Miracle-dz/UniFAR-FTUs huggingface dataset:
Internal Wave and Turbulence Observations with Very High-Resolution Temperature Sensors along the Cabauw Mast

Knowledge about the characteristics of the atmospheric boundary layer is vital for the understanding of redistribution of air and suspended contents that are particularly driven by turbulent motions. Despite many modeling studies, detailed observations are still demanded of the development of turbulent exchange under stable and unstable conditions. In this paper, we present an attempt to observationally describe atmospheric internal waves and their associated turbulent eddies in detail, under varying stable conditions. Therefore, we mounted 198 high-resolution temperature (T) sensors with 1-m spacing on a 200-m-long cable. The instrumented cable was attached along the 213-m-tall meteorological mast of Cabauw, Netherlands, during late summer 2017. The mast has standard meteorological equipment at extendable booms at six levels in height. A sonic anemometer is at 60 m above ground. The T sensors have a time constant in air of τa ≈ 3 s and an apparent drift about 0.1°C month−1. Also due to radiation effects, short-term measurement instability is 0.05°C h−1 during nighttime and 0.5°C h−1 during daytime. These T-sensor characteristics hamper quantitative atmospheric turbulence research, due to a relatively narrow inertial subrange of maximum one order of magnitude. Nevertheless, height–time images from two contrasting nights show internal waves up to the buoyancy period of about 300 s, and shear and convective deformation of the stratification over the entire 197-m range of observations, supported by nocturnal marginally stable stratification. Moderate winds lead to 20-m-tall convection across weaker stratification, weak winds to episodic <10-m-tall shear instability across larger stratification.
On Procedural Adversarial Noise Attack And Defense

Deep Neural Networks (DNNs) are vulnerable to adversarial examples which would inveigle neural networks to make prediction errors with small perturbations on the input images. Researchers have been devoted to promoting the research on the universal adversarial perturbations (UAPs) which are gradient-free and have little prior knowledge on data distributions. Procedural adversarial noise attack is a data-free universal perturbation generation method. In this paper, we propose two universal adversarial perturbation (UAP) generation methods based on procedural noise functions: Simplex noise and Worley noise. In our framework, the shading which disturbs visual classification is generated with rendering technology. Without changing the semantic representations, the adversarial examples generated via our methods show superior performance on the attack.
Effect of N719 dye concentration on the Conversion Efficiency of Dye Sensitized Solar Cells (DSSCs)

In this study, DSSCs with various concentrations (0.125, 0.25 and 0.5 mM) of N719 dye have been successfully prepared using simple steps. The X-ray diffraction results of the TiO 2 film showed that it is polycrystalline with anatase phase (tetragonal system) having crystallite size of about 12 nm. The absorbance spectrum of the TiO 2 film and N719 dye at various concentrations was recorded by Ultra Violet – Visible (UV-Vis) spectrophotometer. The energy band gap of the TiO 2 film calculated by Tauc’s formula was ~ 3.1 eV. The scanning electron microscope (SEM) image of the TiO 2 surface shows a spongy-like morphology having open pores which can enhance the adsorption of the dye molecules the transport of electrons. The atomic force microscope (AFM) image and the distribution chart of the grains of the TiO 2 film show that the grain size was~ 82 nm. The DSSC prepared using N719 dye concentration of 0.5 mM achieved the highest conversion efficiency (η) of 2.504 %, respectively. Subsequently, the enhancement in efficiency was ~ 86 % compared with the conversion efficiency of DSSCs prepared with at N719 dye concentration of 0.125 mM and 0.25 mM.
Star Formation Histories of Ultra-faint Dwarf Galaxies: Environmental Differences between Magellanic and Non-Magellanic Satellites?

We present the color–magnitude diagrams and star formation histories (SFHs) of seven ultra-faint dwarf galaxies: Horologium 1, Hydra 2, Phoenix 2, Reticulum 2, Sagittarius 2, Triangulum 2, and Tucana 2, derived from high-precision Hubble Space Telescope photometry. We find that the SFH of each galaxy is consistent with them having created at least 80% of the stellar mass by z ∼ 6. For all galaxies, we find quenching times older than 11.5 Gyr ago, compatible with the scenario in which reionization suppresses the star formation of small dark matter halos. However, our analysis also reveals some differences in the SFHs of candidate Magellanic Cloud satellites, i.e., galaxies that are likely satellites of the Large Magellanic Cloud and that entered the Milky Way potential only recently. Indeed, Magellanic satellites show quenching times about 600 Myr more recent with respect to those of other Milky Way satellites, on average, even though the respective timings are still compatible within the errors. This finding is consistent with theoretical models that suggest that satellites’ SFHs may depend on their host environment at early times, although we caution that within the error bars all galaxies in our sample are consistent with being quenched at a single epoch.
TrUMAn: Trope Understanding in Movies and Animations

Understanding and comprehending video content is crucial for many real-world applications such as search and recommendation systems. While recent progress of deep learning has boosted performance on various tasks using visual cues, deep cognition to reason intentions, motivation, or causality remains challenging. Existing datasets that aim to examine video reasoning capability focus on visual signals such as actions, objects, relations, or could be answered utilizing text bias. Observing this, we propose a novel task, along with a new dataset: Trope Understanding in Movies and Animations (TrUMAn), with 2423 videos associated with 132 tropes, intending to evaluate and develop learning systems beyond visual signals. Tropes are frequently used storytelling devices for creative works. By coping with the trope understanding task and enabling the deep cognition skills of machines, data mining applications and algorithms could be taken to the next level. To tackle the challenging TrUMAn dataset, we present a Trope Understanding and Storytelling (TrUSt) with a new Conceptual Storyteller module, which guides the video encoder by performing video storytelling on a latent space. Experimental results demonstrate that state-of-the-art learning systems on existing tasks reach only 12.01% of accuracy with raw input signals. Also, even in the oracle case with human-annotated descriptions, BERT contextual embedding achieves at most 28% of accuracy. Our proposed TrUSt boosts the model performance and reaches 13.94% performance. We also provide detailed analysis to pave the way for future research. TrUMAn is publicly available at:https://www.cmlab. csie.ntu. edu.tw/project/trope
A Novel Markovian Framework for Integrating Absolute and Relative Ordinal Emotion Information

There is growing interest in affective computing for the representation and prediction of emotions along ordinal scales. However, the term ordinal emotion label has been used to refer to both absolute notions such as low or high arousal, as well as relation notions such as arousal is higher at one instance compared to another. In this paper, we introduce the terminology absolute and relative ordinal labels to make this distinction clear and investigate both with a view to integrate them and exploit their complementary nature. We propose a Markovian framework referred to as Dynamic Ordinal Markov Model (DOMM) that makes use of both absolute and relative ordinal information, to improve speech based ordinal emotion prediction. Finally, the proposed framework is validated on two speech corpora commonly used in affective computing, the RECOLA and the IEMOCAP databases, across a range of system configurations. The results consistently indicate that integrating relative ordinal information improves absolute ordinal emotion prediction.
Falling for Phishing: An Empirical Investigation into People's Email Response Behaviors

Despite sophisticated phishing email detection systems, and training and awareness programs, humans continue to be tricked by phishing emails. In an attempt to better understand why phishing email attacks still work and how best to mitigate them, we have carried out an empirical study to investigate people's thought processes when reading their emails. We used a scenario-based role-play"think aloud"method and follow-up interviews to collect data from 19 participants. The experiment was conducted using a simulated web email client, and real phishing and legitimate emails adapted to the given scenario. The analysis of the collected data has enabled us to identify eleven factors that influence people's response decisions to both phishing and legitimate emails. Furthermore, based on the user study findings, we discuss novel insights into flaws in the general email decision-making behaviors that could make people susceptible to phishing attacks.
Stellar triples on the edge. Comprehensive overview of the evolution of destabilised triples leading to stellar and binary exotica

Hierarchical triple stars are ideal laboratories for studying the interplay between orbital dynamics and stellar evolution. Both stellar wind mass loss and three-body dynamics cooperate to destabilise triples, which can lead to a variety of astrophysical exotica. So far our understanding of their evolution was mainly built upon results from extensive binary-single scattering experiments. Starting from generic initial conditions, we evolve an extensive set of hierarchical triples using a combination of the triple evolution code TRES and an N-body code. We find that the majority of triples preserve their hierarchy throughout their evolution, which is in contradiction with the commonly adopted picture that unstable triples always experience a chaotic, democratic resonant interaction. The duration of the unstable phase is much longer than expected, so that stellar evolution cannot be neglected. Typically an unstable triple dissolve into a single star and a binary; sometimes democratically (the initial hierarchy is lost and the lightest body usually escapes), but also in a hierarchical way (the tertiary is ejected in a slingshot, independent of its mass). Collisions are common, and mostly involve the two original inner binary components still on the main-sequence. This contradicts the idea that collisions with a giant during democratic encounters dominate. Together with collisions in stable triples, we find that triple evolution is the dominant mechanism for stellar collisions in the Milky Way. Furthermore, our simulations produce runaway and walk-away stars with speeds up to several tens km/s, with a maximum of a few 100km/s. We suggest that destabilised triples can alleviate the tension behind the origin of the observed run-away stars. Lastly, we present a promising indicator to make general predictions for the fate of a specific triple, based on the initial inclination of the system.
AdaRNN: Adaptive Learning and Forecasting of Time Series

Time series has wide applications in the real world and is known to be difficult to forecast. Since its statistical properties change over time, its distribution also changes temporally, which will cause severe distribution shift problem to existing methods. However, it remains unexplored to model the time series in the distribution perspective. In this paper, we term this as Temporal Covariate Shift (TCS). This paper proposes Adaptive RNNs (AdaRNN) to tackle the TCS problem by building an adaptive model that generalizes well on the unseen test data. AdaRNN is sequentially composed of two novel algorithms. First, we propose Temporal Distribution Characterization to better characterize the distribution information in the TS. Second, we propose Temporal Distribution Matching to reduce the distribution mismatch in TS to learn the adaptive TS model. AdaRNN is a general framework with flexible distribution distances integrated. Experiments on human activity recognition, air quality prediction, and financial analysis show that AdaRNN outperforms the latest methods by a classification accuracy of 2.6% and significantly reduces the RMSE by 9.0%. We also show that the temporal distribution matching algorithm can be extended in Transformer structure to boost its performance.
“Here we go again”: the inspection of collagen extraction protocols for 14C dating and palaeodietary analysis

ABSTRACT Archaeological bone collagen is highly useful for radiocarbon (14C) dating and palaeodietary reconstruction. However, collagen preservation and carbon contamination are essential considerations when extracting collagen, becoming especially crucial close to the limit of the method (50,000 years before present = BP). Strong progress has been achieved in the past two decades by 14C and stable isotopic laboratories in removing contamination from archaeological bones, but different pretreatment protocols have been proven to produce varying results. Here we compare three collagen extraction protocols used for palaeodietary studies and 14C dating, considering collagen yield, elemental and stable isotopic data, FTIR analysis, and 14C dates. We focus on the impact of ultrafiltration on the yield and quality of the extracted material. The results again underline the importance of rigorous decontamination methods to gain accurate 14C dates and demonstrate that different protocols have significant effects on the quality and yield of extracted collagen.
Coronavirus Disease 2019 in a Patient With a Systemic Autoinflammatory Syndrome due to an NLRC4 Inflammasomopathy

Abstract The effect of autoinflammatory diseases on severe acute respiratory syndrome coronavirus 2 infection remains unknown. We report a case of coronavirus disease 2019 (COVID-19) in a patient with autoinflammation with infantile enterocolitis with inflammatory flares due to a mutation in the inflammasome component NLRC4. This case highlights the role of immunosuppression in patients with autoinflammation with COVID-19.
A systematic review assessing the quality of patient reported outcomes measures in dry eye diseases

Background Patient-reported outcome measures (PROMs) can provide valuable insights on the impact of a disease or treatment on a patient’s health-related quality of life. In ophthalmology, particularly in dry eye disease (DED) and ocular surface disease (OSD), it is unclear whether the available PROMs were developed using comprehensive guidelines. To address this, we evaluated the methodological quality of studies assessing the psychometric properties of PROMs in DED and OSD [PROSPERO registration number CRD42019142328]. Methods Four databases were searched; reference list and citation searching of included studies was also conducted. The COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist was used to appraise the quality of the studies evaluating the psychometric properties of PROMs used in DED and OSD. Results The search strategy (S3 Table) retrieved 5,761 records, 573 duplicates were removed, 5,188 abstracts were screened and 127 full-text articles were retrieved for further review. Of these, 118 full-text articles did not meet the eligibility criteria and were excluded. Reference list and citation searching, identified an additional 8 articles bringing the total numbers of papers reviewed to 17. In general, psychometric properties such as content validity, measurement error and structural validity were not assessed by the studies included in this review. Studies reviewing The Impact of Dry Eye on Everyday Life (IDEEL) presented with the highest quality scores together with the Ocular Surface Disease Index (OSDI) questionnaire. Conclusions The quality of studies evaluating PROMs in DED and OSD was considered using the COSMIN standards. The majority of the studies evaluating PROMs included in this review did not meet the recommended COSMIN criteria and the quality of the PROMs evaluated is not assured. Further evaluation of their psychometric properties is required if these are going to be used in clinical practice or research.
The role of the intestinal ultrasound in Crohn’s disease diagnosis and monitoring

Crohn’s disease is characterized by persistent or recurrent chronic inflammation that may affect any segment of the gastrointestinal tract. It has an oscillating evolution, with periods of activity alternating with periods of remission. Crohn’s disease has a significant impact on the economic status due to its increasing prevalence, often affecting young people. Suitable management for these patients involves frequent evaluations. Even though colonoscopy is the gold standard for the assessment of severity and mucosal healing, it is an invasive maneuver, not easily accepted by patients, and it does not have good repeatability. Intestinal ultrasound has the advantage of being non-irradiating, non-invasive, well-tolerated, cheap, and easy to repeat. Ultrasound parameters such as bowel wall thickness, intestinal wall architecture, intramural vascularisation, proliferation of mesenteric fatty conjunctive tissue, and intraperitoneal fluid can provide good information regarding the severity of the disease, the differentiation between remission and relapse, and its complications. Some of the latest studies show good correlations between ultrasound parameters and inflammation markers (C-reactive protein, fecal calprotectin) and clinical severity scores of Crohn’s disease. Consequently, the importance of intestinal ultrasound has increased lately, and recent studies support its use to evaluate the severity of inflammation, differentiate between active disease and relapse, monitor therapy response and guide treatment, evaluate prognosis, and diagnose complications.
Effect of Bunch Feeding on Reproductive Parameters, Bunch Parameters, Hand Parameters and Fingers Parameters in Banana cv. Rajapuri (Musa AAB)

Banana is one of the important fruit crop of India. The name banana comes from the Arabic word ‘BANANA’, which means finger. Banana is also known by other synonyms like ‘Adam’s fig’, ‘Kalpataru’, ‘Tree of wisdom’ and ‘Apple of Paradise’. Banana (Musa spp) is one of the major commercial fruit crops grown in the tropics, subtropics and plays a key role in the economy of developing countries. In India it is cultivated throughout the year. Among the banana varieties grown, the cultivar ‘Rajapuri’ belongs to the Musa AAB group is one of the popular varieties among growers and consumers, particularly in Karnataka and Kerala for domestic markets. Banana has many varieties but among those, local or indigeneous cultivars are more tolerant to biotic and abiotic stresses and suitable to local agro-climatic conditions.
Native and oxidised lipoproteins negatively regulate the serum amyloid A‐induced NLRP3 inflammasome activation in human macrophages

The NLRP3 inflammasome plays a key role in arterial wall inflammation. In this study, we elucidated the role of serum lipoproteins in the regulation of NLRP3 inflammasome activation by serum amyloid A (SAA) and other inflammasome activators.
Application of High-Resolution Remote-Sensing Data for Land Use Land Cover Mapping of University Campus

The study of Land Use Land Cover (LULC) is essential to understanding how land has been altered in recent years and what has caused the processes behind the change. This is significant for the future development of the area, particularly on the campus of the Universitas Padjadjaran Jatinangor. The purpose of this study was to apply remote-sensing techniques to map a university campus and vicinity by comparing the area of urban green space (UGS) and floor area ratios (FARs) of the campus in 2015 and 2017. Additionally, surface runoff analysis was also conducted. For our research, we used WorldView-2's high-resolution satellite imagery with a resolution of 0.46 m in the Universitas Padjadjaran (Padjadjaran University, or Unpad) Jatinangor campus, Jawa Barat, Indonesia. Our approach was to interpret the imagery by running the normalized difference vegetation index (NDVI) to distinguish UGS and FAR and using digital elevation model (DEM) interferometric synthetic aperture radar (SAR) data with hydrologic analysis to identify the direction of surface runoff. The results obtained are as follows: the UGS remained more extensive compared with FAR, but the difference decreased over time owing to infrastructure development. Surface runoff has tended to flow toward the southeast in direct relation to the slope configuration.
Mechanism Exploration of 3-Hinge Gyral Formation and Pattern Recognition

Abstract The 3-hinge gyral folding is the conjunction of gyrus crest lines from three different orientations. Previous studies have not explored the possible mechanisms of formation of such 3-hinge gyri, which are preserved across species in primate brains. We develop a biomechanical model to mimic the formation of 3-hinge patterns on a real brain and determine how special types of 3-hinge patterns form in certain areas of the model. Our computational and experimental imaging results show that most tertiary convolutions and exact locations of 3-hinge patterns after growth and folding are unpredictable, but they help explain the consistency of locations and patterns of certain 3-hinge patterns. Growing fibers within the white matter is posited as a determining factor to affect the location and shape of these 3-hinge patterns. Even if the growing fibers do not exert strong enough forces to guide gyrification directly, they still may seed a heterogeneous growth profile that leads to the formation of 3-hinge patterns in specific locations. A minor difference in initial morphology between two growing model brains can lead to distinct numbers and locations of 3-hinge patterns after folding.
Shallow population structure of southern bluefin tuna, Thunnus maccoyii (Castelnau, 1872) between Indian and Atlantic Oceans inferred from mitochondrial DNA sequences

Abstract Southern bluefin tuna (Thunnus maccoyii Castelnau, 1872) is distributed across most of the southern temperate ocean and migrates extensively between 30°S and 50°S. Since T. maccoyii has been continually and heavily exploited, it is necessary to investigate the genetic diversity, population structure and demographic history of T. maccoyii for effective management and conservation. Thirty-seven gonad tissues of T. maccoyii were sampled from two locations, which were in the eastern Indian Ocean and the eastern Atlantic Ocean, by scientific observers onboard Korean T. maccoyii longline vessels in 2015. We compared 1240-bp sequences of combined mitochondrial DNA (mtDNA) from the cytochrome c oxidase subunit I (COI, 504-bp) and control region (CR, 736-bp) sequences. The pairwise fixation index (F ST) and maximum-likelihood tree showed that two clades (A and B) were formed regardless of locations. Clade A occurred more commonly than clade B in both localities: the occurrence ratio of clade A was 69% in the Indian Ocean, and 79% in the Atlantic Ocean, respectively. Our findings suggest that a historic differentiation event may have occurred in T. maccoyii, but recently the connectivity between the two oceans may be possible in T. maccoyii populations.