Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Partial Monitoring: It is Always too Soon to Give Up

Runtime Verification is a lightweight formal verification technique. It is used to verify at runtime whether the system under analysis behaves as expected. The expected behaviour is usually formally specified by means of properties, which are used to automatically synthesise monitors. A monitor is a device that, given a sequence of events representing a system execution, returns a verdict symbolising the satisfaction or violation of the formal property. Properties that can (resp. cannot) be verified at runtime by a monitor are called monitorable and non-monitorable, respectively. In this paper, we revise the notion of monitorability from a practical perspective, where we show how non-monitorable properties can still be used to generate partial monitors, which can partially check the properties. Finally, we present the implications both from a theoretical and practical perspectives.
When Blockchain Meets Auction Models: A Survey, Some Applications, and Challenges

—In recent years, blockchain has gained widespread attention as an emerging technology for decentralization, trans-parency, and immutability in advancing online activities over public networks. As an essential market process, auctions have been well studied and applied in many business ﬁelds due to their efﬁciency and contributions to fair trade. Complementary features between blockchain and auction models trigger a great potential for research and innovation. On the one hand, the decentralized nature of blockchain can provide a trustworthy, secure, and cost-effective mechanism to manage the auction process; on the other hand, auction models can be utilized to design incentive and consensus protocols in blockchain architectures. These opportunities have attracted enormous research and innovation activities in both academia and industry; however, there is a lack of an in-depth review of existing solutions and achievements. In this paper, we conduct a comprehensive state-of-the-art survey of these two research topics. We review the existing solutions for integrating blockchain and auction models, with some application-oriented taxonomies generated. Additionally, we highlight some open research challenges and future directions towards integrated blockchain-auction models.
Microscopic mechanism for fluctuating pair density wave

In weakly coupled BCS superconductors, only electrons within a tiny energy window around the Fermi energy, EF, form Cooper pairs. This may not be the case in strong coupling superconductors such as cuprates, FeSe, SrTiO3 or cold atom condensates where the pairing scale, EB, becomes comparable or even larger than EF. In cuprates, for example, a plausible candidate for the pseudogap state at low doping is a fluctuating pair density wave, but no microscopic model has yet been found which supports such a state. In this work, we write an analytically solvable model to examine pairing phases in the strongly coupled regime and in the presence of anisotropic interactions. Already for moderate coupling we find an unusual finite temperature phase, below an instability temperature Ti, where local pair correlations have non-zero center-of-mass momentum but lack long-range order. At low temperature, this fluctuating pair density wave can condense either to a uniform d-wave super- conductor or the widely postulated pair-density wave phase depending on the interaction strength. Our minimal model offers a unified microscopic framework to understand the emergence of both fluctuating and long range pair density waves in realistic systems.
A Simple Baseline for Low-Budget Active Learning

Active learning focuses on choosing a subset of unlabeled data to be labeled. However, most such methods assume that a large subset of the data can be annotated. We are interested in low-budget active learning where only a small subset (e.g., 0.2% of ImageNet) can be annotated. Instead of proposing a new query strategy to iteratively sample batches of unlabeled data given an initial pool, we learn rich features by an off-the-shelf self-supervised learning method only once, and then study the effectiveness of different sampling strategies given a low labeling budget on a variety of datasets including ImageNet. We show that although the state-of-the-art active learning methods work well given a large labeling budget, a simple K-means clustering algorithm can outperform them on low budgets. We believe this method can be used as a simple baseline for low-budget active learning on image classification. Code is available at: https://github.com/UCDvision/low-budget-al
Doping evolution of superconductivity, charge order and band topology in hole-doped topological kagome superconductors Cs(V$_{1-x}$Ti$_x$)$_3$Sb$_5$

The newly discovered Kagome superconductors $A$V$_3$Sb$_5$ ($A$ = K, Rb, Cs) exhibit superconductivity, charge order, and band topology simultaneously. To explore the intricate interplay between the superconducting and charge orders, we investigate the doping evolution of superconductivity, charge-density-wave (CDW) order, and band topology in doped topological kagome superconductors Cs(V$_{1-x}$Ti$_x$)$_3$Sb$_5$ where the Ti-dopant introduces hole-like charge carriers. Despite the absence of the CDW phase transition in doped compounds even for the lowest doping level of $x=0.047$, the superconductivity survives in all doped samples with enhanced critical temperatures. The high-resolution angle-resolved photoemission spectroscopy (ARPES) measurements reveal that the Ti-dopant in the kagome plane lowers the chemical potential, pushing the van Hove singularity (VHS) at $M$ point above the Fermi level. First-principle simulations corroborate the doping evolution of the band structure observed in ARPES, and affirm that the CDW instability does not occur once the VHS is pushed above the Fermi level, explaining the absence of the CDW ordering in our doped samples Cs(V$_{1-x}$Ti$_x$)$_3$Sb$_5$. Our results demonstrate a competition between the CDW and superconducting orders in the kagome-metal superconductor CsV$_3$Sb$_5$, although the superconductivity is likely inconsequential of the CDW order.
PhotoWCT2: Compact Autoencoder for Photorealistic Style Transfer Resulting from Blockwise Training and Skip Connections of High-Frequency Residuals

Photorealistic style transfer is an image editing task with the goal to modify an image to match the style of another image while ensuring the result looks like a real photograph. A limitation of existing models is that they have many parameters, which in turn prevents their use for larger image resolutions and leads to slower run-times. We introduce two mechanisms that enable our design of a more compact model that we call PhotoWCT2, which preserves state-of-art stylization strength and photorealism. First, we introduce blockwise training to perform coarse-to-fine feature transformations that enable state-of-art stylization strength in a single autoencoder in place of the inefficient cascade of four autoencoders used in PhotoWCT. Second, we introduce skip connections of high-frequency residuals in order to preserve image quality when applying the sequential coarse-to-fine feature transformations. Our PhotoWCT2 model requires fewer parameters (e.g., 30.3% fewer) while supporting higher resolution images (e.g., 4K) and achieving faster stylization than existing models.
Adjusting for Unobserved Confounding Using Large-Scale Propensity Scores

Even though observational data contain an enormous number of covariates, the existence of unobserved confounders still cannot be excluded and remains a major barrier to drawing causal inference from observational data. A large-scale propensity score (LSPS) approach may adjust for unobserved confounders by including tens of thousands of available covariates that may be correlated with them. In this paper, we present conditions under which LSPS can remove bias due to unobserved confounders. In addition, we show that LSPS may avoid bias that can be induced when adjusting for various unwanted variables (e.g., M-structure colliders). We demonstrate the performance of LSPS on bias reduction using both simulations and real medical data.
Gravitational instabilities of uniform black strings in AdS space

Locally AdSd−1 × R uniform black strings (UBS) in the presence of a massless scalar field are believed to avoid the onset of the Gregory-Laflamme (GL) instability in d ≥ 4 as no tachyonic modes exist in the spectrum of the Laplace-Beltrami operator. We present analytic and numerical evidence of GL modes in the Lichnerowicz spectrum indicating that AdSd−1 UBSs are classically and thermodynamically unstable at the linear level in d > 4. In d = 4, we confirm that uniform BTZ3 strings are indeed stable as previously suggested. We propose that linear instabilities of black strings are triggered if and only if a tachyonic mode exists in the Lichnerowicz spectrum. At the end state of the instability, AdSd−1 UBSs of finite length may tunnel to a SAdSd black hole or converge onto a novel non-uniform AdSd black string. We conjecture that weak cosmic censorship is violated if the non-uniform solution is an exact AdSd black funnel and compute entropy estimates in d > 4 as evidence.
SoK: Securing Email -- A Stakeholder-Based Analysis (Extended Version)

While email is the most ubiquitous and interoperable form of online communication today, it was not conceived with strong security guarantees, and the ensuing security enhancements are, by contrast, lacking in both ubiquity and interoperability. This situation motivates our research. We begin by identifying a variety of stakeholders who have an interest in the current email system and in efforts to provide secure solutions. We then use the tussle among stakeholders to explain the evolution of fragmented secure email solutions undertaken by industry, academia, and independent developers. We also evaluate the building blocks of secure email -- cryptographic primitives, key management schemes, and system designs -- to identify their support for stakeholder properties. From our analysis, we conclude that a one-size-fits-all solution is unlikely. Furthermore, we highlight that vulnerable users are not well served by current solutions, account for the failure of PGP, and argue that secure messaging, while complementary, is not a fully substitutable technology.
Empathy is the Message

To communicate affectively you need to know the content of what you are communicating and, importantly, you need to know your audience. Social philosopher George Mead contended that the self emerges through social interaction and, through this, the ability to take the role of the other (see, Mead, 1934). Similarly, Harry Stack Sullivan’s theory of interpersonal processes posited that interpersonal relationships are critical to social development and the ability to understand and communicate with another, e.g., consensual validation (see, Sullivan, 1947). Importantly, Sullivan suggested that communication skills could be taught, including the ability to respond with empathy. Building on the pioneering theories of social interaction, the early work of Cottrell and Dymond brought attention to the lack of research on empathy. They emphasized the need to operationally define and systematically measure empathic responses with the goal of stimulating research in order to advance our understanding of empathy. Drymond (1949) developed a measure of empathetic ability, defined as, “. the imaginative transposing of oneself into the thinking, feeling and acting of another and so structuring the world as he does” (p. 127), and tested it empirically in college students. Differences in the ability to empathize suggested the need to better understand how empathy develops, and the importance of teaching people this essential interpersonal skill. Empathetic capacity derives from social psychology and neuroscience, enabling us to take the perspective of another (cognitive empathy) and feel what another feels (emotional empathy). We respond with empathy when mirror neurons are stimulated by observing the experiential responses of another through, for example, body language. We are more likely to respond with empathy if the other person is similar to oneself, experiences similar events or has similar goals (Riess, 2010). Responding with empathy can be a function of perceived personal risk (Galea, 2020), for example, a person might feel empathy for another’s loss because they can imagine that it could be their loss. The experience of, ‘it could have been me,’ in
The preoperative abundance of Prevotella associates with anastomotic healing after colorectal surgery.

Anastomotic leakage (AL) is a frequent and potentially life-threatening postoperative complication in patients undergoing colorectal surgery with a multifactorial yet unknown pathophysiology. In the present study, we aimed to unravel AL etiology and intestinal anastomotic healing (AH) physiology focusing on both host epithelial and gut microbial components. We make use of patients-related samples and two high throughput next generation sequencing analysis approaches, including anastomotic tissue-associated bulk RNA sequencing and preoperative fecal 16S rRNA gene sequencing. We find that in the absence of host epithelial gene expression differences, the preoperative fecal microbiota of patients who undergo colorectal resection with successful AH differs in the group of patients who develop AL in the abundance of Prevotella and suggests a potential beneficial role of Prevotella that may prove useful as predictive biomarker for AH.
Plasmonic interference modulation for broadband nanofocusing

Abstract Metallic plasmonic probes have been successfully applied in near-field imaging, nanolithography, and Raman enhanced spectroscopy because of their ability to squeeze light into nanoscale and provide significant electric field enhancement. Most of these probes rely on nanometric alignment of incident beam and resonant structures with limited spectral bandwidth. This paper proposes and experimentally demonstrates an asymmetric fiber tip for broadband interference nanofocusing within its full optical wavelengths (500–800 nm) at the nanotip with 10 nm apex. The asymmetric geometry consisting of two semicircular slits rotates plasmonic polarization and converts the linearly polarized plasmonic mode to the radially polarized plasmonic mode when the linearly polarized beam couples to the optical fiber. The three-dimensional plasmonic modulation induces circumference interference and nanofocus of surface plasmons, which is significantly different from the nanofocusing through plasmon propagation and plasmon evolution. The plasmonic interference modulation provides fundamental insights into the plasmon engineering and has important applications in plasmon nanophotonic technologies.
Attitudes of Young Consumers on the Security of their Data Collected By Smart Devices in the Age of the Internet of Things

Abstract The popularity of smart devices that collect and share data on user behaviour grows every year, and the number of such devices in households is forecast to rise steadily. Therefore, the purpose of this paper is to present the attitudes of young consumers regarding the security of their data collected by smart devices, interconnected via the existing Internet infrastructure or other network technologies within the Internet of Things (IoT) systems. The paper was written based on both secondary and primary sources of information. Secondary sources were used to define the discussed issues related to the Internet of Things and the security of data collected by smart devices. Primary sources, on the other hand, offered direct evidence of the attitudes of young consumers on the security of such data. Direct research was carried out using an online survey carried out in 2021 on a sample of 588 consumers aged 18–34 living in Poland. The results show that more than half of the respondents pay great attention to where the data collected by the devices used in their households is kept and whether such data is safe. In spite of such declarations, more than half of those surveyed have no knowledge about the level of the security of such data. The respondents agreed with the statement that consumers accepted the uncertainty related to the loss of control over their personal data collected by smart devices more quickly than the risk involved in becoming disconnected from them.
Hinge point emergence in mammalian spinal neurulation

Neurulation is the process in early vertebrate embryonic development during which the neural plate folds to form the neural tube. Spinal neural tube folding in the posterior neuropore changes over time, first showing a median hingepoint, then both the median hingepoint and dorsolateral hingepoints, followed by dorsolateral hingepoints only. The biomechanical mechanism of hingepoint formation in the mammalian neural tube is poorly understood. Here, we employ a mechanical finite element model to study neural tube formation. The computational model mimics the mammalian neural tube using microscopy data from mouse and human embryos. While intrinsic curvature at the neural plate midline has been hypothesized to drive neural tube folding, intrinsic curvature was not sufficient for tube closure in our simulations. We achieved neural tube closure with an alternative model combining mesoderm expansion, non-neural ectoderm expansion and neural plate adhesion to the notochord. Dorsolateral hingepoints emerged in simulations with low mesoderm expansion and zippering. We propose that zippering provides the biomechanical force for dorsolateral hingepoint formation in settings where the neural plate lateral sides extend above the mesoderm. Together, these results provide a new perspective on the biomechanical and molecular mechanism of mammalian spinal neurulation.
Habitat loss exacerbates pathogen spread: An Agent-based model of avian influenza infection in migratory waterfowl

Habitat availability determines the distribution of migratory waterfowl along their flyway, which further influences the transmission and spatial spread of avian influenza viruses (AIVs). The extensive habitat loss in the East Asian-Australasian Flyway (EAAF) may have potentially altered the virus spread and transmission, but those consequences are rarely studied. We constructed 6 fall migration networks that differed in their level of habitat loss, wherein an increase in habitat loss resulted in smaller networks with fewer sites and links. We integrated an agent-based model and a susceptible-infected-recovered model to simulate waterfowl migration and AIV transmission. We found that extensive habitat loss in the EAAF can 1) relocate the outbreaks northwards, responding to the distribution changes of wintering waterfowl geese, 2) increase the outbreak risk in remaining sites due to larger goose congregations, and 3) facilitate AIV transmission in the migratory population. In addition, our modeling output was in line with the predictions from the concept of “migratory escape”, i.e., the migration allows the geese to “escape” from the location where infection risk is high, affecting the pattern of infection prevalence in the waterfowl population. Our modeling shed light on the potential consequences of habitat loss in spreading and transmitting AIV at the flyway scale and suggested the driving mechanisms behind these effects, indicating the importance of conservation in changing spatial and temporal patterns of AIV outbreaks.
The organizer of chromatin topology RIF1 ensures cellular resilience to DNA replication stress

The conserved protein RIF1 stabilizes replication factories and regulates cohesin recruitment in response to replication stress to limit DNA lesions. Eukaryotic genomes are duplicated from thousands of replication origins that fire sequentially forming a defined spatiotemporal pattern of replication clusters. The temporal order of DNA replication is determined by chromatin architecture and, more specifically, by chromatin contacts that are stabilized by RIF1. Here, we show that RIF1 localizes near newly synthesized DNA. In cells exposed to the DNA replication inhibitor aphidicolin, suppression of RIF1 markedly decreased the efficacy of isolation of proteins on nascent DNA, suggesting that the isolation of proteins on nascent DNA procedure is biased by chromatin topology. RIF1 was required to limit the accumulation of DNA lesions induced by aphidicolin treatment and promoted the recruitment of cohesins in the vicinity of nascent DNA. Collectively, the data suggest that the stabilization of chromatin topology by RIF1 limits replication-associated genomic instability.
Whole-Genome Sequencing, Phylogenetic and Genomic Analysis of Lactiplantibacillus pentosus L33, a Potential Probiotic Strain Isolated From Fermented Sausages

Lactobacillus is a diverse genus that includes species of industrial and biomedical interest. Lactiplantibacillus pentosus, formerly known as Lactobacillus pentosus, is a recently reclassified species, that contains strains isolated from diverse environmental niches, ranging from fermented products to mammalian gut microbiota. Importantly, several L. pentosus strains present health-promoting properties, such as immunomodulatory and antiproliferative activities, and are regarded as potential probiotic strains. In this study, we present the draft genome sequence of the potential probiotic strain L. pentosus L33, originally isolated from fermented sausages. Comprehensive bioinformatic analysis and whole-genome annotation were performed to highlight the genetic loci involved in host-microbe interactions and the probiotic phenotype. Consequently, we found that this strain codes for bile salt hydrolases, adhesins and moonlighting proteins, and for Class IIb bacteriocin peptides lacking the GxxxG and GxxxG-like motifs, crucial for their inhibitory activity. Its adhesion ability was also validated in vitro, on human cancer cells. Furthermore, L. pentosus L33 contains an exopolysaccharide (EPS) biosynthesis cluster, and it does not carry transferable antibiotic resistance genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and CAZymes analyses showed that L. pentosus L33 possesses biosynthetic pathways for seven amino acids, while it can degrade a wide array of carbohydrates. In parallel, Clusters of Orthologous Groups (COGs) and KEGG profiles of L. pentosus L33 are similar to those of 26 L. pentosus strains, as well as of two well documented L. plantarum probiotic strains. Conclusively, L. pentosus L33 exhibits good probiotic potential, although further studies are needed to elucidate the extent of its biological properties.
Effects of Slaughter Age on Myosin Heavy Chain Isoforms, Muscle Fibers, Fatty Acids, and Meat Quality in Longissimus Thoracis Muscle of Tibetan Sheep

Tibetan sheep is one of the dominant livestock at Qinghai-Tibet Plateau, which is the main food source of local people. In order to investigate the effect of slaughter age on meat quality, fatty acid profile and expression of myosin heavy chain (MyHC) isoform genes were analyzed in Tibetan sheep. A total of 24 Tibetan sheep including 4 months old (4 m), 1.5 years old (1.5 y), 3.5 years old (3.5 y), and 6 years old (6 y) were randomly selected. The results indicated that the MyHC IIx and MyHC IIb mRNAs increased with age, whereas MyHC IIa mRNA decreased. MyHC I mRNA was highest at 3.5 y. There were differences in the muscle fiber types of Tibetan sheep at different ages. Intramuscular fat (IMF) was highest at 1.5 y, the pH45min and pH24h value of 6 y sheep were lower than the other groups, the shear force increased with age (p < 0.05), and drip loss increased with age (p < 0.01). Tibetan sheep at 1.5 y had lower saturated fatty acid (SFA) contents and higher monounsaturated fatty acid (MUFA) contents (p < 0.05). Different muscle fiber types influence the meat quality and fatty acid composition of Tibetan sheep with increasing age. These results demonstrated the effect of age on meat quality of Tibetan sheep through regulation of expression of the MyHC isoforms which changed the myofiber types, and 1.5 y Tibetan sheep meat was more suitable for a healthy human diet.