Miracle-dz/UniFAR-FTUs huggingface dataset:
Temporal Adaptive RGBT Tracking with Modality Prompt

RGBT tracking has been widely used in various fields such as robotics, surveillance processing, and autonomous driving. Existing RGBT trackers fully explore the spatial information between the template and the search region and locate the target based on the appearance matching results. However, these RGBT trackers have very limited exploitation of temporal information, either ignoring temporal information or exploiting it through online sampling and training. The former struggles to cope with the object state changes, while the latter neglects the correlation between spatial and temporal information. To alleviate these limitations, we propose a novel Temporal Adaptive RGBT Tracking framework, named as TATrack. TATrack has a spatio-temporal two-stream structure and captures temporal information by an online updated template, where the two-stream structure refers to the multi-modal feature extraction and cross-modal interaction for the initial template and the online update template respectively. TATrack contributes to comprehensively exploit spatio-temporal information and multi-modal information for target localization. In addition, we design a spatio-temporal interaction (STI) mechanism that bridges two branches and enables cross-modal interaction to span longer time scales. Extensive experiments on three popular RGBT tracking benchmarks show that our method achieves state-of-the-art performance, while running at real-time speed.
Vietnamese Poem Generation & The Prospect Of Cross-Language Poem-To-Poem Translation

Poetry generation has been a challenging task in the field of Natural Language Processing, as it requires the model to understand the nuances of language, sentiment, and style. In this paper, we propose using Large Language Models to generate Vietnamese poems of various genres from natural language prompts, thereby facilitating an intuitive process with enhanced content control. Our most efficacious model, the GPT-3 Babbage variant, achieves a custom evaluation score of 0.8, specifically tailored to the"luc bat"genre of Vietnamese poetry. Furthermore, we also explore the idea of paraphrasing poems into normal text prompts and yield a relatively high score of 0.781 in the"luc bat"genre. This experiment presents the potential for cross-Language poem-to-poem translation with translated poems as the inputs while concurrently maintaining complete control over the generated content.
A Survey of Computation Offloading with Task Type

Computation task offloading is one of the enabling technologies for computation-intensive applications and edge intelligence, which experiences the explosive growth of massive data generated. Different techniques, wireless technologies and mechanisms have been proposed in the literature for task offloading in order to improve the services provided to the users. Although there is a rich literature of computation task offloading, the role of data in the scope of it has not received much attention yet. This motivates us to propose a survey which classified the state-of-the-art (SoTA) of computation task offloading from the view point of data. First, a thorough literature review is conducted to reveal the SoTA from various aspects with the consideration of task generation, i.e., architecture, objective, offloading strategy, task types, etc. It is found that types of task offloading is related to the data and will affect the offloading procedure, which contains resource allocation, task allocation etc. Then computation offloading is classified into two categories based on task types, namely static task based offloading and dynamic task based offloading. Finally, our views on future computation offloading are provided with the corresponding challenges and opportunities.
Monogamy and tradeoff relations for wave-particle duality information

The notions of predictability and visibility are essential in the mathematical formulation of wave particle duality. The work of Jakob and Bergou [Phys. Rev. A 76, 052107] generalises these notions for higher-dimensional quantum systems, which were initially defined for qubits, and subsequently proves a complementarity relation between predictability and visibility. By defining the single-party information content of a quantum system as the addition of predictability and visibility, and assuming that entanglement in a bipartite system in the form of concurrence mutually excludes the single-party information, the authors have proposed a complementarity relation between the concurrence and the single-party information content. We show that the information content of a quantum system defined by Jakob and Bergou is nothing but the Hilbert-Schmidt distance between the state of the quantum system of our consideration and the maximally mixed state. Motivated by the fact that the trace distance is a good measure of distance as compared to the Hilbert-Schmidt distance from the information theoretic point of view, we, in this work, define the information content of a quantum system as the trace distance between the quantum state and the maximally mixed state. We then employ the quantum Pinsker's inequality and the reverse Pinsker's inequality to derive a new complementarity and a reverse complementarity relation between the single-party information content and the entanglement present in a bipartite quantum system in a pure state. As a consequence of our findings, we show that for a bipartite system in a pure state, its entanglement and the predictabilities and visibilities associated with the subsystems cannot be arbitrarily small as well as arbitrarily large.
Teach Large Language Models to Forget Privacy

Large Language Models (LLMs) have proven powerful, but the risk of privacy leakage remains a significant concern. Traditional privacy-preserving methods, such as Differential Privacy and Homomorphic Encryption, are inadequate for black-box API-only settings, demanding either model transparency or heavy computational resources. We propose Prompt2Forget (P2F), the first framework designed to tackle the LLM local privacy challenge by teaching LLM to forget. The method involves decomposing full questions into smaller segments, generating fabricated answers, and obfuscating the model's memory of the original input. A benchmark dataset was crafted with questions containing privacy-sensitive information from diverse fields. P2F achieves zero-shot generalization, allowing adaptability across a wide range of use cases without manual adjustments. Experimental results indicate P2F's robust capability to obfuscate LLM's memory, attaining a forgetfulness score of around 90\% without any utility loss. This represents an enhancement of up to 63\% when contrasted with the naive direct instruction technique, highlighting P2F's efficacy in mitigating memory retention of sensitive information within LLMs. Our findings establish the first benchmark in the novel field of the LLM forgetting task, representing a meaningful advancement in privacy preservation in the emerging LLM domain.
Partial Wave Analysis of $J/\psi\rightarrow \gamma \gamma \phi$

Using a sample of $(10087\pm44)\times10^{6}$ $J/\psi$ events collected with the BESIII detector at the BEPCII collider, a partial wave analysis on the decay $\gamma\gamma\phi$ is performed to investigate the intermediate resonances in $J/\psi\rightarrow\gamma X, X\rightarrow\gamma\phi$. The resonances $f_{1}(1285)$, $\eta(1405)$, $f_{1}(1420)$, $f_{1}(1510)$, $f_{2}(1525)$, $X(1835)$, $f_{2}(1950)$, $f_{2}(2010)$, $f_{0}(2200)$ and $\eta_{c}$ are observed with statistical significance greater than 5$\sigma$. The product branching fractions $\mathcal{B}(J/\psi\rightarrow\gamma X, X\rightarrow \gamma \phi)$ are reported. The resonance parameters of $\eta(1405)$ and $X(1835)$ are also measured.
MOC-RVQ: Multilevel Codebook-assisted Digital Generative Semantic Communication

Vector quantization-based image semantic communication systems have successfully boosted transmission efficiency, but face a challenge with conflicting requirements between codebook design and digital constellation modulation. Traditional codebooks need a wide index range, while modulation favors few discrete states. To address this, we propose a multilevel generative semantic communication system with a two-stage training framework. In the first stage, we train a high-quality codebook, using a multi-head octonary codebook (MOC) to compress the index range. We also integrate a residual vector quantization (RVQ) mechanism for effective multilevel communication. In the second stage, a noise reduction block (NRB) based on Swin Transformer is introduced, coupled with the multilevel codebook from the first stage, serving as a high-quality semantic knowledge base (SKB) for generative feature restoration. Experimental results highlight MOC-RVQ's superior performance over methods like BPG or JPEG, even without channel error correction coding.
KCES: A Workflow Containerization Scheduling Scheme Under Cloud-Edge Collaboration Framework

As more IoT applications gradually move towards the cloud-edge collaborative mode, the containerized scheduling of workflows extends from the cloud to the edge. However, given the high delay of the communication network, loose coupling of structure, and resource heterogeneity between cloud and edge, workflow containerization scheduling in the cloud-edge scenarios faces the difficulty of resource coordination and application collaboration management. To address these two issues, we propose a KubeEdge-Cloud-Edge-Scheduling scheme named KCES, a workflow containerization scheduling scheme for the KubeEdge cloud-edge framework. The KCES includes a cloud-edge workflow scheduling engine for KubeEdge and workflow scheduling strategies for task horizontal roaming and vertical offloading. Considering the scheduling optimization of cloud-edge workflows, this paper proposes a cloud-edge workflow scheduling model and cloud-edge node model and designs a cloud-edge workflow scheduling engine to maximize cloud-edge resource utilization under the constraint of workflow task delay. A cloud-edge resource hybrid management technology is used to design the cloud-edge resource evaluation and resource allocation algorithms to achieve cloud-edge resource collaboration. Based on the ideas of distributed functional roles and the hierarchical division of computing power, the horizontal roaming among the edges and vertical offloading strategies between the cloud and edges for workflow tasks are designed to realize the cloud-edge application collaboration. Through a customized IoT application workflow instance, experimental results show that KCES is superior to the baseline in total workflow duration, average workflow duration, and resource usage and has the capabilities of horizontal roaming and vertical offloading for workflow tasks.
Almost Perfect Shadow Prices

Shadow prices simplify the derivation of optimal trading strategies in markets with transaction costs by transferring optimization into a more tractable, frictionless market. This paper establishes that a naïve shadow price ansatz for maximizing long-term returns, given average volatility yields a strategy that is, for small bid–ask spreads, asymptotically optimal at the third order. Considering the second-order impact of transaction costs, such a strategy is essentially optimal. However, for risk aversion different from one, we devise alternative strategies that outperform the shadow market at the fourth order. Finally, it is shown that the risk-neutral objective rules out the existence of shadow prices.
PTE: Axiomatic Semantics based Compiler Testing

The correctness of a compiler affects the correctness of every program written in the language, and thus must be thoroughly evaluated. Existing automatic compiler testing methods however either rely on weak oracles (e.g., a program behaves the same if only dead code is modified), or require substantial initial effort (e.g., having a complete operational language semantics). While the former prevents a comprehensive correctness evaluation, the latter makes those methods irrelevant in practice. In this work, we propose an axiomatic semantics based approach for testing compilers, called PTE. The idea is to incrementally develop a set of ``axioms'' capturing anecdotes of the language semantics in the form of \emph{(\textbf{p}recondition, \textbf{t}ransformation, \textbf{e}xpectation) triples, which allows us to test the compiler automatically. } Such axioms are written in the same language whose compiler is under test, and can be developed either based on the language specification, or by generalizing the bug reports. PTE has been applied to a newly developed compiler (i.e., Cangjie) and a mature compiler (i.e., Java), and successfully identified 42 implementation bugs and 9 potential language design issues.
On the area swept by a biased diffusion till its first-exit time: Martingale approach and gambling opportunities

Using martingale theory, we compute, in very few lines, exact analytical expressions for various first-exit-time statistics associated with one-dimensional biased diffusion. Examples include the distribution for the first-exit time from an interval, moments for the first-exit site, and functionals of the position, which involve memory and time integration. As a key example, we compute analytically the mean area swept by a biased diffusion until it escapes an interval that may be asymmetric and have arbitrary length. The mean area allows us to derive the hitherto unexplored cross-correlation function between the first-exit time and the first-exit site, which vanishes only for exit problems from symmetric intervals. As a colophon, we explore connections of our results with gambling, showing that betting on the time-integrated value of a losing game it is possible to design a strategy that leads to a net average win.
Opening A Pandora's Box: Things You Should Know in the Era of Custom GPTs

The emergence of large language models (LLMs) has significantly accelerated the development of a wide range of applications across various fields. There is a growing trend in the construction of specialized platforms based on LLMs, such as the newly introduced custom GPTs by OpenAI. While custom GPTs provide various functionalities like web browsing and code execution, they also introduce significant security threats. In this paper, we conduct a comprehensive analysis of the security and privacy issues arising from the custom GPT platform. Our systematic examination categorizes potential attack scenarios into three threat models based on the role of the malicious actor, and identifies critical data exchange channels in custom GPTs. Utilizing the STRIDE threat modeling framework, we identify 26 potential attack vectors, with 19 being partially or fully validated in real-world settings. Our findings emphasize the urgent need for robust security and privacy measures in the custom GPT ecosystem, especially in light of the forthcoming launch of the official GPT store by OpenAI.
Selection for evasive mimicry imposed by an arthropod predator

It has long been hypothesized that a species that is relatively easy to catch by predators may face selection to resemble a species that is harder to catch. Several experiments using avian predators have since supported this ‘evasive mimicry’ hypothesis. However, the sudden movement of artificial evasive prey in each of the above experiments may have startled the predators, generating an avoidance response unrelated to difficulty of capture. Additionally in the above experiments the catchability of prey was all or nothing, while in nature predators may occasionally catch evasive prey or fail to catch slower species, which might inhibit learning. Here, using mantids as predators, we conducted an experimental test of the evasive mimicry hypothesis that circumvents these limitations, using live painted calyptrate flies with modified evasive capabilities as prey. We found that mantids readily learned to avoid pursuing the more evasive prey types. Warning signals based on evasiveness and their associated mimicry may be widespread phenomena in nature. These findings not only further support its plausibility but demonstrate that even arthropod predators can select for it.
Vertebral morphology in the tail-whipping common thresher shark, Alopias vulpinus

Thresher sharks (Alopias spp.) are characterized by an elongated, scythe-like caudal fin that is used in tail-whipping, a behaviour where the tail is thrown overhead to stun prey. Tail-whipping is performed via extreme dorsoventral bending of the vertebral column, and is dramatically different from lateral oscillatory motion used for swimming. Previous work has examined thresher shark vertebral morphology and mechanical properties, but in the context of swimming loads. Our goal was to assess centra morphometrics and microarchitecture for variations that may support extreme dorsoventral bending. We examined anterior and posterior body vertebrae from an embryo, five juvenile, and four adult thresher sharks using micro-computed tomography. We used principal component and landmark analyses to examine variables influencing vertebral morphology and mineral arrangement, respectively. We found that morphology and microstructure significantly varied across body regions and ontogeny. We hypothesize that anterior body vertebrae increase stability, while posterior body vertebrae support the caudal fin. Vertebral size and quantity of mineral structures (lamellae and nodes) increased across ontogeny, suggesting vertebrae adapt over development to support a larger body and tail. Based on our results, we hypothesize that thresher shark vertebrae vary in morphometrics and mineralization (amount and arrangement) supporting the mechanical needs for tail-whipping.
Mosquito ageing modulates the development, virulence and transmission potential of pathogens

Host age variation is a striking source of heterogeneity that can shape the evolution and transmission dynamic of pathogens. Compared with vertebrate systems, our understanding of the impact of host age on invertebrate–pathogen interactions remains limited. We examined the influence of mosquito age on key life-history traits driving human malaria transmission. Females of Anopheles coluzzii, a major malaria vector, belonging to three age classes (4-, 8- and 12-day-old), were experimentally infected with Plasmodium falciparum field isolates. Our findings revealed reduced competence in 12-day-old mosquitoes, characterized by lower oocyst/sporozoite rates and intensities compared with younger mosquitoes. Despite shorter median longevities in older age classes, infected 12-day-old mosquitoes exhibited improved survival, suggesting that the infection might act as a fountain of youth for older mosquitoes specifically. The timing of sporozoite appearance in the salivary glands remained consistent across mosquito age classes, with an extrinsic incubation period of approximately 13 days. Integrating these results into an epidemiological model revealed a lower vectorial capacity for older mosquitoes compared with younger ones, albeit still substantial owing to extended longevity in the presence of infection. Considering age heterogeneity provides valuable insights for ecological and epidemiological studies, informing targeted control strategies to mitigate pathogen transmission.
Towards a practical trap for deer flies (Diptera: Tabanidae): initial tests of a bi-level Nzi trap

Abstract A modified Nzi trap was tested at a residence and at a farm in eastern Ontario, Canada to better capture high-flying tabanids (Diptera) such as Chrysops Meigen. A new upper trap entrance was created to provide a higher and larger opening by reducing the front blue top shelf to half its height. To minimise escape of low-flying tabanids, a vertical inner baffle was added to direct low-flying tabanids up into the cone. Half of the tests of 18 new designs caught 1.5–2.7 times more deer flies than the Nzi trap did, with the other trap designs being as effective as the Nzi trap. The optimal design that maintained equal catches of other biting flies relative to the Nzi trap was one with a phthalogen inner horizontal shelf and a netting inner vertical baffle. This design is defined in the present as the “bi-level Nzi trap. ” Chrysops entered the trap mostly through the top (88%; 17 spp.), along with Hybomitra Enderlein (94%; 12 spp.). Tabanus Linnaeus (9 spp.) entered through both entrances. The most abundant Tabanus, T. quinquevittatus Wiedemann, entered mostly through the bottom (70%), whereas Stomoxys calcitrans Linnaeus entered mostly through the top (92%).
Optical Flow Estimation Based on Curvelet Transform and Spatio-temporal Derivatives

Optical flow estimation is still one of the key problems in computer vision. When estimating the displacement field between two images, it is applied as soon as correspondenc es between pixels are needed. The choice of the transform is an important tool in optical flow estimation. So in this paper curvelet transform is proposed to estimate the optical flow. it is found that the proposed algorithm is much better than most recently previous work based on multiwavelet. This is because curvelet transform can be efficient in finding estimates along curves.
Using Program Comprehension Models to Teach Comprehensibility

There is general agreement that code should be written to be as comprehensible as possible, and therefore should be an important topic when teaching software development. The challenge faced by educators is that the advice as to what makes code comprehensible is often too general to be useful in a teaching setting, or seems to be inconsistent. In this practitioner paper, we discuss our experience in addressing these issues through the novel use of program comprehension models (PCM). We found our use of PCMs helped us to provide better explanations as to what some advice means or why it seems inconsistent, and provided a tool to students to help them make decisions that leads to their code being more comprehensible.
Auditory training alters the cortical representation of both learned and task irrelevant sound features

Auditory learning is supported by long-term changes in the neural processing of sound. We mapped neural sensitivity to timbre, pitch and location in animals trained to discriminate the identity of artificial vowels based on their spectral timbre in a two-alternative forced choice (T2AFC, n=3, female ferrets) or to detect changes in fundamental frequency or timbre of repeating artificial vowels in a go/no-go task (n=2 female ferrets). Neural responses were recorded under anaesthesia in two primary cortical fields and two tonotopically organised non-primary fields. Responses were compared these data to that of naïve control animals. We observed that in both groups of trained animals the overall sensitivity to sound timbre was reduced across three cortical fields but enhanced in non-primary field PSF. Neural responses in trained animals were able to discriminate vowels that differed in either their first or second formant frequency unlike control animals whose sensitivity was mostly driven by changes in the second formant. Neural responses in the T2AFC animals, who were required to generalise across pitch when discriminating timbre, became less modulated by fundamental frequency, while those in the go/no-go animals were unchanged relative to controls. Finally, both trained groups showed increased spatial sensitivity and altered tuning. Trained animals showed an enhanced representation of the midline, where the speaker was located in the experimental chamber. Overall, these results demonstrate training elicited widespread changes in the way in which auditory cortical neurons represent complex sounds with changes in how both task relevant and task-irrelevant features were represented.