated the association between age acceleration and PSC-related clinical events (e.g. decompensation, cholangitis, transplantation). Results:Age acceleration was significantly higher in patients with PSC compared to a healthy reference cohort (median, 11.1 years, p

In this study low-input RNA-sequencing was used to annotate the molecular identity of endothelial cells isolated and immunopurified with CD144 microbeads. Using this technique, comparative gene expression profiling from healthy subjects and patients with type 2 diabetes mellitus identified both known and novel pathways linked with EC dysfunction. Modeling of diabetes by treating cultured ECs with high glucose identified shared changes in gene expression in diabetic cells. Overall, the data demonstrate how purified ECs from patients can be used to generate new hypotheses about mechanisms of human vascular disease.

The purpose of this study was to analyze the effect of performance ratios, namely capital adequacy ratio (CAR), non-performing financing (NPF), and financing to deposit ratio (FDR), on third-party funds (TPF) at Islamic commercial banks (ICB). Then, analyze the performance ratio and growth of TPF before and during the covid-19 pandemic on ICB. The method in this research uses a quantitative approach. Data collection uses secondary data in the form of documentation. The population of this study is all ICB registered with the financial services authority (FSA) for the 2019-2020 period. Sampling in this study uses purposive sampling. The data analysis technique used multiple linear regression analysis and comparison of paired samples. The results showed that partially CAR, NPF, and FDR did not affect the growth of TPF in ICB. However, CAR, NPF, and FDR simultaneously affect the growth of TPF in ICB. Then the comparison results show no difference in CAR, NPF, and FDR before and during the covid-19 pandemic. However, the growth of TPF shows a significant difference before and during the covid-19 pandemic.

MSME has a massive contribution to national economic development. In order to expand and strengthen the MSME sector, Islamic Commercial Banks as financial intermediary should consider some of the main factors before distributing their financing to the MSME sector. This study aims to identify and analyze the effect of NPF, FDR, Bank Size, and Covid-19 on MSME Financing at Shariah Rural Banks in Indonesia in the period of 2018-2021 both partially and simultaneously. This study uses a panel data approach where the data needed in this study are from 7 Indonesian Islamic Banks with 112 of total data quarterly. The data was collected from quarterly Islamic bank reports. The results of this study indicate that FDR and Bank Size variables have a positive significant effect on MSMEs Financing at Shariah Rural Banks. Meanwhile, NPF and the dummy variable Covid-19 have no significant effect on MSMEs Financing at Shariah Rural Banks. This study is expected to developing of the grand theory and knowledge on the impact of MSME Financing especially in the Shariah Rural Banks in Indonesia.

Crimes tend to concentrate in high-risk places known as crime hotspots. While the size and locations of such hotspots vary between different types of crime as would the underlying conditions that trigger each crime, the extent of overlaps between their hotspots is understudied. Using crime data from Chicago aggregated at the community-area and the census-tract levels, this paper investigates the patterns of overlapping hotspots between different crime types to see whether a specific group of crime types regularly form a joint cluster. Specifically, we identify statistically significant hotspots for each crime and, using the frequent-pattern-growth algorithm, analyse the frequency of each combination of crimes sharing their hotspot locations across the study area. Results suggest that crime hotspots form stable multi-layered colocations and that each area holds its subset: namely, the pervasive, primary colocations consisting of assault, battery and criminal damage to property, which are frequently joined by 7 additional (e.g. street robbery, motor vehicle theft, weapons violation) crimes to comprise secondary colocations, some of which evolving to an even larger, tertiary colocation of hotspots with up to 11 additional crime types (e.g. homicide, criminal sexual assault, narcotics) to form crime-riddled neighbourhoods. This multi-layered structure of colocations as well as the crime colocation diagrams that show the most representative crimes at each colocation size would improve our understanding of the association between different crime types and the crime indicators of other crimes. [ABSTRACT FROM AUTHOR]

The following outline deals with the Ukrainian edition of the book «Watching Darkness Fall: FDR, His Ambassadors, and the Rise of Adolf Hitler» by the attorney, political adviser, and former American ambassador to Luxembourg David MacKean (translated into Ukrainian by Yuliia Lazarenko). The book was originally published in 2021 (New York, St. Martin’s Press), the Ukrainian version came out in 2022 (Kyiv, Laboratoriya). «Watching Darkness Fall…» shows how the international situation in the 1930s was changing tremendously from the perspective of William Bullitt, William Dodd, Breckinridge Long and Joseph Kennedy – four Franklin Delano Roosevelt’s ambassadors in Moscow (later in Paris), Berlin, Rome, and London, respectively. Through the stories of the United States ambassadors to European countries and their relationship with the American president, the book looks at the global road to World War II and its first years (the main part deals with the events between 1933 and 1941). Besides covering international relations issues in this period, McKean’s research also touches on such topics as the domestic policy of FDR’s administration – the «New deal», political processes (elections, political appointments, etc.) in the USA in the 1930s. Among the internal affairs of other countries, special attention is paid to the rise of the Third Reich in Germany. The whole book consists of an epilogue, 41 main sections and a prologue. This study is broader than a traditional book review. That’s because the author is trying to identify and present to the Ukrainian readers the main problems and political figures featured in McKean’s book. Of no less importance is to emphasize the context in which the Ukrainian edition of «Watching Darkness Fall…» has appeared, as well as the value of this book for the American studies development in Ukraine.

Abstract Background Genome-wide association studies (GWAS) are limited in power to detect associations that exceed the stringent genome-wide significance threshold. This limitation can be alleviated by leveraging relevant auxiliary data, such as functional genomic data. Frameworks utilising the conditional false discovery rate have been developed for this purpose, and have been shown to increase power for GWAS discovery whilst controlling the false discovery rate. However, the methods are currently only applicable for continuous auxiliary data and cannot be used to leverage auxiliary data with a binary representation, such as whether SNPs are synonymous or non-synonymous, or whether they reside in regions of the genome with specific activity states. Results We describe an extension to the cFDR framework for binary auxiliary data, called “Binary cFDR”. We demonstrate FDR control of our method using detailed simulations, and show that Binary cFDR performs better than a comparator method in terms of sensitivity and FDR control. We introduce an all-encompassing user-oriented CRAN R package ( https://annahutch.github.io/fcfdr/ ; https://cran.r-project.org/web/packages/fcfdr/index.html ) and demonstrate its utility in an application to type 1 diabetes, where we identify additional genetic associations. Conclusions Our all-encompassing R package, fcfdr, serves as a comprehensive toolkit to unite GWAS and functional genomic data in order to increase statistical power to detect genetic associations.

Profitability as a benchmark in assessing profit becomes very important in checking whether a company has run its business efficiently, a bank uses ROA or Return on Assets as a measure of bank profitability. PT Bank BCA Syariah, Tbk, which is one of the Islamic banks in Indonesia with stable ROA growth, can be used as a benchmark for the growth of Islamic banking in Indonesia. This study aims to determine internal and external factors that can affect the profitability of PT Bank BCA Syariah, Tbk for the period 2012 to 2021. Internal factors use the Financing to Deposit Ratio (FDR), Non Performing Financing (NPF) and Operational costs and operating income (BOPO). Then on external factors using the BI Rate and GDP, using multiple linear regression analysis techniques. Results of this study shows that FDR and BOPO has an effect on ROA, meanwhile NPF, BI Rate and GDP has no effect. This research is expected to be useful for the development of Islamic banks in Indonesia, by knowing the factors that has an effect on profitability of Islamic banks.

Background: The number of aircraft-assisted suicides can only be considered a rough estimate because it is difficult and, at times, impossible to identify all cases of suicide. Methods: Four recent reports of accidents occurring in 1997 in Indonesia, 1999 in Massachusetts in the United States, 2013 in Namibia, and 2015 in France related to commercial aircraft-assisted suicides were analyzed. This analysis relied on data extracted from the accident reports that supported aircraft-assisted suicide from the: (a) cockpit voice recorder (CVR) and flight data recorder (FDR), (b) medical history, (c) psychosocial history, (d) toxicology, (e) autopsy, and (f) any methodology that utilized aviation medicine. There are some limitations in this study. Although all analyzed accident investigations followed ICAO Annex 13 guidelines, there is variability in their accident investigations and reporting. In addition, accident investigation reports represent accidents from 1997 to 2015, and during this time, there has been a change in the way accidents are reported. The nature of this analysis is explorative. The aim was to identify how the various aircraft accident investigators concluded that the accidents were due to suicidal acts. Results: In all four accident reports, FDR data were available. CVR data were also available, except for one accident where CVR data were only partially available. Comprehensive medical and psychosocial histories were available in only one of four of the accident reports. Conclusion: To prevent accidents involving commercial aircraft, it is necessary to identify the causes of these accidents to be able to provide meaningful safety recommendations. A detailed psychological autopsy of pilots can and likely will assist in investigations, as well as generate recommendations that will substantially contribute to mitigating accidents due to pilot suicide. Airborne image recording may be a useful tool to provide additional information about events leading up to a crash and thus assist in accident investigations. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has had a tremendous impact on the Indonesian economy. The physical distancing policy to reduce the risk of the spread of the Covid-19 virus has resulted in increased credit risk and decreased bank profitability. This study aims to determine the effect of CAR, FDR, BOPO, company size and GDP on the profitability of Islamic commercial banks in Indonesia with NPF as a moderating variable during the pandemic. This study uses time series data taken from the semiannual financial statements of Islamic commercial banks for the period 2019 to 2020. This research method uses descriptive analysis methods and inferential analysis processed with smartpls 3.2.8. The research population used were 14 Islamic commercial banks registered with the OJK. The research sample used was 11 Islamic commercial banks obtained by purposive sampling method. The results showed that CAR had no effect on ROA, FDR had a positive effect on ROA, BOPO and firm size had a negative effect on ROA, GDP had no effect on ROA. NPF is able to moderate the effect of CAR, FDR, and BOPO on ROA but NPF is not able to moderate firm size and GDP on ROA. [ABSTRACT FROM AUTHOR]