Miracle-dz/UniFAR-FTUs huggingface dataset:
Scientific guidelines for evaluating the validity of forensic feature-comparison methods

When it comes to questions of fact in a legal context—particularly questions about measurement, association, and causality—courts should employ ordinary standards of applied science. Applied sciences generally develop along a path that proceeds from a basic scientific discovery about some natural process to the formation of a theory of how the process works and what causes it to fail, to the development of an invention intended to assess, repair, or improve the process, to the specification of predictions of the instrument’s actions and, finally, empirical validation to determine that the instrument achieves the intended effect. These elements are salient and deeply embedded in the cultures of the applied sciences of medicine and engineering, both of which primarily grew from basic sciences. However, the inventions that underlie most forensic science disciplines have few roots in basic science, and they do not have sound theories to justify their predicted actions or results of empirical tests to prove that they work as advertised. Inspired by the “Bradford Hill Guidelines”—the dominant framework for causal inference in epidemiology—we set forth four guidelines that can be used to establish the validity of forensic comparison methods generally. This framework is not intended as a checklist establishing a threshold of minimum validity, as no magic formula determines when particular disciplines or hypotheses have passed a necessary threshold. We illustrate how these guidelines can be applied by considering the discipline of firearm and tool mark examination.
Magnetic history of Early and Middle Ordovician sedimentary sequence, northern Estonia

SUMMARY Alternating field and thermal demagnetization of lime- and dolostones from the Lower and Middle Ordovician (Floian to Darriwilian stages) subhorizontally bedded sequences in NW and NE Estonia reveal two characteristic magnetization components (named P and S). The intermediate-coercivity (demagnetized at 30–60 mT, up to 300–350 °C) reversed polarity component P (mean of Floian Stage: Dref= 147.8 ± 10.8°, Iref= 65.8 ± 5.4°; combined mean of Dapingian and Darriwilian stages: Dref= 166.0 ± 8.4°, Iref= 56.1 ± 6.5°) is regarded as the primary remanence of early diagenetic (chemical) origin. On the Baltica's apparent polar wander path (APWP), the palaeopoles (Floian: Plat= 25.0 °N, Plon= 50.8 °E, K= 52.7, A95= 7.2°; Dapingian and Darriwilian: Plat= 11.4 °N, Plon= 39.1 °E, K= 33.8, A95= 6.7°) are placed on the Lower and Middle Ordovician segment. The poles indicate that Estonia was located at southerly latitudes, decreasing with time (Floian: ∼48 °S; Dapingian and Darriwilian: ∼37 °S), when the remanence was acquired. A high-coercivity and high-unblocking-temperature component S (mean of samples: Dref= 33.7 ± 6.3°, Iref= 51.9 ± 5.7°) that is regarded as a secondary remanence has both normal and reversed polarities. On the European APWP, its palaeopole (Plat= 52.5 °N, Plon= 157.9 °E, K= 38.9, A95= 5.3°) gives middle to late Permian age. According to mineralogical (SEM and optical microscopy) and rock magnetic (three-component induced remnant magnetization) studies, component P is carried by magnetite (coexisting with glauconite) and component S by haematite. Magnetite is of chemical origin, formed in the course of early diagenesis and/or dolomitization. During the Permian continental period haematite, the carrier of component S, was likely precipitated from oxidizing meteoric fluids in the already existing or simultaneously formed pore space between the dolomite crystals.
ATG9A modulated by miR-195-5p can boost the malignant progression of cervical cancer cells

ABSTRACT Cervical cancer (CC) is a major public health problem, and its molecular mechanism requires further investigation. The goal of this study was to determine the role of miR-195-5p and the autophagy-related protein ATG9A in tumour metastasis, epithelial – mesenchymal transition (EMT), apoptosis, and autophagy of CC cells. Using bioinformatics analysis, we predicted ATG9A as a downstream target gene of miR-195-5p, an integral membrane protein required for autophagosome formation and involved in tumorigenesis. Next, western blotting and Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) showed that upregulation of miR-195-5p decreased protein and mRNA expression of ATG9A, and downregulation of miR-195-5p promoted ATG9A protein and mRNA expression. In addition, detection of the dual luciferase reporter gene further indicated ATG9A is a direct downstream target gene of miR-195-5p. Finally, the effects of miR-195-5p and ATG9A on CC cell proliferation, migration, invasion, EMT, autophagy, and apoptosis were evaluated in vitro. Our results showed that upregulation of miR-195-5p not only inhibits proliferation, migration, and the EMT of CC cells, but also induces apoptosis and autophagy. Conversely, downregulation of miR-195-5p increased malignant metastasis and the EMT of CC cells, and inhibited apoptosis as well as autophagy. In addition, miR-195-5p targeted and negatively regulated ATG9A, and rescue experiments suggested that overexpression of ATG9A could partially abolish miR-195-5p-mediated suppression of CC cells. Our findings improve our understanding of the mechanism of action of miR-195-5p in the malignant behaviour of CC. miR-195-5p is likely to be a promising cancer suppressor gene, which provides clinical evidence for targeted therapy of CC.
Perioperative optimisation in low- and middle-income countries (LMICs): A systematic review and meta-analysis of enhanced recovery after surgery (ERAS)

Background Enhanced recovery after surgery (ERAS) protocols have largely been incorporated into practice in high-income settings due to proven improvement in perioperative outcomes. We aimed to review the implementation of ERAS protocols and other perioperative optimisation strategies in low- and middle-income countries (LMICs) and their impact on length of hospital stay (LOS). Methods We searched MEDLINE, PubMed, Global Health (CABI), WHO Global Index Medicus, Index Medicus, and Latin American and Caribbean Health Sciences Literature (LILACS) for studies incorporating ERAS or other prehabilitation approaches in LMICs. We conducted a pooled analysis of LOS using a random-effects model to evaluate the impact of such programs. This systematic review was pre-registered on PROSPERO. Results We screened 1205 studies and included 70 for a full-text review; six were eligible for inclusion and five for quantitative analysis, two of which were randomised controlled trials. ERAS was compared to routine practice in all included studies, while none implemented prehabilitation or other preoperative optimisation strategies. Pooled analysis of 290 patients showed reduced LOS in the ERAS group with a standardised mean difference of -2.18 (95% confidence interval (CI) = -4.13, -. 0.05, P < 0.01). The prediction interval was wide (95% CI = -7.85, 3.48) with substantial heterogeneity (I2 = 94%). Conclusions Perioperative optimisation is feasible in LMICs and appears to reduce LOS, despite high levels of between-study heterogeneity. There is a need for high-quality data on perioperative practice in LMICs and supplementary qualitative analysis to further understand barriers to perioperative optimisation implementation. Registration PROSPERO: CRD42021279053.
Algorithms on Strings, Trees, and Sequences: Computer Science and Computational Biology

Part I. Exact String Matching: The Fundamental String Problem: 1. Exact matching: fundamental preprocessing and first algorithms 2. Exact matching: classical comparison-based methods 3. Exact matching: a deeper look at classical methods 4. Semi-numerical string matching Part II. Suffix Trees and their Uses: 5. Introduction to suffix trees 6. Linear time construction of suffix trees 7. First applications of suffix trees 8. Constant time lowest common ancestor retrieval 9. More applications of suffix trees Part III. Inexact Matching, Sequence Alignment and Dynamic Programming: 10. The importance of (sub)sequence comparison in molecular biology 11. Core string edits, alignments and dynamic programming 12. Refining core string edits and alignments 13. Extending the core problems 14. Multiple string comparison: the Holy Grail 15. Sequence database and their uses: the motherlode Part IV. Currents, Cousins and Cameos: 16. Maps, mapping, sequencing and superstrings 17. Strings and evolutionary trees 18. Three short topics 19. Models of genome-level mutations.
Annual floods in New England (USA) and Atlantic Canada: synoptic climatology and generating mechanisms

New England and Atlantic Canada are characterized by mixed flood regimes that reflect different storm types, antecedent land surface conditions, and flood seasonality. Mixed flood regimes are known to complicate flood risk analyses, yet the synoptic climatology and precipitation mechanisms that generate annual floods in this region have not been described in detail. We analyzed a set of long-term annual flood records at climate-sensitive stream gauges across the region and classified the synoptic climatology of each annual flood, quantitatively describing the precipitation mechanisms, and characterize flood seasonality. We find that annual floods here are dominantly generated by Great Lakes-sourced storms and Coastal lows, known locally as ‘nor’easters. ’ Great Lakes storms tend to be associated with lower magnitude annual floods (<75th percentile) and Coastal lows are more clearly associated with higher magnitude events (>75th percentile). Tropical cyclones account for few of all annual floods, including extreme events, despite causing some of the region’s largest and most destructive floods. Late winter/early spring is when the greatest number of annual floods occur region wide, and rainfall is the dominant flood-producing mechanism. Rainfall in combination with snowmelt is also important. Both mechanisms are expected to be impacted by projected regional climate change. We find little evidence for associations between flood-producing synoptic storm types or precipitation mechanisms and large-scale atmospheric circulation indices or time periods, despite upward trends in New England annual flood magnitudes. To more completely investigate such associations, partial duration flood series that include more floods than just the largest of each year, and their associated synoptic climatologies and precipitation mechanisms, should be analyzed.
Dissipation-induced cooperative advantage in a quantum thermal machine

We show that a quantum heat engine where the working medium is composed by two non-interacting quantum harmonic oscillators, connected to common baths via periodically modulated couplings, exhibits a cooperative advantage with respect to the case of two independent single-oscillator engines working in parallel. The advantage extends from weak to strong damping, being particularly evident in the latter case, where the independent engines cannot deliver any useful power, while the coupling to common baths allows for efficiency and power comparable and in some parameter regions even higher than those obtained in the limit of weak dissipation. The surprising fact that strong dissipation is a useful resource for a thermal machine is explained in terms of the appearance of a collective mode, with the two oscillators locked at a common, hybrid frequency, intermediate between their bare frequencies. Our results are first illustrated in the simplest case of monochromatic drivings and then corroborated after optimization over generic periodic driving protocols. Using machine learning tools, we perform an optimization over arbitrary driving protocols to find the Pareto front representing optimal tradeoffs between the power and the efficiency that the engine can deliver. Finally, we find a protocol to measure the entanglement established in the working medium via measurement of a small set of thermodynamic quantities, that is, the output work under specific driving protocols.
Contraction Properties of the Global Workspace Primitive

To push forward the important emerging research field surrounding multi-area recurrent neural networks (RNNs), we expand theoretically and empirically on the provably stable RNNs of RNNs introduced by Kozachkov et al. in"RNNs of RNNs: Recursive Construction of Stable Assemblies of Recurrent Neural Networks". We prove relaxed stability conditions for salient special cases of this architecture, most notably for a global workspace modular structure. We then demonstrate empirical success for Global Workspace Sparse Combo Nets with a small number of trainable parameters, not only through strong overall test performance but also greater resilience to removal of individual subnetworks. These empirical results for the global workspace inter-area topology are contingent on stability preservation, highlighting the relevance of our theoretical work for enabling modular RNN success. Further, by exploring sparsity in the connectivity structure between different subnetwork modules more broadly, we improve the state of the art performance for stable RNNs on benchmark sequence processing tasks, thus underscoring the general utility of specialized graph structures for multi-area RNNs.
GNNX-BENCH: Unravelling the Utility of Perturbation-based GNN Explainers through In-depth Benchmarking

Numerous explainability methods have been proposed to shed light on the inner workings of GNNs. Despite the inclusion of empirical evaluations in all the proposed algorithms, the interrogative aspects of these evaluations lack diversity. As a result, various facets of explainability pertaining to GNNs, such as a comparative analysis of counterfactual reasoners, their stability to variational factors such as different GNN architectures, noise, stochasticity in non-convex loss surfaces, feasibility amidst domain constraints, and so forth, have yet to be formally investigated. Motivated by this need, we present a benchmarking study on perturbation-based explainability methods for GNNs, aiming to systematically evaluate and compare a wide range of explainability techniques. Among the key findings of our study, we identify the Pareto-optimal methods that exhibit superior efficacy and stability in the presence of noise. Nonetheless, our study reveals that all algorithms are affected by stability issues when faced with noisy data. Furthermore, we have established that the current generation of counterfactual explainers often fails to provide feasible recourses due to violations of topological constraints encoded by domain-specific considerations. Overall, this benchmarking study empowers stakeholders in the field of GNNs with a comprehensive understanding of the state-of-the-art explainability methods, potential research problems for further enhancement, and the implications of their application in real-world scenarios.
A critical neumann problem with anisotropic p-laplacian

We are concerned with the existence of solution of the problem $ -\Delta ^H_pu+|u|^{p-2}u=\lambda|u|^{q-2}u+ |u|^{p^*-2}u\quad \mbox{in}\quad\Omega,$ $u>0\quad \mbox{in}\quad\Omega,$ $a(\nabla u)\cdot \nu =0\quad \mbox{on}\quad\partial \Omega,$ where $\Delta ^H_pu=\mbox{div\,}(a(\nabla u))$, with $a(\xi)=H^{p-1}(\xi)\nabla H(\xi),\, \xi \in \mathbb{R}^N,$ $N\geqslant3,$ is the anisotropic $p$-Laplacian with $1<p<N$, $\lambda>0$ is a parameter, and $p<q<p^*=pN/(N-p)$. Further, $\Omega \subset \Sigma$ is a $C^1$ bounded domain inside a convex open cone $\Sigma$ in $\mathbb{R}^N$ with $\partial \Omega \cap \partial \Sigma$ being a $C^1$-manifold, and $\nu$ is the unit outward normal to $\partial \Omega$. To succeed with a variational approach, where the strong convergence of a bounded (PS) subsequence needs to be proved, one has to deal with anisotropic norms in the absence of a Tartar's type inequality, unlike the isotropic $p$-Laplace case. This is overcome by proving the a.e. convergence of its gradients. Furthermore, the solution of $(P)$ is shown to belong to $C^{1,\alpha}(\Omega)$, and is strictly positive in $\Omega$. Such conclusions are achieved from classical elliptic regularity theory and a Harnack inequality, since the solution of $(P)$ is bounded. This in turn is a consequence of a result in this paper which ensures that any $W^{1,p}$-solution of critical Neumann problems with the anisotropic $p$-Laplacian operator on bounded Lipschitz domains in $\mathbb{R}^N$ $(N\geqslant3)$ is bounded.
Eruptive and seismic activity at Etna Volcano (Italy) between 1977 and 1991

Abstract A review of volcanic and seismic activity at Etna (Sicily, Italy) between 1977–1991 is presented with the purpose of looking for possible relations between the main phases of seismic energy release and the principal eruptive episodes. Flank eruptions are normally preceded by both deep and shallow seismic swarms (0 <h<20km) which accompany the opening of fracture systems some hours before the eruption onset. Conversely, summit eruptions usually take place without any immediate change in the seismic patterns, even if moderate seismic activity some months before the onset suggests that magma uprises gradually and might rest within shallow reservoirs during ascent. It is worth noting that in some cases (1981, 1983, 1984 and 1986) significant episodes of seismic energy release occurred during the late phases of the eruptions. The analysis of the temporal evolution of the coefficient b of the magnitude-frequency relation suggests that the shallow seismicity of the eastern flank reflects the existence of a high level of geodynamic activity, probably associated with both regional tectonic forces and seaward sliding of this unbuttressed sector of the volcano.
Keypoint-Augmented Self-Supervised Learning for Medical Image Segmentation with Limited Annotation

Pretraining CNN models (i.e., UNet) through self-supervision has become a powerful approach to facilitate medical image segmentation under low annotation regimes. Recent contrastive learning methods encourage similar global representations when the same image undergoes different transformations, or enforce invariance across different image/patch features that are intrinsically correlated. However, CNN-extracted global and local features are limited in capturing long-range spatial dependencies that are essential in biological anatomy. To this end, we present a keypoint-augmented fusion layer that extracts representations preserving both short- and long-range self-attention. In particular, we augment the CNN feature map at multiple scales by incorporating an additional input that learns long-range spatial self-attention among localized keypoint features. Further, we introduce both global and local self-supervised pretraining for the framework. At the global scale, we obtain global representations from both the bottleneck of the UNet, and by aggregating multiscale keypoint features. These global features are subsequently regularized through image-level contrastive objectives. At the local scale, we define a distance-based criterion to first establish correspondences among keypoints and encourage similarity between their features. Through extensive experiments on both MRI and CT segmentation tasks, we demonstrate the architectural advantages of our proposed method in comparison to both CNN and Transformer-based UNets, when all architectures are trained with randomly initialized weights. With our proposed pretraining strategy, our method further outperforms existing SSL methods by producing more robust self-attention and achieving state-of-the-art segmentation results. The code is available at https://github.com/zshyang/kaf.git.
The mixed Schur transform: efficient quantum circuit and applications

The Schur transform, which block-diagonalizes the tensor representation $U^{\otimes n}$ of the unitary group $\mathbf{U}_d$ on $n$ qudits, is an important primitive in quantum information and theoretical physics. We give a generalization of its quantum circuit implementation due to Bacon, Chuang, and Harrow (SODA 2007) to the case of mixed tensor $U^{\otimes n} \otimes \bar{U}^{\otimes m}$, where $\bar{U}$ is the dual representation. This representation is the symmetry of unitary-equivariant channels, which find various applications in quantum majority vote, multiport-based teleportation, asymmetric state cloning, black-box unitary transformations, etc. The"mixed"Schur transform contains several natural extensions of the representation theory used in the Schur transform, in which the main ingredient is a duality between the mixed tensor representations and the walled Brauer algebra. Another element is an efficient implementation of a"dual"Clebsch-Gordan transform for $\bar{U}$. The overall circuit has complexity $\widetilde{O} ((n+m)d^4)$. Finally, we show how the mixed Schur transform enables efficient implementation of unitary-equivariant channels in various settings and discuss other potential applications, including an extension of permutational quantum computing that includes partial transposes.
Symmetry-based classification of exact flat bands in single and bilayer moir\'e systems

We study the influence of spatial symmetries on the appearance and the number of exact flat bands (FBs) in single and bilayer systems with Dirac or quadratic band crossing points, and systematically classify all possible number of exact flat bands in systems with different point group symmetries. We find that a maximum of 6 FBs can be protected by symmetries, and show an example of 6 FBs in a system with QBCP under periodic strain field of $\mathcal{C}_{6v}$ point group symmetry. All known examples of exact FBs in single and bilayer systems fall under this classification, including chiral twisted bilayer graphene, and new examples of exact FBs are found. We show the construction of wavefunctions for the highly degenerate FBs, and prove that any such set of FBs are $\mathds{Z}_2$ nontrivial, where all WFs polarized on one sublattice together have Chern number $C = 1$ and WFs polarized on the other sublattice together have $C = -1$. These bands also satisfy ideal non-Abelian quantum geometry condition. We further show that, just like in TBG, topological heavy fermion description of the FBs with higher degeneracy is possible as long as the Berry curvature distribution is peaked around a point in the BZ.
Drainage basin responses to climate change

Recent investigations have shown that the extent of the channel network in some drainage basins is controlled by a threshold for overland flow erosion. The sensitivity of such basins to climate change is analyzed using a physically based model of drainage basin evolution. The GOLEM model simulates basin evolution under the action of weathering processes, hillslope transport, and fluvial bedrock erosion and sediment transport. Results from perturbation analyses reveal that the nature and timescale of basin response depends on the direction of change. An increase in runoff intensity (or a decrease in vegetation cover) will lead to a rapid expansion of the channel network, with the resulting increase in sediment supply initially generating aggradation along the main network, followed by downcutting as the sediment supply tapers off. By contrast, a decrease in runoff intensity (or an increase in the erosion threshold) will lead to a retraction of the active channel network and a much more gradual geomorphic response. Cyclic changes in runoff intensity are shown to produce aggradational‐degradational cycles that resemble those observed in the field. Cyclic variations in runoff also lead to highly punctuated denudation rates, with denudation concentrated during periods of increasing runoff intensity and/or decreasing vegetation cover. The sediment yield from threshold‐dominated basins may therefore exhibit significant variability in response to relatively subtle environmental changes, a finding which underscores the need for caution in interpreting modern sediment‐yield data.