Miracle-dz/UniFAR-FTUs huggingface dataset:
Interaction of Large- and Small-scale Dynamos in Isotropic Turbulent Flows from GPU-accelerated Simulations

Magnetohydrodynamical (MHD) dynamos emerge in many different astrophysical situations where turbulence is present, but the interaction between large-scale dynamos (LSDs) and small-scale dynamos (SSDs) is not fully understood. We performed a systematic study of turbulent dynamos driven by isotropic forcing in isothermal MHD with magnetic Prandtl number of unity, focusing on the exponential growth stage. Both helical and nonhelical forcing was employed to separate the effects of LSD and SSD in a periodic domain. Reynolds numbers ( ) up to ≈250 were examined and multiple resolutions used for convergence checks. We ran our simulations with the Astaroth code, designed to accelerate 3D stencil computations on graphics processing units (GPUs) and to employ multiple GPUs with peer-to-peer communication. We observed a speedup of ≈35 in single-node performance compared to the widely used multi-CPU MHD solver Pencil Code. We estimated the growth rates from both the averaged magnetic fields and their power spectra. At low LSD growth dominates, but at high SSD appears to dominate in both helically and nonhelically forced cases. Pure SSD growth rates follow a logarithmic scaling as a function of . Probability density functions of the magnetic field from the growth stage exhibit SSD behavior in helically forced cases even at intermediate . We estimated mean field turbulence transport coefficients using closures like the second-order correlation approximation (SOCA). They yield growth rates similar to the directly measured ones and provide evidence of α quenching. Our results are consistent with the SSD inhibiting the growth of the LSD at moderate , while the dynamo growth is enhanced at higher .
Quantum phases of two-dimensional $\mathbb{Z}_2$ gauge theory coupled to spinless fermion matter

We investigate the rich quantum phase diagram of Wegner's theory of discrete Ising gauge fields interacting with $U(1)$ symmetric single-component fermion matter hopping on a two-dimensional square lattice. In particular limits the model reduces to (i) pure $\mathbb{Z}_2$ even and odd gauge theories, (ii) free fermions in a static background of deconfined $\mathbb{Z}_2$ gauge fields, (iii) the kinetic Rokhsar-Kivelson quantum dimer model at a generic dimer filling. We develop a local transformation that maps the lattice gauge theory onto a model of $\mathbb{Z}_2$ gauge-invariant spin $1/2$ degrees of freedom. Using the mapping, we perform numerical density matrix renormalization group calculations that corroborate our understanding of the limits identified above. Moreover, in the absence of the magnetic plaquette term, we reveal signatures of topologically ordered Dirac semimetal and staggered Mott insulator phases at half-filling. At strong coupling, the lattice gauge theory displays fracton phenomenology with isolated fermions being completely frozen and dimers exhibiting restricted mobility. In that limit, we predict that in the ground state dimers form compact clusters, whose hopping is suppressed exponentially in their size. We determine the band structure of the smallest clusters numerically using exact diagonalization.
Exploring Data-Efficient 3D Scene Understanding with Contrastive Scene Contexts

The rapid progress in 3D scene understanding has come with growing demand for data; however, collecting and an-notating 3D scenes (e.g. point clouds) are notoriously hard. For example, the number of scenes (e.g. indoor rooms) that can be accessed and scanned might be limited; even given sufficient data, acquiring 3D labels (e.g. instance masks) requires intensive human labor. In this paper, we explore data-efficient learning for 3D point cloud. As a first step towards this direction, we propose Contrastive Scene Contexts, a 3D pre-training method that makes use of both point-level correspondences and spatial contexts in a scene. Our method achieves state-of-the-art results on a suite of benchmarks where training data or labels are scarce. Our study reveals that exhaustive labelling of 3D point clouds might be unnecessary; and remarkably, on ScanNet, even using 0.1% of point labels, we still achieve 89% (instance segmentation) and 96% (semantic segmentation) of the baseline performance that uses full annotations.
Trace Elements in Human Milk, Cow’s Milk, and Infant Formula

Analysis of trace elements using a polarized Zeeman atomic absorption spectrophotometer was performed on breast milk, cow’s milk, and a modified milk powder commonly consumed in Japan. The elements examined in the samples were cobalt, nickel, chromium, manganese, molybdenum, and iron.Average values of contents (per g wet weight) of these elements in breast milk obtained from mothers 19~384 days postpartum were 1.4ng, 3.6 ng, 6.5 ng, 9.5 ng, 24 ng and 0.32/zg, respectively and those in cow’s milk were 2.4 ng, 9.5 ng, 14 ng, 27 ng, 50 ng and 0.23 fig, respectively. The ratio of contents of cobalt, nickel, chromium, manganese, and molybdenum in breast milk was similar to that in cow’s milk. There was no infant formula deficient in these elements as compared to those in breast milk when the levels of trace elements were expressed per ml of 14% (w/v) milk reconstituted from each milk powder. In addition, higher contents of iron and manganese in milk powder were noted.
Towards Recognizing New Semantic Concepts in New Visual Domains

Deep learning models heavily rely on large scale annotated datasets for training. Unfortunately, datasets cannot capture the infinite variability of the real world, thus neural networks are inherently limited by the restricted visual and semantic information contained in their training set. In this thesis, we argue that it is crucial to design deep architectures that can operate in previously unseen visual domains and recognize novel semantic concepts. In the first part of the thesis, we describe different solutions to enable deep models to generalize to new visual domains, by transferring knowledge from a labeled source domain(s) to a domain (target) where no labeled data are available. We will show how variants of batch-normalization (BN) can be applied to different scenarios, from domain adaptation when source and target are mixtures of multiple latent domains, to domain generalization, continuous domain adaptation, and predictive domain adaptation, where information about the target domain is available only in the form of metadata. In the second part of the thesis, we show how to extend the knowledge of a pretrained deep model to new semantic concepts, without access to the original training set. We address the scenarios of sequential multi-task learning, using transformed task-specific binary masks, open-world recognition, with end-to-end training and enforced clustering, and incremental class learning in semantic segmentation, where we highlight and address the problem of the semantic shift of the background class. In the final part, we tackle a more challenging problem: given images of multiple domains and semantic categories (with their attributes), how to build a model that recognizes images of unseen concepts in unseen domains? We also propose an approach based on domain and semantic mixing of inputs and features, which is a first, promising step towards solving this problem.
Disome-seq reveals widespread ribosome collisions that recruit co-translational chaperones

Regulation of translation elongation plays a crucial role in determining absolute protein levels and ensuring the correct localization and folding of proteins. Much of our knowledge regarding translation elongation comes from the sequencing of mRNA fragments protected by single ribosomes (ribo-seq). However, larger protected mRNA fragments have been observed, suggesting the existence of an alternative and previously hidden layer of regulation. In this study, we performed disome-seq to sequence mRNA fragments protected by two stacked ribosomes — a product of translational pauses during which the 5′-ribosome collides with the 3′-paused one. We detected widespread ribosome collisions that are missed in traditional ribo-seq. These collisions are due to 1) slow ribosome release when stop codons are at the A-site, 2) slow peptide bond formation from proline, glycine, asparagine, and cysteine when they are at the P-site, and 3) slow leaving of polylysine from the exit tunnel of ribosomes. The paused ribosomes can continue translating after collisions, as suggested by the structure of disomes obtained by cryo-electron microscopy (cryo-EM). Collided ribosomes recruit chaperones, which can aid in the co-translational folding of the nascent peptides. Therefore, cells use regulated ribosome collisions to ensure protein homeostasis.
Factors influencing read coverage variation in a genome assembled using short reads

Availability of genome sequences has led to significant progress in biological sciences and beyond. With few exceptions, the great majority of existing genome assemblies are derived from short read sequencing technologies. While extremely useful, the short-read coverages across the assemblies are highly uneven, indicative of sequencing and assembly issues. To assess the underlying causes of such uneven read coverage, we used the tomato genome as an example and integrated multiple sequence features to establish machine learning models capable of predicting whether a genomic region has significantly high or low read coverage. Importantly, 0.6% (5.1Mb) and 9.7% (79.6Mb) of tomato genome assembly had significantly higher and lower coverage compared to background, respectively. By evaluating features important for the prediction, we found that GC content and high density of transposon elements are the major contributors to break points in an assembly, leading to gaps filled with Ns and the resulting low read coverages. In contrast, simple sequence repeats and tandemly duplicated genes, especially specialized metabolism genes, tend to be mis-assembled, resulting in high read coverages. We also present evidence of a misassembled regions containing tandemly duplicated specialized metabolism genes. The presence of variable coverage regions is expected to significantly impact genome-wide studies, highlighting the need to detect them in short-read based assemblies.
Chemistry in isolation: High CCH/HCO + line ratio in the AMIGA galaxy CIG 638

Context. Multi-molecule observations towards an increasing variety of galaxies have been showing that the relative molecular abundances are affected by the type of activity. However, these studies are biased towards bright active galaxies, which are typically in interaction. Aims. We study the molecular composition of one of the most isolated galaxies in the local Universe where the physical and chemical properties of their molecular clouds have been determined by intrinsic mechanisms. Methods. We present 3 mm broad band observations of the galaxy CIG 638, extracted from the AMIGA sample of isolated galaxies. The emission of the J = 1–0 transitions of CCH, HCN, HCO + , and HNC are detected. Integrated intensity ratios between these line are compared with similar observations from the literature towards active galaxies including starburst galaxies (SB), active galactic nuclei, luminous infrared galaxies (LIRG), and GMCs in M 33. Results. A significantly high ratio of CCH with respect to HCN, HCO + , and HNC is found towards CIG 638 when compared with all other galaxies where these species have been detected. This points to either an overabundance of CCH or to a relative lack of dense molecular gas as supported by the low HCN/CO ratio, or both. Conclusions. The data suggest that the CIG 638 is naturally a less perturbed galaxy where a lower fraction of dense molecular gas, as well as a more even distribution could explain the measured ratios. In this scenario the dense gas tracers would be naturally dimmer, while the UV enhanced CCH, would be overproduced in a less shielded medium.
Developing Future Human-Centered Smart Cities: Critical Analysis of Smart City Security, Interpretability, and Ethical Challenges

As we make tremendous advances in machine learning and artificial intelligence technosciences, there is a renewed understanding in the AI community that we must ensure that humans being are at the center of our deliberations so that we don't end in technology-induced dystopias. As strongly argued by Green in his book Smart Enough City, the incorporation of technology in city environs does not automatically translate into prosperity, wellbeing, urban livability, or social justice. There is a great need to deliberate on the future of the cities worth living and designing. There are philosophical and ethical questions involved along with various challenges that relate to the security, safety, and interpretability of AI algorithms that will form the technological bedrock of future cities. Several research institutes on human centered AI have been established at top international universities. Globally there are calls for technology to be made more humane and human-compatible. For example, Stuart Russell has a book called Human Compatible AI. The Center for Humane Technology advocates for regulators and technology companies to avoid business models and product features that contribute to social problems such as extremism, polarization, misinformation, and Internet addiction. In this paper, we analyze and explore key challenges including security, robustness, interpretability, and ethical challenges to a successful deployment of AI or ML in human-centric applications, with a particular emphasis on the convergence of these challenges. We provide a detailed review of existing literature on these key challenges and analyze how one of these challenges may lead to others or help in solving other challenges. The paper also advises on the current limitations, pitfalls, and future directions of research in these domains, and how it can fill the current gaps and lead to better solutions.
Two‐dimensional model of ion dynamics during plasma source ion implantation

Ion dynamics in the plasma sheath following the application of a negative voltage pulse to a two‐dimensional target are modeled using a time‐dependent, two‐fluid simulation. The target considered is a square bar of infinite length. We find that the sheath focuses ions near to, but not on, the corner of the bar, resulting in an enhancement of the dose received there.
Influence of E-Commerce on Enterprises’ Brand in Developing Countries. A Case Study of Small to Medium Enterprise (SMEs) in Zimbabwe

Currently, most small businesses use e-commerce as a marketing tool and attach great importance to exchanging information and information about products and services. This study shows that improving internal efficiency and increasing communication are the main benefits of e-commerce for small businesses. By increasing the exchange of information, companies can cover a much larger customer area and attract new customers. Because they are aware of product characteristics, customers are happier and ready to give orders. This study shows that companies are changing a new way of finding customers that will allow them to reduce their advertising costs. At the same time, businesses are experiencing cost savings through better stagnated business. The main obstacles for small businesses are the lack of innovative culture and knowledge. Although some companies still consider the most important cost factor, this is due to the lack of understanding of e-commerce and positive effects. This in turn will lead to an end to the lack of conformity or innovation process. Another major obstacle is the lack of customer demand. In addition, the study shows that many small businesses do not benefit from these improvements, given the nature of the companies or markets that do not promote the innovation process. The results of the study showed that although access to finance could have a positive impact on SME performance, it was not fully exploited for Zimbabwe SMEs. Banks should therefore improve their lending conditions, collateral requirements and the number of years in order to improve performance. The survey results showed that management skills can have a positive and significant impact on the performance of SMEs, but only a small proportion of companies have embraced them. DOI: 10.7176/JESD/11-20-10 Publication date: October 31 st 2020
Nitrogen isotope composition of ammonium and nitrate in bulk precipitation and forest throughfall

Abstract The stable nitrogen isotope composition of ammonium (NH+ 4) and nitrate (NO− 3) ions in bulk precipitation and forest throughfall was determined at Walker Branch watershed, a low elevation site (340 m) in northeastern Tennessee, and in cloud water from Whitetop Mountain, a high elevation site (1680 m) in southwestern Virginia. Tests of the method used indicated that sample processing did not introduce significant isotopic fractionation in measurements of nitrogen isotope composition. Mean δ15N values for NH+ 4 and NO− 3 in solutions of artificial rain were within 0.3%o of the mean δ15N values of nitrogen compounds used to make the solutions. Over a one-year period on Walker Branch watershed, the measured mean (± SD) δ15N value for NH+ 4 in bulk precipitation and throughfall (− 3.4 ± 2.1%o) was significantly less than that for NO− 3(+ 2.3 ± 2.4%o). The same relative pattern was observed in cloud water from Whitetop Mountain: mean (± SD) δ15N in cloud water NH+ 4 was −5.5 ± 3.2%o; i.e., isotopicall.
A Systematic Literature Review on Teaching and Learning English Using Mobile Technology

Mobile technology has become increasingly popular in the past decade and provides a chance to move forward towards 21 century education. The art of teaching and learning English with the adoption of mobile technology creates a different learning environment for both teachers and students. Hence, reviewing existing works systematically is crucial in finding the gaps in teaching and learning English using mobile technology. A Systematic Literature Review (SLR) is conducted to identify important factors influenced in the teaching and learning English using mobile technology and existing studies in overcoming the issues. The results show that providing suitable educational technology is one of the key success factors to enhance teaching and learning English. This paper reports the key gap and limitation in current studies that focus on teaching and learning English using mobile technology.
Exposure to sexually explicit Internet material among adolescents: a study in Vietnam

BACKGROUND With the influence of Confucian culture, sex is often considered a taboo subject in Vietnam. This study aimed to examine the prevalence of exposure to sexually explicit Internet material (SEIM) among adolescents in Vietnam, as well as the factors affecting exposure to SEIM. PARTICIPANTS AND PROCEDURE The sample consisted of 886 Vietnamese adolescents (58.10% female) aged 15 to 18 years (M = 16.72, SD = 0.72). The survey was adapted from the study of Van Ouytsel, Ponnet and Walrave to assess the frequency of exposure to SEIM. Several measurement scales of factors affecting exposure to SEIM among adolescents were used including the Perceived Realism of SEIM, the Sexual Sensation Seeking Scale, the Family Cohesion and the Parental Monitoring Scale. RESULTS The overall prevalence of exposure to SEIM was 84.10%, with a gender difference: 89.80% in males and 80.00% in females. The prevalence of passive exposure to SEIM was 58.30%, higher than 41.70% for active exposure. Perceived realism of SEIM, sexual sensation seeking and Internet usage time for entertainment are factors affecting frequencies of exposure to SEIM among adolescents, with β coefficient values of . 29, . 18 and . 16 respectively. CONCLUSIONS The majority of children in this study reported SEIM exposure. Parents, schools and other stakeholders should pay attention to sex education for children early on, diversifying forms and subjects of sex education. The content of sex education should emphasize the responsibility in the decisions made by children related to sex.
Dissociation behavior of poly(α‐hydroxy acrylic acid)

Dissociation behavior of poly(a-hydroxy acrylic acid) (PHA) was investigated by potentiometric titration in the presence of NaCl and/or divalent metal chlorides. It was found that pH values of PHA aqueous solutions increased with time when the degree of dissociation, α, is high (α ≥ 0.5 for NaCl system) and decreased in the lower α region (α < 0.5 for NaCl). The increase of pH was attributed to lactone ring formation that occurs between a carboxyl group and a neighbor hydroxyl group upon protonation to the former, and the decrease of pH to an induction effect by lactone ring to -COOH group. The pH-increasing process was analyzed by assuming it being of a first order to obtain a time constant. On the basis of time constant thus estimated and pKa values for divalent counterion systems, a correlation between counterion binding and lactone ring formation was discussed.
The Ability of Avicennia marina to Uptake Ions of Sodium and Chloride in Reed Bed System Reactor

Many technologies can be used to solve the clean water crisis. One of the technologies is desalination, but this technology is expensive. So that, it is necessary to find cheaper desalination technology and easier to operate. Bio-desalination is a technology that utilizes bacteria to remove sodium and chloride ions in seawater. In this research, the application of the phytotechnology concept for bio-desalination reactors was carried out. Bio-desalination technology used the uniqueness of mangrove plants (Avicennia marina) in a reed bed system reactor that adapted from a reed bed system commonly used in constructed wetlands (CWs). The aim of the research was to determine the uptake of sodium and chloride ions by Avicennia marina in a reed bed system bio-desalination reactor. The namely of reactor were AM15‰, AM25‰, AMVA15‰ and AMVA25‰. The VA code was shown that Vibrio alginolyticus addition in this reactor. The artificial saline water with initial salinity of 15‰ and 25‰ was chosen based on our previous study. Parameter of salinity was determined using salinometer. Concentration of sodium and chloride ions were analyses using ion chromatography. Based on the results, the concentration of sodium and chloride ions in Avicennia marina at AM15‰ were 843.18 mg/kg and 4959.96 mg/kg, respectively. Meanwhile, those were 1410.01 mg/kg and 5292.64 mg/kg at AM25 ‰, respectively. The concentration of sodium and chloride ions in AMVA15‰ were 1003.39 mg/kg and 3186.96 mg/kg, and it were 8036.43 mg/kg and 9783.91 mg/kg at AMVA25‰. The value of Bio-concentration Factor (BCF) and Translocation Factor (TF) were greater than 1, it indicated that Avicennia marina was as an hyperaccumulator plant for sodium and chloride ions. In conclusion, the Avicennia marina can be used in reed bed system bio-desalination reactor to reduce salinity.