Miracle-dz/UniFAR-FTUs huggingface dataset:
Parameters Calibration for Power Grid Stability Models using Deep Learning Methods

This paper presents a novel parameter calibration approach for power system stability models using automatic data generation and advanced deep learning technology. A PMU-measurement-based event playback approach is used to identify potential inaccurate parameters and automatically generate extensive simulation data, which are used for training a convolutional neural network (CNN). The accurate parameters will be predicted by the well-trained CNN model and validated by original PMU measurements. The accuracy and effectiveness of the proposed deep learning approach have been validated through extensive simulation and field data.
Targeted disruption of int‐2 (fgf‐3) causes developmental defects in the tail and inner ear

The int‐2 gene (also designated fgf‐3) was originally identified because its transcription is activated by the nearby integration of mouse mammary tumor virus in virus‐induced tumors. Molecular analyses have revealed that the int‐2 gene produces at least four mRNAs, all of which encode a protein that has 40–50% amino acid sequence similarity with the fibroblast growth factors (FGFs). Int‐2 gene expression is localized to a small number of discrete sites in the developing mouse, but has not been detected in any nonneoplastic adult tissue. The expression data and the amino acid sequence similarity with the FGFs suggested several potential roles for int‐2 during normal development.
Goal-oriented Object Importance Estimation in On-road Driving Videos

We formulate a new problem as Object Importance Estimation (OIE) in on-road driving videos, where the road users are considered as important objects if they have influence on the control decision of the ego-vehicle’s driver. The importance of a road user depends on both its visual dynamics, e.g., appearance, motion and location, in the driving scene and the driving goal, e.g., the planned path, of the ego vehicle. We propose a novel framework that incorporates both visual model and goal representation to conduct OIE. To evaluate our framework, we collect an on-road driving dataset at traffic intersections in the real world and conduct human-labeled annotation of the important objects. Experimental results show that our goal-oriented method outperforms baselines and has much more improvement on the left-turn and right-turn scenarios. Furthermore, we explore the possibility of using object importance for driving control prediction and demonstrate that binary brake prediction can be improved with the information of object importance.
J-PLUS: Discovery and characterisation of ultracool dwarfs using Virtual Observatory tools

Context. Ultracool dwarfs are objects with spectral types equal to or later than M7. Most of them have been discovered using wide-field imaging surveys. The Virtual Observatory has proven to be very useful for efficiently exploiting these astronomical resources. Aims. We aim to validate a Virtual Observatory methodology designed to discover and characterise ultracool dwarfs in the J-PLUS photometric survey. J-PLUS is a multiband survey carried out with the wide-angle T80Cam optical camera mounted on the 0.83 m telescope JAST/T80 in the Observatorio Astrofísico de Javalambre. We make use of the Internal Data Release covering 528 deg2. Methods. We complemented J-PLUS photometry with other catalogues in the optical and infrared using VOSA, a Virtual Observatory tool that estimates physical parameters from the spectral energy distribution fitting to collections of theoretical models. Objects identified as ultracool dwarfs were distinguished from background M giants and highly reddened stars using parallaxes and proper motions from Gaia DR2. Results. We identify 559 ultracool dwarfs, ranging from i = 16.2 mag to i = 22.4 mag, of which 187 are candidate ultracool dwarfs not previously reported in the literature. This represents an increase in the number of known ultracool dwarfs of about 50% in the region of the sky we studied, particularly at the faint end of our sensitivity, which is interesting as reference for future wide and deep surveys such as Euclid. Three candidates are interesting targets for exoplanet surveys because of their proximity (distances less than 40 pc). We also analysed the kinematics of ultracool dwarfs in our catalogue and found evidence that it is consistent with a Galactic thin-disc population, except for six objects that might be members of the thick disc. Conclusion. The results we obtained validate the proposed methodology, which will be used in future J-PLUS and J-PAS releases. Considering the region of the sky covered by the Internal Data Release used in this work, we estimate that 3000–3500 new ultracool dwarfs will be discovered at the end of the J-PLUS project.
Why, when, and how did yeast evolve alcoholic fermentation?

The origin of modern fruits brought to microbial communities an abundant source of rich food based on simple sugars. Yeasts, especially Saccharomyces cerevisiae, usually become the predominant group in these niches. One of the most prominent and unique features and likely a winning trait of these yeasts is their ability to rapidly convert sugars to ethanol at both anaerobic and aerobic conditions. Why, when, and how did yeasts remodel their carbon metabolism to be able to accumulate ethanol under aerobic conditions and at the expense of decreasing biomass production? We hereby review the recent data on the carbon metabolism in Saccharomycetaceae species and attempt to reconstruct the ancient environment, which could promote the evolution of alcoholic fermentation. We speculate that the first step toward the so-called fermentative lifestyle was the exploration of anaerobic niches resulting in an increased metabolic capacity to degrade sugar to ethanol. The strengthened glycolytic flow had in parallel a beneficial effect on the microbial competition outcome and later evolved as a “new” tool promoting the yeast competition ability under aerobic conditions. The basic aerobic alcoholic fermentation ability was subsequently “upgraded” in several lineages by evolving additional regulatory steps, such as glucose repression in the S. cerevisiae clade, to achieve a more precise metabolic control.
Skin Lesion Classification Using CNNs With Patch-Based Attention and Diagnosis-Guided Loss Weighting

<italic>Objective:</italic> This paper addresses two key problems of skin lesion classification. The first problem is the effective use of high-resolution images with pretrained standard architectures for image classification. The second problem is the high-class imbalance encountered in real-world multi-class datasets. <italic>Methods:</italic> To use high-resolution images, we propose a novel patch-based attention architecture that provides global context between small, high-resolution patches. We modify three pretrained architectures and study the performance of patch-based attention. To counter class imbalance problems, we compare oversampling, balanced batch sampling, and class-specific loss weighting. Additionally, we propose a novel diagnosis-guided loss weighting method that takes the method used for ground-truth annotation into account. <italic>Results:</italic> Our patch-based attention mechanism outperforms previous methods and improves the mean sensitivity by <inline-formula><tex-math notation="LaTeX">$\text{7}\%$</tex-math></inline-formula>. Class balancing significantly improves the mean sensitivity and we show that our diagnosis-guided loss weighting method improves the mean sensitivity by <inline-formula><tex-math notation="LaTeX">$\text{3}\%$</tex-math></inline-formula> over normal loss balancing. <italic>Conclusion:</italic> The novel patch-based attention mechanism can be integrated into pretrained architectures and provides global context between local patches while outperforming other patch-based methods. Hence, pretrained architectures can be readily used with high-resolution images without downsampling. The new diagnosis-guided loss weighting method outperforms other methods and allows for effective training when facing class imbalance. <italic>Significance:</italic> The proposed methods improve automatic skin lesion classification. They can be extended to other clinical applications where high-resolution image data and class imbalance are relevant.
A Genetic Algorithm Enabled Similarity-Based Attack on Cancellable Biometrics

Cancellable biometrics (CB) as a means for biometric template protection approach refers to an irreversible yet similarity preserving transformation on the original template. With similarity preserving property, the matching between template and query instance can be performed in the transform domain without jeopardizing accuracy performance. Unfortunately, this trait invites a class of attack, namely similarity-based attack (SA). SA produces a preimage, an inverse of transformed template, which can be exploited for impersonation and cross-matching. In this paper, we propose a Genetic Algorithm enabled similarity-based attack framework (GASAF) to demonstrate that CB schemes whose possess similarity preserving property are highly vulnerable to similarity-based attack. Besides that, a set of new metrics is designed to measure the effectiveness of the similarity-based attack. We conduct the experiment on two representative CB schemes, i.e. BioHashing and Bloom-filter. The experimental results attest the vulnerability under this type of attack.
Design and Optimization of Conforming Lattice Structures

Inspired by natural cellular materials such as trabecular bone, lattice structures have been developed as a new type of lightweight material. In this paper we present a novel method to design lattice structures that conform with both the principal stress directions and the boundary of the optimized shape. Our method consists of two major steps: the first optimizes concurrently the shape (including its topology) and the distribution of orthotropic lattice materials inside the shape to maximize stiffness under application-specific external loads; the second takes the optimized configuration (i.e., locally-defined orientation, porosity, and anisotropy) of lattice materials from the previous step, and extracts a globally consistent lattice structure by field-aligned parameterization. Our approach is robust and works for both 2D planar and 3D volumetric domains. Numerical results and physical verifications demonstrate remarkable structural properties of conforming lattice structures generated by our method.
Convolutional Neural Network for Intrusion Detection System In Cyber Physical Systems

The extensive use of Information and Communication Technology in critical infrastructures such as Industrial Control Systems make them vulnerable to cyber-attacks. One particular class of cyber-attacks is advanced persistent threats where highly skilled attackers can steal user authentication information's and move in the network from host to host until a valuable target is reached. The detection of the attacker should occur as soon as possible in order to take appropriate response, otherwise the attacker will have enough time to reach sensitive assets. When facing intelligent threats, intelligent solutions have to be designed. Therefore, in this paper, we take advantage of recent progress in deep learning to build a convolutional neural networks that can detect intrusions in cyber physical system. The Intrusion Detection System is applied on the NSL-KDD dataset and the performances of the proposed approach are presented and compared with the state of art. Results show the effectiveness of the techniques.
Identification, in mouse macrophages and in serum, of a soluble receptor for the Fc portion of IgG (Fc gamma R) encoded by an alternatively spliced transcript of the Fc gamma RII gene.

Low affinity Fc gamma R are a heterogeneous group of glycoproteins which exist in transmembrane (TM) as well as in soluble forms. Two membrane isoforms of the murine type II Fc gamma R, Fc gamma RIIb1 and Fc gamma RIIb2, have been described. They result from the translation of alternatively spliced pre-mRNA, Fc gamma RIIb2 lacking sequences of the first intracytoplasmic domain (IC1). Soluble forms of Fc gamma R (sFc gamma R) have previously been shown to result from proteolysis of membrane receptors. We report here the identification, in macrophages, of a mRNA derived from the Fc gamma RII gene by splicing exons encoding the TM and IC1 domains, i.e. corresponding to a TM-deleted Fc gamma RIIb2 mRNA. A soluble protein possibly encoded by this mRNA was identified in macrophage supernatants. In accordance with Fc gamma R nomenclature, we propose to name this new Fc gamma RII isoform Fc gamma RIIb3. It is the most abundant sFc gamma R present in serum, as compared with sFc gamma R resulting from cleavage of membrane Fc gamma R.
Dark-age reionization and galaxy formation simulation – XIX. Predictions of infrared excess and cosmic star formation rate density from UV observations

We present a new analysis of high-redshift UV observations using a semi-analytic galaxy formation model, and provide self-consistent predictions of the infrared excess (IRX)–β relations and cosmic star formation rate density. We combine the Charlot & Fall dust attenuation model with the meraxes semi-analytic model, and explore three different parametrizations for the dust optical depths, linked to star formation rate, dust-to-gas ratio, and gas column density, respectively. A Bayesian approach is employed to statistically calibrate model-free parameters including star formation efficiency, mass loading factor, dust optical depths, and reddening slope directly against UV luminosity functions and colour–magnitude relations at $z$ ∼ 4–7. The best-fitting models show excellent agreement with the observations. We calculate IRX using energy balance arguments and find that the large intrinsic scatter in the IRX–β plane correlates with specific star formation rate. Additionally, the difference among the three dust models suggests at least a factor of 2 systematic uncertainty in the dust-corrected star formation rate when using the Meurer IRX–β relation at $z$ ≳ 4.
Flexible Transparent Electrode of Hybrid Ag-Nanowire/Reduced-Graphene-Oxide Thin Film on PET Substrate Prepared Using H2/Ar Low-Damage Plasma

We employ H2/Ar low-damage plasma treatment (H2/Ar-LDPT) to reduce graphene oxide (GO) coating on a polymer substrate—polyethylene terephthalate (PET)—with the assistance of atomic hydrogen (Hα) at low temperature of 70 °C. Four-point probing and ultraviolet-visible (UV-Vis) spectroscopy demonstrate that the conductivity and transmittance can be controlled by varying the H2/Ar flow rate, treatment time, and radio-frequency (RF) power. Optical emission spectroscopy reveals that the Hα intensity depends on these processing parameters, which influence the removal of oxidative functional groups (confirmed via X-ray photoelectron spectroscopy) to yield reduced GO (rGO). To further improve the conductivity while maintaining high transmittance, we introduce silver nanowires (AgNWs) between rGO and a PET substrate to obtain a hybrid rGO/AgNWs/PET with a sheet resistance of ~100 Ω/sq and 81% transmittance. In addition, the hybrid rGO/AgNWs thin film also shows high flexibility and durability and is suitable for flexible and wearable electronics applications.
Parameter-free Clustering of Free Energy Landscapes with Gaussian Mixtures

Free energy landscapes provide insights into conformational ensembles of biomolecules. In order to analyze these landscapes and elucidate mechanisms underlying conformational changes, there is a need to extract metastable states with limited noise. This has remained a formidable task, despite a plethora of existing clustering methods. We propose a novel method for extracting well-defined core states from free energy landscapes. The method is based on a Gaussian mixture free energy estimator, and exploits the shape of the estimated density landscape. The core states that naturally arise from the clustering allow for detailed characterization of the conformational ensemble in a parameter-free way. The clustering quality is evaluated on three toy models with different properties, where the method is shown to consistently outperform other conventional clustering methods. Finally, the method is applied to a temperature enhanced molecular dynamics simulation of Ca 2+ -bound Calmodulin. Through the free energy landscape, we discover a pathway between a canonical and a compact state, revealing conformational changes driven by electrostatic interactions.
Issues in the design and interpretation of antifungal drug trials in the critically ill

Purpose of review Invasive fungal infections, such as invasive candidiasis and aspergillosis, are increasingly important in the critical care setting. This review will focus on clinical trials of antifungals in this setting and the methodological issues surrounding them. Recent findings Critically ill patients have traditionally only comprised a fraction of the patients enrolled in clinical trials exploring antifungal use, but recently a few clinical trials with specific therapeutic approaches have focused on this subpopulation. Increased mortality and problems with diagnosis have fostered the development of new management strategies, such as prophylaxis, pre-emptive treatment, and empirical antifungal therapy. Summary Although there are limited data supporting preventive and early therapeutic strategies, their use is recommended in highly selected patients and settings. Although critically ill patients are under-represented in clinical trials of antifungals conducted for the purpose of licensing, most experts agree that it is reasonable to extrapolate from these data until specific trials are conducted.
A Symbolic Descriptive System for Facial Expression Conveying Linguistic Information In Signing

The kinds of change in facial expression which can be produced by a sender's neural control of facial muscles, and, at the same time, can be visually perceived by a listener are described in discrete symbols. The linguistic information supplemented by the facial expressions in signing is categorized into syllabic, lexical and syntactic components. In order to control the facial expressions for this linguistic information, the timing and duration of the symbols are specified, and, by applying a set of concatenation rules, the control commands are generated. The adequacy of the symbolic descriptive system and its control rules have been examined through a computer synthesis of artificial facial expression, taking the example of transmitting syntactic information in traditional Japanese sign language. These facial expressions are combined with the symbolic descriptive system for hand shapes and arm actions and their control rules for the pictorial display of signing gestures. 1. SYMBOLIC DESCRIPTION 1. 1 . Elements of Facial Expression The kinds of change in facial expression which can be produced by a sender's neural control of facial muscles [References 1 and 2], and, at the same time, can be perceived visually by a listener, are described in discrete symbols. Parameters used for the element of facial expression are as follows: 1. Opening and closing of the eyelids 2. the eye direction 3. raising, knitting and lowering of the eyebrows 4. opening of the nostrils 5. opening or closing of the mouth 6. protrusion or corner pull of the lips 7. popping up or drawing of the chin and 8. nod or shake of the head The correspondence between the parameters of the elements and their symbols in a symbolic ELEMENTS SYMBOLS PARAMETERS EYELIDS: NEUTRAL EL0 WIDELY OPENED EL+ NARROWED, OR ELCLOSED EL-EYE DIRECTION: NEUTRAL EY0 DIRECTLY UP EYu+, u++ DOWN EYd+, d++ LEFT, OR EYl+, l++ RIGHT EYr+, r++ EACH IN TWO STEPS DIRECT TO A PARTICULAR POINT EYxy EYEBROWS: NEUTRAL EB0 THE INSIDES RAISED, OR EBi+, i++ KNITTED EBi-, i-THE LATERAL SIDES RAISED, OR EBl+, l++ LOWERED EBl-, l-EACH IN TWO STEPS. NOSTRILS: NEUTRAL NR0 WIDELY OPENED NR+ MOUTH: NEUTRAL MO0 WIDELY OPENED MO+ NARROWED, OR MOCLOSED MO-THE LIPS PROTRUDED, OR LP+, ++ THE CORNERS PULLED LATERALLY LP-, -EACH IN TWO STEPS CHIN: NEUTRAL CN0 POPPING UP, OR CN+, ++ DRAWING IN THE CHIN CN+, ++ EACH IN TWO STEPS HEAD: NEUTRAL HD0 NOD, OR HDN SHAKE. HDS TILT FORWARD, OR HD+, ++ BACKWARD HD-, -EACH IN TWO STEPS Tabl e 1 : Correspondence between the parameters of elements and their symbols in a symbolic descriptive system of the facial expressions. " # $ ISCA Archive %&&'''( ( & )
Abnormal, Error-Prone Bypass of Photoproducts by Xeroderma Pigmentosum Variant Cell Extracts Results in Extreme Strand Bias for the Kinds of Mutations Induced by UV Light

ABSTRACT Xeroderma pigmentosum (XP) is a rare genetic disease characterized by a greatly increased susceptibility to sunlight-induced skin cancer. Cells from the majority of patients are defective in nucleotide excision repair. However, cells from one set of patients, XP variants, exhibit normal repair but are abnormally slow in replicating DNA containing UV photoproducts. The frequency of UV radiation-induced mutations in the XP variant cells is significantly higher than that in normal human cells. Furthermore, the kinds of UV-induced mutations differ very significantly from normal. Instead of transitions, mainly C→T, 30% of the base substitutions consist of C→A transversions, all arising from photoproducts located in one strand. Mutations involving cytosine in the other strand are almost all C→T transitions. Forty-five percent of the substitutions involve thymine, and the majority are transversions. To test the hypothesis that the UV hypermutability and the abnormal spectrum of mutations result from abnormal bypass of photoproducts in DNA, we compared extracts from XP variant cells with those from HeLa cells and a fibroblast cell strain, MSU-1.2, for the ability to replicate a UV-irradiated form I M13 phage. The M13 template contains a simian virus 40 origin of replication located directly to the left or to the right of the target gene,lacZα, so that the template for the leading and lagging strands of DNA replication is defined. Reduction of replication to ∼37% of the control value required only 1 photoproduct per template for XP variant cell extracts, but ∼2.2 photoproducts for HeLa or MSU-1.2 cell extracts. The frequency of mutants induced was four times higher with XP variant cell extracts than with HeLa or MSU-1.2 cell extracts. With XP variant cell extracts, the proportion of C→A transversions reached as high as 43% with either M13 template and arose from photoproducts located in the template for leading-strand synthesis; with HeLa or MSU-1.2 cell extracts, this value was only 5%, and these arose from photoproducts in either strand. With the XP variant extracts, 26% of the substitutions involved thymine, and virtually all were T→A transversions. Sequence analysis of the coding region of the catalytic subunit of DNA polymerase delta in XP variant cell lines revealed two polymorphisms, but these do not account for the reduced bypass fidelity. Our data indicate that the UV hypermutability of XP variant cells results from reduced bypass fidelity and that unlike for normal cells, bypass of photoproducts involving cytosine in the template for the leading strand differs significantly from that of photoproducts in the lagging strand.