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Evaluation of rice husk biochar influence as a partial cement replacement material on the physical, mechanical, microstructural, and radiation shielding properties of ordinary concrete
No full textThis study investigated the viability of rice husk-derived biochar (RHB) as a partial substitute for cement in concrete. The used RHB, characterized by a novel chemical composition abundant in silicon and aluminum oxides, was incorporated into ordinary concrete at increasing substitution ratios up to 25% by cement weight. A comprehensive evaluation was conducted to assess the influence of RHB on various properties of concrete, including physical (setting time, standard consistency, workability), mechanical (compressive and tensile strength), microstructural (XRD, and EDX), and radiation shielding characteristics. The results indicated that RHB marginally increased cement setting time, with a maximum 7.14% increase observed at a 25% replacement level. However, it significantly increased water demand for standard consistency, reaching 35.7% at 25% replacement. The increased water demand correlated with a reduction in workability, with a maximum slump reduction rate of 57.3% at a 25% replacement level. The optimal replacement levels for mechanical strength enhancement were at 10% for compressive strength and 15% for tensile strength, achieving improvements of 13.74% and 9.48%, respectively. Additionally, Monte Carlo simulation code and PhyX software were employed for assessing gamma and fast neutron radiation attenuation characteristics of concrete. Gamma-ray attenuation tests revealed moderate improvements in the concrete's gamma-ray shielding capacity. Interestingly, the 15% RHB sample demonstrated a higher linear attenuation compared to the other samples, a result of its increased density. On the contrary, the 25RHB sample is less valuable. The 15RHB sample had the highest value for FCS (0.090 cm ) indicating its efficacy as a neutron shield. [Abstract copyright: © 2025. The Author(s).
“Crime and Punishment”: the effect of antagonistic personality traits on punitive attitudes and offender dehumanization
No full textThis study examined the relationships between antagonistic personality, Right-Wing Authoritarianism (RWA), Social Dominance Orientation (SDO), punitive attitudes, and offender dehumanization across Romanian and UK samples. Using a network approach, Study 1 (N = 636) found a negative correlation between psychopathy and punitive attitudes in Romania but not in the UK, while psychopathy showed high centrality in both samples. Study 2 (N = 679) tested whether primary (PPS) and secondary psychopathy (SPS) predict offender identification and dehumanization across offender traits and crime types. The results showed that PPS consistently predict identification in both countries, while a three-way interaction in Romania indicated that PPS negatively predicts dehumanization for violent offenders and those with psychopathic traits in white-collar crimes, while neither RWA nor SDO mediate the path between PPS and dehumanization. SPS predicts identification in Romania but not in the UK. These findings advance theory on the relationships between punitive attitudes and antagonistic personality, especially psychology. In particular, they challenge the assumption that psychopathy uniformly and positively predicts harsher punishment and dehumanization, highlighting the need for distinguishing between psychopathy subtypes and context-sensitive approaches in research and practice.<br/
Determining the polarization of a Coronal standing kink oscillation using spectral imaging techniques with CoMP
No full textCoronal oscillations offer insight into energy transport and driving in the solar atmosphere. Knowing its polarization state helps constrain a wave's displacement and velocity amplitude, improving estimates of wave energy flux and deposition rate. We demonstrate a method to combine imaging and spectral data to infer the polarization of a coronal loop's standing kink wave, without the need for multiple instruments or multiple lines of sight. We use the unique capabilities of the Coronal Multi-channel Polarimeter (CoMP) to observe the standing kink mode of an off-limb coronal loop perturbed by an eruption. The full off-disk corona is observed using the 1074 nm Fe xiii spectral line, providing Doppler velocity, intensity, and line width. By tracking the oscillatory motion of a loop apex in a time–distance map, we extract the line-of-sight (Doppler) velocity of the inhomogeneity as it sways and compare it with the derivative of its plane-of-sky displacement. This analysis provides the loop's velocity in two perpendicular planes as it oscillates with a period of 8.9 +0.5-0.5 minutes. Through detailed analysis of the phase relation between the transverse velocities, we infer the kink oscillation to be horizontally polarized, oscillating in a plane tilted d 13.6+2.9-3.0 away from the plane of sky. The line widths show a periodic enhancement during the kink oscillation, exhibiting both the kink period and its double. This study is the first to combine direct imaging and spectral data to infer the polarization of a coronal loop oscillation from a single viewpoint.<br/
How should e-product OEMs invest in design for remanufacturing under the take-back regulation in a competitive environment?
No full textThis study investigates the effects of take-back regulations and remanufacturing competition on e-product OEM design for remanufacturing (DfR) strategies and remanufacturing decisions within a closed-loop supply chain. Considering the monopolistic remanufacturing scenario where the remanufacturer does not enter the remanufacturing market as a benchmark model, we establish a Stackelberg game model involving an OEM and a remanufacturer to explore the OEM’s optimal DfR decisions under take-back regulations and in a competitive environment. The Lagrangian function and Karush–Kuhn–Tucker conditions are formulated to identify the optimal solutions. The findings reveal the following: (i) Whether the remanufacturer engages in remanufacturing activity or not, take-back regulation consistently prompts OEMs to increase DfR investment. (ii) DfR investment level is lower in competitive markets compared to monopolistic scenarios, while remanufactured product output is higher. (iii) While consumer welfare improves with remanufacturer entry, environmental benefits deteriorate due to potential increased competition. Notably, competitive remanufacturing is advantageous for OEMs only when take-back regulation is stringent and the cost savings of remanufactured products are relatively low.<br/
Reinforcement learning with LLMs interaction for distributed diffusion model services
No full textDistributed Artificial Intelligence-Generated Content (AIGC) has attracted significant attention, but two key challenges remain: maximizing subjective Quality of Experience (QoE) and improving energy efficiency, which are particularly pronounced in widely adopted Generative Diffusion Model (GDM)-based image generation services. In this paper, we propose a novel user-centric Interactive AI (IAI) approach for service management, with a distributed GDM-based AIGC framework that emphasizes efficient and cooperative deployment. The proposed method restructures the GDM inference process by allowing users with semantically similar prompts to share parts of the denoising chain. Furthermore, to maximize the users' subjective QoE, we propose an IAI approach, i.e., Reinforcement Learning With Large Language Models Interaction (RLLI), which utilizes Large Language Model (LLM)-empowered generative agents to replicate users interactions, providing real-time and subjective QoE feedback aligned with diverse user personalities. Lastly, we present the GDM-based Deep Deterministic Policy Gradient (G-DDPG) algorithm, adapted to the proposed RLLI framework, to allocate communication and computing resources effectively while accounting for subjective user traits and dynamic wireless conditions. Simulation results demonstrate that G-DDPG improves total QoE by 15% compared with the standard DDPG algorithm
Assessing the impacts of land-use change and climate variability on cyanobacterial abundance and toxicity in shallow lakes
No full text1. The global increase in the frequency and intensity of cyanobacteria blooms has been widely attributed to changes in land-use practices and climate variability, yet little is known of how toxicity has varied historically relative to cyanobacteria abundance.2. Fossil pigments from cyanobacteria and algae were quantified from shallow lake sediment core records using high-performance liquid chromatography, whilst past concentrations of microcystin congeners were measured using liquid chromatography high-resolution mass spectrometry. These metrics were combined with measures of sedimentary geochemistry (δ13C, δ15N, %N, %C, C:N ratio) to estimate how lake production and abundance of toxigenic cyanobacteria varied during the past ~300 years in two small lakes in New Brunswick, Canada. Harvey Lake is an impacted site with a history of intensive catchment land use, whilst Wheaton Lake is a relatively undisturbed reference site.3. Stratigraphically constrained cluster analysis (CONISS) revealed that primary production increased steadily in both lakes since the second half of the 20th century, whilst microcystin production increased by an order of magnitude after ca. 2000 CE. Fossil pigment concentrations were initially lower in Harvey Lake but shifted to more productive conditions after initial forest clearance and settlement and again after agricultural intensification during the 20th century. Although Wheaton Lake exhibited higher overall fossil pigment concentrations, including a pre-colonial eutrophic interval (ca. 1680–1750 CE), this reference basin also underwent enrichment since ca. 1980, possibly reflecting longer growing seasons in the last 50 years.4. Although cyanobacterial pigments and microcystin concentrations were elevated in sediments deposited since ca. 2000 CE in both lakes, these variables were uncorrelated over the entire 300-year record, with the pre-colonial eutrophic interval in Wheaton Lake having low toxin concentrations. This pattern suggests either that cyanobacterial dominance and toxicity are regulated by different factors or that the preservation of microcystins and pigments is under unique controls.5. Statistical analyses showed that these small shallow maritime lakes are sensitive to relatively small land-use perturbations within their catchments and that even undisturbed basins may be vulnerable to toxic cyanobacteria blooms in a warming climate.<br/
The first Phoenician funerary manifestations on the banks of the Guadalhorce: the necropolis of Cortijo de San Isidro
No full textDuring the archaeological intervention carried out ahead of construction works for the Málaga Airport expan- sion, the early Phoenician cremation necropolis of Cortijo de San Isidro was located on the right bank of the current bed of the Guadalhorce River, directly related to the Phoenician cult complex of La Rebanadilla (9th-8th centuries BC). The archaeological intervention consisted of evaluation trenching to establish the characteristics of the cemetery and its physical boundaries. This article presents the results from that work
Impact of Platt scaling on calibration in ML-based wireless resource allocation
No full textIn this paper, we study the calibration performance of a machine learning (ML)-based outage predictor applied to a single-user, multi-resource allocation system. Our approach models the wireless channel using Rayleigh fading with temporal characteristics that are consistent with Clarke’s 3D model. This allows us to account for the mobility of the receiver, introducing correlation between successive channel samples. Building upon this, we study the calibration performance of the outage predictor when Platt scaling is applied. Its calibration performance is assessed by generating histogram-based reliability plots with logarithmic binning. This outage predictor is trained using a customized outage loss function (OLF) as well as the commonly employed binary cross entropy. Using the negative log likelihood as an indicator, our results show that Platt scaling has a clear impact upon calibration performance, with greater enhancement observed at higher confidence levels and less improvement at lower ones. Furthermore, we observe that Platt scaling is particularly effective in minimizing overconfidence for predictors trained with OLF at lower classification thresholds and as the signal-to-noise ratio increases
