Miracle-dz/UniFAR-FTUs huggingface dataset:
Rapid neural categorization of facelike objects predicts the perceptual awareness of a face (face pareidolia)

The human brain rapidly and automatically categorizes faces vs. other visual objects. However, whether face-selective neural activity predicts the subjective experience of a face – perceptual awareness – is debated. To clarify this issue, here we use face pareidolia, i.e., the illusory perception of a face, as a proxy to relate the neural categorization of a variety of facelike objects to conscious face perception. In Experiment 1, scalp electroencephalogram (EEG) is recorded while pictures of human faces or facelike objects – in different stimulation sequences – are interleaved every second (i.e., at 1 Hz) in a rapid 6-Hz train of natural images of nonface objects. Participants do not perform any explicit face categorization task during stimulation, and report whether they perceived illusory faces post-stimulation. A robust categorization response to facelike objects is identified at 1 Hz and harmonics in the EEG frequency spectrum with a facelike occipito-temporal topography. Across all individuals, the facelike categorization response is of about 20% of the response to human faces, but more strongly right-lateralized. Critically, its amplitude is much larger in participants who report having perceived illusory faces. In Experiment 2, facelike or matched nonface objects from the same categories appear at 1 Hz in sequences of nonface objects presented at variable stimulation rates (60 Hz to 12 Hz) and participants explicitly report after each sequence whether they perceived illusory faces. The facelike categorization response already emerges at the shortest stimulus duration (i.e., 17 ms at 60 Hz) and predicts the behavioral report of conscious perception. Strikingly, neural facelike-selectivity emerges exclusively when participants report illusory faces. Collectively, these experiments characterize a neural signature of face pareidolia in the context of rapid categorization, supporting the view that face-selective brain activity reliably predicts the subjective experience of a face from a single glance at a variety of stimuli. Highlights - EEG frequency-tagging measures the rapid categorization of facelike objects - Facelike objects elicit a facelike neural categorization response - Neural face categorization predicts conscious face perception across variable inputs
Charge density waves in layered metals observed by X-ray photoemission

Abstract Temperature dependent X-ray photoemission spectroscopy (ESCA or XPS) studies on the Ta 4f lines in 1T-TaS2, 1T-TaSe2, 1T-Ta0.97Hf0. 03S2 and 2H-TaSe2 are reported. Striking effects arising from charge density waves (CDWs) are observed at low temperature. While electron diffraction evaluates the periodicity and direction of the CDWs, these XPS observations allow the different configurations of the CDWs with respect to the crystal lattice to be deduced. The results indicate the existence of CDW fluctuations in commensurate phases, and that in some incommensurate and ‘quasi-commensurate’ phases the CDWs cannot maintain long-range coherence. In 1T-Ta0.97Hf0. 03S2 the Hf impurities pin the incommensurate CDWs into domains.
Improved transformation efficiency of group A Streptococcus by inactivation of a type I restriction modification system

Streptococcus pyogenes or group A Streptococcus (GAS) is a leading cause of bacterial pharyngitis, skin and soft tissue infections, life-threatening invasive infections, and the post-infectious autoimmune syndromes of acute rheumatic fever and post-streptococcal glomerulonephritis. Genetic manipulation of this important pathogen is complicated by resistance of the organism to genetic transformation. Very low transformation efficiency is attributed to recognition and degradation of introduced foreign DNA by a type I restriction-modification system encoded by the hsdRSM locus. DNA sequence analysis of this locus in ten GAS strains that had been previously transformed with an unrelated plasmid revealed that six of the ten harbored a spontaneous mutation in hsdR, S, or M. The mutations were all different, and at least five of the six were predicted to result in loss of function of the respective hsd gene product. The unexpected occurrence of such mutations in previously transformed isolates suggested that the process of transformation selects for spontaneous inactivating mutations in the Hsd system. We investigated the possibility of exploiting the increased transformability of hsd mutants by constructing a deletion mutation in hsdM in GAS strain 854, a clinical isolate representative of the globally dominant M1T1 clonal group. Mutant strain 854ΔhsdM exhibited a 5-fold increase in transformation efficiency compared to the wild type parent strain and no obvious change in growth or off-target gene expression. We conclude that genetic transformation of GAS selects for spontaneous mutants the hsdRSM restriction modification system. We propose that use of a defined hsdM mutant as a parent strain for genetic manipulation of GAS will enhance transformation efficiency and reduce the likelihood of selecting spontaneous hsd mutants with uncharacterized genotypes.
An Autoantigen Profile of Human A549 Lung Cells Reveals Viral and Host Etiologic Molecular Attributes of Autoimmunity in COVID-19

We aim to establish a comprehensive COVID-19 autoantigen atlas in order to understand autoimmune diseases caused by SARS-CoV-2 infection. Based on the unique affinity between dermatan sulfate and autoantigens, we identified 348 proteins from human lung A549 cells, of which 198 are known targets of autoantibodies. Comparison with current COVID data identified 291 proteins that are altered at protein or transcript level in SARS-CoV-2 infection, with 191 being known autoantigens. These known and putative autoantigens are significantly associated with viral replication and trafficking processes, including gene expression, ribonucleoprotein biogenesis, mRNA metabolism, translation, vesicle and vesicle-mediated transport, and apoptosis. They are also associated with cytoskeleton, platelet degranulation, IL-12 signaling, and smooth muscle contraction. Host proteins that interact with and that are perturbed by viral proteins are a major source of autoantigens. Orf3 induces the largest number of protein alterations, Orf9 affects the mitochondrial ribosome, and they and E, M, N, and Nsp proteins affect protein localization to membrane, immune responses, and apoptosis. Phosphorylation and ubiquitination alterations by viral infection define major molecular changes in autoantigen origination. This study provides a large list of autoantigens as well as new targets for future investigation, e.g., UBA1, UCHL1, USP7, CDK11A, PRKDC, PLD3, PSAT1, RAB1A, SLC2A1, platelet activating factor acetylhydrolase, and mitochondrial ribosomal proteins. This study illustrates how viral infection can modify host cellular proteins extensively, yield diverse autoantigens, and trigger a myriad of autoimmune sequelae.
Gradients of receptor expression in the macaque cortex

Dynamics and functions of neural circuits depend on synaptic interactions mediated by receptors. Therefore, a comprehensive map of receptor organization is needed to understand how different functions may emerge across distinct cortical regions. Here we use in-vitro receptor autoradiography to measure the density of 14 neurotransmitter receptor types in 109 areas of macaque cortex. We integrate the receptor data with other anatomical, genetic and functional connectivity data into a common cortical space. We uncovered a principal gradient of increasing receptor expression per neuron aligned with cortical hierarchy from early sensory cortex to higher cognitive areas. A second gradient, primarily driven by 5-HT1A receptors, peaks in the anterior and subcallosal cingulate, suggesting that the macaque may be a promising animal model for major depressive disorder. The receptor gradients may enable rapid, reliable information processing in sensory cortical areas and slow, flexible integration of information in higher cognitive areas.
Waves of sumoylation support transcription dynamics during adipocyte differentiation

Tight control of gene expression networks required for adipose tissue formation and plasticity is essential for adaptation to energy needs and environmental cues. However, little is known about the mechanisms that orchestrate the dramatic transcriptional changes leading to adipocyte differentiation. We investigated the regulation of nascent transcription by the sumoylation pathway during adipocyte differentiation using SLAMseq and ChIPseq. We discovered that the sumoylation pathway has a dual function in differentiation; it supports the initial downregulation of pre-adipocyte-specific genes, while it promotes the establishment of the mature adipocyte transcriptional program. By characterizing sumoylome dynamics in differentiating adipocytes by mass spectrometry, we found that sumoylation of specific transcription factors like Pparγ/RXR and their co-factors is associated with the transcription of adipogenic genes. Our data demonstrate that the sumoylation pathway coordinates the rewiring of transcriptional networks required for formation of functional adipocytes. This study also provides an in-depth resource of gene transcription dynamics, SUMO-regulated genes and sumoylation sites during adipogenesis.
Rules for the self-assembly of ESCRT-III on endosomes

We, the authors, have withdrawn this manuscript. During our work on the revision of this manuscript for eLife, it became clear that several key results of the manuscript were not reproducible by my lab. The rules for ESCRT-III assembly and the model that we have proposed in this manuscript are no longer supported by the data. Currently we are performing additional experiments to test some of our conclusions further. Therefore, we do not wish this work to be cited. We sincerely apologize to the scientific community for any inconvenience resulting from this manuscript. If you have any questions, please contact the corresponding author.
Detachment of Droplets in a Fully Developed Turbulent Channel Flow

Liquid aerosols deform and detach from solid surfaces under an external force. It is a familiar phenomenon in many engineering applications. This article experimentally investigates the deformation and detachment of liquid droplets on three different solid surfaces in a fully developed turbulent channel flow. It is shown that the droplets either are compressed or elongate under the turbulent flow. The elongation of the droplet due to the turbulent flow is measured and presented. When the friction velocity of the flow exceeds a critical value, the droplets slide along the surface. The critical friction velocity is found empirically to be inversely proportional to the square root of the contact diameter. The sliding velocity after detachment is also reported. It has been observed by many researchers that, when the external force is gravity or a simple shear flow, the retention force of the droplet is proportional to the difference between the cosines of the receding and advancing contact angles. As the shape of a deformed droplet is much more complex under a turbulent flow, this article discusses the applicability of the same relation to the turbulent channel flow. Copyright 2014 American Association for Aerosol Research
The amyloid concentric β-barrel hypothesis: models of Synuclein oligomers, annular protofibrils, lipoproteins, and transmembrane channels

Amyloid beta (Aβ of Alzheimer’s disease) and α-synuclein (α-Syn of Parkinson’s disease) form large fibrils. Evidence is increasing however that much smaller oligomers are more toxic and that these oligomers can form transmembrane ion channels. We have proposed previously that Aβ42 oligomers, annular protofibrils, and ion channels adopt concentric β-barrel molecular structures. Here we extend that hypothesis to the superfamily of α, β, and γ-synucleins. Our models of numerous Synuclein oligomers, annular protofibrils, tubular protofibrils, lipoproteins, and ion channels were developed to be consistent with sizes, shapes, molecular weights, and secondary structures of assemblies as determined by EM and other studies. The models have the following features: 1) all subunits have identical structures and interactions; 2) they are consistent with conventional β-barrel theory; 3) the distance between walls of adjacent β-barrels is between 0.6 and 1.2 nm; 4) hydrogen bonds, salt bridges, interactions among aromatic side-chains, burial and tight packing of hydrophobic side-chains, and aqueous solvent exposure of hydrophilic side-chains are relatively optimal; and 5) residues that are identical among distantly related homologous proteins cluster in the interior of most oligomers whereas residues that are hypervariable are exposed on protein surfaces. Atomic scale models of some assemblies were developed.
Rational Design of High-RI Resists for 193nm Immersion Lithography

We have developed a Quantitative Structure Property Relationship (QSPR) model for predicting the refractive index of small molecules and polymers at 193 nm. This model has been useful for screening databases of compounds for high refractive index to include in our program of synthesis of polymer having high RI. A range of novel target structures were identified and prepared via free radical polymerization. In addition polymers were also synthesized via Michael addition polymerization. Preliminary dose-to-clear and imaging experiments identified a number of promising candidates for incorporation into high refractive index resist materials. The platforms presented may be limited by relatively high intrinsic absorbance, and so design limits for incorporation of sulfur are given.
Reconfigurable broadband printed monopole antenna for portable smart IoT applications

The proposed work presents a design of a smart printed monopole antenna separated from a Hexagonal Matching Load (HML) with an air gap. The patch is fed by a coplanar waveguide, while the HML is connected to the ground plane through two pin diodes to realize antenna reconfiguration through controlling the surface current motion. The antenna structure is mounted on FR‐4 epoxy substrate with size of 23 mm × 30 mm to fit the portable devices. After running four different switching scenarios, an observable change in the antenna performance is demonstrated. The proposed antenna provides a gain of 3.1 dBi at 2.45 GHz when the two diodes are switched ON. However, the antenna gain is changed to 1.6 dBi when the two diodes are set OFF. It is demonstrated that the proposed technique shows an effective approach to control the antenna performance without the need for DC blocking capacitor for RF choke. Nevertheless, the Specific Absorption Rate (SAR) effects are evaluated with respect to the human head tissues for all considered scenarios. Finally, the antenna radiation leakages to the human body are also tested numerically and experimentally for validation.
An efficient anonymous user authentication and key agreement protocol for wireless sensor networks

Due to fast development of wireless technology, wireless sensor networks (WSNs) are used in many applications such environmental monitoring, health monitoring, and area monitoring. To protect WSNs from various security threats, many user authentication protocols have been proposed. Recently, Gope and Hwang have discussed an authentication protocol for WSNs. Here, we show that their scheme is not resistant to stolen verifier, user impersonation, smart card loss, and insider attacks. Also, it does not maintain secrecy of session key and anonymity of sensor node. Then we devise an efficient user authentication protocol using physically unclonable function (PUF) for WSNs to overcome the limitations of their scheme. We present our protocol's informal security analysis to show that is resistant to various known attacks. Formal security verification and analysis of the proposed protocol are done using ProVerif tool and widely accepted Real‐Or‐Random (ROR) model, respectively. In the performance analysis, we show that our protocol offers more security features than the others related schemes.
A dielectric resonator based line stripe miniaturized ultra‐wideband antenna for fifth‐generation applications

This work presents an original dielectric resonator based line stripe miniature ultra‐wideband (UWB) antenna for 5G applications. The length, width, and height of the designed antenna are 23, 15, and 1.605 mm, respectively. The projected antenna prototype is composed of a simple line structure‐based modified scattered patch and a rectangular ground plane consisting of a saw tooth orientation in the upper end. A number of rectangular resonators are placed on both sides of the patch and ground to optimize the desired results. This technique ensures the lower operating band and made a significant improvement of efficiency without compromising the antenna size. The proposed design obtained the range of frequency bandwidth from 3.55 to 4.2 GHz under the −10‐dB scale, which covers the lower fifth‐generation (5G) communication band offered by Federal Communications Commission (FCC). The moderate gain and more than 80% radiation efficiency at a resonant point with strong fidelity factor confirms the usability and lower signal distortion of the antenna. The design offers an omnidirectional radiation pattern with 90° elevated directivity for cross polarization. This proposed design is compact in size and can be integrated into limited space around microwave circuitry with low manufacturing cost. The performance parameters like operating bandwidth, antenna size, and area of application, dielectric constant, fractional bandwidth, and omnidirectional radiation pattern were proposed as a suitable candidate for 5G application.
Gibbs' Energy of Formation of Nickel Orthosilicate (Ni2SiO4)

A solid-state galvanic cell was used to detect the free energy of formation of $Ni_2SiO_4$ [13775-54-7], from NiO and quartz at 925-1375 K. The value for the olivine form is (-13,050 + 5.67 T) $\pm 100 J/mol$ (T in K). The free energy of formation of the spinel form was obtained from the above value and the high-pressure data for olivine spinel transition reported in the literature: (-6970 + 9.70 T) $\pm 710 J/mol$ at 900-1500 K.
Survival of patients with asbestosis can be assessed by risk-predicting models

Objectives Our aim was to investigate the pulmonary function test (PFT) results of patients with asbestosis and determine whether baseline PFTs and the risk-predicting models such as gender, age and physiologic (GAP) variables model and composite physiologic index (CPI) would be useful in predicting survival in these patients. Methods Demographics and PFTs of 100 patients with asbestosis were evaluated. The survival difference between the GAP stages was determined with Kaplan-Meier survival curves with statistical significance analysed with log-rank test. The suitability of the risk-predicting models and baseline PFTs to predict the survival of patients was analysed with Cox regression. Results At baseline, the mean value of diffusion capacity for carbon monoxide (DLCO) was 65%; for forced vital capacity it was 81%, with restrictive lung function being the most common impairment. The median estimated survival of the patients was 124 months, that is, 171 months in GAP stage I, 50 months in stage II and 21 months in stage III (p<0.001). CPI, DLCO% predicted, age at baseline and GAP stage were significant predictors of mortality (all p values under 0.001). Conclusions GAP and CPI as well as baseline DLCO% predicted were significant parameters in the evaluation of the prognosis of the patients with asbestosis; they may be useful in clinical practice when considering treatment strategies of individual patients.
Review on Real Time Background Extraction: Models, Applications, Environments, Challenges and Evaluation Approaches

In the computer vision, background extraction is a promising technique. It is characterized by being applied in many different real time applications in diverse environments and with variety of challenges. Background extraction is the most popular technique employed in the domain of detecting moving foreground objects taken by stationary surveillance cameras. Achieving high performance is required with many perspectives and demands. Choosing the suitable background extraction model plays the major role in affecting the performance matrices of time, memory, and accuracy.In this article we present an extensive review on background extraction in which we attempt to cover all the related topics. We list the four process stages of background extraction and we consider several well-known models starting with the conventional models and ending up with the state-of-the art models. This review also focuses on the model environments whether it is human activities, Nature or sport environments and illuminates on some of the real time applications where background extraction method is adopted. Many challenges are addressed in respect to environment, camera, foreground objects, background, and computation time. In addition, this article provides handy tables containing different common datasets and libraries used in the field of background extraction experiments. Eventually, we illustrate the performance evaluation with a table of the set performance metrics to measure the robustness of the background extraction model against other models in terms of time, accurate performance and required memory.
Stress detection from Twitter posts using LDA

Psychological stress detection continues to remain a large problem among individuals. Identifying and combating stress before letting it take the face of some severe problems is of utmost importance. Traditional psychological stress detection techniques need professional devices and specialists to analyse the data, so it is very important that a method has to be introduced in which one can automatically detect the stress state of the user. In this work, we have made an effort to detect stress from the tweets of the users. We have collected different stressed and non-stressed related tweets from Twitter. Then, we have applied latent Dirichlet allocation (LDA), a popular machine learning algorithm, to detect stress among the individuals from their tweets and categorised the tweets into two classes stressed and non-stressed. We have also found experimentally that our LDA-based system performs better than the SVM-based system.
Rapid sequential determination of americium and plutonium in sediment and soil samples by ICP-SFMS and alpha-spectrometry

An improved sample preparation method for the determination of americium and plutonium in sediment and soil samples by inductively coupled plasma sector field mass spectrometry (ICP-SFMS) and alpha-spectrometry is described. The developed procedure involves a selective CaF2 co-precipitation for pre-concentration and matrix removal followed by a sequential extraction chromatographic separation. The average chemical recovery of sample preparation was between 81–94% for both americium and plutonium. The method development also focused on the elimination of possible interferences in mass spectrometric analysis caused by molecular ions (e.g.238U 1H+, 204Pb 36Ar+ or 208Pb 16O2+) employing the suitable matrix separation prior to ICP-SFMS analysis coupled with a desolvation sample introduction system. For 239Pu, 240Pu, 241Pu and 241Am limits of detection of 15, 9.2, 14 and 23 fg g-1 was achieved by ICP-SFMS, respectively. The applied sample preparation and measurement can be carried out within 6 h for one batch of samples. Results of certified reference materials (IAEA-384 and IAEA-385) analysed by the two different measurement techniques agreed well with the recommended or information values.