Miracle-dz/UniFAR-FTUs huggingface dataset:
Human–Computer Collaboration for Visual Analytics: an Agent‐based Framework

The visual analytics community has long aimed to understand users better and assist them in their analytic endeavors. As a result, numerous conceptual models of visual analytics aim to formalize common workflows, techniques, and goals leveraged by analysts. While many of the existing approaches are rich in detail, they each are specific to a particular aspect of the visual analytic process. Furthermore, with an ever‐expanding array of novel artificial intelligence techniques and advances in visual analytic settings, existing conceptual models may not provide enough expressivity to bridge the two fields. In this work, we propose an agent‐based conceptual model for the visual analytic process by drawing parallels from the artificial intelligence literature. We present three examples from the visual analytics literature as case studies and examine them in detail using our framework. Our simple yet robust framework unifies the visual analytic pipeline to enable researchers and practitioners to reason about scenarios that are becoming increasingly prominent in the field, namely mixed‐initiative, guided, and collaborative analysis. Furthermore, it will allow us to characterize analysts, visual analytic settings, and guidance from the lenses of human agents, environments, and artificial agents, respectively.
A direct derivation of the Gent–McWilliams/Redi diffusion tensor from quasi-geostrophic dynamics

Abstract The transport induced by ocean mesoscale eddies remains unresolved in most state-of-the-art climate models and needs to be parametrized instead. The natural scale separation between the forcing and the emergent turbulent flow calls for a diffusive parametrization, where the eddy-induced fluxes are related to the large-scale gradients by a diffusion tensor. The standard parametrization scheme in climate modelling consists in adopting the Gent–McWilliams/Redi (GM/R) form for the diffusion tensor, initially put forward based on physical intuition and educated guesses before being put on firm analytical footing using a thickness-weighted average (TWA). In the present contribution, we provide a direct derivation of this diffusion tensor from the quasi-geostrophic (QG) dynamics of a horizontally homogeneous three-dimensional patch of ocean hosting a large-scale vertically sheared zonal flow on the $\beta$ plane. The derivation hinges on the identification of a useful cross-invariant defined as the product of the buoyancy and QG potential vorticity fluctuations. While less general than the TWA approach, the present QG framework leads to rigorous constraints on the diffusion tensor. First, there is no diapycnal diffusivity arising in the QG GM/R tensor for low viscosity and small-scale diffusivities. The diffusion tensor then involves only two vertically dependent coefficients, namely the GM transport coefficient $K_{GM}(z)$ and the Redi diffusivity $K_R(z)$. Second, as identified already by previous authors, the vertical structures of the two coefficients are related by the so-called Taylor–Bretherton relation. Finally, while the two coefficients differ generically in the interior of the water column, we show that they are equal to one another near the surface and near the bottom of the domain for low-enough dissipative coefficients. We illustrate these findings by simulating numerically the QG dynamics of a horizontally homogeneous patch of ocean hosting a vertically sheared zonal current resembling the Antarctic Circumpolar Current.
Heterogeneous Integration of In-Memory Analog Computing Architectures with Tensor Processing Units

Tensor processing units (TPUs), specialized hardware accelerators for machine learning tasks, have shown significant performance improvements when executing convolutional layers in convolutional neural networks (CNNs). However, they struggle to maintain the same efficiency in fully connected (FC) layers, leading to suboptimal hardware utilization. In-memory analog computing (IMAC) architectures, on the other hand, have demonstrated notable speedup in executing FC layers. This paper introduces a novel, heterogeneous, mixed-signal, and mixed-precision architecture that integrates an IMAC unit with an edge TPU to enhance mobile CNN performance. To leverage the strengths of TPUs for convolutional layers and IMAC circuits for dense layers, we propose a unified learning algorithm that incorporates mixed-precision training techniques to mitigate potential accuracy drops when deploying models on the TPU-IMAC architecture. The simulations demonstrate that the TPU-IMAC configuration achieves up to 2.59× performance improvements, and 88% memory reductions compared to conventional TPU architectures for various CNN models while maintaining comparable accuracy. The TPU-IMAC architecture shows potential for various applications where energy efficiency and high performance are essential, such as edge computing and real-time processing in mobile devices. The unified training algorithm and the integration of IMAC and TPU architectures contribute to the potential impact of this research on the broader machine learning landscape.
Calibration-Independent Certification of a Quantum Frequency Converter

We report on a method to certify a unitary operation with the help of source and measurement apparatuses whose calibration throughout the certification process needs not be trusted. As in the device-independent paradigm our certification method relies on a Bell test, but it removes the need for high detection efficiencies by including the single additional assumption that non-detected events are independent of the measurement settings. The relevance of the proposed method is demonstrated experimentally with the certification of a quantum frequency converter. The experiment starts with the heralded creation of a maximally entangled two-qubit state between a single $^{40}$Ca$^+$ ion and a 854$\,$nm photon. Entanglement preserving frequency conversion to the telecom band is then realized with a non-linear waveguide embedded in a Sagnac interferometer. The resulting ion-telecom photon entangled state is characterized by means of a Bell-CHSH test from which the quality of the frequency conversion is quantified. We demonstrate the successful frequency conversion with an average certified fidelity of $\geq 84\,\%$ and an efficiency $\geq 3.1\times 10^{-6}$ at a confidence level of $99\,\%$. This ensures the suitability of the converter for integration in quantum networks from a trustful characterization procedure.
WASEF: Web Acceleration Solutions Evaluation Framework

The World Wide Web has become increasingly complex in recent years. This complexity severely affects users in the developing regions due to slow cellular data connectivity and usage of low-end smartphone devices. Existing solutions to simplify the Web are generally evaluated using several different metrics and settings, which hinders the comparison of these solutions against each other. Hence, it is difficult to select the appropriate solution for a specific context and use case. This paper presents Wasef, a framework that uses a comprehensive set of timing, saving, and quality metrics to evaluate and compare different web complexity solutions in a reproducible manner and under realistic settings. The framework integrates a set of existing state-of-the-art solutions and facilitates the addition of newer solutions down the line. Wasef first creates a cache of web pages by crawling both landing and internal ones. Each page in the cache is then passed through a web complexity solution to generate an optimized version of the page. Finally, each optimized version is evaluated in a consistent manner using a uniform environment and metrics. We demonstrate how the framework can be used to compare and contrast the performance characteristics of different web complexity solutions under realistic conditions. We also show that the accessibility to pages in developing regions can be significantly improved, by evaluating the top 100 global pages in the developed world against the top 100 pages in the lowest 50 developing countries. Results show a significant difference in terms of complexity and a potential benefit for our framework in improving web accessibility in these countries.
Two Warm Super-Earths Transiting the Nearby M Dwarf TOI-2095

We report the detection and validation of two planets orbiting TOI-2095 (TIC 235678745). The host star is a 3700 K M1V dwarf with a high proper motion. The star lies at a distance of 42 pc in a sparsely populated portion of the sky and is bright in the infrared (K = 9). With data from 24 sectors of observation during Cycles 2 and 4 of the Transiting Exoplanet Survey Satellite, TOI-2095 exhibits two sets of transits associated with super-Earth-sized planets. The planets have orbital periods of 17.7 days and 28.2 days and radii of 1.30 R ⊕ and 1.39 R ⊕, respectively. Archival data, preliminary follow-up observations, and vetting analyses support the planetary interpretation of the detected transit signals. The pair of planets have estimated equilibrium temperatures of approximately 400 K, with stellar insolations of 3.23 and 1.73 S ⊕, placing them in the Venus zone. The planets also lie in a radius regime signaling the transition between rock-dominated and volatile-rich compositions. They are thus prime targets for follow-up mass measurements to better understand the properties of warm, transition-radius planets. The relatively long orbital periods of these two planets provide crucial data that can help shed light on the processes that shape the composition of small planets orbiting M dwarfs.
Quantum Magic via Perfect Pauli Sampling of Matrix Product States

We introduce a novel breakthrough approach to evaluate the nonstabilizerness of an $N$-qubits Matrix Product State (MPS) with bond dimension $\chi$. In particular, we consider the recently introduced Stabilizer R\'enyi Entropies (SREs). We show that the exponentially hard evaluation of the SREs can be achieved by means of a simple perfect sampling of the many-body wave function over the Pauli string configurations. The sampling is achieved with a novel MPS technique, which enables to compute each sample in an efficient way with a computational cost $O(N\chi^3)$. We benchmark our method over randomly generated magic states, as well as in the ground-state of the quantum Ising chain. Exploiting the extremely favourable scaling, we easily have access to the non-equilibrium dynamics of the SREs after a quantum quench.
Image Compression Algorithm of SPIHT Based on Block-Tree

After analyzing the characteristics of images through wavelet transform,this paper proposes an improved SPIHT algorithm.Because the low-frequency coefficients hold 90% energy of image and they are very important for reconstructing the image,so they are not compressed and is transmitted directly.However the high-frequency coefficients are insignificant relatively,They arel not handled and transmitted.They will be appointed only during reconstructing the image.So,the quality of the image is improved and the compression rate is increased.Block-tree structure is proposed in this paper.The new algorithm demands less memory and its application area is expanded.
Attention Weighted Local Descriptors

Local features detection and description are widely used in many vision applications with high industrial and commercial demands. With large-scale applications, these tasks raise high expectations for both the accuracy and speed of local features. Most existing studies on local features learning focus on the local descriptions of individual keypoints, which neglect their relationships established from global spatial awareness. In this paper, we present AWDesc with a consistent attention mechanism (CoAM) that opens up the possibility for local descriptors to embrace image-level spatial awareness in both the training and matching stages. For local features detection, we adopt local features detection with feature pyramid to obtain more stable and accurate keypoints localization. For local features description, we provide two versions of AWDesc to cope with different accuracy and speed requirements. On the one hand, we introduce Context Augmentation to address the inherent locality of convolutional neural networks by injecting non-local context information, so that local descriptors can “look wider to describe better”. Specifically, well-designed Adaptive Global Context Augmented Module (AGCA) and Diverse Surrounding Context Augmented Module (DSCA) are proposed to construct robust local descriptors with context information from global to surrounding. On the other hand, we design an extremely lightweight backbone network coupled with the proposed special knowledge distillation strategy to achieve the best trade-off in accuracy and speed. What is more, we perform thorough experiments on image matching, homography estimation, visual localization, and 3D reconstruction tasks, and the results demonstrate that our method surpasses the current state-of-the-art local descriptors. Code is available at: https://github.com/vignywang/AWDesc.
COMPARING ANTIBIOTIC RESISTANCE IN FREE-RANGING VS. CAPTIVE AFRICAN WILD HERBIVORES

Abstract: Antimicrobial resistance (AMR) is a critical challenge of the 21st century for public and animal health. The role of host biodiversity and the environment in the evolution and transmission of resistant bacteria between populations and species, and specifically at the wildlife-livestock-human interface, needs to be further investigated. We evaluated the AMR of commensal Escherichia coli in three mammalian herbivore species—impala (Aepyceros melampus), greater kudu (Tragelaphus strepsiceros), and plains zebra (Equus quagga)—targeting populations living under two conditions: captivity (French zoos) and free ranging (natural and private parks in Zimbabwe). From 137 fecal samples from these three host species, 328 E. coli isolates were isolated. We measured the AMR of each isolate against eight antibiotics, and we assessed the presence of AMR genes and mobile genetic element class 1 integrons (int1). Isolates obtained from captive hosts had a higher probability of being resistant than those obtained from free-ranging hosts (odds ratio, 293.8; confidence interval, 10–94,000). This statistically higher proportion of AMR bacteria in zoos than in natural parks was especially observed for bacteria resistant to amoxicillin. The percentage of int1 detection was higher when isolates were obtained from captive hosts, particularly captive impalas. Ninety percent of bacterial isolates with genes involved in antibiotic resistance also had the int1 gene. The sul1, sul2, blaTEM, and stra genes were found in 14, 19, 0, and 31%, respectively, of E. coli with respective antibiotic resistance. Finally, plains zebra carried AMR significantly more often than the other species.
Molecular detection of

Glanders is a contagious disease of equids caused by the Gram-negative bacterium Burkholderia mallei. In Brazil, the disease is considered to be reemerging and has been expanding, with records of equids with positive serology in most of the federative units. However, there are few reports describing the genotypic detection of the agent. This study demonstrated the detection of B. mallei by species-specific PCR directly from tissues or from bacterial cultures, followed by amplicon sequencing in equids (equines, mules, and asinines) with positive serology for glanders in all five geographic regions of Brazil. The molecular evidence of B. mallei infection in serologically positive equids in this study expands the possibility of strain isolation and the conduction of epidemiological characterizations based on molecular information. The microbiological detection of B. mallei in cultures from nasal and palate swabs, even in equids without clinical manifestations, raises the possibility of environmental elimination of the agent.
Nonrandom X Chromosome Inactivation Detection

X chromosome inactivation patterns may be clinically useful in assessing tumor clonality, determining carrier status for certain X‐linked disorders, and evaluating the pathogenicity of a genetic variant identified in an X‐linked gene. The protocols in this article utilize the highly polymorphic trinucleotide repeat within the first exon of the human androgen receptor gene (AR) and the methylation‐sensitive restriction enzyme HpaII to distinguish between the maternal and paternal alleles and simultaneously determine their methylation status. The data obtained from these protocols can be used to calculate the ratio of inactivation between the two alleles that ultimately reflects whether a female has a random or nonrandom pattern of X chromosome inactivation. © 2023 Wiley Periodicals LLC.
Corrected and Republished from: “Isolation and Characterization of the First Freshwater Cyanophage Infecting Pseudanabaena”

This study presents the isolation of the very first freshwater cyanophage, PA-SR01, that infects Pseudanabaena, and fills an important knowledge gap on freshwater cyanophages as well as cyanophages infecting Pseudanabaena. ABSTRACT Cyanobacteria are the major primary producers in both freshwater and marine environments. However, the majority of freshwater cyanophages remain unknown due to the limited number of cyanophage isolates. In this study, we present a novel lytic freshwater cyanophage, PA-SR01, which was isolated from the Singapore Serangoon Reservoir. To our knowledge, this is the first isolate of a cyanophage that has been found to infect the cyanobacterium Pseudanabaena. PA-SR01 has a narrow host range, a short latent period, and is chloroform sensitive. PA-SR01 is a member of Siphoviridae with a long noncontractile tail. It is a double-stranded DNA virus with a 137,012-bp genome. Functional annotation for the predicted open reading frames (ORFs) of the PA-SR01 genome identified genes with putative functions related to DNA metabolism, structural proteins, lysis, host-derived metabolic genes, and DNA packaging. Out of 166 predicted ORFs, only 17 ORFs have homology with genes with known function. Phylogenetic analysis of the major capsid protein and terminase large subunit further suggests that phage PA-SR01 is evolutionary distinct from known cyanophages. Metagenomics sequence recruitment onto the PA-SR01 genome indicates that PA-SR01 represents a new evolutionary lineage of phage which shares considerable genetic similarities with phage sequences in aquatic environments and could play key ecological roles. IMPORTANCE This study presents the isolation of the very first freshwater cyanophage, PA-SR01, that infects Pseudanabaena, and fills an important knowledge gap on freshwater cyanophages as well as cyanophages infecting Pseudanabaena.
Familial aggregation of early‐onset cancers in early‐onset breast cancer families

The risk of early‐onset (EO) breast cancer is known to be increased in relatives of EO breast cancer patients, but less is known about the familial risk of other EO cancers. We assessed familial risks of EO cancers (aged ≤40 years) other than breast cancer in 54 753 relatives of 5562 women with EO breast cancer (probands) by using a population‐based cohort from Finland. Standardized incidence ratios (SIRs) and 95% confidence intervals (CI) were estimated by using gender‐, age‐ and period‐specific cancer incidences of the general population as reference. The risk of any cancer excluding breast cancer in first‐degree relatives was comparable to population cancer risk (SIR 0.99, 95% CI: 0.84‐1.16). Siblings' children of women with EO breast cancer were at an elevated risk of EO testicular and ovarian cancer (SIR = 1.74, 95% CI: 1.07‐2.69 and 2.69, 95% CI: 1.08‐5.53, respectively). The risk of EO pancreatic cancer was elevated in siblings of the probands (7.61, 95% CI: 1.57‐22.23) and an increased risk of any other cancer than breast cancer was observed in children of the probands (1.27, 95% CI: 1.03‐1.55). In conclusion, relatives of women with EO breast cancer are at higher familial risk of certain discordant EO cancers, with the risk extending beyond first‐degree relatives.
Do statins decrease vascular inflammation in patients at risk for large-vessel vasculitis? A retrospective observational study with FDG-PET/CT in polymyalgia rheumatica, giant cell arteritis and fever of unknown origin.

OBJECTIVES [18F] Fluorodeoxyglucose (FDG) positron emission tomography/computed tomography (PET/CT) can detect the presence of large-vessel vasculitis (LVV) in patients with polymyalgia rheumatica (PMR), giant cell arteritis (GCA) and fever of unknown origin (FUO). The aim of this study was to evaluate whether statins could reduce FDG-PET/CT-assessed vascular inflammation in this group of patients. METHODS Clinical, demographic, laboratory data, current pharmacological treatments, and cardiovascular risk factors of patients with PMR, GCA and FUO, who underwent FDG-PET/CT, were recorded. FDG uptake was measured at prespecified arterial sites with the mean standardised uptake value (SUV), and with a qualitative visual score, summed up to obtain a total vascular score (TVS). LVV was diagnosed if arterial FDG visual uptake was equal or higher of liver uptake. RESULTS 129 patients were included (96 with PMR, 16 with GCA, 13 with both PMR and GCA, and 4 with FUO), of whom 75 (58.1%) showed LVV. Twenty out of 129 (15.5%) patients were taking statins. TVS was significantly lower in patients treated with statins (p=0.02), especially in the aorta (p=0.023) and femoral arteries (p=0.027). CONCLUSIONS Our preliminary results suggest that statins may exert a potential protective role on vascular inflammation in patients with PMR and GCA. Statin use could spuriously decrease FDG uptake of the vessel walls.