Miracle-dz/UniFAR-FTUs huggingface dataset:
Hyperspectral Anomaly Detection via Spatial Density Background Purification

In the research of anomaly detection methods, obtaining a pure background without abnormal pixels can effectively improve the detection performance and reduce the false-alarm rate. Therefore, this paper proposes a spatial density background purification (SDBP) method for hyperspectral anomaly detection. First, a density peak clustering (DP) algorithm is used to calculate the local density of pixels within a single window. Then, the local densities are sorted into descending order and the m pixels that have the highest local density are selected from high to low. Therefore, the potential abnormal pixels in the background can be effectively removed, and a purer background set can be obtained. Finally, the collaborative representation detector (CRD) is employed for anomaly detection. Considering that the neighboring area of each pixel will have homogeneous material pixels, we adopt the double window strategy to improve the above method. The local densities of the pixels between the large window and the small window are calculated, while all pixels are removed from the small window. This makes the background estimation more accurate, reduces the false-alarm rate, and improves the detection performance. Experimental results on three real hyperspectral datasets such as Airport, Beach, and Urban scenes indicate that the detection accuracy of this method outperforms other commonly used anomaly detection methods.
SAR Target Recognition via Joint Sparse and Dense Representation of Monogenic Signal

Synthetic aperture radar (SAR) target recognition under extended operating conditions (EOCs) is a challenging problem due to the complex application environment, especially for insufficient target variations and corrupted SAR images in the training samples. This paper proposes a new strategy to solve these problems for target recognition. The SAR images are firstly characterized by multi-scale components of monogenic signal. The generated monogenic features are decomposed to learn a class dictionary and a shared dictionary, which represent the possible intraclass variations information and the common information, respectively. Moreover, a sparse representation of the class dictionary and a dense representation of the shared dictionary are jointly employed to represent a query sample for classification. The validity of the proposed strategy is demonstrated with multiple comparative experiments on moving and stationary target acquisition and recognition (MSTAR) database.
A skin-like two-dimensionally pixelized full-color quantum dot photodetector

We report a skin-like full-band on-chip photodetector enabled by two-dimensionally pixelized chalcometallate ligand quantum dots. Direct full-color photodetectors without sophisticated color filters and interferometric optics have attracted considerable attention for widespread applications. However, difficulties of combining various multispectral semiconductors and improving photon transfer efficiency for high-performance optoelectronic devices have impeded the translation of these platforms into practical realization. Here, we report a low-temperature (<150°C) fabricated two-dimensionally pixelized full-color photodetector by using monolithic integration of various-sized colloidal quantum dots (QDs) and amorphous indium-gallium-zinc-oxide semiconductors. By introducing trap-reduced chelating chalcometallate ligands, highly efficient charge carrier transport and photoresistor-free fine-patterning of QD layers were successfully realized, exhibiting extremely high photodetectivity (>4.2 × 1017 Jones) and photoresponsivity (>8.3 × 103 A W−1) in a broad range of wavelengths (365 to 1310 nm). On the basis of these technologies, a wavelength discriminable phototransistor circuit array (>600 phototransistors) was implemented on a skin-like soft platform, which is expected to be a versatile and scalable approach for wide spectral image sensors and human-oriented biological devices.
TRIM8 is required for virus-induced IFN response in human plasmacytoid dendritic cells

TRIM8 and Pin1 oppositely control IRF7-induced interferon production. Plasmacytoid dendritic cells (pDCs) play a crucial role in antiviral innate immunity through their unique capacity to produce large amounts of type I interferons (IFNs) upon viral detection. Tripartite motif (TRIM) proteins have recently come forth as important modulators of innate signaling, but their involvement in pDCs has not been investigated. Here, we performed a rationally streamlined small interfering RNA (siRNA)–based screen of TRIM proteins in human primary pDCs to identify those that are critical for the IFN response. Among candidate hits, TRIM8 emerged as an essential regulator of IFN regulatory factor 7 (IRF7) function. Mechanistically, TRIM8 protects phosphorylated IRF7 (pIRF7) from proteasomal degradation in an E3 ubiquitin ligase–independent manner by preventing its recognition by the peptidyl-prolyl isomerase Pin1. Our findings uncover a previously unknown regulatory mechanism of type I IFN production in pDCs by which TRIM8 and Pin1 oppositely regulate the stability of pIRF7.
Observation of exceptional points in magnonic parity-time symmetry devices

Parity-time symmetry has been theoretically and experimentally demonstrated in magnonics. Non-Hermitian Hamiltonians may still have real eigenvalues, provided that a combined parity-time (ƤƮ) symmetry exists. The prospect of ƤƮ symmetry has been explored in several physical systems such as photonics, acoustics, and electronics. The eigenvalues in these systems undergo a transition from real to complex at exceptional points (EPs), where the ƤƮ symmetry is broken. Here, we demonstrate the existence of EP in magnonic devices composed of two coupled magnets with different magnon losses. The eigenfrequencies and damping rates change from crossing to anti-crossing at the EP when the coupling strength increases. The magnonic dispersion includes a strong “acoustic-like” mode and a weak “optic-like” mode. Moreover, upon microwave radiation, the ƤƮ magnonic devices act as magnon resonant cavity with unique response compared to conventional magnonic systems.
Preventing undesirable behavior of intelligent machines

Making well-behaved algorithms Machine learning algorithms are being used in an ever-increasing number of applications, and many of these applications affect quality of life. Yet such algorithms often exhibit undesirable behavior, from various types of bias to causing financial loss or delaying medical diagnoses. In standard machine learning approaches, the burden of avoiding this harmful behavior is placed on the user of the algorithm, who most often is not a computer scientist. Thomas et al. introduce a general framework for algorithm design in which this burden is shifted from the user to the designer of the algorithm. The researchers illustrate the benefits of their approach using examples in gender fairness and diabetes management. Science, this issue p. 999 A machine learning algorithm design framework shifts the burden of avoiding undesirable behavior from user to designer. Intelligent machines using machine learning algorithms are ubiquitous, ranging from simple data analysis and pattern recognition tools to complex systems that achieve superhuman performance on various tasks. Ensuring that they do not exhibit undesirable behavior—that they do not, for example, cause harm to humans—is therefore a pressing problem. We propose a general and flexible framework for designing machine learning algorithms. This framework simplifies the problem of specifying and regulating undesirable behavior. To show the viability of this framework, we used it to create machine learning algorithms that precluded the dangerous behavior caused by standard machine learning algorithms in our experiments. Our framework for designing machine learning algorithms simplifies the safe and responsible application of machine learning.
Mechanisms of nuclear content loading to exosomes

Nuclear-derived exosomes generated by micronuclear collapse provide an accurate snapshot of genomic features in ovarian cancer. Exosome cargoes are highly varied and include proteins, small RNAs, and genomic DNA (gDNA). The presence of gDNA suggests that different intracellular compartments contribute to exosome loading, resulting in distinct exosome subpopulations. However, the loading of gDNA and other nuclear contents into exosomes (nExo) remains poorly understood. Here, we identify the relationship between cancer cell micronuclei (MN), which are markers of genomic instability, and nExo formation. Imaging flow cytometry analyses reveal that 10% of exosomes derived from cancer cells and <1% of exosomes derived from blood and ascites from patients with ovarian cancer carry nuclear contents. Treatment with genotoxic drugs resulted in increased MN and nExos both in vitro and in vivo. We observed that multivesicular body precursors and exosomal markers, such as the tetraspanins, directly interact with MN. Collectively, this work provides new insights related to nExos, which have implications for cancer biomarker development.
Excision margins in human immunodeficiency virus seropositive women undergoing large loop excision of the transformation zone for cervical dysplasia

Department of Obstetrics and Gynaecology University of the Witwatersrand Johannesburg February 2015 A research report submitted to the Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, in partial fulfilment of the requirements for the degree of Masters in Medicine, in the branch of Obstetrics and Gynaecology.
Commentary on the White Paper: The House of Lords - Completing the Reform

This report is sold subject to the condition that is shall not, by way of trade or otherwise, be lent, hired out or otherwise circulated without the publisher's prior consent in any form of binding or cover other than that in which it is published and without a similar condition including this condition being imposed on the subsequent purchaser.
Figs — The Earliest Known Ancient Drug for Cutaneous Anthrax

BACKGROUND: Anthrax is an often fatal bacterial infection, occurring in cutaneous, inhalational, gastrointestinal, and meningeal forms. Evaluation of anthrax treatment from ancient history may help healthcare providers to handle this serious disease more efficiently. OBJECTIVE: To evaluate the biblical descriptions of anthrax, focusing on its therapy in ancient times. STUDY SELECTION: All biblical texts associated with anthrax were examined and passages relating to this disease were studied closely. DATA SYNTHESIS: Biblical passages such as: “Take a cluster of figs. And they took and laid it on the boil [anthrax], and he recovered,” and “Let them take a cluster of figs, and lay it upon the boil [anthrax], and he shall recover,” convincingly indicate that figs have healing properties in cutaneous anthrax lesions. CONCLUSIONS: On the basis of this study, the National Institutes of Health together with the pharmaceutical industry may consider to work on isolation of compounds from fig plants to develop products against cutaneous and possibly other forms of anthrax once screening tests are completed.
Indoor localization using multiple stereo speakers for smartphones

In this paper, we propose an acoustic indoor localization method for an embedded microphone of a smartphone using multiple stereo speakers installed indoors. In this configuration, although stereo speakers are synchronized, speakers not producing stereo sound are not synchronized. Therefore, a moving microphone could receive acoustic signals required for localization at different locations. This causes bias error in the conventional method. To address this issue, we propose a method that utilizes an asynchronous tracking filter and compensates the differences in locations of received signals using motion modelling. Through experiments, we verify that our proposed method can effectively reduce the bias error.
STATISTICAL, SPECTRAL AND WAVELET FEATURES OF THE AMBIENT NOISE DETECTED IN THE SOUTHERN BALTIC SEA

The level of underwater noise in the oceans has increased evidently over the past 70 years mainly due to increase of shipping. Noise can disturb physiology and behaviour of marine organisms disrupting their life processes. The level of noise of the anthropogenic origin is especially very high in the Baltic Sea, where shipping density is one of the highest in the world. Throughout the year 2014 eight Baltic countries in the project BIAS (Baltic Sea Information on the Acoustic Soundscape), were measuring the level of underwater noise in 38 locations mainly in the vicinity of shipping lines. Five WildLife Acoustics SM2M recorders were deployed at depths from 12m to 80m in the Polish zone of the Baltic Sea. The devices were continuously registering ambient noise with sampling frequencies from 24kHz to 96 kHz. Additionally, the wind speed and its direction were recorded. The dislocation of ships, their speed and course were acquired from the AIS system data. Recognition and quantification of the noise events was done in 1/3-octave frequency bands. In addition, spectral, statistical and wavelet energy parameters were computed as input to Principal Component Analysis and fuzzy logic clusterization algorithm, resulting in the separation of ambient noise sources. The presented method enabled the automatic detection of noise generated by vessels from the underwater ambient noise.
Image Colorization

The article discusses one of the latest ways to colorize a black and white image using deep learning methods. For colorization, a convolutional neural network with a large number of layers (Deep convolutional) is used, the architecture of which includes a ResNet model. This model was pre-trained on images of the ImageNet dataset. A neural network receives a black and white image and returns a colorized color. Since, due to the characteristics of ResNet, an input multiple of 255 is received, a program was written that, using frames, enlarges the image for the required size. During the operation of the neural network, the CIE Lab color model is used, which allows to separate the black and white component of the image from the color. For training the neural network, the Place 365 dataset was used, containing 365 different classes, such as animals, landscape elements, people, and so on. The training was carried out on the Nvidia GTX 1080 video card. The result was a trained neural network capable of colorizing images of any size and format. As example we had a speed of 0.08 seconds and an image of 256 by 256 pixels in size. In connection with the concept of the dataset used for training, the resulting model is focused on the recognition of natural landscapes and urban areas.
Disentangling the coexistence strategies of mud-daubing wasp species through trophic analysis in oases of Baja California peninsula

Species within the same trophic level show different strategies to avoid competition. Among these mechanisms, differences in body size, spatio-temporal segregation, and diet preference often leads to a niche partitioning. Nonetheless, little attention on coexisting predatory insects and their network interactions has been paid. In this study, we analyzed the strategies to avoid competition among three sympatric mud-daubing wasps of the genus Trypoxylon (Hymenoptera: Crabronidae) in oases and their surrounding xeric area from the Baja California peninsula, Mexico. We compared the prey richness, composition and proportion of spider guilds that were captured by the wasps. We tested whether the differences in wasp body size explained the niche breadth, niche overlap and the size of spider prey. We assessed the spider-wasp interactions through a network analysis. With the use of trap-nests, we collected 52 spider species captured by the wasps. Both the guild and species composition of preyed spiders was different between the three wasp species. Differential proportions in the capture of spider guilds and a little diet overlap were found among the wasp species. We found that the wasp body size was positively correlated with prey size, but it was not a proxy of niche breadth. Moreover, the largest wasp species was able to nest in both mesic and xeric habitats, while the two smaller species were restricted to the oases. This study reveals that the diversity of spiders in oases of Baja California peninsula is crucial to maintain highly specialized oasis-dependent wasp species. The niche partitioning between mud-daubing wasps can be shaped by their inherent body size limitations and hunting strategies through foraging specialization for specific spider guilds. Food selection and slight differences in body size reduce competition and allow the coexistence of sympatric wasps. Our study is the first approach exploring the interaction networks between mud-daubing wasps and their spider preys, highlighting new insights into the morphological and ecological factors that shape antagonistic interactions, and allow the coexistence of predators in deserts.
Sex differences in body composition but not neuromuscular function following long-term, doxycycline-induced reduction in circulating levels of myostatin in mice

Age-related declines in muscle function result from changes in muscle structure and contractile properties, as well as from neural adaptations. Blocking myostatin to drive muscle growth is one potential therapeutic approach. While the effects of myostatin depletion on muscle characteristics are well established, we have very little understanding of its effects on the neural system. Here we assess the effects of long-term, post-developmental myostatin reduction on electrophysiological motor unit characteristics and body composition in aging mice. We used male (N = 21) and female (N = 26) mice containing a tetracycline-inducible system to delete the myostatin gene in skeletal muscle. Starting at 12 months of age, half of the mice were administered doxycycline (tetracycline) through their chow for one year. During that time we measured food intake, body composition, and hindlimb electromyographic responses. Doxycycline-induced myostatin reduction had no effect on motor unit properties for either sex, though significant age-dependent declines in motor unit number occurred in all mice. However, treatment with doxycycline induced different changes in body composition between sexes. All female mice increased in total, lean and fat mass, but doxycycline-treated female mice experienced a significantly larger increase in lean mass than controls. All male mice also increased total and lean mass, but administration of doxycycline had no effect. Additionally, doxycycline-treated male mice maintained their fat mass at baseline levels, while the control group experienced a significant increase from baseline and compared to the doxycycline treated group. Our results show that long-term administration of doxycycline results in body composition adaptations that are distinctive between male and female mice, and that the effects of myostatin reduction are most pronounced during the first three months of treatment. We also report that age-related changes in motor unit number are not offset by reduced myostatin levels, despite increased lean mass exhibited by female mice.
A randomized controlled trial comparing isosorbide dinitrate-oxytocin versus misoprostol-oxytocin at management of foetal intrauterine death

Background The metabolic activity of endogenous nitric oxide (NO) and the medical use of nitrovasodilatory drugs like isosorbide dinitrate have been shown to be potential inducers inducers of cervical ripening prior to surgical evacuation of the uterus. Objective To assess the therapeutic efficacy and safety of combined isosorbide dinitrate-oxytocin in the management of intrauterine foetal death (IUFD). Methods Sixty women with IUFD after 20 weeks of gestation requesting uterine evacuation were randomly selected to receive isosorbide dinitrate gel solution (80 mg/1.5 mL; n = 30) or misoprostol gel solution (100 mcg/1.5 mL; n = 30) every 3 h with a maximum of four doses or until a Bishop score >7 was reached. Subsequently, patients received a high dose of intravenous oxytocin until complete uterus evacuation was achieved. Therapeutic efficacy was evaluated by mean the relative risk of the foetal expulsion based on comparison of event rates, and the proportion of women induced to labor at 7, 10 and 15 h after the administration of isosorbide dinitrate or misoprostol. Safety was assessed on the basis of woman´s vital signs and evaluation of adverse effects, including headache, abdominal pain, pelvic pain, lower back pain, nausea, dizziness and vomiting. Results The foetal expulsion rate using the isosorbide dinitrate-oxytocin combination was approximately 4.4 times, and at least 2.1 times, the foetal expulsion rate with the misoprostol-oxytocin regimen at any given point in time. The proportion of women achieved vaginal delivery at 15 hours was 100% for the isosorbide dinitrate-oxytocin group and 86.7% for the misoprostol-oxytocin group. The average delivery induction interval was significantly lower when isosorbide dinitrate-oxytocin was used (8.7 ± 3.1 h) than when misoprostol-oxytocin (11.9 ± 3.1 h) was used. A total of 20% of patients in the isosorbide dinitrate-oxytocin group recorded headache, and no cases of uterine tachysystole, haemorrhage or coagulopathy were recorded. Conclusion This study indicates that intravaginal isosorbide dinitrate followed by intravenous oxytocin was more effective than the conventional method used to induce labour in the medical management of foetal death in pregnancies after 20 weeks of gestation. Trial registration Clinicaltrials.gov NCT02488642.
Temporal Trends in Maternal Food Intake Frequencies and Associations with Gestational Diabetes: The Cambridge Baby Growth Study

Previous studies have suggested that in the first decade of this century the incidence of gestational diabetes (GDM) in pregnancy rose worldwide. In the Cambridge Baby Growth Study cohort we observed that this temporal trend was associated with an index of multiple deprivation and reductions in indices of insulin secretion. Deprivation level was not directly associated with GDM, suggesting that the temporal trend may relate more to other factors linked to it, such as dietary composition. In this study we investigated temporal trends in perceived food intake frequencies, derived from a qualitative, short questionnaire, in 865 pregnant Cambridge Baby Growth Study (CBGS) recruits. A number of food frequency ranks showed both temporal trends and associations with GDM, but of note is the frequency of egg consumption (negative temporal trend p = 0.03, slope = −6.2 ranks/year; negative association with GDM p = 3.0 × 10−8, slope = −0.002 increased risk/rank) as it was also positively associated with the insulin disposition index (p = 1.17 × 10−3, slope = 0.42 ranks. L/mmoL). These results are consistent with a potential protective effect of factors related to the frequency of egg consumption in pregnancy. Such factors may have contributed to the observed temporal trend in GDM risk but the overall detectable effect appears to have been small.
Early‐Stage Parkinson's Patients Show Selective Impairment in Reactive But Not Proactive Inhibition

It is well known that a deficit in inhibitory control is a hallmark of Parkinson's disease (PD). However, inhibition is not a unitary construct, and it is unclear whether patients in the early stage of the disease (Hoehn and Yahr stage 1) exhibit a deficit in outright stopping (reactive inhibition), a deficit in the ability to shape their response strategies according to the context (proactive inhibition), or both.