Miracle-dz/UniFAR-FTUs huggingface dataset:
Optical Properties of Small Gold Particles

The optical absorption of dispersions of gold particles is studied as a function of particle size, temperature, and method of preparation. The absorption spectra for gold sols in glass and water with small spread in particle size are compared to spectra calculated from Mie theory and the most reliable of recently measured optical constants of gold. The comparisons indicate that the real part of the dielectric constant e1 for particles from 85 to 200 A in diameter is the same as for bulk gold, and that the imaginary part e2 is similar for particles and bulk, although some discrepancies exist. Gold sols in glass have optical properties closer to bulk gold than sols in water, probably because of defects and adsorbed material on the particles in water. Between wavelengths of about 0.40 and 0.45 μ the optical properties of the particles in glass are unchanged down to particles containing very few atoms. The optical absorption peak at 0.525 μ is unaffected by particle size down to a particle diameter of about 8.
New Constraints on Lorentz Invariance Violation from Combined Linear and Circular Optical Polarimetry of Extragalactic Sources

Expanding on our prior efforts to search for Lorentz invariance violation (LIV) using the linear optical polarimetry of extragalactic objects, we propose a new method that combines linear and circular polarization measurements. While existing work has focused on the tendency of LIV to reduce the linear polarization degree, this new method additionally takes into account the coupling between photon helicities induced by some models. This coupling can generate circular polarization as light propagates, even if there is no circular polarization at the source. Combining significant detections of linear polarization of light from extragalactic objects with the absence of the detection of circular polarization in most measurements results in significantly tighter constraints regarding LIV. The analysis was carried out in the framework of the Standard-Model Extension (SME), an effective field theory framework to describe the low-energy effects of an underlying fundamental quantum gravity theory. We evaluate the performance of our method by deriving constraints on the mass dimension d=4 CPT-even SME coefficients from a small set of archival circular and linear optical polarimetry constraints and compare them to similar constraints derived in previous works with far larger sample sizes and based on linear polarimetry only. The new method yielded constraints that are an order of magnitude tighter even for our modest sample size of 21 objects. Based on the demonstrated gain in constraining power from scarce circular data, we advocate for the need for future extragalactic circular polarization surveys.
Critical Temperature in the BCS-BEC Crossover with Spin-Orbit Coupling

We review the study of the superfluid phase transition in a system of fermions whose interaction can be tuned continuously along the crossover from Bardeen–Cooper–Schrieffer (BCS) superconducting phase to a Bose–Einstein condensate (BEC), also in the presence of a spin–orbit coupling. Below a critical temperature the system is characterized by an order parameter. Generally a mean field approximation cannot reproduce the correct behavior of the critical temperature Tc over the whole crossover. We analyze the crucial role of quantum fluctuations beyond the mean-field approach useful to find Tc along the crossover in the presence of a spin–orbit coupling, within a path integral approach. A formal and detailed derivation for the set of equations useful to derive Tc is performed in the presence of Rashba, Dresselhaus and Zeeman couplings. In particular in the case of only Rashba coupling, for which the spin–orbit effects are more relevant, the two-body bound state exists for any value of the interaction, namely in the full crossover. As a result the effective masses of the emerging bosonic excitations are finite also in the BCS regime.
EfficientNetV2: Smaller Models and Faster Training

This paper introduces EfficientNetV2, a new family of convolutional networks that have faster training speed and better parameter efficiency than previous models. To develop this family of models, we use a combination of training-aware neural architecture search and scaling, to jointly optimize training speed and parameter efficiency. The models were searched from the search space enriched with new ops such as Fused-MBConv. Our experiments show that EfficientNetV2 models train much faster than state-of-the-art models while being up to 6.8x smaller. Our training can be further sped up by progressively increasing the image size during training, but it often causes a drop in accuracy. To compensate for this accuracy drop, we propose to adaptively adjust regularization (e.g., dropout and data augmentation) as well, such that we can achieve both fast training and good accuracy. With progressive learning, our EfficientNetV2 significantly outperforms previous models on ImageNet and CIFAR/Cars/Flowers datasets. By pretraining on the same ImageNet21k, our EfficientNetV2 achieves 87.3% top-1 accuracy on ImageNet ILSVRC2012, outperforming the recent ViT by 2.0% accuracy while training 5x-11x faster using the same computing resources. Code will be available at https://github.com/google/automl/tree/master/efficientnetv2.
The JCMT BISTRO-2 Survey: The Magnetic Field in the Center of the Rosette Molecular Cloud

We present the first 850 μm polarization observations in the most active star-forming site of the Rosette Molecular Cloud (d ∼ 1.6 kpc) in the wall of the Rosette Nebula, imaged with the SCUBA-2/POL-2 instruments of the James Clerk Maxwell telescope, as part of the B-Fields In Star-forming Region Observations 2 (BISTRO-2) survey. From the POL-2 data we find that the polarization fraction decreases with the 850 μm continuum intensity with α = 0.49 ± 0.08 in the p ∝ I −α relation, which suggests that some fraction of the dust grains remain aligned at high densities. The north of our 850 μm image reveals a “gemstone ring” morphology, which is a ∼1 pc diameter ring-like structure with extended emission in the “head” to the southwest. We hypothesize that it might have been blown by feedback in its interior, while the B-field is parallel to its circumference in most places. In the south of our SCUBA-2 field the clumps are apparently connected with filaments that follow infrared dark clouds. Here, the POL-2 magnetic field orientations appear bimodal with respect to the large-scale Planck field. The mass of our effective mapped area is ∼174 M ⊙, which we calculate from 850 μm flux densities. We compare our results with masses from large-scale emission-subtracted Herschel 250 μm data and find agreement within 30%. We estimate the plane-of-sky B-field strength in one typical subregion using the Davis–Chandrasekhar–Fermi technique and find 80 ± 30 μG toward a clump and its outskirts. The estimated mass-to-flux ratio of λ = 2.3 ± 1.0 suggests that the B-field is not sufficiently strong to prevent gravitational collapse in this subregion.
Latent Variable Nested Set Transformers & AutoBots

Humans have the innate ability to attend to the most relevant actors in their vicinity and can forecast how they may behave in the future. This ability will be crucial for the deployment of safety-critical agents such as robots or vehicles which interact with humans. We propose a theoretical framework for this problem setting based on autoregressively modelling sequences of nested sets, using latent variables to better capture multimodal distributions over future sets of sets. We present a new model architecture which we call a Nested Set Transformer which employs multi-head self-attention blocks over sets of sets that serve as a form of social attention between the elements of the sets at every timestep. Our approach can produce a distribution over future trajectories for all agents under consideration, or focus upon the trajectory of an ego-agent. We validate the Nested Set Transformer for autonomous driving settings which we refer to as (“AutoBot”), where we model the trajectory of an ego-agent based on the sequential observations of key attributes of multiple agents in a scene. AutoBot produces results better than state-of-the-art published prior work on the challenging nuScenes vehicle trajectory modeling benchmark. We also examine the multi-agent prediction version of our model and jointly forecast an ego-agent’s future trajectory along with the other agents in the scene. We validate the behavior of our proposed Nested Set Transformer for scene level forecasting with a pedestrian trajectory dataset.
Text to Image Generation with Semantic-Spatial Aware GAN

Text-to-image synthesis (T2I) aims to generate photorealistic images which are semantically consistent with the text descriptions. Existing methods are usually built upon conditional generative adversarial networks (GANs) and initialize an image from noise with sentence embedding, and then refine the features with fine-grained word embedding iteratively. A close inspection of their generated images reveals a major limitation: even though the generated image holistically matches the description, individual image regions or parts of somethings are often not recognizable or consistent with words in the sentence, e.g. “a white crown”. To address this problem, we propose a novel framework Semantic-Spatial Aware GAN for synthesizing images from input text. Concretely, we introduce a simple and effective Semantic-Spatial Aware block, which (1) learns semantic-adaptive transformation conditioned on text to effectively fuse text features and image features, and (2) learns a semantic mask in a weakly-supervised way that depends on the current text-image fusion process in order to guide the transformation spatially. Experiments on the challenging COCO and CUB bird datasets demonstrate the advantage of our method over the recent state-of-the-art approaches, regarding both visual fidelity and alignment with input text description. Code available at https://github.com/wtliao/text2image.
Conducting polymers and their inorganic composites for advanced Li-ion batteries: a review

Conducting polymers are promising materials for organic–inorganic hybrid composites in lithium-ion batteries due to their electrical conductivity and high coulombic efficiency and are able to be cycled hundreds or thousands of times with only slight degradation. Inorganic compounds generally possess good lithium storage properties but lack the conductivity and cyclability required for commercial application. Therefore, these problems need to be overcome before they can be used as effective electrodes. Over the past few years, conductive polymers in combination with inorganic compounds have attracted great interest as promising matrices for the construction of lithium-ion batteries. Because conducting polymers can interact synergistically with inorganic compounds, noteworthy improvements in electrode lifetime, rate capabilities, and voltage, as well as mechanical and thermal stability, have been achieved. This review covers recent advances in synthetic methods and functions of conducting polymers in hybrid composites and their application in lithium-ion batteries. We then present a comparison of other synthetic methods for new research and development in batteries. A brief appraisal of avenues for future developments in this area is also presented.
Comparison of Two PCR-Based Genetic Fingerprinting Methods for Assessment of Genetic Diversity in Saccharomyces Strains

Two molecular methods, interdelta polymorphism fingerprinting of genomic DNA and COX1 intron polymorphism fingerprinting of mitochondrial DNA, were used to characterize 52 strains of Saccharomyces identified to species by 26S rDNA sequencing only in order to assess the potential of these techniques for strain typing and genetic analysis individually and in combination. Two laboratory isolates derived from the same parentage served as a control. Forty-seven S. cerevisiae strains representing a mix of commercial strains and vineyard or winery isolates were used. Five of these strains have been given the commercial designation S. cerevisiae race bayanus. Three strains were identified as S. bayanus, S. kudriavzevii, and S. servazzii from their 26S rDNA sequence and thus may be hybrids. Forty-four genetic patterns were found among the strains by interdelta polymorphism fingerprinting and 47 genetic patterns were found by COX1 intron polymorphism fingerprinting. Each method allowed differentiation of the majority of strains but grouped strains into different clusters. Strains were clustered into eight groups using both techniques in combination. The two laboratory strains clustered together but were in a larger grouping of wine strains. Saccharomyces bayanus, S. kudriavzevii, and S. servazzii were separated from each other but each clustered with S. cerevisiae strains and could not be differentiated from S. cerevisiae by either method. Three of the S. cerevisiae race bayanus strains clustered together but the other two were in different groupings. Of the 10 commercial strains, 904 (French Red) was grouped alone, while 522 (Montrachet) and 905 (Premier Cuvee) were grouped with wild isolates from different areas. Thus both methods reveal patterns of strain similarity but neither method differentiated strains by species or by origin.
Investigating the mediating role of online learning motivation in the COVID‐19 pandemic situation in Bangladesh

Abstract The purpose of this paper is to investigate the mediating role of online learning motivation (OLM) in the COVID‐19 pandemic situation in Bangladesh by observing and comparing direct lectures (DL), instructor–learner interaction (ILI), learner–learner interaction (LLI), and internet self‐efficacy (ISE) as predictors of OLM and online learning satisfaction (OLS). Data were collected from 442 undergraduate and graduate students from more than 35 universities in Bangladesh. To test the hypotheses, the PLS‐SEM approach was applied using SmartPLS 3.0. The study shows a significant mediating role of OLM between the independent variables and learning satisfaction. In addition, DL, ILI, and ISE are shown to be significant predictors of student satisfaction. The findings have a number of valuable implications for education policy makers, universities, instructors, and students. Moreover, the study suggests some new research perspectives to overcome the limitations of this research and to gain precise knowledge on students' learning motivation and satisfaction regarding other online classes for different categories of students (e.g., high school and college, professional, and PhD).
The first sixty days of COVID-19 in a humanitarian response setting: a descriptive epidemiological analysis of the outbreak in South Sudan

Introduction the coronavirus disease 2019 (COVID-19) was declared a pandemic on March 11, 2020. South Sudan, a low-income and humanitarian response setting, reported its first case of COVID-19 on April 5, 2020. We describe the socio-demographic and epidemiologic characteristics of COVID-19 cases in this setting. Methods we conducted a cross-sectional descriptive analysis of data for 1,330 confirmed COVID-19 cases from the first 60 days of the outbreak. Results among the 1,330 confirmed cases, the mean age was 37.1 years, 77% were male, 17% were symptomatic with 95% categorized as mild, and the case fatality rate was 1.1%. Only 24.7% of cases were detected through alerts and sentinel site surveillance, with 95% of the cases reported from the capital, Juba. Epidemic doubling time averaged 9.8 days (95% confidence interval [CI] 7.7 - 13.4), with an attack rate of 11.5 per 100,000 population. Test positivity rate was 18.2%, with test rate per 100,000 population of 53 and mean test turn-around time of 9 days. The case to contact ratio was 1: 2.2. Conclusion this 2-month initial period of COVID-19 in South Sudan demonstrated mostly young adults and men affected, with most cases reported as asymptomatic. Systems´ limitations highlighted included a small proportion of cases detected through surveillance, low testing rates, low contact elicitation, and long collection to test turn-around times limiting the country´s ability to effectively respond to the outbreak. A multi-pronged response including greater access to testing, scale-up of surveillance, contact tracing and community engagement, among other interventions are needed to improve the COVID-19 response in this setting.
COVID‐19 infection in patients with connective tissue disease: A multicity study in Hubei province, China

Abstract Novel Coronavirus disease 2019 (COVID‐19) has spread rapidly around the world. Individuals with immune dysregulation and/or on immunosuppressive therapy, such as rheumatic patients, are considered at greater risk for infections. However, the risks of patients with each subcategory of rheumatic diseases have not been reported. Here, we identified 100 rheumatic patients from 18,786 COVID‐19 patients hospitalized in 23 centers affiliated to Hubei COVID‐19 Rheumatology Alliance between January 1 and April 1, 2020. Demographic information, medical history, length of hospital stay, classification of disease severity, symptoms and signs, laboratory tests, disease outcome, computed tomography, and treatments information were collected. Compared to gout and ankylosing spondylitis (AS) patients, patients with connective tissue disease (CTD) tend to be more severe after COVID‐19 infection (p = 0.081). CTD patients also had lower lymphocyte counts, hemoglobin, and platelet counts (p values were 0.033, < 0.001, and 0.071, respectively). Hydroxychloroquine therapy and low‐ to medium‐dose glucocorticoids before COVID‐19 diagnosis reduced the progression of COVID‐19 to severe/critical conditions (p = 0.001 for hydroxychloroquine; p = 0.006 for glucocorticoids). Our data suggests that COVID‐19 in CTD patients may be more severe compared to patients with AS or gout.
Clonal Dissemination of KPC-2, VIM-1, OXA-48-Producing Klebsiella pneumoniae ST147 in Katowice, Poland

Abstract Carbapenem-resistant Klebsiella pneumoniae (CRKP) is an important bacterium of nosocomial infections. In this study, CRKP strains, which were mainly isolated from fecal samples of 14 patients in three wards of the hospital in the Silesia Voivodship, rapidly increased from February to August 2018. Therefore, we conducted microbiological and molecular studies of the CRKP isolates analyzed. Colonized patients had critical underlying diseases and comorbidities; one developed bloodstream infection, and five died (33.3%). Antibiotic susceptibilities were determined by the E-test method. A disc synergy test confirmed carbapenemase production. CTX-Mplex PCR evaluated the presence of resistance genes blaCTX-M-type, blaCTX-M-1, blaCTX-M-9, and the genes blaSHV, blaTEM, blaKPC-2, blaNDM-1, blaOXA-48, blaIMP, and blaVIM-1 was detected with the PCR method. Clonality was evaluated by Multi Locus Sequence Typing (MLST) and Pulsed Field Gel Electrophoresis (PFGE). Six (40%) strains were of XDR (Extensively Drug-Resistant) phenotype, and nine (60%) of the isolates exhibited MDR (Multidrug-Resistant) phenotype. The range of carbapenem minimal inhibitory concentrations (MICs, μg/mL) was as follows doripenem (16 to >32), ertapenem (> 32), imipenem (4 to > 32), and meropenem (> 32). PCR and sequencing confirmed the blaCTX-M-15, blaKPC-2, blaOXA-48, and blaVIM-1 genes in all strains. The isolates formed one large PFGE cluster (clone A). MLST assigned them to the emerging high-risk clone of ST147 (CC147) pandemic lineage harboring the blaOXA-48 gene. This study showed that the K. pneumoniae isolates detected in the multi-profile medical centre in Katowice represented a single strain of the microorganism spreading in the hospital environment.
Experiences and Reflections about Teaching Atomic Structure in a Jigsaw Classroom in Lower Secondary School Chemistry Lessons

This article describes and discusses an example of how atomic structure can be taught in lower secondary chemistry using a modified jigsaw-classroom method. The lesson was taught in grades 9 and 10 (age range 15–17 years) chemistry in 13 learning groups with a total of 313 students in various grammar, middle, and comprehensive schools in Germany. The written evaluation of the lesson focused on determining the students’ opinions on the teaching methods that were used. Emphasis was on gathering information from the students’ viewpoint. Did the students think that these methods could make science lessons more attractive? Could these methods help to promote more active student learning, cooperative learning, or communicative and social abilities? Additional data that were derived from a cognitive test and teacher feedback are also presented. The results of the study show that teaching methods like the jigsaw classroom have potential to improve students’ attitude towards science. The results may also indicate .
The effect of unilateral training on contralateral limb power in young women and men

The purpose of this study was to determine the effect of training of one side of the body on the muscle torques and power output on the trained and untrained side. Seventeen female and twenty-two male students were subject to a four-week knee joint power training regimen on a specially designed stand. The subjects were divided into two groups: a training group (female – N = 11 and male – N = 16) and a control group (female – N = 6 and male – N = 6). Effectiveness of power training on the stand described previously was estimated based on bilateral knee torque and power under static and isokinetic conditions. The experiment lasted for 39 days and was preceded by preliminary studies (pre-training). Control measurements in training groups were made after four weeks of training (post-training) and after the next two weeks (de-training). Power training caused an insignificant increase in force and power in both groups for the untrained leg and a significant increase in RMS EMG. Therefore, the study confirmed the hypothesis that resistance training performed in dynamic conditions can affect the contralateral limb and may also trigger delayed adaptations to training conditions during the detraining phase. Sex differences in adaptation to power training are not clear; however, the differences in gains in contralateral effects between men and women were not confirmed.