Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating the proportion of signal variables under arbitrary covariance dependence

Accurately estimating the proportion of signals hidden in a large amount of noise variables is of interest in many scientific inquires. In this paper, we consider realistic but theoretically challenging settings with arbitrary covariance dependence between variables. We define mean absolute correlation (MAC) to measure the overall dependence strength and investigate a family of estimators for their performances in the full range of MAC. We explicit the joint effect of MAC and signal sparsity on the performances of the family of estimators and discover that the most powerful estimator under independence is no longer most effective when the MAC dependence is strong enough. Motivated by the theoretical insight, we propose a new estimator to better adapt to arbitrary covariance dependence. The proposed method compares favorably to several existing methods in extensive finite-sample settings with strong to weak covariance dependence and real dependence structures from genetic association studies.
Scanning the Cycle: Timing-based Authentication on PLCs

Programmable Logic Controllers (PLCs) are a core component of an Industrial Control System (ICS). However, if a PLC is compromised or the commands sent across a network from the PLCs are spoofed, consequences could be catastrophic. In this work, a novel technique to authenticate PLCs is proposed that aims at raising the bar against powerful attackers while being compatible with real-time systems. The proposed technique captures timing information for each controller in a non-invasive manner. It is argued that Scan Cycle is a unique feature of a PLC that can be approximated passively by observing network traffic. An attacker that spoofs commands issued by the PLCs would deviate from such fingerprints. To detect replay attacks a PLC Watermarking technique is proposed. PLC Watermarking models the relation between the scan cycle and the control logic by modeling the input/output as a function of request/response messages of a PLC. The proposed technique is validated on an operational water treatment plant (SWaT) and smart grid (EPIC) testbeds. Results from experiments indicate that PLCs can be distinguished based on their scan cycle timing characteristics.
Jeans modelling of axisymmetric galaxies with multiple stellar populations

We present the theoretical framework to efficiently solve the Jeans equations for multi-component axisymmetric stellar systems, focusing on the scaling of all quantities entering them. The models may include an arbitrary number of stellar distributions, a dark matter halo, and a central supermassive black hole; each stellar distribution is implicitly described by a twoor three-integral distribution function, and the stellar components can have different structural (density profile, flattening, mass, scale-length), dynamical (rotation, velocity dispersion anisotropy), and population (age, metallicity, initial mass function, mass-to-light ratio) properties. In order to determine the ordered rotational velocity and the azimuthal velocity dispersion fields of each component, we introduce a decomposition that can be used when the commonly adopted Satoh decomposition cannot be applied. The scheme developed is particularly suitable for a numerical implementation; we describe its realisation within our code JASMINE2, optimised to maximally exploit the scalings allowed by the Poisson and the Jeans equations, also in the post-processing procedures. As applications, we illustrate the building of three multi-component galaxy models with two distinct stellar populations, a central black hole, and a dark matter halo; we also study the solution of the Jeans equations for an exponential thick disc, and for its multi-component representation as the superposition of three Miyamoto-Nagai discs. A useful general formula for the numerical evaluation of the gravitational potential of factorised thick discs is finally given.
Graph based Data Dependence Identifier for Parallelization of Programs

Automatic parallelization improves the performance of serial program by automatically converting to parallel program. Automatic parallelization typically works in three phases: check for data dependencies in the input program, perform transformations, and generate the parallel code for target machine. Though automatic parallelization is beneficial, it is not done as a part of compiling process because of the time complexity of the data dependence tests and transformation techniques. Data dependencies arise because of data access from memory required for the execution of instructions of the program. In a program, memory is allocated for variables like scalars, arrays and pointers. As of now, different techniques are used to identify data dependencies in scalars, arrays and pointers in a program. In this paper, we propose a graph based Data Dependence Identifier (DDI), which is capable of identifying all types of data dependencies that arise in all types of variables, in polynomial time. In our proposed DDI model, for identifying data dependence in a program, we represent a program as graph. Though many graphical representation of program exist, our approach of representing a program as graph takes a different approach. Also using our DDI model, one can perform basic transformations like dead code elimination, constant propagation, and induction variable detection.
A Reinforcement learning method for Optical Thin-Film Design

Machine learning, especially deep learning, is dramatically changing the methods associated with optical thin-film inverse design. The vast majority of this research has focused on the parameter optimization (layer thickness, and structure size) of optical thin-films. A challenging problem that arises is an automated material search. In this work, we propose a new end-to-end algorithm for optical thin-film inverse design. This method combines the ability of unsupervised learning, reinforcement learning(RL) and includes a genetic algorithm to design an optical thin-film without any human intervention. Furthermore, with several concrete examples, we have shown how one can use this technique to optimize the spectra of a multi-layer solar absorber device.
Simultaneous and sensitive analysis of Ag(I), Mn(II), and Cr(III) in aqueous solution by LIBS combined with dispersive solid phase micro-extraction using nano-graphite as an adsorbent

In the present research, dispersive solid phase micro-extraction was combined with laser induced breakdown spectroscopy for the first time to achieve matrix conversion and preconcentration of Ag+, Mn2+ and Cr3+ in liquid samples. Nano-graphite was selected as a novel adsorbent due to its superior adsorption ability, water solubility and lower cost compared with carbon nanotubes and graphene. Sodium diethyldithiocarbamate was used as a complexing reagent to enhance the interaction between nano-graphite and metal ions. After adsorption, the nano-graphite powder was immobilized by mixing with commercial epoxy adhesive before LIBS analysis instead of the traditional tableting method to solve the problem that some carbonaceous materials are difficult to be tableted. Under optimized experimental conditions, the calibration curves were built in the range of 0.1–1.2 mg L−1 and good linearity (R squared better than 0.980 for all of the three target elements) can be obtained. The detection limits of Ag+, Mn2+ and Cr3+ were 16.59 ng mL−1, 10.85 ng mL−1 and 9.51 ng mL−1 respectively. In real sample analyses, the recoveries of three elements at different concentration levels were all in the range of 92.66–105.80% and the relative standard deviations of parallel samples were less than 8.98%.
A Case-Control Study of Prone Positioning in Awake and Nonintubated Hospitalized Coronavirus Disease 2019 Patients

Supplemental Digital Content is available in the text. Objectives: To determine the association between prone positioning in nonintubated patients with coronavirus disease 2019 and frequency of invasive mechanical ventilation or inhospital mortality. Design: A nested case-matched control analysis. Setting: Three hospital sites in Bronx, NY. Patients: Adult coronavirus disease 2019 patients admitted between March 1, 2020, and April 1, 2020. We excluded patients with do-not-intubate orders. Cases were defined by invasive mechanical ventilation or inhospital mortality. Each case was matched with two controls based on age, gender, admission date, and hospital length of stay greater than index time of matched case via risk-set sampling. The presence of nonintubated proning was identified from provider documentation. Intervention: Nonintubated proning documented prior to invasive mechanical ventilation or inhospital mortality for cases or prior to corresponding index time for matched controls. Measurements and Main Results: We included 600 patients, 41 (6.8%) underwent nonintubated proning. Cases had lower Spo2/Fio2 ratios prior to invasive mechanical ventilation or inhospital mortality compared with controls (case median, 97 [interquartile range, 90–290] vs control median, 404 [interquartile range, 296–452]). Although most providers (58.5%) documented immediate improvement in oxygenation status after initiating nonintubated proning, there was no difference in worst Spo2/Fio2 ratios before and after nonintubated proning in both case and control (case median Spo2/Fio2 ratio difference, 3 [interquartile range, –3 to 8] vs control median Spo2/Fio2 ratio difference, 0 [interquartile range, –3 to 50]). In the univariate analysis, patients who underwent nonintubated proning were 2.57 times more likely to require invasive mechanical ventilation or experience inhospital mortality (hazard ratio, 2.57; 95% CI, 1.17–5.64; p = 0.02). Following adjustment for patient level differences, we found no association between nonintubated proning and invasive mechanical ventilation or inhospital mortality (adjusted hazard ratio, 0.92; 95% CI, 0.34–2.45; p = 0.86). Conclusions: There was no significant association with reduced risk of invasive mechanical ventilation or inhospital mortality after adjusting for baseline severity of illness and oxygenation status.
First person – Xin Huang

ABSTRACT First Person is a series of interviews with the first authors of a selection of papers published in Biology Open, helping early-career researchers promote themselves alongside their papers. Xin Huang is first author on ‘Dissecting dynamics and differences of selective pressures in the evolution of human pigmentation’, published in BiO. Xin conducted the research described in this article while a PhD student in Li Jin, Yungang He's laboratory, Shanghai, China. He is now a Postdoctoral Research Associate in the lab of Ryan Gutenkunst at University of Arizona, Tucson, AZ, USA, investigating new methods and tools to quantify natural selection from large-scale population genomic data.
Construction and validation of an N6-methyladenosine-associated prognostic signature in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is among the most common types of cancer that threat the public health worldwide. N6-methyladenosine (m6A) RNA methylation is associated with cancer initiation and progression, and is dynamically regulated by m6A RNA methylation-associated genes. However, little is known about the expression status and the prognostic value of m6A-associated genes in HCC. The present study aimed to identify the expression profiling pattern and clinical significance of m6A-associated genes in HCC. Consensus clustering analysis was performed to identify the clusters of HCC with different clinical outcomes. A prognostic signature built by the least absolute shrinkage and selection operator Cox regression model was utilized to discover subtypes associated with different clinical outcomes of patients with HCC in the discovery cohort from The Cancer Genome Atlas. The differences between subgroups were characterized in terms of epigenetic dysregulation and somatic mutation frequencies. The International Cancer Genome Consortium cohort and two independent cohorts from the meta-Gene Expression Omnibus database were used for external validation. Most of the m6A-associated genes were upregulated and involved in the prognosis and malignancy of HCC. A four-gene prognostic signature revealed two HCC subtypes (namely, high- and low-risk group) that was associated with different clinical outcomes. Patients in the high-risk group were accompanied with increased epigenetic silencing and significant mutations in TP53 and FLG, while ALB was frequently mutated in the low-risk group. In conclusion, an m6A-based signature was constructed to predict the prognosis of patients with HCC, which may provide a tool for reliable prognosis assessment for clinicians, and aid clinical treatment decision-making.
Splenic Infarction in a Postpartum Patient with COVID-19

Thrombotic events have been reported in patients with coronavirus disease 2019 (COVID-19). Pregnant and postpar-tumpatients are also known tobehypercoagulable and those with COVID-19 may therefore be at an even higher risk of thrombotic complications. Here, we discuss a postpartum patient with COVID-19 who developed an isolated splenic infarction. While describing a rare thrombotic event, this case serves to alert physicians to the higher risk of thrombosis in pregnant or postpartum patients with COVID-19. A
Point defects in Si thin films grown by molecular beam epitaxy

Depth profiles of vacancylike defects have been determined by positron annihilation spectroscopy in 200‐nm‐thick Si films grown by molecular beam epitaxy on Si(100) substrates at growth temperatures Tgrowth=200–560 °C. The line shape of the radiation emitted from implanted positrons annihilating in the near‐surface region of a solid gives quantitative, depth‐resolved information on defect concentrations in a nondestructive way. In particular, the method is sensitive to vacancylike defects in a concentration range inaccessible to electron microscopy or ion scattering, but important for electrical device characteristics. The sensitivity limit for these defects in the present experiments is estimated as 5×1015 cm−3. Films grown at Tgrowth≥475±20 °C are indistinguishable from virgin wafers. So are samples with Tgrowth=220±20 °C, subjected to a 2 min, TRTA≳500 °C rapid thermal anneal (RTA) after every ≊30 nm of Si growth. If TRTA=450±20 °C, part of the film contains a concentration of vacancylike defects on th.
The preterm social brain: altered functional networks for Theory of Mind in very preterm children

Abstract Neurodevelopmental difficulties emerge in very preterm born children (<32-week gestation) in infancy and continue to early adulthood but little is known about their social-cognitive development. This study utilized the complementary methodological advantages of both functional MRI and magnetoencephalography to examine the neural underpinnings of Theory of Mind in very preterm birth. Theory of Mind, one of the core social-cognitive skills, is the ability to attribute mental states to others, and is crucial for predicting others’ behaviours in social interactions. Eighty-three children (40 very preterm born, 24 boys, age = 8.7 ± 0.5 years, and 43 full-term born, 22 boys, age = 8.6 ± 0.5 years) completed the study. In functional MRI, both groups recruited classic Theory of Mind areas, without significant group differences. However, reduced Theory of Mind connectivity in the very preterm born group was found in magnetoencephalography in distinct theta, alpha and beta-band networks anchored in a set of brain regions that comprise the social brain. These networks included regions such as the angular gyrus, the medial pre-frontal cortex, the superior temporal gyrus and the temporal poles. Very preterm born children showed increased connectivity compared to controls in a network anchored in the occipital gyri rather than classical social-processing regions. Very preterm born children made significantly more attribution errors and mis-construed the social scenarios. Findings offer novel insight into the neural networks, supporting social cognition in very preterm born children and highlight the importance of multimodal neuroimaging to interrogate the social brain in clinical populations.
Optimal Upper Limits of Plateau Pressure for Patients With Acute Respiratory Distress Syndrome During the First Seven Days: A Meta-Regression Analysis

Background The effects of plateau pressure during the initial days of mechanical ventilation on outcomes for patients with acute respiratory distress syndrome have not been fully examined. We conducted meta-regression analysis of plateau pressure during the first 7 days using randomized control trials to investigate the optimal upper limits of plateau pressure on different days of mechanical ventilation. Methods Randomized controlled trials comparing two mechanical ventilation strategies with lower and higher plateau pressures in patients with acute respiratory distress syndrome were included. Meta-regression analysis was performed to determine the association of plateau pressure with mortality on days 1, 3, and 7 of mechanical ventilation. Results After evaluation of 2,975 citations from a comprehensive search across electronic databases, 14 studies were included in the final qualitative analysis. A total of 4,984 patients were included in the quantitative analysis. As a result of the pairwise comparison, overall short-term mortality was significantly higher for patients with plateau pressures over 32 cm H2O during the first 3 days after intensive care unit (ICU) admission (day 1: relative risk (RR), 0.77; 95% confidence interval (CI), 0.66 - 0.89; I2 = 0%; day 3: RR, 0.76; 95% CI, 0.64 - 0.90; I2 = 0%), but not on day 7 (RR, 0.82; 95% CI, 0.65 - 1.04; I2 = 16%). Plateau pressures below 27 cm H2O and 30 cm H2O were not associated with an absolute risk reduction of short-term mortality. According to univariable meta-regression analysis, mortality was significantly associated with plateau pressure on day 1 (β = 0.01 (95% CI, 0.002 - 0.024), P = 0.02). On days 3 and 7, however, no significant difference was detected. When the cutoffs were set at 27, 30 and 32 cm H2O on day 1, which showed a significant difference, plateau pressure tended to be associated with increased mortality at pressures above the cut-off values, and there were no significant differences at pressures below the cut-off values, regardless of the cutoff used. Conclusions This study suggests that the optimal cut-off value for plateau pressure may be 27 cm H2O especially during the initial period of mechanical ventilation, although this association may not continue during the latter period of mechanical ventilation.
Expression profiles of interferon-related genes in cells infected with influenza A viruses or transiently transfected with plasmids encoding viral RNA polymerase

Influenza A viruses frequently change their genetic characteristics, which leads to the emergence of new viruses. Consequently, elucidation of the relationship between influenza A virus and host cells has a great importance to cope with viral infections. In this study, it was aimed to determine expression profiles of interferon response genes in human embryonic kidney 293 (HEK293) cells infected with human (A/WSN-H1N1) and avian influenza A viruses (duck/Pennsylvania/10218/84/H5N2) or transfected with plasmids encoding viral RdRP subunits and, to obtain clues about the genes that may be important for the viral pathogenesis. The HEK293 cells cultured in a 12-well plate were infected with influenza A viruses or transfected with plasmids encoding viral polymerase. Total RNA extraction and cDNA preparation were carried out with commercial kits. Qiagen 96-well-RT2 Profiler PCR Array plates designated for interferons response genes were used for quantitation of the transcripts. The relative quantities of transcripts were normalized with STAT3 gen, and the results were evaluated. Quantitative RT-PCR results showed that there are substantial differences of the interferon response gene transcription in cells infected with viruses or transfected with plasmids. A higher number of interferon-related genes were found to be downregulated in the cells infected with DkPen compared to WSN. On the other hand, significant differences in the expression profiles of interferon response genes were observed in the cells expressing viral PA protein. In particular, avian influenza PA protein was found to cause more aggressive changes on the transcript levels. Human and avian influenza A viruses cause a substantial change in interferon response gene expression in HEK293 cells. However, a higher number of genes were downregulated in the cells infected with avian influenza DkPen compared to WSN. It has been also concluded that the viral PA protein is one of the important viral factors affecting the transcript level of host genes.
The Post‐visit Consumer Behaviour of New Zealand Winery Visitors

Visitation to wineries has often been cited as an important way in which a winery can establish and/or reinforce loyalty amongst its consumers. However, to date few studies have explored the consumer behaviour of winery visitors beyond the cellar door. A study by King and Morris (n.d.) concluded that just 13% of visitors to Margaret River wineries made a purchase of wine from the winery of survey in the 18 months following their visit. In contrast, this paper reports that more than 46% of visitors to New Zealand wineries made a post visit purchase in a period of just six to eight months following their visit. This paper presents some of the results of the second phase of a two‐phase tracking survey of New Zealand winery visitors. The study found a higher propensity for brand loyalty was apparent amongst visitors to certain regions and to medium and large‐sized wineries, domestic visitors, females, those with intermediate or advanced wine knowledge, those that drink wine more frequently and purchase more wine. More importantly however, it found brand loyal behaviour (post‐visit purchase and repeat visitation) amongst repeat visitors to wineries and those that purchased wine during their visit. The study further found that there is a high degree of positive word of mouth (a by‐product of brand loyalty) amongst all winery visitors.
Growth of ultralong ZnO nanowires on silicon substrates by vapor transport and their use as recyclable photocatalysts

We report the growth of ultralong ZnO nanowires on silicon (100) substrates via the gold-catalyzed vapor transport approach. An ample supply of zinc vapor generated through carbothermal reduction of ZnO powder at 917 °C and a suitable amount of oxygen facilitate the rapid growth of nanowires. These ZnO nanowires are extremely long with lengths of 85−100 μm, and exhibit an overall vertical orientation. The nanowires have largely diameters of 250−400 nm. Crystal structure analysis indicates typical ZnO nanowire growth along the [0001] direction. The band gap of these nanowires was determined to be 3.22 eV. These nanowires show a relatively weak near-band-edge emission peak at 390 nm, and a significant oxygen vacancy-related emission band at 495 nm. Good photocatalytic activity of these nanowires on substrates toward the photodegradation of rhodamine B and 4-chlorophenol was demonstrated. Furthermore, we showed that these nanowires on substrates can serve as effective and convenient recyclable photocatalysts.