Search Results (12)

The growing demand for personalized human–computer interaction calls for methods that jointly model emotional states and personality traits. However, large-scale multimodal corpora annotated for both tasks are still lacking. This challenge stems from integrating diverse, task-specific corpora with divergent modality informativeness and domain characteristics. To address it, we propose SSL-MEPR, a semi-supervised multi-task cross-domain learning framework for Multimodal Emotion and Personality Recognition, which enables cross-task knowledge transfer without jointly labeled data. SSL-MEPR employs a three-stage strategy, progressively integrating unimodal single-task, unimodal multi-task, and multimodal multi-task models. Key innovations include Graph Attention Fusion, task-specific query-based cross-attention, predict projectors, and guide banks, which enable robust fusion and effective use of semi-labeled data via a modified GradNorm method. Evaluated on MOSEI (emotion) and FIv2 (personality), SSL-MEPR achieves a mean Weighted Accuracy (mWACC) of 70.26 and a mean Accuracy (mACC) of 92.88 in single-task cross-domain settings, outperforming state-of-the-art methods. Multi-task learning reveals domain-induced misalignment in modality informativeness but still uncovers consistent psychological patterns: sadness correlates with lower personality trait scores, while happiness aligns with higher ones. This work establishes a new paradigm for extracting cross-task psychological knowledge from disjoint multimodal corpora, demonstrating that semi-supervised multi-task cross-domain learning can bridge annotation gaps while preserving theoretically grounded emotion–personality relationships. Full article

In the domain of automatic parking systems, parking space detection and localization represent fundamental challenges that must be addressed. As a core research focus within the field of intelligent automatic parking, they constitute the essential prerequisite for the realization of fully autonomous parking. Accurate and effective detection of parking spaces is still the core problem that needs to be solved in automatic parking systems. In this study, building upon existing public parking space datasets, a comprehensive panoramic parking space dataset named PSEX (Parking Slot Extended) with complex environmental diversity was constructed by integrating the concept of GAN (Generative Adversarial Network)-based image style transfer. Meanwhile, an improved algorithm based on PP-Yoloe (Paddle-Paddle Yoloe) is used to detect the state (free or occupied) and angle (T-shaped or L-shaped) of the parking space in real-time. For the many and small labels of the parking space, the ResSpp in it is replaced by the ResSimSppf module, the SimSppf structure is introduced at the neck end, and Silu is replaced by Relu in the basic structure of the CBS (Conv-BN-SiLU), and finally an auxiliary detector head is added at the prediction head. Experimental results show that the proposed SimSppf_mepre-Yoloe model achieves an average improvement of 4.5% in mAP50 and 2.95% in mAP50:95 over the baseline PP-Yoloe across various parking space detection tasks. In terms of efficiency, the model maintains comparable inference latency with the baseline, reaching up to 33.7 FPS on the Jetson AGX Xavier platform under TensorRT optimization. And the improved enhancement algorithm can greatly enrich the diversity of parking space data. These results demonstrate that the proposed model achieves a better balance between detection accuracy and real-time performance, making it suitable for deployment in intelligent vehicle and robotic perception systems. Full article

Methicillin-resistant Staphylococcus aureus (MRSA) poses a significant clinical challenge due to its resistance to multiple antibiotics. The urgent need for new therapeutic approaches has led to the exploration of natural compounds as potential treatments, particularly those targeting the key bacterial proteins involved in antibiotic resistance. This study focused on the multidrug ABC transporter and MecA proteins, which play crucial roles in MRSA′s pathogenicity and resistance mechanisms. Using computational techniques and molecular docking methods, we assessed the interactions of 80 natural compounds with S. aureus multidrug ABC transporter SAV1866 (SAV1866) and MecA proteins. Our analysis revealed 14 compounds with robust binding to SAV1866 and one compound with a strong affinity for MecA. Notably, these compounds showed weaker affinities for the MgrA, MepR, and arlR proteins, suggesting specificity in their interactions. Among the 15 promising compounds identified, 1′,2-Binaphthalen-4-one-2′,3-dimethyl-1,8′-epoxy-1,4′,5,5′,8,8′-hexahydroxy-8-O-β-glucopyranosyl-5′-O-β-xylopyranosyl(1→6)-β-glucopyranoside; Cis-3,4-dihydrohamacanthin b; and Mamegakinone exhibited the highest binding affinities to S. aureus SAV1866. These compounds represent diverse chemical classes, including alkaloids, indole derivatives, naphthalenes, and naphthoquinones, offering a range of structural scaffolds for further drug development. Our findings provide valuable insights into potential new antibacterial agents targeting S. aureus SAV1866 and MecA proteins. These results lay the groundwork for future in vitro and in vivo studies to validate these compounds′ efficacy for combating MRSA infections, potentially leading to the development of novel therapeutic strategies against antibiotic-resistant bacteria. Full article

The significant reduction in cassava (Manihot esculenta Crantz) yields attributed to cassava bacterial blight (CBB) constitutes an urgent matter demanding prompt attention. The current study centered on the MebHLH149 transcription factor, which is acknowledged to be reactive to CBB and exhibits augmented expression levels, as indicated by laboratory transcriptome data. Our exploration, encompassing Xanthomonas phaseoli pv. manihotis strain CHN01 (Xpm CHN01) and hormone stress, disclosed that the MebHLH149 gene interacts with the pathogen at the early stage of infection. Furthermore, the MebHLH149 gene has been discovered to be responsive to the plant hormones abscisic acid (ABA), methyl jasmonate (MeJA), and salicylic acid (SA), intimating a potential role in the signaling pathways mediated by these hormones. An analysis of the protein’s subcellular localization suggested that MebHLH149 is predominantly located within the nucleus. Through virus-induced gene silencing (VIGS) in cassava, we discovered that MebHLH149-silenced plants manifested higher disease susceptibility, less ROS accumulation, and significantly larger leaf spot areas compared to control plants. The proteins MePRE5 and MePRE6, which are predicted to interact with MebHLH149, demonstrated complementary downregulation and upregulation patterns in response to silencing and overexpression of the MebHLH149 gene. This implies a potential interaction between MebHLH149 and these proteins. Both MePRE5 and MePRE6 genes are involved in the initial immune response to CBB. Notably, MebHLH149 was identified as a protein that physically interacts with MePRE5 and MePRE6. Based on these findings, it is hypothesized that the MebHLH149 gene likely functions as a positive regulator in the defense mechanisms of cassava against CBB. Full article

A postulate that relates global warming to higher entropy generation rate demand in the tropospheric is offered and tested. This article introduces a low-complexity model to calculate the entropy generation rate required in the troposphere. The entropy generation rate per unit volume is noted to be proportional to the square of the Earth’s average surface temperature for a given positive rate of surface warming. The main postulate is that the troposphere responds with mechanisms to provide for the entropy generation rate that involves specific cloud morphologies and wind behavior. A diffuse-interface model is used to calculate the entropy generation rates of clouds. Clouds with limited vertical development, like the high-altitude cirrus or mid-altitude stratus clouds, are close-to-equilibrium clouds that do not generate much entropy but contribute to warming. Clouds like the cumulonimbus permit rapid vertical cloud development and can rapidly generate new entropy. Several extreme weather events that the Earth is experiencing are related to entropy-generating clouds that discharge a high rate of rain, hail, or transfer energy in the form of lightning. The water discharge from a cloud can cool the surface below the cloud but also add to the demand for a higher entropy generation rate in the cloud and troposphere. The model proposed predicts the atmospheric conditions required for bifurcations to severe-weather clouds. The calculated vertical velocity of thunderclouds associated with high entropy generation rates matches the recorded observations. The scale of instabilities for an evolving diffuse interface is related to the entropy generation rate per unit volume. Significant similarities exist between the morphologies and the entropy generation rate correlations in vertical cloud evolution and directionally solidified grainy microstructures. Such similarities are also explored to explore a generalized framework of pattern evolution and establish the relationships with the corresponding entropy generation rate. A complex system like the troposphere can invoke multiple phenomena that dominate at different spatial scales to meet the demand for an entropy generation rate. A few such possibilities are presented in the context of rapid and slow changes in weather patterns. Full article

Staphylococcus aureus (S. aureus) is a frequent cause of eye infections with some isolates exhibiting increased antimicrobial resistance to commonly prescribed antibiotics. The increasing resistance of ocular S. aureus to ciprofloxacin is a serious concern as it is a commonly used as a first line antibiotic to treat S. aureus keratitis. This study aimed to analyse genetic mutations in the genomes of 25 S. aureus isolates from infections or non-infectious ocular conditions from the USA and Australia and their relationship to ciprofloxacin resistance. Overall, 14/25 isolates were phenotypically resistant to ciprofloxacin. All isolates were analyzed for mutations in their quinolone resistance-determining regions (QRDRs) and efflux pump genes. Of the fourteen resistant isolates, 9/14 had ciprofloxacin resistance mutations within their QRDRs, at codons 80 or 84 within the parC subunit and codon 84 within the gyrA subunit of DNA gyrase. The highest resistance (MIC = 2560 μg/mL) was associated with two SNPs in both gyrA and parC. Other resistant isolates (3/14) had mutations within norB. Mutations in genes of other efflux pumps and their regulator (norA, norC, mepA, mdeA, sepA, sdrM, mepR, arlR, and arlS) or the DNA mismatch repair (MMR) system (mutL and mutS) were not associated with increased resistance to ciprofloxacin. The functional mutations associated with ciprofloxacin resistance in QRDRs (gyrA and parC) and norB suggests that these are the most common reasons for ciprofloxacin resistance in ocular isolates. Novel SNPs of gyrA Glu-88-Leu, Asn-860-Thr and Thr-845-Ala and IIe-855-Met, identified in this study, need further gene knock out/in studies to better understand their effect on ciprofloxacin resistance. Full article

In this paper, I reformulate Sterba’s argument from evil and consider the various ways theists might respond to it. There are two basic families of responses. On the one hand, theists can deny that God, as a perfect being, needs to act in accordance with Sterba’s moral evil prevention requirements (MEPRs). We can call these responses exceptionalist responses. On the other hand, the theist can deny that God’s acting in accordance with the MEPRs would imply an absence of significant and especially horrendous evil consequences of immoral actions in the world. We can call these responses compatibilist responses. I argue that the availability of both sorts of responses shows that Sterba’s argument should not be taken as a logical argument from evil. A good God is logically possible. However, this does not show that Sterba’s argument fails as an evidential argument from evil. In the second section, I argue that if we work within the framework of what Jonathan Kvanvig calls Creator Theology (CT), the force of Sterba’s argument as an evidential argument is greatly weakened. Full article

James Sterba argues that a good God is not logically possible. He argues that what he calls the Pauline Principle, which says that we should never do evil that good may come of it, implies that a good God would prevent horrendous evil consequences of immoral actions. However, there are plenty of examples of such actions in our world. So, a good God does not exist. I offer an example from Derek Parfit, and one of my own, that calls the Pauline Principle into question. Sterba believes that what he calls Moral Evil Prevention Requirements (MEPRs) follow from the Pauline Principle, and that they are necessary truths which imply that a good God would prevent horrendous evil consequences of immoral actions. Whether these (MEPRs) follow from the Pauline Principle or do not, they may be necessary truths that could form the basis of Sterba’s argument. However, I argue that they are not necessary truths. If modified to become such, Sterba faces a challenge from the Skeptical Theists that can only be met by turning his argument into an evidential version of the problem of evil. I compare Sterba’s argument with my version of the evidential argument from evil that says that if God exists, there is not excessive, unnecessary suffering and whose second premise says there is. I argue that it is easier to establish that there is excessive, unnecessary suffering than to establish Sterba’s second premise (once his principles are modified). That second premise will say that there are no goods that logically require God to allow immoral actions that have horrendous evil consequences. Sterba faces a dilemma: either he has an unsound logical argument or a weak evidential argument for the non-existence of God. In either case, he does not have a good logical argument for atheism. Full article

Nowadays, increasing interest has recently been given to the exploration of new food preservatives to avoid foodborne outbreaks or food spoilage. Likewise, new compounds that substitute the commonly used synthetic food preservatives are required to restrain the rising problem of microbial resistance. Accordingly, the present study was conducted to examine the chemical composition and the mechanism(s) of action of the Cupressus sempervirens essential oil (CSEO) against Salmonella enterica Typhimuriumand Staphyloccocus aureus. The gas chromatography analysis revealed α-pinene (38.47%) and δ-3-carene (25.14%) are the major components of the CSEO. By using computational methods, such as quantitative structure–activity relationship (QSAR), we revealed that many CSEO components had no toxic effects. Moreover, findings indicated that α-pinene, δ-3-carene and borneol, a minor compound of CSEO, could inhibit the AcrB-TolC and MepR efflux pump activity of S. enterica Typhimurium and S. aureus, respectively. In addition, our molecular docking predictions indicated the high affinity of these three compounds with active sites of bacterial DNA and RNA polymerases, pointing to plausible impairments of the pathogenic bacteria cell replication processes. As well, the safety profile was developed through the zebrafish model. The in vivo toxicological evaluation of (CSEO) exhibited a concentration-dependent manner, with a lethal concentration (LC₅₀) equal to 6.6 µg/mL. Full article

Self-organization that leads to the discontinuous emergence of optimized new patterns is related to entropy generation and the export of entropy. Compared to the original pattern that the new, self-organized pattern replaces, the new features could involve an abrupt change in the pattern-volume. There is no clear principle of pathway selection for self-organization that is known for triggering a particular new self-organization pattern. The new pattern displays different types of boundary-defects necessary for stabilizing the new order. Boundary-defects can contain high entropy regions of concentrated chemical species. On the other hand, the reorganization (or refinement) of an established pattern is a more kinetically tractable process, where the entropy generation rate varies continuously with the imposed variables that enable and sustain the pattern features. The maximum entropy production rate (MEPR) principle is one possibility that may have predictive capability for self-organization. The scale of shapes that form or evolve during self-organization and reorganization are influenced by the export of specific defects from the control volume of study. The control volume (CV) approach must include the texture patterns to be located inside the CV for the MEPR analysis to be applicable. These hypotheses were examined for patterns that are well-characterized for solidification and wear processes. We tested the governing equations for bifurcations (the onset of new patterns) and for reorganization (the fine tuning of existing patterns) with published experimental data, across the range of solidification morphologies and nonequilibrium phases, for metallic glass and featureless crystalline solids. The self-assembling features of surface-texture patterns for friction and wear conditions were also modeled with the entropy generation (MEPR) principle, including defect production (wear debris). We found that surface texture and entropy generation in the control volume could be predictive for self-organization. The main results of this study provide support to the hypothesis that self-organized patterns are a consequence of the maximum entropy production rate per volume principle. Patterns at any scale optimize a certain outcome and have utility. We discuss some similarities between the self-organization behavior of both inanimate and living systems, with ideas regarding the optimizing features of self-organized pattern features that impact functionality, beauty, and consciousness. Full article

The use of the principle of maximum entropy generation per unit volume is a new approach in materials science that has implications for understanding the morphological evolution during solid–liquid interface growth, including bifurcations with or without diffuseness. A review based on a pre-publication arXiv preprint is first presented. A detailed comparison with experimental observations indicates that the Maximum Entropy Production Rate-density model (MEPR) can correctly predict bifurcations for dilute alloys during solidification. The model predicts a critical diffuseness of the interface at which a plane-front or any other form of diffuse interface will become unstable. A further confidence test for the model is offered in this article by comparing the predicted liquid diffusion coefficients to those obtained experimentally. A comparison of the experimentally determined solute diffusion constant in dilute binary Pb–Sn alloys with those predicted by the various solidification instability models (1953–2011) is additionally discussed. A good predictability is noted for the MEPR model when the interface diffuseness is small. In comparison, the more traditional interface break-down models have low predictiveness. Full article

Microalgae are an excellent source of valuable compounds for nutraceutical and cosmeceutical applications. These photosynthesizing microorganisms are amenable for large-scale production, thus overcoming the bottleneck of biomass supply for chemical and activity characterization of bioactive compounds. This characteristic has recently also prompted the screening of microalgae for potential pharmaceutical applications. Here, we show that monoacylglycerides (MAGs) purified from the marine diatom Skeletonema marinoi have selective cytotoxic activity against the haematological cancer cell line U-937 and colon cancer cell line HCT-116 compared to normal MePR-2B cells. LC-MS analysis of the raw extract revealed that in their natural form, MAGs occur as 2-monoacyl derivatives and include mainly C16 and C20 analogues, but they are converted into the corresponding 1-isomers during purification processes. Pure compounds along with the synthetic 1-monoarachidonoylglycerol tested on HCT-116 and U-937 tumor cell lines induced cell death via apoptosis. The mechanism of action was investigated, and we show that it involves the induction of apoptosis through caspase 3/7 activation. These findings pave the way for the possible use of these molecules as potential anticancer agents or as precursors for the generation of new and more potent and selective compounds against tumor cells. Full article