Miracle-dz/UniFAR-FTUs huggingface dataset:
L AYER - WISE A DVERSARIAL D EFENSE : A N ODE P ER - SPECTIVE

Deep neural networks are observed to be fragile against adversarial attacks, which have dramatically limited their practical applicability. On improving model robustness, the adversarial training techniques have proven effective and gained increasing attention from research communities. Existing adversarial training approaches mainly focus on perturbations to inputs, while the effect of the perturbations in hidden layers remains underexplored. In this work, we propose layer-wise adversarial defense which improves adversarial training by a noticeable margin. The basic idea of our method is to strengthen all of the hidden layers with perturbations that are proportional to the back-propagated gradients. In order to study the layer-wise neural dynamics, we formulate our approach from the perspective of ordinary differential equations (ODEs) and build up its extended relationship with conventional adversarial training methods, which tightens the relationship between neural networks and ODEs. In the implementation, we propose two different training algorithms by discretizing the ODE model with the Lie-Trotter and the Strang-Marchuk splitting schemes from the operator-splitting theory. Experiments on CIFAR-10 and CIFAR-100 benchmarks show that our methods consistently improve adversarial model robustness on top of widely-used strong adversarial training techniques.
Self-similar expansion of a plasmoid supplied by pellet ablation

Cryogenic pellet injection is an important means of refuelling and terminating fusion plasmas, with fuel pellets exhibiting a range of phenomena beneficial to confinement and the energy balance between ions and electrons. In this investigation we consider the self-similar expansion along magnetic field lines of the plasmoid produced by a small pellet. In particular, we consider the case when the expansion timescale is comparable to the time taken for the pellet gas cloud to cross a field line. It is shown that plasmoid ions acquire a significant fraction of the energy that is transferred to plasmoid electrons via collisions with the ambient plasma. It is found that the expansion is insensitive to the profile of the gas cloud and details of the ionisation of the gas—the plasma flux emerging from the gas cloud is the only quantity that affects the expansion.
Students’ experience of online game-based assessment tool during emergency remote teaching

Emergency remote teaching makes teachers should review the appropriate way of assessing students appropriately. Various programs and applications have been developed to assess students online. However, as learners do not always perceive learning tool effectiveness in the same way as educators, this study tries to investigate the perspectives of learners regarding the use of game-based assessment tool, namely Quizizz. The perceptions of sixty freshmen college students regarding the use of this tool are documented using questionnaires. The main findings of the study show that the students demonstrated positive attitudes towards the use of Quizizz during emergency remote teaching. They perceived it as a useful program that was easy to use, and they reported the intention to use it in the future in the post-pandemic era. Besides, this program could enhance students’ learning engagement in terms of cognitive, behavioral, and emotional engagement. It, therefore, can be concluded that Quizizz becomes an alternative way of assessing the students online, while at the same time promoting their learning engagement.
Solar Cycle 25 is Currently Very Similar to Solar Cycle 24

Solar Cycle 25 started in 2019 December. Different predictions for its amplitude have been published so far without general consensus. We compared the evolution of Solar Cycle 25, using the first available values of the smoothed sunspot number, with past solar cycles. Our analysis shows that Solar Cycle 25 is very similar to Solar Cycles 24 and 7. Therefore, the maximum amplitude for this Solar Cycle 25 could be small-moderate.
Broad photoluminescence in ternary Ag-In-S and quaternary Ag-In-Zn-S nanoparticles: the role of Zn incorporation

Ternary Ag-In-S and quaternary Ag-In-Zn-S nanoparticles with different ratio of Ag/In/Zn/S are synthesized. The incorporation of Zn into Ag-In-S nanoparticles leads to the increase in the optical bandgap and the blue shift of photoluminescence (PL). The optical properties of these nanoparticles are significantly dependent on the chemical composition of nanoparticles. Time-resolved PL spectroscopy in nanosecond time regime is used to study the recombination processes of carriers, which involve the surface states and intrinsic crystallographic defects. These measurements support the donor-acceptor model, in which the PL is achieved by radiative recombination of the localized electron and hole.
Edu-Game media based on Android to learn Least Common Multiplication (LCM) and Great Common Divisor (GCD) for the 4th graders

Learning mathematics for elementary school students is often considered a creepy thing. Some of the tricks that can be used to remove this paradigm is the use of learning media that are attractive to students, one of which is the edu-game media based on android along with current technological developments. This development research developed the edu-game media based on android which aims to: describe the process of developing the edu-game media based on android to learn LCM and GCD for the 4th graders and (2) analyze the feasibility level of the edu-game media based on android to learn LCM and GCD for the 4th graders. The trial subjects of this study were the 4th graders of Laboratory Unesa Elementary School Surabaya and Geluran 1 Elementary School Taman Sidoarjo. The model used in this research is Plomp’s development model. From this research, the results obtained from the material expert validator with a percentage of 94.7% (valid), and from the media expert validator with a percentage of 93.75% (valid). Testing the test subjects got an average percentage of the entire program of 93.4% (very feasible).
multi-decadal variability in the North Atlantic: a multi-model

14 Abstract. The Subpolar North Atlantic (SPNA) is a region with prominent decadal variability that has experienced 15 remarkable warming and cooling trends in the last few decades. These observed trends have been preceded by 16 slow-paced increases and decreases in the Labrador Sea density (LSD), which are thought to be a precursor of large 17 scale ocean circulation changes. This article analyses the inter-relationships between the LSD and the wider North 18 Atlantic across an ensemble of coupled climate model simulations. In particular, it analyses the link between 19 subsurface density and the deep boundary density, the Atlantic Meridional Overturning Circulation (AMOC), the 20 Subpolar Gyre (SPG) circulation, and the upper ocean temperature in the eastern SPNA. 21 22 All simulations exhibit considerable multidecadal variability in the LSD and the ocean circulation indices, which are 23 found to be interrelated. LSD is strongly linked with the strength of subpolar AMOC and gyre circulation, and is 24 also linked with the subtropical AMOC, although the strength of this relationship is model dependent and affected 25 by the inclusion of the Ekman component. The connectivity of LSD with the subtropics is found to be sensitive to 26 different model features, including: the mean density stratification in the Labrador Sea; the strength and depth of the 27 AMOC; and the depth at which the LSD propagates southward along the western boundary. Several of these 28 quantities can also be computed from observations, and comparison with these observation-based quantities suggests 29 that models representing a weaker link with the subtropical AMOC might be more realistic.
Outcome of Femoral Fractures Treated with External Fixators in the Douala General Hospital: A Referral Hospital in a Poor Resource Setting in Africa

Background: The femur is the most robust and the longest bone in the body. It is a weight bearing bone and when fractured requires a strong and stable fixation. Intramedullary nailing is the best treatment option however other options also give successful results. External fixator has been used as temporary method especially in polytraumatised patients and open fractures. In our environment where secondary procedure is not very feasible because of limited resources, external fixators have been used as a definitive treatment with satisfactory outcome.
Factors that Determine Continuous Intention to Use Mobile Payments in Malawi

The proliferation of mobile phones has made mobile payments to be widely used in developing economies. However, mobile payment usage in Malawi is low, and there are many limitations to encourage users to continuously use mobile payments. The purpose of this research was to examine determinants of continuous intention to use mobile payments in Malawi. A conceptual framework adapted from Technology Acceptance Model was developed. Data was collected through a survey while data analysis used Structural Equation Modelling Partial Least Squares using SmartPLS software. The findings of this study showed that society norms significantly influence continuous intention to use mobile payments (p=0.012). Most interestingly, prior knowledge (p=0.000) and seamlessness (p=0.000) had the strongest influence as compared to structural assurance (p=0.008). Seamlessness significantly influenced satisfaction (p=0.002) and society norms (p=0.001). Seamlessness and service quality had significantly negative effects on satisfaction. The findings of this research provide several considerations to guide the mobile payments industry in Malawi. The findings may also improve the existing mobile payments system’s business models, marketing strategies, customer engagement on security issues, transparency, and interoperability of payment systems. Regulators may also find the findings of this study very insightful in advancing the mobile payments agenda in Malawi.
Improved Denoising Diffusion Probabilistic Models (Supplementary)

For all of our experiments, we use a UNet model architecture1 similar to that used by Ho et al. (2020). We changed the attention layers to use multi-head attention (Vaswani et al., 2017), and opted to use four attention heads rather than one (while keeping the same total number of channels). We employ attention not only at the 16x16 resolution, but also at the 8x8 resolution. Additionally, we changed the way the model conditions on t. In particular, instead of computing a conditioning vector v and injecting it into hidden state h as GroupNorm(h + v), we compute conditioning vectors w and b and inject them into the hidden state as GroupNorm(h)(w + 1) + b. We found in preliminary experiments on ImageNet 64 × 64 that these modifications slightly improved FID.
Higher-Order Lookup Table Masking in Essentially Constant Memory

Masking using randomised lookup tables is a popular countermeasure for side-channel attacks, particularly at small masking orders. An advantage of this class of countermeasures for masking S-boxes compared to ISW-based masking is that it supports pre-processing and thus significantly reducing the amount of computation to be done after the unmasked inputs are available. Indeed, the “online” computation can be as fast as just a table lookup. But the size of the randomised lookup table increases linearly with the masking order, and hence the RAM memory required to store pre-processed tables becomes infeasible for higher masking orders. Hence demonstrating the feasibility of full pre-processing of higher-order lookup table-based masking schemes on resource-constrained devices has remained an open problem. In this work, we solve the above problem by implementing a higher-order lookup table-based scheme using an amount of RAM memory that is essentially independent of the masking order. More concretely, we reduce the amount of RAM memory needed for the table-based scheme of Coron et al. (TCHES 2018) approximately by a factor equal to the number of shares. Our technique is based upon the use of pseudorandom number generator (PRG) to minimise the randomness complexity of ISW-based masking schemes proposed by Ishai et al. (ICALP 2013) and Coron et al. (Eurocrypt 2020). Hence we show that for lookup table-based masking schemes, the use of a PRG not only reduces the randomness complexity (now logarithmic in the size of the S-box) but also the memory complexity, and without any significant increase in the overall running time. We have implemented in software the higher-order table-based masking scheme of Coron et al. (TCHES 2018) at tenth order with full pre-processing of a single execution of all the AES S-boxes on a ARM Cortex-M4 device that has 256 KB RAM memory. Our technique requires only 41.2 KB of RAM memory, whereas the original scheme would have needed 440 KB. Moreover, our 8-bit implementation results demonstrate that the online execution time of our variant is about 1.5 times faster compared to the 8-bit bitsliced masked implementation of AES-128.
Karoo Supergroup in the Eastern Cape Province of South Africa

The stratigraphy of the Ecca Group has been subdivided into the Prince Albert, Whitehill, Collingham, Ripon, and Fort Brown Formations in the Eastern Cape Province, South Africa. In this article, we present detailed stratigraphic and facies analyses of borehole data and road-cut exposures of the Ecca Group along regional roads R67 (Ecca Pass), R344 (GrahamstownAdelaide), R350 (Kirkwood-Somerset East), and national roads N2 (Grahamstown-Peddie) and N10 (Paterson-Cookhouse). Facies analysis of the Ecca Group in the study area was performed to deduce their depositional environments. Based on the lithological and facies characteristics, the stratigraphy of the Prince Albert, Whitehill, Collingham, and Fort Brown Formations is now subdivided into two informal members each, while the Ripon Formation is subdivided into three members. A total of twelve lithofacies were identified in the Ecca Group and were further grouped into seven distinct facies associations (FAs), namely: Laminated to thin-bedded black-greyish shale and mudstones (FA 1); Laminated black-greyish shale and interbedded chert (FA 2); Mudstone rhythmite and thin beds of tuff alternation (FA 3); Thin to thick-bedded sandstone and mudstone intercalation (FA 4); Medium to thick-bedded dark-grey shale (FA 5); Alternated thin to medium-bedded sandstone and mudstone (FA 6); and Varved mudstone rhythmite and sandstone intercalation (FA 7). The FAs revealed gradually change of sea-level from deep marine (FA 1, FA 2, FA 3 and FA 4, FA 5, and FA 6) to prodelta environment (FA 7). This implies that the main Karoo Basin was gradually filling up with Ecca sediments, resulting in the gradual shallowing up of the water depth of the depositional basin.
Title: Genetic diversity and taxonomic issues in Gastridium P.Beauv (Poaceae) inferred from plastid and nuclear DNA sequence analysis

Incomplete taxonomic knowledge may seriously hamper biodiversity conservation efforts that are crucial in a context of global change. Gastridium P.Beauv. is a Mediterranean-Paleotropical member of the Poaceae family, inhabiting ephemeral grass habitats, whose species number and diversity are still imperfectly known. In order to progress towards a comprehensive taxonomic treatment of this genus, we examined patterns of DNA diversity in the four taxa (Gastridium lainzii, G. phleoides, G. scabrum, and G. ventricosum) that have been recently advanced by different authors, based on new morpho-ecological descriptors. We explored nucleotide sequence variation at two plastid (trnH-psbA, trnL-F) and one nuclear (ITS) DNA markers in 44 total individuals. Diversity data were treated with multiple statistical and phylogenetic tools, and integrated with available GenBank sequences of Gastridium and other closely related genera. Despite the limited variability detected, evidence of within-taxon genetic cohesion and estimates of molecular divergence comparable with those of species in the same subtribal lineage (Agrostidinae) were recovered. The identified plastid genealogies appeared congruent with a subdivision of the genus into (at least) three distinct entities, and coherent with collected morphological descriptors. Phylogenetic reconstructions with ITS were less corresponding to taxa identities, likely due to reticulation and polyploidization. Once placed in a broader taxonomic context, the investigated dataset produced plastid and nuclear tree topologies consistent with previous assessments, highlighting the overall little resolution of species and genera within Agrostidinae. In the plastid tree, a sister relationship between Gastridium and Triplachne was weakly supported. In the ITS tree, relationships among these genera were unresolved. The hypothesis of closely related but separately evolving lineages within Gastridium is discussed, suggesting a re-evaluation of its current assessment in taxonomic authorities to enhance our knowledge of the grass family, and assist future biodiversity surveys of key Mediterranean grassland ecosystems.
D I P B ENCHMARK T ESTS : E VALUATION B ENCH - MARKS FOR D I SCOURSE P HENOMENA IN MT

Despite increasing instances of machine translation (MT) systems including extrasentential context information, the evidence for translation quality improvement is sparse, especially for discourse phenomena. Popular metrics like BLEU are not expressive or sensitive enough to capture quality improvements or drops that are minor in size but significant in perception. We introduce the first of their kind MT benchmark testsets that aim to track and hail improvements across four main discourse phenomena: anaphora, lexical consistency, coherence and readability, and discourse connective translation. We also introduce evaluation methods for these tasks, and evaluate several competitive baseline MT systems on the curated datasets. Surprisingly, we find that the complex context-aware models that we test do not improve discourse-related translations consistently across languages and phenomena. Our evaluation benchmark is available as a leaderboard at <dipbenchmark1.github. io>.
W EAKLY S UPERVISED S CENE G RAPH G ROUNDING

Recent researches have achieved substantial advances in learning structured representations from images. However, current methods rely heavily on the annotated mapping between the nodes of scene graphs and object bounding boxes inside images. Here, we explore the problem of learning the mapping between scene graph nodes and visual objects under weak supervision. Our proposed method learns a metric among visual objects and scene graph nodes by incorporating information from both object features and relational features. Extensive experiments on Visual Genome (VG) and Visual Relation Detection (VRD) datasets verify that our model post an improvement on scene graph grounding task over current state-of-the-art approaches. Further experiments on scene graph parsing task verify the grounding found by our model can reinforce the performance of the existing method.
Neural Synchrony for Adaptive Control

Abstract Cognitive control can be adaptive along several dimensions, including intensity (how intensely do control signals influence bottom–up processing) and selectivity (what information is selected for further processing). Furthermore, control can be exerted along slow or fast time scales. Whereas control on a slow time scale is used to proactively prepare for upcoming challenges, control can also be used on a faster time scale to react to unexpected events that require control. Importantly, a systematic comparison of these dimensions and time scales remains lacking. Moreover, most current models of adaptive control allow predictions only at a behavioral, not neurophysiological, level, thus seriously reducing the range of available empirical restrictions for informing model formulation. The current article addresses this issue by implementing a control loop in an earlier model of neural synchrony. The resulting model is tested on a Stroop task. We observe that only the model that exerts cognitive control on intensity and selectivity dimensions, as well as on two time scales, can account for relevant behavioral and neurophysiological data. Our findings hold important implications for both cognitive control and how computational models can be empirically constrained.
Effect of organic solvents and acidic catalysts on biodiesel yields from primary sewage sludge, and characterization of fuel properties

ABSTRACT Biodiesel is considered the most convenient biofuel, due to its direct use in existing combustion engines; however, its production is not economically optimal due to processes that utilize costly substrates, require high energy expenditure or achieve low biodiesel yields. We used primary sewage sludge for the production of biodiesel and compared yields at different temperatures (40, 50 and 60 °C) and with different organic solvents (chloroform, toluene and hexane), acid catalysts (HCl and H2SO4) and catalyst concentrations (3, 5 and 7%). A maximum of 18 wt% biodiesel was obtained using chloroform with 3% H2SO4 at 40 °C. The conversion efficiency of the primary sludge to biodiesel under these conditions was 86.4%. Based on the fatty acid methyl ester composition of the obtained biodiesel and measured fuel properties, it was deduced that fuel from primary sludge is more suitable for areas with warmer climates than ones that reach temperatures close to 0 °C. However, the fuel properties of the produced biodiesel were within the limits of accepted international standards. We conclude that production of biodiesel from primary sewage sludge under optimized conditions reduces the impact of the feedstock on the environment, decreases overall costs and produces fuel with acceptable properties.
Inequality and the Zero Lower Bound

This paper studies how household inequality shapes the effects of the zero lower bound (ZLB) on nominal interest rates on aggregate dynamics. To do so, we consider a heterogeneous agent New Keynesian (HANK) model with an occasionally binding ZLB and solve for its fully non-linear stochastic equilibrium using a novel neural network algorithm. In this setting, changes in the monetary policy stance influence households’precautionary savings by altering the frequency of ZLB events. As a result, the model features monetary policy non-neutrality in the long run. The degree of long-run non-neutrality, i.e., by how much monetary policy shifts real rates in the ergodic distribution of the model, can be substantial when we combine low inflation targets and high levels of wealth inequality.
The valuation of intangible assets and hedonic pricing models

This paper investigates the use of Lancaster’s hedonic pricing model in the valuation of intangible assets owned by firms. It is hypothesised that the presence of intangible assets will lead to higher productivity, that there is a set of characteristics that objectively measures firm productivity, and that the market will “price” the set of these characteristics. Once the “prices” of the characteristics are known, the value of individual intangible assets can be calculated. The paper investigates the empirical usefulness of this approach by examining US firms over a 5 year period. The results appear to be promising.