Search Results (1,019)

The compiler serves as a bridge connecting hardware architecture and application software, converting source code into executable files and optimizing code. Fuzz testing is an automated testing technology that evaluates software reliability by providing a large amount of random or mutated input data to the target system to trigger abnormal program behavior. When existing fuzz testing methods are applied to compiler testing, although they can detect common errors like lexical and syntax errors, there are issues such as insufficient pertinence in constructing the input corpus, limited support for structured Intermediate Representation (IR) node manipulation, and limited perfection of the mutation strategy. This study proposes a deep fuzz testing framework named BoostPolyGlot for GCC compiler frontend IR generation, which effectively covers the code-execution paths and improves the code-coverage rate through constructing an input corpus, employing translation by a master–slave IR translator, conducting operations on structured program characteristic IR nodes, and implementing an IR mutation strategy with dynamic weight adjustment. This study evaluates the fuzz testing capabilities of BoostPolyGlot based on dependency relationships, loop structures, and their synergistic effect. The experimental outcomes confirm that, when measured against five crucial performance indicators including total paths, count coverage, favored paths rate, new edges on rate, and level, BoostPolyGlot demonstrated statistically significant improvements compared with American Fuzzy Lop (AFL) and PolyGlot. These findings validate the effectiveness and practicality of the proposed framework. Full article

Task scheduling for multiple humanoid robot manipulators in industrial and collaborative settings remains a significant challenge due to the complexity of coordination, resource sharing, and real-time decision-making. In this study, we propose a framework for modeling task scheduling for multiple humanoid robot manipulators by using the symbolic discrete controller synthesis technique. We encode the task scheduling problem as discrete events using parallel synchronous dataflow equations and apply our synthesis algorithms to manage the task scheduling of multiple humanoid robots via the resulting controller. The control objectives encompass the fundamental behaviors of the system, strict rules, and mutual exclusions over shared resources, categorized as the safety property, whereas the optimization objectives are directed toward maximizing the throughput of robot-processed products with optimal efficiency. The humanoid robots considered in this study consist of two pairs of six-degree-of-freedom (6-DOF) robot manipulators, and the inverse kinematics problem of the 6-DOF arms is addressed using metaheuristic approaches inspired by biomimetic principles. Our approach is experimentally validated, and the results demonstrate high accuracy and performance compared to other approaches reported in the literature. Our approach achieved an average efficiency improvement of 40% in 70-robot systems, 20% in 30-robot systems, and 10% in 10-robot systems in terms of production throughput compared to systems without a controller. Full article

Ice accumulation on cold surfaces presents significant operational and safety challenges in various fields such as power transmission, aviation, and polar marine transportation. This study investigates the effectiveness of selectively applied superhydrophobic patterns on hydrophilic substrates to locally control freezing behaviors. The freezing dynamics of water droplets impacting surfaces with hybrid wettability patterns were investigated experimentally under cold conditions. The results demonstrate that superhydrophobic surfaces significantly reduce the freezing rate due to decreased contact time and the contact region. By selectively placing superhydrophobic patterns on hydrophilic surfaces, the location of ice formation could be effectively manipulated. The use of multiple superhydrophobic stripes was found to segment the impacting droplets into several parts, implying the ability to selectively avoid ice accumulation at specific areas. Furthermore, experiments identified critical temperature thresholds at which the effectiveness of superhydrophobic stripes diminishes. When the temperature of the substrate is higher than −25 °C, the superhydrophobic stripes can sufficiently divide an impacting droplet leaving no ice at the superhydrophobic region. In the tested temperature range between −25 °C and −40 °C, the ice coverage ratio at the superhydrophobic region increases as temperature decreases, with a maximum value of 25.6 ± 2.33% at −40 °C. Superhydrophobic patterns also exhibited improved deicing efficiency during melting processes, highlighting their potential for robust ice management applications. Full article

This study examines the relevance of the Fraud Pentagon Theory in detecting fraudulent financial reporting among companies listed on the Bucharest Stock Exchange. While financial reporting is essential for informed stakeholder decisions, requiring information to be accurate, reliable, and fairly presented and pressure to meet expectations can lead to manipulation. The Fraud Pentagon Theory identifies five potential drivers of such behavior: pressure, opportunity, rationalization, capability, and arrogance. This research contributes to the literature by empirically testing the theory in the Romanian context, an emerging market with limited prior analysis, using a sample of 62 listed companies over the 2017–2021 period. Regression analysis was applied, using the Dechow F-score, which combines accrual quality and financial performance to assess the likelihood of fraudulent financial reporting. The findings reveal that not all dimensions of the theory significantly affect the likelihood of fraudulent reporting. Specifically, pressure-related factors (financial performance and financial stability) were found to be statistically significant, while external pressure, opportunity (external auditor quality and nature of industry), rationalization (change of auditor), capability (change of director), and arrogance (number of CEO’s pictures) did not show significant influence in the Romanian framework. These results highlight the importance of contextual factors such as market structure, governance practices, and stakeholder expectations, suggesting that fraudulent reporting risk indicators may vary across different economic environments. Full article

Objectives: With the advancement of modern society, people in cognitively demanding jobs are increasingly exposed to occupational stress. Prolonged and high-intensity cognitive activities are prone to inducing mental fatigue (MF), which adversely affects both psychological and physiological well-being, as well as task performance. Existing methods for inducing MF often demonstrate limited effectiveness due to insufficient cognitive load from overly simplistic tasks and the potential emotional disturbance caused by prolonged task duration. This study aims to explore a comprehensive cognitive task paradigm that integrates task complexity and time pressure, thereby developing a novel and effective method for inducing MF based on high mental workload (HMW) and the effects of time on task (ToT). Methods: Using convenience sampling, university students from a medical college were recruited as participants. The study was conducted in three steps. In the first step, we constructed a 1-back Stroop (BS) task paradigm by designing tasks with varying levels of complexity and incorporating time pressure through experimental manipulation. In the second step, the efficacy of the BS task paradigm was validated by comparing it with the traditional 2-back cognitive task in inducing HMW. In the third step, an MF induction protocol was established by combining the BS task paradigm with the ToT effect (i.e., a continuous 30 min task). Effectiveness was assessed using validated subjective measures (NASA Task Load Index [NASA-TLX] and Visual Analog Scale [VAS]) and objective behavioral metrics (reaction time and accuracy). Statistical analyses were performed using analysis of variance (ANOVA) and t-tests. Results: The BS task paradigm, which integrates complex cognitive abilities such as attention, working memory, inhibitory control, cognitive flexibility, and time pressure, demonstrated significantly higher NASA-TLX total scores, as well as elevated scores in mental demand, temporal demand, performance, and frustration scales, compared to the 2-back task. Additionally, the BS task paradigm resulted in longer reaction times and lower accuracy. As the BS task progressed, participants exhibited significant increases in mental fatigue (MF), mental effort (ME), mental stress (MS), and subjective feelings of fatigue, while the overall number of correct trials and accuracy showed a significant decline. Furthermore, reaction times in the psychomotor vigilance test (PVT) were significantly prolonged, and the number of lapses significantly increased between pre- and post-task assessments. Conclusions: The BS task paradigm based on complex cognitive abilities and time pressure could effectively induce an HMW state. Combined with the ToT effect, the BS paradigm demonstrated effective MF induction capabilities. This study provides a novel and reliable method for inducing HMW and MF, offering a valuable tool for future research in related fields. Full article

Ectotherms can elevate their body temperature in response to infection by seeking warmer environments, a phenomenon known as behavioral fever. This adaptive response, widely documented in fish, activates immune defenses and improves survival. To explore an eco-friendly approach for managing Vibrio-induced enteritis in lined seahorse (Hippocampus erectus) aquaculture, we investigated whether Vibrio harveyi infection triggers behavioral fever and enhances immune function. Seahorses were intraperitoneally injected with V. harveyi (1 × 10⁷ cfu/fish) and placed in a thermal gradient tank (19–31 °C), allowing free movement between chambers. Challenged seahorses exhibited a significant preference (p < 0.05, 1.31-fold) for warmer zones compared to unchallenged controls, whereas no such difference (p > 0.05) was observed in a constant temperature (25 °C) tank, confirming behavioral fever. Furthermore, fevered seahorses showed significantly elevated plasma cytokine levels (PGE2, IL-1β, IL-6, and TNF-α; p < 0.05), which normalized (p > 0.05) to baseline levels, except for TNF-α, compared to unfevered individuals. In kidney tissue, challenged seahorses expressing behavioral fever exhibited gene expression levels (tnf-α, il-6, ifn-g, and il-10) similar to unchallenged controls (p > 0.05) but significantly lower (p < 0.05) than those kept at constant temperature. These findings suggest that behavioral fever in H. erectus modulates core temperature to regulate cytokine release and immune-related gene expression. This study provides foundational insights for developing practical, non-invasive strategies to mitigate enteritis in seahorse aquaculture through thermal behavior manipulation. Full article

Specific gut microorganisms and their metabolic by-products have been identified as key regulators of host physiology, contributing to the modulation of the immune system, inflammatory processes, brain function, and behavior, which highlights the gut microbiome as a potential modulator of the neurobiological mechanisms involved in substance use disorders. This narrative review provides an updated overview of how drugs of abuse influence the composition and dynamics of the human gut microbiome and how bacterial dysbiosis may be a contributing factor to substance use disorders by modulating the communication between the gut and the brain. Thus, by examining commonly abused substances such as alcohol, psychostimulants, opioids, cannabinoids, and nicotine, this review aimed to deepen the understanding of the bidirectional relationship between the gut microbiome and substance use. There is evidence indicating that gut microbiome alterations may influence addiction through changes in gut-brain signaling. Furthermore, changes in the gut microbiome and its metabolites may not only result from substance use disorders, but could also modulate behavioral responses to drugs of abuse. Although the exact mechanisms by which the gut microbiome modulates behavioral responses to drugs of abuse are not fully understood, microbial products such as short-chain fatty acids, tryptophan metabolites, bile acids, and neurotransmitters have been suggested to play a role in this process by influencing the blood–brain barrier permeability, host immune activation, neural signaling, and gene expression. Therefore, manipulating the gut microbiome or its by-products may represent a promising approach for enhancing substance use disorder treatments, identifying individuals at increased risk of pathological drug use, and elucidating its role in substance-related behaviors. Full article

Reliable assessment of protection in venom immunotherapy (VIT) patients remains a clinical challenge, especially due to the limitations of conventional sting challenge tests (SCTs), which require complex insect handling and may compromise test accuracy. This study introduces StingReady, a novel, user-friendly device designed to streamline the SCT process by enabling safe, efficient, and minimally manipulative exposure to hymenopteran stings. For the first time, StingReady was applied to conduct SCTs with Vespa velutina, an invasive hornet species of increasing clinical relevance. The device was tested in a real-world setting at Belvís Park in Santiago de Compostela, Spain, where hornets were successfully captured and transported to the hospital without anesthesia or limb removal. The design features adjustable mesh sizes, allowing compatibility with various hymenopteran taxa. Using StingReady, nine patients underwent SCTs with no need for direct insect handling during the hospital procedure. The process improved patient safety and comfort while preserving the insect’s natural stinging behavior, thereby enhancing test reliability. This study demonstrates that StingReady significantly improves SCT methodology, offering a practical, reproducible, and ethically sound alternative for evaluating VIT efficacy across diverse hymenopteran species. Full article

Bone marrow-derived macrophages (BMMs) exhibit dynamic behavior and functional capabilities in response to specific microenvironmental stimuli. Recent investigations have proved that BMMs play crucial roles in promoting necrotic lesion resolution. Despite substantial advancements in understanding their activation and interaction with injured livers, researchers face challenges to develop effective treatments based on manipulating BMMs function. Caveolin-1 (Cav-1) is the major structural protein on the plasma membrane. We previously reported that Cav-1 knockout (KO) mice exhibited less functional damage and necrosis in carbon tetrachloride (CCl₄)-induced liver injury. We hypothesize that the activation and recruitment of BMMs are involved in the resolution of necrotic lesions in Cav-1 KO mice. Wild-type (WT) and Cav-1 KO mice were injected with CCl₄ (10% v/v) to induce acute liver injury model. Blood samples and hepatic tissues were harvested for serum alanine transaminase (ALT) activity assessment, histopathological examination through hematoxylin–eosin (H&E) staining, and BMMs subpopulation analysis via flow cytometry. Then, primary BMMs were isolated and cultured to investigate the effect of Cav-1 on BMMs polarization, migration, and activation of STAT3 signal pathway. Validation of hepatic macrophage depletion was induced by administrating clodronate liposomes (CLs), and BMMs reconstitution was evaluated by EGFP labelled BMMs. Following this, hepatic macrophages were depleted by CLs, BMMs were isolated from Cav-1 KO, and WT mice were cultured and administrated to evaluate the protective role of Cav-1-deleted BMMs on the resolution of hepatocellular necrosis and apoptosis in acute liver injury. The BMMs ratio significantly increased from 2.12% (1D), 4.38% (1W), and 5.38% (2W) in oil control mice to 7.17%, 14.90%, and 19.30% in CCl₄-treated mice (p < 0.01 or p < 0.001). Concurrently, Cav-1 positive BMMs exhibited a marked elevation from 6.41% at 1D to 24.90% by 2W (p = 0.0228). Cav-1 KO exerted protective effects by reducing serum ALT by 26% (p = 0.0265) and necrotic areas by 28% (p = 0.0220) and enhancing BMMs infiltration by 60% (p = 0.0059). In vitro, Cav-1 KO BMMs showed a decrease in CD206 fluorescence intensity (p < 0.001), a time-dependent upregulation of arginase-1 mRNA (p < 0.05 or p < 0.01), a 1.22-fold increase in phosphorylated STAT3 (p = 0.0036), and impaired wound healing from 12 to 24 h (p < 0.001). The macrophage-depleting action in livers by CL injection persists for a minimum of 48 h. Administrated EGFP⁺ BMMs emerged as the predominant population following CL injection for a duration of 48 h. Following clodronate liposome-mediated hepatic macrophage depletion, the adoptive transfer of Cav-1 KO BMMs demonstrated therapeutic efficacy in CCl₄-induced acute liver injury. In CCl₄-induced acute liver injury, the adoptive transfer of Cav-1 KO BMMs reduced necrosis by 12.8% (p = 0.0105), apoptosis by 25.2% (p = 0.0127), doubled macrophages infiltration (p = 0.0269), and suppressed CXCL9/10 mRNA expression (p = 0.0044 or p = 0.0385). BMMs play a key role in the resolution of liver necrotic lesions in CCl₄-induced acute liver injury. Cav-1 depletion attenuates hepatocellular necrosis and apoptosis by accelerating BMMs recruitment and M2 polarization. Cav-1 in macrophages may represent a potential therapeutic target for acute liver injury. Full article

By combining density functional theory with the non-equilibrium Green’s function method, we conducted a first-principles investigation of spin-dependent transport properties in a molecular device featuring a dynamic covalent chemical bridge connected to zigzag graphene nanoribbon electrodes. The effects of spin-filtering and spin-rectifying on the I–V characteristics are revealed and explained for the proposed molecular device. Interestingly, our results demonstrate that all three devices exhibit significant single-spin-filtering behavior in parallel (P) magnetization and dual-spin-filtering effects in antiparallel (AP) configurations, achieving nearly 100% spin-filtering efficiency. At the same time, from the I–V curves, we find that there is a weak negative differential resistance effect. Moreover, a high rectifying ratio is found for spin-up electron transport in AP magnetization, which is explained by the transmission spectrum and local density of state. The fundamental mechanisms governing these phenomena have been elucidated through a systematic analysis of spin-resolved transmission spectra and spin-polarized electron transport pathways. These results extend the design principles of spin-controlled molecular electronics beyond graphene-based systems, offering a universal strategy for manipulating spin-polarized currents through dynamic covalent interfaces. The nearly ideal spin-filtering efficiency and tunable rectification suggest potential applications in energy-efficient spintronic logic gates and non-volatile memory devices, while the methodology provides a framework for optimizing spin-dependent transport in hybrid organic–inorganic nanoarchitectures. Our findings suggest that such systems are promising candidates for future spintronic applications. Full article

This paper introduces a novel three-dimensional financial risk system that exhibits complex dynamical behaviors, including chaos, multistability, and a butterfly attractor. The proposed system is an extension of the Zhang financial risk model (ZFRM), with modifications that enhance its applicability to real-world economic stability assessments. Through numerical simulations, we confirm the system’s chaotic nature using Lyapunov exponents (LE), with values calculated as $L_1=3.5547,$ $L_2=0,$ $L_3=-22.5642$, indicating a positive Maximal Lyapunov Exponent (MLE) that confirms chaos. The Kaplan–Yorke Dimension (KYD) is determined as D_k = 2.1575, reflecting the system’s fractal characteristics. Bifurcation analysis (BA) reveals parameter ranges where transitions between periodic, chaotic, and multistable states occur. Additionally, the system demonstrates coexisting attractors, where different initial conditions lead to distinct long-term behaviors, emphasizing its sensitivity to market fluctuations. Offset Boosting Control (OBC) is implemented to manipulate the chaotic attractor, shifting its amplitude without altering the underlying system dynamics. These findings provide deeper insights into financial risk modeling and economic stability, with potential applications in financial forecasting, risk assessment, and secure economic data transmission. Full article

Electrical transport in 2D materials exhibits unique behaviors due to reduced dimensionality, broken symmetries, and quantum confinement. It serves as both a sensitive probe for the emergence of coherent electronic phases and a tool to actively manipulate many-body correlated states. Exploring their interplay and interdependence is crucial but remains underexplored. This review integratively cross-examines the atomic and electronic structures and transport properties of van der Waals-layered crystals ZrTe₃, 2H-TaS₂, and Cr₂Si₂Te₆, providing a comprehensive understanding and uncovering new discoveries and insights. A common observation from these crystals is that modifying the atomic and electronic interface structures of 2D van der Waals interfaces using heteroatoms significantly influences the emergence and stability of coherent phases, as well as phase-sensitive transport responses. In ZrTe₃, substitution and intercalation with Se, Hf, Cu, or Ni at the 2D vdW interface alter phonon–electron coupling, valence states, and the quasi-1D interface Fermi band, affecting the onset of CDW and SC, manifested as resistance upturns and zero-resistance states. We conclude here that these phenomena originate from dopant-induced variations in the lattice spacing of the quasi-1D Te chains of the 2D vdW interface, and propose an unconventional superconducting mechanism driven by valence fluctuations at the van Hove singularity, arising from quasi-1D lattice vibrations. Short-range in-plane electronic heterostructures at the vdW interface of Cr₂Si₂Te₆ result in a narrowed band gap. The sharp increase in in-plane resistance is found to be linked to the emergence and development of out-of-plane ferromagnetism. The insertion of 2D magnetic layers such as Mn, Fe, and Co into the vdW gap of 2H-TaS₂ induces anisotropic magnetism and associated transport responses to magnetic transitions. Overall, 2D vdW interface modification offers control over collective electronic behavior, transport properties, and their interplays, advancing fundamental science and nanoelectronic devices. Full article

Combinatorial magnetron sputtering and electrical characterization were used to systematically study the impact of compositional changes in the resistive switching of transition metal oxides, specifically the Zr_xTa_1−xO_y system. Current-voltage behavior across a range of temperatures provided insights into the mechanisms that contribute to differences in the electrical conductivity of the pristine Ta₂O₅ and ZrO₂, and mixed Zr_xTa_1−xO_y devices. The underlying conductive mechanism was found to be a mixture of charge trapping and ionic motion, where charge trapping/emission dictated the short-term cycling behavior while ion motion contributed to changes in the conduction with increased cycling number. ToF-SIMS was used to identify the origin of the “wake-up” behavior of the devices, revealing an ionic motion contribution. This understanding of how cation concentration affects conduction in mixed valence systems helps provide a foundation for a new approach toward manipulating resistive switching in these active layer materials. Full article

Collaborative filtering, as a widely used recommendation method, is widely applied but susceptible to data poisoning attacks, where malicious actors inject synthetic user interaction data to manipulate recommendation results and secure illicit benefits. Traditional poisoning attack methods require in-depth understanding of the recommendation system. However, they fail to address its dynamic nature and algorithmic complexity, thereby hindering effective breaches of the system’s defensive mechanisms. In this paper, we propose DRLAttack, a deep reinforcement learning-based framework for data poisoning attacks. DRLAttack can launch both white-box and black-box data poisoning attacks. In the white-box setting, DRLAttack dynamically tailors attack strategies to recommendation context changes, generating more potent and stealthy fake user interactions for the precise targeting of data poisoning. Furthermore, we extend DRLAttack to black-box settings. By introducing spy users to simulate the behavior of active and inactive users into the training dataset, we indirectly obtain the promotion status of target items and adjust the attack strategy in response. Experimental results on real-world recommendation system datasets demonstrate that DRLAttack can effectively manipulate recommendation results. Full article

Graph neural networks (GNNs) have exhibited remarkable performance in various applications. Still, research has revealed their vulnerability to backdoor attacks, where Adversaries inject malicious patterns during the training phase to establish a relationship between backdoor patterns and a specific target label, thereby manipulating the behavior of poisoned GNNs. The inherent symmetry present in the behavior of GNNs can be leveraged to strengthen the robustness of GNNs. This paper presents a quantitative metric, termed Logit Margin Rate (LMR), for analyzing the symmetric properties of the output landscapes across GNN layers. Additionally, a learning paradigm of graph self-distillation is combined with LMR to distill the symmetry knowledge from shallow layers, which can serve as the defensive supervision signals to preserve the benign symmetric relationships in deep layers, thus improving both model stability and adversarial robustness. Experiments were conducted on four benchmark datasets to evaluate the robustness of the proposed Graph Self-Distillation-based Backdoor Defense (GSD-BD) method against three widely used backdoor attack algorithms, demonstrating the robustness of GSD-BD even under severe infection scenarios. Full article