Miracle-dz/UniFAR-FTUs huggingface dataset:
Barking dogs: A Fréchet distance variant for detour detection

Imagine you are a dog behind a fence $Q$ and a hiker is passing by at constant speed along the hiking path $P$. In order to fulfil your duties as a watchdog, you desire to bark as long as possible at the human. However, your barks can only be heard in a fixed radius $\rho$ and, as a dog, you have bounded speed $s$. Can you optimize your route along the fence $Q$ in order to maximize the barking time with radius $\rho$, assuming you can run backwards and forward at speed at most $s$? We define the barking distance from a polyline $P$ on $n$ vertices to a polyline $Q$ on $m$ vertices as the time that the hiker stays in your barking radius if you run optimally along $Q$. This asymmetric similarity measure between two curves can be used to detect outliers in $Q$ compared to $P$ that other established measures like the Fr\'echet distance and Dynamic Time Warping fail to capture at times. We consider this measure in three different settings. In the discrete setting, the traversals of $P$ and $Q$ are both discrete. For this case we show that the barking distance from $P$ to $Q$ can be computed in $O(nm\log s)$ time. In the semi-discrete setting, the traversal of $Q$ is continuous while the one of $P$ is again discrete. Here, we show how to compute the barking distance in time $O(nm\log (nm))$. Finally, in the continuous setting in which both traversals are continuous, we show that the problem can be solved in polynomial time. For all the settings we show that, assuming SETH, no truly subquadratic algorithm can exist.
Epstein Semantics: Characterization, Interpolation, Undefinability, and (In)Completeness

This paper is a mathematical investigation on Epstein semantics. One of the main tools of the present paper is the model-theoretic S-set construction introduced in (Krawczyk 2022). We use it to prove several results: 1) that each Epstein model has uncountably many equivalent Epstein models, 2) that the logic of generalised Epstein models is the S-set invariant fragment of CPL (analogon of the celebrated van Benthem characterization theorem for modal logic), 3) that several sets of Epstein relations are undefinable, 4) that logics of undefinable sets of relations can be finitely axiomatised. We also use other techniques to prove: 5) that there is uncountably many Epstein-incomplete logics and that 6) the logic of generalised Epstein models has the interpolation property.
Two-stage Rainfall-Forecasting Diffusion Model

Deep neural networks have made great achievements in rainfall prediction.However, the current forecasting methods have certain limitations, such as with blurry generated images and incorrect spatial positions. To overcome these challenges, we propose a Two-stage Rainfall-Forecasting Diffusion Model (TRDM) aimed at improving the accuracy of long-term rainfall forecasts and addressing the imbalance in performance between temporal and spatial modeling. TRDM is a two-stage method for rainfall prediction tasks. The task of the first stage is to capture robust temporal information while preserving spatial information under low-resolution conditions. The task of the second stage is to reconstruct the low-resolution images generated in the first stage into high-resolution images. We demonstrate state-of-the-art results on the MRMS and Swedish radar datasets. Our project is open source and available on GitHub at: \href{https://github.com/clearlyzerolxd/TRDM}{https://github.com/clearlyzerolxd/TRDM}.
Holographic Tests for Giant Graviton Expansion

It has been proposed that the superconformal index admits a novel reformulation, called giant graviton expansion. In this paper, we investigate the properties of dual $AdS_5$ black holes using the giant graviton expansion framework. First, we compute the entropy of black holes in $AdS_5\times S^5$ with fixed charges through a large $N$ saddle point analysis on the giant graviton index and further extremize it in the wrapping number. We identify a specific regime of fugacities where our saddle point analysis is valid. It turns out that this condition ensures the absence of closed-time-like curves and the stability of dual black hole solutions with equal charges. In addition, the giant graviton expansion of the index provides insights into how small black holes in AdS can be interpreted as bound states of branes. We extend our study to include the giant graviton expansion with the insertion of a half-BPS surface defect in $\mathcal{N}=4$ SYM with a $U(N)$ gauge group. Finally, we test the giant graviton expansion in various holographic theories whose dual geometries are $AdS_5\times S^5/\mathbb{Z}_k$ and $AdS_5\times SE_5$.
An 8-flow theorem for signed graphs

We prove that a signed graph admits a nowhere-zero $8$-flow provided that it is flow-admissible and the underlying graph admits a nowhere-zero $4$-flow. When combined with the 4-color theorem, this implies that every flow-admissible bridgeless planar signed graph admits a nowhere-zero $8$-flow. Our result improves and generalizes previous results of Li et al. (European J. Combin. 108 (2023), 103627), which state that every flow-admissible signed $3$-edge-colorable cubic graph admits a nowhere-zero $10$-flow, and that every flow-admissible signed hamiltonian graph admits a nowhere-zero $8$-flow.
Review of Impact of CO_2 Leakage From Geologic Storage on Near-Surface Terrestrial Ecological System

Carbon dioxide capture and storage(CCS) has been recognized as an effective way to mitigate emission of CO2 to the atmosphere and may become a critical technology for global CO2 mitigation,however,the risk of CO2 leaking from its geologic storage will pose a potential threat to the terrestrial ecosystem,especially the near-surface terrestrial ecosystem.From the aspects of the three major components(ground water,soil and vegetation) of the near-surface terrestrial ecosystem,a review is presented of the potential impact of the leakage on the ecosystem and its process,and progresses and shortcomings of the researches,abroad and at home,in this field are summarized.On such a basis,it is indicated that the study on impacts of CO2 leakage from its geologic storage should be focused on evaluation of its impacts on farmland ecosystems,determination of threshold of tolerance of the ecosystems to the leakage,construction of an early warning system for CO2 leakage,and proposition of a system of countermeasures for the terrestrial ecosystem to avoid or mitigate disasters CO2 leakage may cause.
Fits for the convective envelope mass in massive stars

We explore the evolution of massive stars (>8 solar masses) with 1-D models and present analytical fits to the masses and binding energies of the convective portions of their envelopes. These fits are given as functions of total mass, metallicity, and surface temperature (used as a proxy for evolutionary phase). They enable the application of the two-stage common envelope formalism (Hirai&Mandel 2022) in rapid binary population synthesis frameworks. We estimate that the degree of orbital hardening following common-envelope ejection spans 6 orders of magnitude and is a very strong function of the accretor mass, and, to a lesser extent, donor evolutionary phase.
An Adaptive Cubic Regularization quasi-Newton Method on Riemannian Manifolds

A quasi-Newton method with cubic regularization is designed for solving Riemannian unconstrained nonconvex optimization problems. The proposed algorithm is fully adaptive with at most ${\cal O} (\epsilon_g^{-3/2})$ iterations to achieve a gradient smaller than $\epsilon_g$ for given $\epsilon_g$, and at most $\mathcal O(\max\{ \epsilon_g^{-\frac{3}{2}}, \epsilon_H^{-3} \})$ iterations to reach a second-order stationary point respectively. Notably, the proposed algorithm remains applicable even in cases of the gradient and Hessian of the objective function unknown. Numerical experiments are performed with gradient and Hessian being approximated by forward finite-differences to illustrate the theoretical results and numerical comparison.
Off-Path TCP Hijacking in Wi-Fi Networks: A Packet-Size Side Channel Attack

In this paper, we unveil a fundamental side channel in Wi-Fi networks, specifically the observable frame size, which can be exploited by attackers to conduct TCP hijacking attacks. Despite the various security mechanisms (e.g., WEP and WPA2/WPA3) implemented to safeguard Wi-Fi networks, our study reveals that an off path attacker can still extract sufficient information from the frame size side channel to hijack the victim's TCP connection. Our side channel attack is based on two significant findings: (i) response packets (e.g., ACK and RST) generated by TCP receivers vary in size, and (ii) the encrypted frames containing these response packets have consistent and distinguishable sizes. By observing the size of the victim's encrypted frames, the attacker can detect and hijack the victim's TCP connections. We validate the effectiveness of this side channel attack through two case studies, i.e., SSH DoS and web traffic manipulation. Furthermore, we conduct extensive measurements to evaluate the impact of our attack on real-world Wi-Fi networks. We test 30 popular wireless routers from 9 well-known vendors, and none of these routers can protect victims from our attack. Also, we implement our attack in 80 real-world Wi-Fi networks and successfully hijack the victim's TCP connections in 69 (86%) evaluated Wi-Fi networks. We have responsibly disclosed the vulnerability to the Wi-Fi Alliance and proposed several mitigation strategies to address this issue.
Learning Generalization and Regularization of Nonhomogeneous Temporal Poisson Processes

The Poisson process, especially the nonhomogeneous Poisson process (NHPP), is an essentially important counting process with numerous real-world applications. Up to date, almost all works in the literature have been on the estimation of NHPPs with infinite data using non-data driven binning methods. In this paper, we formulate the problem of estimation of NHPPs from finite and limited data as a learning generalization problem. We mathematically show that while binning methods are essential for the estimation of NHPPs, they pose a threat of overfitting when the amount of data is limited. We propose a framework for regularized learning of NHPPs with two new adaptive and data-driven binning methods that help to remove the ad-hoc tuning of binning parameters. Our methods are experimentally tested on synthetic and real-world datasets and the results show their effectiveness.
Density matrix renormalization group study of the interacting Kitaev chain with quasi-periodic disorder

We document the ground state phase diagram of the one-dimensional Kitaev chain with quasi-periodic disorder in the presence of two-body interactions. Our data was obtained for systems of $L=1000$ sites using large-scale density matrix renormalization group numerics and is benchmarked against known results for the clean system. We demonstrate that moderate quasi-periodic disorder stabilizes the topological phase both for repulsive and attractive interactions. For larger disorder strengths, the system features re-entrance behavior and multiple phase transitions.
Documentation of nearshore interactive wave - current - topography change models

This report is to document the programs my colleague and I developed for computing time-dependent nearshore hydrographic changes including beach profile responses. The time scale of the model is suitable for storm events to seasonal changes, currently up to one year period. The model is very stable and is capable of handling complicated topographies including inlets and irregularly-shaped structures such as curved jetties and breakwaters. The purpose of three-dimensional models is to predict the change of bottom topography from the spatial distribution of the sediment transport rates, which are evaluated from the nearshore wave and current fields computed point by point in small areas defined by a horizontal grid placed over the region of interest. Models of 3-D beach topography change require much fewer idealizations than do the line models. (Document has 43 pages.)
Expanding the phage galaxy: Isolation and characterization of five novel Streptomyces siphoviruses Ankus, Byblos, DekoNeimoidia, Mandalore, and Naboo

Key features of the actinobacterial genus Streptomyces are multicellular, filamentous growth and production of a broad portfolio of bioactive molecules. These characteristics appear to play an important role in phage-host interactions and are modulated by phages during infection. To accelerate research of such interactions and the investigation of novel immune systems in multicellular bacteria, phage isolation, sequencing, and characterization are needed. This is a prerequisite for establishing systematic collections that appropriately cover phage diversity for comparative analyses. As part of a public outreach programme within the priority programme SPP 2330, involving local schools, we describe the isolation and characterization of five novel Streptomyces siphoviruses infecting S. griseus, S. venezuelae, and S. olivaceus. All isolates are virulent members of two existing genera and, additionally, establish a new genus in the Stanwilliamsviridae family. In addition to an extensive set of tRNAs and proteins involved in phage replication, about 80% of phage genes encode hypothetical proteins, underlining the yet underexplored phage diversity and genomic dark matter still found in bacteriophages infecting actinobacteria. Taken together, phages Ankus, Byblos, DekoNeimoidia, Mandalore, and Naboo expand the phage diversity and contribute to ongoing research in the field of Streptomyces phage-host interactions.
Optimizing the Dynamic Economic Dispatch Problem by the Distributed Consensus-Based ADMM Approach

This paper proposes a novel distributed approach to solve a new dynamic economic dispatch problem (DEDP) in which environmental cost function and ramp rate constraints are taken into consideration in islanded microgrid. In our proposed optimization model, the environmental cost function with E-exponential term and ramp rate constraints are considered to make the optimization problem more practical. Then a novel fully distributed algorithm is proposed to address the DEDP based on the alternating direction method of multipliers (ADMM) and distributed consensus theory of the multiagents system. A Lambert $W$ function is employed to tackle the E-exponential term in the environmental cost function, which is different from most existing papers which discuss the DEDP only with quadratic cost functions. A parallel projection method on account of ADMM is used to deal with the ramp rate constraints in this paper. In addition, the power balance can be guaranteed every time when the sum of initial powder output is equal to the total demand. Therefore, the proposed algorithm can deal with the supply-demand constraints, capacity limit constraints, and ramp rate constraints. Finally, simulations on IEEE14-bus are introduced to further illustrate the effectiveness of the proposed algorithm.
Polyamine-mediated sensitization of Klebsiella pneumoniae to macrolides through a dual mode of action

The chemical landscape bacteria encounter at the infection site could shape their stress and antibiotic responses; these altered responses are not typically detected in standard lab conditions. Polyamines are small molecules typically overproduced by the host during infection and have been shown to alter bacterial stress responses. We sought to determine the effect of polyamines on the antibiotic response of Klebsiella pneumoniae, a Gram-negative priority pathogen. Interestingly, putrescine and other natural polyamines sensitized K. pneumoniae, including pan-drug resistant and hypervirulent isolates, to azithromycin, a macrolide protein translation inhibitor typically used for Gram-positive bacteria. The synergy was further potentiated in the physiological buffer, bicarbonate. Chemical genomic screens suggested a dual mechanism whereby putrescine acts at the membrane and ribosome levels. Putrescine permeabilized both the outer and inner membranes of K. pneumoniae in fluorometric (NPN) and colorimetric (Ω-lactamase and Ω-galactosidase) assays. Further, mutants with chemically and genetically perturbed membranes exhibited a loss of putrescine-azithromycin synergy. Putrescine also inhibited protein synthesis in an Escherichia coli-derived cell-free protein expression assay simultaneously monitoring transcription and translation. Profiling the putrescine-azithromycin synergy against a combinatorial array of antibiotics targeting various ribosomal sites suggested that putrescine acts as tetracyclines targeting the 30S ribosomal acceptor site. Next, we exploited the natural polyamine-azithromycin synergy to uncover azithromycin adjuvants by screening a polyamine analog library. We discovered four azithromycin synergists with activity from the low micromolar range, sharing modes of action similar to putrescine. This work sheds light on the bacterial antibiotic responses under conditions more reflective of those at the infection site and provides a new strategy to extend the macrolide spectrum to drug-resistant K. pneumoniae.
Myxomycetes have an allorecognition system that can only discriminate between intraspecies

Myxomycetes are multinucleate unicellular organisms. They form a plasmodium that moves by protoplasmic flow and prey on microorganisms. When encountering intraspecifics, the plasmodium has the capacity for ‘fusion’, actively approaching and fusing its cells, or ‘avoidance’, altering its direction to avoid the other individual. This is an allorecognition ability. However, it remains unclear whether the range of allorecognition extends to other species, and its ecological significance is also obscure. Here, we conduct a quantitative evaluation of contact responses from closely related species of plasmodium to clarify the recognition range of the allorecognition system in Myxomycetes. Behavioral assays demonstrate that the allorecognition system recognizes individuals within the same species while failing to recognize those of different species. The allorecognition is an extremely narrow and inward-focused mechanism, arguing for a highly specialized system of self-other recognition. Summary statement Myxomycetes plasmodium can recognize each other only if the other individuals they encounter are of the same species.
Combining single-gene-resistant and pyramided cultivars in agricultural landscape compromises the benefits of pyramiding in most, but not all, productions situations

Context While resistant cultivars are valuable in safeguarding crops against diseases, they can be rapidly overcome by pathogens. Numerous strategies have been proposed to delay pathogen adaptation (evolutionary control), while still ensuring effective protection (epidemiological control). Resistance genes can be deployed in 1) single-gene-resistant cultivars sown in the same field (mixture strategy) or in different fields (mosaic strategy), 2) a pyramided cultivar (pyramiding strategy) or 3) hybrid strategies that combine the three previous strategies. In addition, the spatial scale at which resistant cultivars are deployed can affect the plant-pathogens interaction: small fields are thought to reduce pest density and disease transmission. Objectives We aim to compare these strategies, focusing on the effects of the simultaneous deployment of single-gene-resistant and pyramided cultivars sharing resistance genes in an agricultural landscape. We also investigate the impact of field size. Methods We used the spatially-explicit stochastic model landsepi to compare the evolutionary and epidemiological control across spatial scales and deployment strategies for two major resistance genes. Results The evolutionary control provided by the pyramiding strategy is at risk when single-gene-resistant cultivars are concurrently planted in the landscape (hybrid strategies). The probabilities of pathogen mutation and the corresponding fitness costs play a crucial role in determining the feasibility of planting pyramided cultivars alongside single-gene-resistant ones. Instead, field size did not affect strategies recommendation. Conclusions Planting pyramided cultivars alongside single-gene-resistant ones should be avoided. Socio-economic perspectives for the adoption of resistance management strategies are discussed.
Using structure prediction of negative sense RNA virus nucleoproteins to assess evolutionary relationships

Negative sense RNA viruses (NSV) include some of the most detrimental human pathogens, including the influenza, Ebola and measles viruses. NSV genomes consist of one or multiple single-stranded RNA molecules that are encapsidated into one or more ribonucleoprotein (RNP) complexes. Current evolutionary relationships within the NSV phylum are based on alignment of conserved RNA-dependent RNA polymerase (RdRp) domain amino acid sequences. However, the RdRp-based phylogeny does not address whether other core proteins in the NSV genome evolved along the same trajectory. Moreover, the current classification of NSVs does not consistently match the segmented and non-segmented nature of negative-sense virus genomes. Viruses belonging to e.g. the Serpentovirales have a segmented genome but are classified among the non-segmented negative-sense RNA viruses. We hypothesized that RNA genome segmentation is not coupled to the RdRp domain, but rather to the nucleocapsid protein (NP) that forms RNP complexes with the viral RNA. Because NP sequences are too short to infer robust phylogenetic relationships, we here used experimentally-obtained and AlphaFold 2.0-predicted NP structures to probe whether evolutionary relationships can be estimated using NSV NP sequences and potentially improve our understanding of the relationships between NSV subphyla and the NSV genome organization. Following flexible structure alignments of modeled structures, we find that the structural homology of the NSV NPs reveals phylogenetic clusters that are consistent with the currently accepted NSV taxonomy based on RdRp sequences with one key difference: the NPs of the segmented Serpentovirales cluster with the other segmented NSV. In addition, we were able to assign viruses for which RdRp sequences are currently missing to phylogenetic clusters. Overall, our results suggest that the NSV RdRp and NP genes largely evolved along similar trajectories, that NP-based clustering is better correlated with the NSV genome structure organization, and that even short pieces of genetic, protein-coding information can be used to infer evolutionary relationships, potentially making metagenomic analyses more valuable.
Sildenafil amplifies calcium influx and insulin secretion in pancreatic β cells

Sildenafil, a phosphodiesterase-5 (PDE5) inhibitor, has been shown to improve insulin sensitivity in animal models and prediabetic patients. However, its other metabolic effects remain poorly investigated. This study examines the impact of sildenafil on insulin secretion in MIN6-K8 mouse clonal β cells. Sildenafil is shown to amplify insulin secretion by enhancing Ca2+ influx, an effect that requires other depolarizing stimuli in MIN6-K8 cells but not in KATP channel-deficient β cells, which are already depolarized. These results indicate that the action of sildenafil is dependent on depolarization and is independent of KATP channels. Furthermore, sildenafil-amplified insulin secretion is not inhibited by nifedipine or PDE5 knockdown. Thus, sildenafil stimulates Ca2+ influx independently of L-type voltage-dependent Ca2+ channels (VDCCs) and PDE5, a mechanism that differs from the known pharmacology of sildenafil and conventional insulin secretory pathways. Our results reposition sildenafil as an insulinotropic agent that can be used as a potential anti-diabetic medicine or a tool to elucidate the molecular mechanism of insulin secretion.