Miracle-dz/UniFAR-FTUs huggingface dataset:
Anatomy of Type-
x
 Spin-Orbit-Torque Switching

Using type-x spin-orbit torque (SOT) switching scheme, in which the easy axis (EA) of the ferromagnetic (FM) layer and the charge current flow direction are collinear, is possible to realize a lower-power-consumption, higher-density, and better-performance SOT magnetoresistive random access memory (SOT-MRAM) as compared to the conventional type-y design. Here, we systematically investigate type-x SOT switching properties by both macrospin and micromagnetic simulations. The out-of-plane external field and anisotropy field dependence of the switching current density (Jsw) is first examined in the ideal type-x configuration. Next, we study the FM layer canting angle (φEA) dependence of Jsw through macrospin simulations and experiments, which show a transformation of switching dynamics from type-x to type-y with increasing φEA. By further integrating field-like torque (FLT) into the simulated system, we find that a positive FLT can assist type-x SOT switching while a negative one brings about complex dynamics. More crucially, with the existence of a sizable FLT, type-x switching mode results in a lower critical switching current than type-y at current pulse width less than ~ 10 ns, indicating the advantage of employing type-x design for ultrafast switching using materials systems with FLT. Our work provides a thorough examination of type-x SOT scheme with various device/materials parameters, which can be informative for designing next-generation SOT-MRAM.
Large-Scale Differentially Private BERT

In this work, we study the large-scale pretraining of BERT-Large with differentially private SGD (DP-SGD). We show that combined with a careful implementation, scaling up the batch size to millions (i.e., mega-batches) improves the utility of the DP-SGD step for BERT; we also enhance its efficiency by using an increasing batch size schedule. Our implementation builds on the recent work of [SVK20], who demonstrated that the overhead of a DP-SGD step is minimized with effective use of JAX [BFH+18, FJL18] primitives in conjunction with the XLA compiler [XLA17]. Our implementation achieves a masked language model accuracy of 60.5% at a batch size of 2M, for $\epsilon = 5.36$. To put this number in perspective, non-private BERT models achieve an accuracy of $\sim$70%.
Multi-Frequency GPR Microwave Imaging of Sparse Targets through a Multi-Task Bayesian Compressive Sensing Approach

An innovative inverse scattering (IS) method is proposed for the quantitative imaging of pixel-sparse scatterers buried within a lossy half-space. On the one hand, such an approach leverages on the wide-band nature of ground penetrating radar (GPR) data by jointly processing the multi-frequency (MF) spectral components of the collected radargrams. On the other hand, it enforces sparsity priors on the problem unknowns to yield regularized solutions of the fully non-linear scattering equations. Towards this end, a multi-task Bayesian compressive sensing (MT-BCS) methodology is adopted and suitably customized to take full advantage of the available frequency diversity and of the a-priori information on the class of imaged targets. Representative results are reported to assess the proposed MF-MT-BCS strategy also in comparison with competitive state-of-the-art alternatives.
GOLDRUSH. IV. Luminosity Functions and Clustering Revealed with ∼4,000,000 Galaxies at z ∼ 2–7: Galaxy–AGN Transition, Star Formation Efficiency, and Implication for Evolution at z > 10

We present new measurements of rest-UV luminosity functions and angular correlation functions from 4,100,221 galaxies at z ∼ 2–7 identified in the Subaru/Hyper Suprime-Cam survey and CFHT Large Area U-band Survey. The obtained luminosity functions at z ∼ 4–7 cover a very wide UV luminosity range of ∼ 0.002–2000LUV* combined with previous studies, confirming that the dropout luminosity function is a superposition of the active galactic nucleus (AGN) luminosity function dominant at M UV ≲ −24 mag and the galaxy luminosity function dominant at M UV ≳ −22 mag, consistent with galaxy fractions based on 1037 spectroscopically identified sources. Galaxy luminosity functions estimated from the spectroscopic galaxy fractions show the bright-end excess beyond the Schechter function at ≳2σ levels, possibly made by inefficient mass quenching, low dust obscuration, and/or hidden AGN activity. By analyzing the correlation functions at z ∼ 2–6 with HOD models, we find a weak redshift evolution (within 0.3 dex) of the ratio of the star formation rate (SFR) to the dark matter accretion rate, SFR/Ṁh , indicating the almost constant star formation efficiency at z ∼ 2–6, as suggested by our earlier work at z ∼ 4–7. Meanwhile, the ratio gradually increases with decreasing redshift at z < 5 within 0.3 dex, which quantitatively reproduces the cosmic SFR density evolution, suggesting that the redshift evolution is primarily driven by the increase of the halo number density due to the structure formation, and the decrease of the accretion rate due to the cosmic expansion. Extrapolating this calculation to higher redshifts assuming the constant efficiency suggests a rapid decrease of the SFR density at z > 10 with ∝ 10−0.5(1+z), which will be directly tested with the James Webb Space Telescope.
Stochasticity of infectious outbreaks and consequences for optimal interventions

Global strategies to contain a pandemic, such as social distancing and protective measures, are designed to reduce the overall transmission rate between individuals. Despite such measures, essential institutions, including hospitals, schools, and food producing plants, remain focal points of local outbreaks. Here we develop a model for the stochastic infection dynamics that predicts the statistics of local outbreaks from observables of the underlying global epidemics. Specifically, we predict two key outbreak characteristics: the probability of proliferation from a first infection in the local community, and the establishment size, which is the threshold size of local infection clusters where proliferation becomes likely. We derive these results using a contact network model of communities, and we show how the proliferation probability depends on the contact degree of the first infected individual. Based on this model, we suggest surveillance protocols by which individuals are tested proportionally to their degree in the contact network. We characterize the efficacy of contact-based protocols as a function of the epidemiological and the contact network parameters, and we show numerically that such protocols outperform random testing.
Algebraic and Graph-Theoretic Conditions for the Herdability of Linear Time-Invariant Systems

In this paper we investigate a relaxed concept of controllability, known in the literature as herdability, namely the capability of a system to be driven towards the (interior of the) positive orthant. Specifically, we investigate herdability for linear time-invariant systems, both from an algebraic perspective and based on the graph representing the systems interactions. In addition, we focus on linear state-space models corresponding to matrix pairs (A,B) in which the matrix B is a selection matrix that determines the leaders in the network, and we show that the weights that followers give to the leaders do not affect the herdability of the system. We then focus on the herdability problem for systems with a single leader in which interactions are symmetric and the network topology is acyclic, in which case an algorithm for the leader selection is provided. In this context, under some additional conditions on the mutual distances, necessary and sufficient conditions for the herdability of the overall system are given.
From augmented microscopy to the topological transformer: a new approach in cell image analysis for Alzheimer's research

Cell image analysis is crucial in Alzheimer’s research to detect the presence of Aβ protein inhibiting cell function. Deep learning speeds up the process by making only low-level data sufficient for the fruitful inspection. We first found Unet is most suitable in augmented microscopy by comparing performance in multi-class semantics segmentation. We develop the augmented microscopy method to capture nuclei in a brightfield image and the transformer using Unet model to convert an input image into a sequence of topological information. The performance regarding Intersection-over-Union is consistent concerning the choice of image preprocessing and ground-truth generation. Training model with data of a specific cell type demonstrates transfer learning applies to some extent. The topological transformer aims to extract persistence silhouettes or landscape signatures containing geometric information of a given image of cells. This feature extraction facilitates studying an image as a collection of one-dimensional data, substantially reducing computational costs. Using the transformer, we attempt grouping cell images by their cell type relying solely on topological features. Performances of the transformers followed by SVM, XGBoost, LGBM, and simple convolutional neural network classifiers are inferior to the conventional image classification. However, since this research initiates a new perspective in biomedical research by combining deep learning and topology for image analysis, we speculate follow-up investigation will reinforce our genuine regime.
RC : caveats not sufficiently discussed Anonymous Referee # 1 Referee comment on " Freshwater Routing In Eddy-permitting Simulations Of The Last Deglacial : Impact Of Realistic Freshwater Discharge

This paper presents a set of sensitivity experiments using an ocean-only GCM forced with atmospheric boundary conditions from CCSM3 in a LGM configuration. The ocean model has a relatively high resolution (about 5 times greater than most CMIP5 models) and can be considered as eddy permitting. The authors perform a set of 5 simulations where freshwater is released from different locations that corresponds to potential region of glacial icebergs and meltwater discharges in the last ice age and deglaciation. All the sensitivity simulations are shorter than 20 years, and the focus is put on the pathway of the freshwater in the Atlantic Ocean, and its impact on the regions of oceanic deep convection. It is found that freshwater pathways are highly dependent on the release location, as was already highlighted in a few studies.
Development of General Purpose Liquid Chromatography Simulator for the Exploration of Novel Liquid Chromatographic Strategies

xxiii 1. Overview of Objectives . 1 2. Introduction . 4 2.1. Liquid Chromatography . 4 2.2. Two-Dimensional Liquid Chromatography (2D-LC). 9 2.3. Simulators . 12 3. Theory . 15 3.1. Craig distribution model . 15 3.2. Linear solvent strength (LSS) theory . 17
Minsk and Budapest , the two capital cities

The current increase of regional inequalities in Europe, and in particular in Central and Eastern Europe (CEE) has led to the reconsideration and revival of the concepts of “polarisation” and “convergence” in academic fi elds like regional economics, economic geography and spatial planning as well. In contrast to the classical view on these concepts determined by functionalism and topology, the new theoretical and empirical perspectives are emphasising a multidimensional perspective. In addition, there is an important debate about the relation between economic inequalities and growth. This article provides a critical overview and assessment of the theoretical and empirical work on regional inequalities with special emphasis on theories of economic and social polarisation, regional economic growth, convergence, and social inequalities. We att empt to combine two powerful concepts of polarisation and convergence, emphasising their relational and multi-scalar nature. Building on this basis, we propose a multidimensional concept of socio-economic polarisation, which comprises processes of convergence and divergence, growth and mobility in economic and social dimensions.
C O ] 3 0 Ju l 2 02 1 Pattern Avoidance Over a Hypergraph

A classic result of Marcus and Tardos (previously known as the StanleyWilf conjecture) bounds from above the number of n-permutations (σ ∈ Sn) that do not contain a specific sub-permutation. In particular, it states that for any fixed permutation π, the number of n-permutations that avoid π is at most exponential in n. In this paper, we generalize this result. We bound the number of avoidant n-permutations even if they only have to avoid π at specific indices. We consider a k-uniform hypergraph Λ on n vertices and count the n-permutations that avoid π at the indices corresponding to the edges of Λ. We analyze both the random and deterministic hypergraph cases. This problem was originally proposed by Asaf Ferber. When Λ is a random hypergraph with edge density α, we show that the expected number of Λ-avoiding n-permutations is bounded (both upper and lower) as exp(O(n))α n k−1 , using a supersaturation version of Füredi-Hajnal. In the deterministic case we show that, for Λ containing many size L cliques, the number of Λ-avoiding n-permutations is O ( n log n L n , giving a nontrivial bound with L polynomial in n. Our main tool in the analysis of this deterministic case is the new and revolutionary hypergraph containers method, developed in [6] and [8].
R ETRIEVAL A UGMENTATION

Recent advances in using retrieval components over external knowledge sources have shown impressive results for a variety of downstream tasks in natural language processing. Here, we explore the use of unstructured external knowledge sources of images and their corresponding captions for improving visual question answering (VQA). First, we train a novel alignment model for embedding images and captions in the same space, which achieves state-of-the-art image-caption retrieval performance w.r. t. similar methods. Second, we show that retrievalaugmented multi-modal transformers using the trained alignment model significantly improve results on VQA over strong baselines. reporting state-of-the-art performance. We further conduct extensive experiments to establish the promise of this approach, and examine novel applications for inference time such as hotswapping indices.
In silico prediction of B and T cell epitopes based on NDV fusion protein for vaccine development against Newcastle disease virus

Newcastle disease (ND) is known as the most common diseases of economic importance worldwide. Vaccination against virulent strains of Newcastle disease virus (NDV) has failed during some outbreaks. Here, we aimed to assess the epitopes of NDV fusion protein as targets for a peptide-based vaccine. To explore the most antigenic epitopes on the F protein, we retrieved virulent strains of genotype VII from National Center for Biotechnology Information (NCBI). Linear and conformational B-cell epitopes were identified. Moreover, T-cell epitopes with high and moderate binding affinities to human major histocompatibility complex (MHC) class I and class II alleles were predicted using bioinformatics tools. Subsequently, the overlapped epitopes of B-cell and MHC class I and MHC class II were determined. To validate our predictions, the best epitopes were docked, to chicken MHC class I (B-F) alleles using the HADDOCK flexible docking server. Seven ‘high ranked epitopes’ were identified. Among them, ‘LYCTRIVTF’ and ‘MRATYLETL’ showed the highest scores. The other five epitopes including LSGEFDATY, LTTPPYMALK, LYLTELTTV, DCIKITQQV and SIAATNEAV obtained very encouraging results as well. SIAATNEAV had been recognized as a neutralizing epitope of F protein using monoclonal antibodies before. Taken together, our results demonstrated that the identified epitopes needed to be tested by in vitro and in vivo experiments.
Study on the influence of environmental factors on AC corrosion behavior and its mechanism

The AC corrosion behavior of X70 steel under the combined action of cathodic protection and AC interference was studied by the laboratory simulation experiments in two kinds of typical soil simulated environments with different contents of calcium ion (Ca2+), magnesium ion (Mg2+), and sodium ion (Na+). The mechanisms of AC corrosion in different environments were investigated by process parameter monitoring, electrochemical measurement, corrosion morphology, and product analyses. The results showed that the corrosion rate of X70 steel in the simulated environment with higher Na+ content was 2 times higher than that in the simulated environment with higher Ca2+ and Mg2+ content under the same CP potential and AC current density. The reason was analyzed and it was found that the performance of product film, AC current distribution through the double layer interface of steel/electrolyte, and the enrichment of some ions near the interface attributed to AC corrosion rate in different environments.
Prevalence of Work-Related Injury and Its Determinants among Construction Workers in Ethiopia: A Systematic Review and Meta-Analysis

Background Construction is one of the highest risky jobs for accident-related fatalities and injuries globally. This systematic review and meta-analysis aimed to estimate the pooled prevalence of work-related injury and its associated factors among construction workers in Ethiopia. Methods A systematic literature search was performed by using PubMed, Science Direct, and Google Scholar. A random-effects model was used to estimate the pooled prevalence of work-related injury and its associated factors. The heterogeneity of the studies was assessed by using the I2 test, and the presence of publication bias was evaluated by using funnel plot and Egger's test. Results After reviewing 292 articles, we included 10 studies that fulfilled the inclusion criteria in the meta-analysis. The findings from the 10 studies showed that the pooled prevalence of work-related injury in Ethiopia was 46.78% (95% CI: 32.17, 61.38). The subgroup analysis of this study showed that the highest prevalence was reported in Addis Ababa with the prevalence of 55.9% (25.42, 86.4), followed by a study conducted in Oromia Region with a prevalence of 43.3% (33.3, 53.3). Lack of occupational safety training (OR: 2.43, 95% CI: 1.76, 3.35), not using of personal protective equipment (OR: 2.32, 95% CI: 1.80, 2.99), and male workers (OR: 2.44, 95% CI: 1.15, 5.17) were the major factors significantly associated with the occurrence of work-related injury among construction workers. Conclusions This study confirmed that construction is still a high-risk job with a high prevalence of work-related injury in Ethiopia. The modifiable risk factors such as the use of personal protective equipment (PPE), lack of safety training, and gender were the major associated factors with injury. Therefore, a continuous safety training and awareness creation program on risk-taking behavior should be given to construction workers.
Roquin2 suppresses breast cancer progression by inhibiting tumor angiogenesis via selectively destabilizing proangiogenic factors mRNA

Tumor angiogenesis is an essential step in tumor growth and metastasis. The initiation of tumor angiogenesis is dictated by a shift in the balance between proangiogenic and antiangiogenic gene expression programs. Roquin2 is a zinc-finger RNA-binding protein with important roles in mediating the expression of inflammatory genes, such as TNF, IL6 and PTGS2, which are also important angiogenic factors. In this study, we demonstrate that Roquin2 functions as a potent tumor angiogenesis regulator that inhibits breast tumor-induced angiogenesis by selectively destabilizing mRNA of proangiogenic gene transcripts, including endoglin (ENG), endothelin-1 (EDN1), vascular endothelial growth factor B (VEGFB) and platelet derived growth factor C (PDGFC). Roquin2 recognizes and binds the stem-loop structure in the 3'untranslated region (3'UTR) of these mRNAs via its ROQ domain to destabilize mRNA. Moreover, we found that Roquin2 expression was reduced in breast cancer cells and tissues, and associated with poor prognosis in breast cancer patients. Overexpression of Roquin2 inhibited breast tumor-induced angiogenesis in vitro and in vivo, whereas silencing Roquin2 enhanced tumor angiogenesis. In vivo induction of Roquin2 by adenovirus significantly suppressed breast tumor growth, metastasis and angiogenesis. Taken together, our results identify that Roquin2 is a novel breast cancer suppressor that inhibits tumor angiogenesis by selectively downregulating the expression of proangiogenic genes.
Cytotoxicity, leishmanicidal, and antioxidant activity of biosynthesised zinc sulphide nanoparticles using Phoenix dactylifera

The synthesis of zinc sulphide nanoparticles (ZnS NPs) using a green approach was explored. The resulting nanoparticles (NPs) were characterised by UV–vis spectroscopy, scanning and transmission electron microscopy, X-ray diffraction and Fourier transform infrared spectroscopy. The leishmanicidal, cytotoxic and antioxidant activity of the resulting synthesised ZnS NPs (<70 nm) were evaluated against Leishmania major (L. major) promastigotes and amastigotes by MTT assay and using a macrophage model. The ZnS NPs were able to counteract the effects of oxidative metabolites as demonstrated by the oxidant activity. The IC50 value of butylated hydroxyanisole was 26.04 µg/ml as compared with the IC50 for ZnS NPs (90.95 µg/ml). The NPs displayed no cytotoxicity for the murine macrophaghes as the selectivity index (SI) fell into the safety range (SI ≥ 10). These nanomaterials exhibited good antileishmanial activity against the L. major stages that were comparable to that of Glucantime, the drug of choice. The IC50 values of ZnS NPs and Glucantime against amastigotes were 11.59 ± 2.51 and 4.95 ± 2.51 μg/ml, respectively. The IC50 values for ZnS NPs and Glucantime versus promastigote were 29.81 ± 3.15 and 14.75 ± 4.05 μg/ml, respectively. Further investigation is essential to explore the biological effects of ZnS NPs on animal and/or clinical models.
Can functional walk tests add value to the prediction of cardiorespiratory fitness after stroke? A prospective cohort study

Background Cardiorespiratory fitness is often impaired following stroke, and peak oxygen consumption (VO2peak) is an important prognostic value of all-cause mortality. The primary objective was to investigate whether functional walk tests assessed in the subacute phase after stroke added value in predicting VO2peak in chronic stroke, in addition to age, sex and functional dependency. Secondary objectives were to investigate associations between daily physical activity and functional walk tests, and with VO2peak in chronic stroke. Methods This prospective cohort study included eligible participants originally included in the randomized controlled trial Life After Stroke. Functional walk tests, i.e., six-minute walk test (6MWT) and maximal gait speed, were assessed at inclusion and 18 months later. VO2peak [ml/kg/min] was assessed by a cardiopulmonary exercise test on a treadmill 20 months after inclusion. Daily physical activity was measured by a uniaxial accelerometer (activPAL) at 18-month follow-up. Results Ninety-two community-dwelling individuals, with a mean (SD) age of 69.2 (10.6) years and 33 (35.9%) women, were included 3 months after stroke onset. Eighty-three (90.2%) participants had a modified Rankin Scale (mRS) score of 1 or 2, indicating functional independence. An overall assessment of four prediction models indicated the combination of age, sex, mRS and 6MWT as predictors to be the best fitted model in predicting VO2peak (adjusted R2 = 0.612). Secondary results showed statistically significant, but not clinically significant, associations between daily physical activity and functional walk tests, and with VO2peak. Conclusions 6MWT add significant value to the prediction of mean VO2peak in the chronic phase in mild strokes, in combination with age, sex and functional dependency. This prediction model may facilitate clinical decisions and rehabilitation strategies for mildly affected stroke survivors in risk of low levels of VO2peak. Future studies should validate the model in various stages after stroke and in patients moderately and severely affected.