Miracle-dz/UniFAR-FTUs huggingface dataset:
Subjective p intervals researchers underestimate the variability of p values over replication

Suppose you obtain p = . 02 in an experiment, then replicate the experiment with new samples. What p value might you obtain, and what interval has an 80% chance of including that replication p? Under conservative assumptions the answer is, perhaps surprisingly (.0003, .30). The authors report three email surveys that asked authors of articles published in leading journals in psychology, medicine, or statistics to estimate such intervals. Overall response rate (7%) was low, but responses from 360 researchers gave intervals with an average 40% to 50% chance of including replication p, rather than the target 80%. Results were similar for all three disciplines. Respondents generally found the task unfamiliar and difficult. There was great variability over respondents, but almost all of them gave intervals that were too short. This widespread, and often severe, underestimation of the variability of p may help to explain why researchers place too much interpretive weight on single p values.
The Human Lung Cell Atlas - A high-resolution reference map of the human lung in health and disease.

Lung disease accounts for every sixth death globally. Profiling the molecular state of all lung cell types in health and disease is currently revolutionizing the identification of disease mechanisms and will aid the design of novel diagnostic and personalized therapeutic regimens. Recent progress in high-throughput techniques for single-cell genomic and transcriptomic analyses has opened up new possibilities to study individual cells within a tissue, classify these into cell types, and characterize variations in their molecular profiles as a function of genetics, environment, cell-cell interactions, developmental processes, ageing or disease. Integration of these cell state definitions with spatial information allows the in-depth molecular description of cellular neighborhoods and tissue microenvironments including the tissue resident structural and immune cells, the tissue matrix as well as the microbiome. The Human Cell Atlas consortium aims to characterize all cells in the healthy human body, and has prioritized lung tissue as one of the flagship projects. Here, we present the rationale, the approach and the expected impact of a Human Lung Cell Atlas.
Selective-area growth of indium nitride nanowires on gold-patterned Si(100) substrates

This letter reports the synthesis of indium nitride (InN) nanowires on gold-patterned silicon substrates in a controlled manner using a method involving thermal evaporation of pure indium. The locations of these InN nanowires were controlled by depositing gold in desired areas on the substrates. Scanning electron microscopy and transmission electron microscopy investigations showed that the InN nanowires are single crystals with diameters ranging from 40 to 80 nm, and lengths up to 5 μm. Energy dispersive x-ray spectrometry showed that the ends of the nanowires are composed primarily of Au, and the rest of the nanowires were InN with no detectable Au incorporations. The Raman spectra showed peaks at 445, 489, and 579 cm−1, which are attributed to the A1(transverse optical), E2, and A1(longitudinal optical) phonon modes of the wurtzite InN structure, respectively. Photoluminescence spectra of the InN nanowires showed a strong broad emission peak at 1.85 eV.
Physical design guidelines to minimize area-specific ON-resistance for rated ON-current and breakdown voltage of GaN power HEMTs

In this article, we report on the development of an analytical model to estimate area-specific ON-state resistance (R ds,on) of GaN-based power high electron mobility transistor (HEMT) using rated device specifications—ON-state drain current (I ON) and maximum operating drain-to-source voltage (V DSO)—as input parameters. The rated I ON and V DSO are considered as fractions k and S, of the maximum possible drain current (I DS,max) and breakdown voltage (V BR), respectively, deliverable by the power device. The developed model is utilized to obtain the optimal physical design space parameters for a comb-like power HEMT design. Due consideration has been given to the trade-off between R ds,on and area-specific R ds,on of the transistor, device processing limitations for all the physical device parameters. The developed model has been validated with experimental results of prior literature. Our calculations impose a lower-bound for the best possible R ds,on as well as the area-specific on-resistance product (R ds,on × AA) that can be obtained for a given starting channel sheet resistance in the comb architecture for a desired I ON − V DSO rating.
Beam pointing error as a significant design parameter for satellite-borne, free-space optical communication systems

The issue of pointing errors between satellite-borne, free-space optical communication systems is examined. The single-axis pointing error distribution is described as a Gaussian function and is used to define a probability of burst error for the pointing subsystem. A relationship between the rms standard deviation of the pointing error distribution, the probability of burst error, and the Airy far field beamwidth is deduced. It is shown that the system beamwidth and antenna diameter are limited by the probability of burst error. Additionally, it is found that typical terminal designs have less temporal communication system availability than one specifically designed to account for the influence of burst errors.
Comparative Analysis of Volatile and Non-Volatile Metabolites Derived from Bacillus subtilis Strains Producing Different Levels of Biogenic Amines

Biogenic amines (BAs), which are mainly generated by the microbial decarboxylation of amino acids, are important nitrogen compounds in fermented foods because of their toxicology. However, amino acids, the precursors of BAs, also play an important role in generating volatile and non-volatile metabolites, which are strongly associated with quality indicators for foods. Bacillus subtilis is one of dominant fermentative microorganism in various fermented foods and is well known as a BA-producing bacterium. In this study, B. subtilis strains which have different BAs-producing capacities, higher level of BAs production strain (BH) and lower level of BAs production strain (BL), were applied to compare the formations of volatile and non-volatile metabolite profiles according to cultivation times. In this study, histamine, putrescine, and spermidine were detected in all strains, however, 2-phenylethylamine was detected only in BH. Partial least squares discriminant analysis (PLS-DA) was applied to investigate the difference of metabolic profiles according to strains. In BH, some amino acids (phenylalanine, leucine, and threonine) and related volatile metabolites (3-methylbutanoic acid, pyrazines, styrene, and 1H-indole) were produced higher levels. On the other hand, BL produced significantly higher contents of metabolites associated with metabolism of fatty acids and nucleotides. It is necessary to consider the formation of metabolites in terms of quality as well as that of BAs during fermentation.
Prevalence of type 2 diabetes complications and its association with diet knowledge and skills and self‐care barriers in Tabriz, Iran: A cross‐sectional study

Diabetes can lead to multiple complications that can reduce the quality of life, impose additional costs on the healthcare systems and ultimately lead to premature death. Proper self‐care in diabetic patients can impede or delay the onset of diabetes complications. This study aimed to investigate diabetes complications and their association with diet knowledge, skills, and self‐care barriers.
Topoplogical Structured Learning for Assessment of Unilateral Spatial Neglect

This paper presents an immersive virtual reality (VR) system for assessment of unilateral spatial neglect (USN). USN is defined by the inability for a person to perceive stimuli on one side of the body or environment that is not due to a lack of sensation. In clinical practice, paper-and-pencil tests are used as the quick assessments. However, the sensitivity of these tests is not sufficient for USN assessment in activities of daily living. Thus, VR systems and multimodal sensing systems have been applied to more sensitive diagnosis for USN. In this study, we aim to propose a method to extract specific features of USN patients in behavioral and cognitive levels.
The void spectrum in two-dimensional numerical simulations of gravitational clustering

An algorithm for deriving a spectrum of void sizes from two-dimensional high-resolution numerical simulations of gravitational clustering is tested, and it is verified that it produces the correct results where those results can be anticipated. The method is used to study the growth of voids as clustering proceeds. It is found that the most stable indicator of the characteristic void 'size' in the simulations is the mean fractional area covered by voids of diameter d, in a density field smoothed at its correlation length. Very accurate scaling behavior is found in power-law numerical models as they evolve. Eventually, this scaling breaks down as the nonlinearity reaches larger scales. It is shown that this breakdown is a manifestation of the undesirable effect of boundary conditions on simulations, even with the very large dynamic range possible here. A simple criterion is suggested for deciding when simulations with modest large-scale power may systematically underestimate the frequency of larger voids.
Simulation of 2D External Viscous Flows by Means of a Domain Decomposition Method

Two-dimensional external viscous flows are numerically approximated by means of a domain decomposition technique which combines a vortex method and a finite differences method. The vortex method is used in the flow region which is dominated by convective effects, whereas the finite differences method is used in the flow region where viscous diffusion effects are dominant. Meanwhile, a new vortex method which is suitable for approximating first-order linear hyperbolic problems supplemented with Dirichlet boundary conditions is presented. Comparison with numerical and experimental data show that the method is well adapted for calculating two-dimensional external flows at moderate Reynolds numbers.
Time-Dependent Systematic Biases in Inferring Ice Cloud Properties from Geostationary Satellite Observations

Geostationary satellite-based remote sensing is a powerful tool to observe and understand the spatiotemporal variation of cloud optical-microphysical properties and their climatologies. Solar reflectances measured from the Advanced Baseline Imager (ABI) instruments aboard Geostationary Operational Environmental Satellites 16 and 17 correspond to different spatial pixel resolutions, from 0.5 km in a visible band, up to 2 km in infrared bands. For multi-band retrievals of cloud properties, reflectances with finer spatial resolution need to be resampled (averaged or sub-sampled) to match the coarsest resolution. Averaging all small pixels within a larger pixel footprint is more accurate but computationally demanding when the data volume is large. Thus, NOAA operational cloud products incorporate sub-sampling (selecting one high-resolution pixel) to resample the reflectance data, which could cause potential retrieval biases. In this study, we examine various error sources of retrieval biases of cloud optical thickness (COT) and cloud effective radius (CER) caused by sub-sampling, including the solar zenith angle, viewing zenith angle, pixel resolutions, and cloud types. CER retrievals from ice clouds based on sub-sampling have larger biases and uncertainties than COT retrievals. The relative error compared to pixel averaging is positive for clouds that have small COT or CER, and negative for clouds that have large COT or CER. The relative error of COT decreases as the pixel resolution becomes coarser. The COT retrieval biases are attributed mainly to cirrus and cirrostratus clouds, while the largest biases of CER retrievals are associated with cirrus clouds.
microRNAs profiling of small extracellular vesicles from midbrain tissue of Parkinson’s disease

Small extracellular vesicles (sEVs) are generated by all types of cells during physiological or pathological conditions. There is growing interest in tissue-derived small extracellular vesicles (tdsEVs) because they can be isolated from a single tissue source. Knowing the representation profile of microRNA (miRNA) in midbrain tissue–derived sEVs (bdsEVs) and their roles is imperative for understanding the pathological mechanism and improving the diagnosis and treatment of Parkinson’s disease (PD). bdsEVs from a rat model of PD and a sham group were separated and purified using ultracentrifugation, size-exclusion chromatography (SEC), and ultrafiltration. Then, miRNA profiling of bdsEVs in both groups was performed using next-generation sequencing (NGS). The expression levels of 180 miRNAs exhibited significant differences between the two groups, including 114 upregulated and 66 downregulated genes in bdsEVs of PD rats compared with the sham group (p < 0.05). Targets of the differentially expressed miRNAs were predicted by miRanda and RNAhybrid, and their involvement in the signaling pathways and cellular function has been analyzed through the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO). Furthermore, we explored the expression levels of miR-103-3p, miR-107-3p, miR-219a-2-3p, and miR-379-5p in bdsEVs, sEVs derived from plasma, and plasma of both groups of rats. Interestingly, the expression levels of miR-103-3p, miR-107-3p, miR-219a-2-3p, and miR-379-5p were elevated in bdsEVs and sEVs from plasma; in contrast, their expression levels were decreased in plasma of the rat model of PD. In summary, miRNAs may play a significant role in the onset and development of PD, and miRNAs need to be selected carefully as a research subject for exploring the pathological mechanism and the potential therapeutic targets and diagnostic markers of PD.
Blockchain application within Net-Zero Energy Factories. A cost-benefit analysis for a German carpentry

The planning of Net-Zero Energy Factories might contribute to the better integration of power generated by volatile renewable energy sources into manufacturing systems. However, the investments needed for operating a Net-Zero Energy Factory might dissuade facility operators. The application of a blockchain might represent the missing element to make Net-Zero Energy Factories an attractive solution. The aim of this study is to present a cost-benefit analysis to plan a German carpentry as a Net-Zero Energy Factory. Businesses can increase the transparency of their energy usage by storing the Net-Zero Energy Factory's information, such as energy production, consumption and manufactured goods, in a blockchain. The increase in transparency can help to satisfy the regulatory compliance of green energy set by their respective governments. It is also helpful for businesses to demand higher prices while selling their products to customers, retailers and government projects.
The acceptability and perceived use of HIV self-testing among technical vocational education and training students in Limpopo province

Background Human immunodeficiency virus self-testing (HIVST) is a most recent testing modality to reach young people to test for HIV, due to their increased vulnerability of contracting HIV. Limited literature is available describing sexual behaviours and the acceptability of HIVST and its perceived use among students. Aim The aim of this study was to assess the acceptability and perceived use of HIV self-testing among students in Limpopo province, South Africa. Setting The study was conducted in Limpopo province, at a technical and vocational education and training (TVET) college. Methods A cross-sectional study was conducted with a sample of 396 students recruited from a TVET college. Results The mean age of the students was 22.9 years, with the majority of the students being female (77.2%). The majority (81.4%) of the students sampled reported regular sexual activity. Sixty per cent of the students had used condoms during their last sexual encounter. The acceptability of HIVST was high, with more women showing the willingness to take up HIVST (82.5%). Being sexually active (odds ratio [OR] 1.23; (confidence interval [CI]: 2.14 -6.94; p = 0.000), a number of sexual partners (OR 1.045; CI: 1.98 -10.02; p = 0.000) and condom use during the last sexual encounter (OR 0.62; CI: 3.81 -9.59; p = 0.000) were factors associated with HIVST. Conclusion The high acceptability of HIV shows a need for innovative demand creation in sexual and reproductive health (SRH) programming. Contribution The study contributes to the body of literature about the acceptability and perceived use of HIV self-testing among students. Findings can be used for improving HIVST interventions using innovative approaches.
Non-Invasive Imaging in Diabetic Cardiomyopathy

There is increasing recognition of a specific diabetic cardiomyopathy beyond ischemic cardiomyopathy, which leads to structural and functional myocardial abnormalities. The aim of this review is to summarize the recent literature on diagnostic findings and prognostic significance of non-invasive imaging including echocardiography, nuclear imaging, computed tomography and cardiovascular magnetic resonance in diabetic cardiomyopathy.
Linguistic Analysis for Identifying Depression and Subsequent Suicidal Ideation on Weibo: Machine Learning Approaches

Depression is one of the most common mental illnesses but remains underdiagnosed. Suicide, as a core symptom of depression, urgently needs to be monitored at an early stage, i.e., the suicidal ideation (SI) stage. Depression and subsequent suicidal ideation should be supervised on social media. In this research, we investigated depression and concomitant suicidal ideation by identifying individuals’ linguistic characteristics through machine learning approaches. On Weibo, we sampled 487,251 posts from 3196 users from the depression super topic community (DSTC) as the depression group and 357,939 posts from 5167 active users on Weibo as the control group. The results of the logistic regression model showed that the SCLIWC (simplified Chinese version of LIWC) features such as affection, positive emotion, negative emotion, sadness, health, and death significantly predicted depression (Nagelkerke’s R2 = 0.64). For model performance: F-measure = 0.78, area under the curve (AUC) = 0.82. The independent samples’ t-test showed that SI was significantly different between the depression (0.28 ± 0.5) and control groups (−0.29 ± 0.72) (t = 24.71, p < 0.001). The results of the linear regression model showed that the SCLIWC features, such as social, family, affection, positive emotion, negative emotion, sadness, health, work, achieve, and death, significantly predicted suicidal ideation. The adjusted R2 was 0.42. For model performance, the correlation between the actual SI and predicted SI on the test set was significant (r = 0.65, p < 0.001). The topic modeling results were in accordance with the machine learning results. This study systematically investigated depression and subsequent SI-related linguistic characteristics based on a large-scale Weibo dataset. The findings suggest that analyzing the linguistic characteristics on online depression communities serves as an efficient approach to identify depression and subsequent suicidal ideation, assisting further prevention and intervention.
Automated coronary plaque characterization with intravascular ultrasound backscatter: In vivo and ex vivo validation

Atherosclerosis is considered both a systemic and local disease. Current diagnostic tools do not allow adequate in vivo characterization of lesions. Intravascular ultrasound (IVUS) backscatter analysis has displayed the potential for real‐time plaque characterization by advanced spectral analysis. One hundred‐fifteen plaques from 51 coronary arteries were imaged ex vivo at physiologic pressure, using 20‐MHz IVUS transducers. After imaging, the arteries were pressure fixed and matching histology was collected. Regions were selected from histology and corresponding IVUS data were used to build the ‘‘VH’’ plaque classification system using spectral analysis and classification trees. VH images were validated ex vivo by comparison with histology via 407 selected regions that comprised 162 fibrous, 84 fibro‐fatty, 69 necrotic‐core, and 92 dense‐calcium regions. The overall predictive accuracies were 92.9%, 93.4%, 94.3%, and 99.3% respectively, with sensitivities and specificities ranging from 84% to 99%. Reprod.
Entinostat-Bortezomib Hybrids against Multiple Myeloma

Although proteasome inhibitors have emerged as the therapeutic backbone of multiple myeloma treatment, patients often relapse and become drug refractory. The combination between proteasome and histone deacetylase inhibitors has shown to be more efficient compared to monotherapy by enhancing the anti-myeloma activity and improving the patient’s lifetime expectancy. Hybrid molecules, combining two drugs/pharmacophores in a single molecular entity, offer improved effectiveness by modulating more than one target and circumventing differences in the pharmacokinetic and pharmacodynamic profiles, which are the main disadvantages of combination therapy. Therefore, eleven histone deacetylase-proteasome inhibitor hybrids were synthesized, combining pharmacophores of entinostat and bortezomib. Compound 3 displayed the strongest antiproliferative activity with an IC50 value of 9.5 nM in the multiple myeloma cells RPMI 8226, 157.7 nM in the same cell line resistant to bortezomib, and 13.1 nM in a 3D spheroid model containing multiple myeloma and mesenchymal stem cells. Moreover, the compound inhibited 33% of histone deacetylase activity when RPMI 8226 cells were treated for 8 h at 10 µM. It also inhibited the proteasome activity with an IC50 value of 23.6 nM.
Review of counterfactual land change modeling for causal inference in land system science

ABSTRACT Land change models are important tools for land systems analysis, but their potential for causal inference using a counterfactual approach remains underdeveloped. This paper reviews the state of counterfactual land change modeling with the intent of causal inference. All of the reviewed studies promoted the value of creating ‘counterfactual worlds’ via simulation modeling to untangle complex causation in land systems in order to assess the effects of specific interventions and/or historical events. Several models used counterfactual analysis to challenge prevailing assumptions motivating past policy interventions, while others isolated the spatial heterogeneity of policy effects. The review also highlights methodological limitations and proposes best practices specific to counterfactual land change modeling for causal inference, such as ensemble approaches and multiple calibration-validation iterations. Counterfactual modeling is still underdeveloped in land system science, but it holds promise for advancing causal inference for some of the most challenging to study land change phenomenon.