Search Results (58)

Fluorogenic glycosides are widely used substrates for assaying lysosomal glycosidase activities in vitro, but they do not provide subcellular information in living cells. In this study, we used glucosylceramide (GlcCer) liposomes as carriers to deliver fluorogenic substrates into live PC12 cells for confocal imaging. The α-4-methylumbelliferyl glucoside (α-4MUG) and β-glucosidase substrate β-4-(trifluoromethyl)umbelliferyl glucoside (β-4FMUG) were co-encapsulated in liposomes. The liposomes (approximately 100 nm in diameter) were taken up by PC12 cells after pulse exposure. Punctate fluorescence signals from both hydrolyzed substrates were observed. The relative intensity of two signals varied among puncta, as assessed by dual-channel imaging and line-scan analysis. These results show that GlcCer liposomes provide a practical platform for long-term and differential analyses of relative α- and β-glucosidase activities in living cells. Full article

Metal pollution from metallurgical emissions poses serious environmental and public health risks in Kazakhstan. A replicated pot-culture experiment (n = 4) in a completely randomized design under controlled phytotron conditions evaluated biomass production and metal accumulation in six crop and forage species, alfalfa (Medicago sativa), amaranth (Amaranthus spp.), corn (Zea mays), mustard (Brassica juncea), rapeseed (Brassica napus), and sunflower (Helianthus annuus); three ornamental species, purple coneflower (Echinacea purpurea), marigold (Tagetes spp., ‘Tiger Eyes’), and sweet alyssum (Lobularia maritima); and three native wild plants, greater burdock (Arctium lappa), horse sorrel (Rumex confertus), and mug wort (Artemisia vulgaris). Plants were grown in soils collected from the Qarmet industrial zone in Temirtau, central Kazakhstan. Initial soil analysis revealed substantial mixed-metal contamination, ranked as Mn > Ba > Zn > Sr > Cr > Pb > Cu > Ni > B > Co. Mn reached 1059 mg·kg⁻¹, ~50-fold higher than B (22.7 mg·kg⁻¹). Ba (620 mg·kg⁻¹) exceeded FAO/WHO limits sixfold, Zn (204 mg·kg⁻¹) surpassed the lower threshold, and Pb (41.6 mg·kg⁻¹) approached permissible levels, while Cr, Cu, Ni, Co, and Sr were lower. Biomass production varied markedly among species: corn and sunflower produced the highest shoot biomass (126.8 and 60.9 g·plant⁻¹), whereas horse sorrel had the greatest root biomass (54.4 g·plant⁻¹). Root-to-shoot ratios indicated shoot-oriented growth (>1–8) in most species, except horse sorrel and burdock (<1). Metal accumulation was strongly species-specific. Corn and marigold accumulated Co, Pb, Cr, Mn, Ni, Cu, B, and Ba but showed limited translocation (transfer function, TF < 0.5), whereas sunflower, amaranth, and mug wort exhibited moderate to high translocation (TF > 0.8 to <1) for selected metals. Corn is recommended for high-biomass metal removal, marigold for stabilization, sunflower, horse sorrel, and mug wort for multi-metal extraction, and amaranth and coneflower for targeted Co, Ni, and Cu translocation, supporting sustainable remediation of industrially contaminated soils. Full article

Rapidly exploring Random Trees (RRT) provide probabilistic completeness but often explore inefficiently in high-DOF manipulation tasks. We address this by proposing a contact-aware, two-level planner that couples a learned toggle–subgoal predictor with a conditional diffusion sampler in joint space under a completeness-preserving mixture with uniform sampling. An upper ResNet-based network predicts task-relevant milestones from RGB images: grasp/release “toggle” configurations and intermediate joint-space subgoals that serve as phase-wise, receding-horizon targets between consecutive contact events. Conditioned on these predictions and the current state, a lower-level diffusion model samples tree-extension segments—joint-space directions and step lengths—instead of absolute configurations. These proposals act as a drop-in replacement for uniform sampling in standard RRT/RRT-Connect, while a nonzero fraction of uniform samples preserves probabilistic completeness. By biasing growth toward contact-relevant regions, the planner concentrates the search near feasible approach manifolds without altering nearest-neighbor, steering, or collision-checking primitives. In mug pick-and-place simulations, the proposed method achieves higher success rates than diffusion and other sequence-based policies trained by imitation learning, and requires fewer RRT expansions than uniform and goal-biased RRT as well as prior learning-guided samplers based on CVAE and conditional GAN, under identical collision checking and iteration limits. Full article

Nowadays, mobile applications are essential tools for everyday life, providing users with anytime, anywhere access to up-to-date information, communication, and entertainment. Needless to say, hardware limitations and the diverse needs of different user groups pose a number of design and development challenges. According to recent studies, usability is one of the most revealing among many others. However, few have made the direct effort to provide and discuss what countermeasures can be applied to avoid usability issues in mobile application development. Through a survey of 20 mobile software design and development practitioners, this study aims to fill this research gap. Given the qualitative nature of the data collected, and with the goal of capturing and preserving the intrinsic meanings embedded in the experts’ statements, we adopted in vivo coding. The analysis of the collected material enabled us to develop a novel framework consisting of ten guidelines and three activities with general applications. In addition, it can be noted that active collaboration with users in testing and collecting feedback was often emphasized at each stage of mobile application development. Future research should consider focused action research that evaluates the effectiveness of our recommendations and validates them across different stakeholder groups. In this regard, the development of automated tools to support early detection and mitigation of usability issues during mobile application development could also be considered. Full article

Emotion recognition plays a crucial role in our day-to-day communication, and detecting emotions is one of the most formidable tasks in the field of human–computer Interaction (HCI). Facial expressions are the most straightforward and efficient way to identify emotions. With so many real-time applications, although automatic facial expression recognition (FER) is essential for numerous real-world applications in computer vision, developing a feature descriptor that accurately captures the subtle variations in facial expressions remains a significant challenge. Towards addressing this issue, a novel feature extraction technique inspired by Dining Philosophers Problem, named Dining Philosophers Problem Inspired Binary Patterns (DPIBP), has been proposed in this work. The proposed DPIBP methods extract three features in a local 5 × 5 neighborhood by considering the impact of both neighboring pixels and the adjacent pixels on the current pixel. To categorize facial expressions, the system used a multi-class Support Vector Machine (SVM) classifier. Reflecting real-world use, researchers tested the method on JAFFE, MUG, CK+, and TFEID benchmark datasets using a person-independent protocol. The proposed method, DPIBP, achieved superior performance compared to existing techniques that rely on manually crafted features for extraction. Full article

Automatic Facial Expression Recognition (AFER) is a key component of affective computing, enabling machines to recognize and interpret human emotions across various applications such as human–computer interaction, healthcare, entertainment, and social robotics. Dynamic AFER systems, which exploit image sequences, can capture the temporal evolution of facial expressions but often suffer from high computational costs, limiting their suitability for real-time use. In this paper, we propose an efficient dynamic AFER approach based on a novel spatio-temporal representation. Facial landmarks are extracted, and all possible Euclidean distances are computed to model the spatial structure. To capture temporal variations, three statistical metrics are applied to each distance sequence. A feature selection stage based on the Extremely Randomized Trees (ExtRa-Trees) algorithm is then performed to reduce dimensionality and enhance classification performance. Finally, the emotions are classified using a linear multi-class Support Vector Machine (SVM) and compared against the k-Nearest Neighbors (k-NN) method. The proposed approach is evaluated on three benchmark datasets: CK+, MUG, and MMI, achieving recognition rates of 94.65%, 93.98%, and 75.59%, respectively. Our results demonstrate that the proposed method achieves a strong balance between accuracy and computational efficiency, making it well-suited for real-time facial expression recognition applications. Full article

The use of eco-organic ingredients as a source of protein in aquaculture diets needs important attention due to the growing demand for organic seafood products. The present study evaluated the effects of fish meal substitution by different organic ingredients on the growth, body composition, retention efficiency, enzyme activity, and nutrient digestibility of white shrimp Penaeus vannamei. The four dietary formulations tested were formulated with organic ingredients and the fish meal was replaced by the following organic protein meals: Iberian pig viscera meal (PIG), trout by-product meal (TRO), insect meal (FLY), and organic vegetable meal (WHT), in addition to a control diet (CON) that included 15% fish meal. A growth trial was carried out for 83 days, raising 1 g shrimp to commercial size (20 g). Shrimp were stocked at 167 shrimp/m³ (15 individuals per 90 L tank). The results showed that the growth obtained by shrimp fed with TRO (19.27 g) and PIG (19.35 g) were similar in weight gain to the control diet (20.76 g), while FLY (16.04 g) and WHT (16.73 g) meals resulted in a significant lower final weight. The FLY diet showed significantly lower protein digestibility (68.89%) compared to the CON, PIG, TRO, and WHT diets, and significantly higher trypsin activity (0.17 mU/g) compared to shrimp fed with the PIG, TRO, and WHT diets. Shrimp fed with WHT have a significantly lower body weight percentage of protein (19.69%) than shrimp fed with the WHT and TRO diets, and some significant differences in dietary aminoacidic levels affecting amino acid body composition. These results indicate that Iberian pig viscera and trout by-product meal can successfully replace fish meal in Pacific white shrimp aquaculture. Full article

The paper is dedicated to the study of organic remains in ceramic drinking vessels from protohistoric Northern Italy. These one-handled mugs are a typical item of the prealpine area, dating from the 5th to the 1st century BCE, and possibly carried high cultural value, given their presence in graves and sanctuaries as well as the presence of alphabetic inscriptions on some of them. The sampled items consist of 10 mug bases from the Iron Age sanctuary of Dos dell’Arca (Capo di Ponte, BS) and the coeval settlement of Castello di Castione della Presolana (BG). The analyses included HT-GC-MS and GC-C-IRMS analyses to identify ancient food/beverage products. The results indicate a differentiated use for the two types of mugs (“Breno” and “Dos dell’Arca” types), suggesting a possible shift in cultic habits. While both types were primarily containers for milk consumption, the earliest type was also used for consuming fermented, millet-based beverages, while the latter was covered with some oily vegetal substance before its disposal. Full article

The field of image classification using Convolutional Neural Networks (CNNs) to predict the principal object in an image has seen many recent innovations. One aspect that has not been extensively explored is the effect of the camera employed to acquire images for inference. We investigate this by capturing comparable images of five drinking vessels using six cameras in various scenarios. We examine the classification ranking of object classes when these images are input to an independently pretrained Resnet-18 model based on the ImageNet-1k dataset. We find that the camera used can affect the top prediction of object class, particularly in scenarios with a more complex background. This is the case even when the cameras have similar fields of view. We also introduce a metric called selectivity, defined as the mean absolute difference between prediction probabilities of similar relevant object classes (such as cups and mugs). We show that the effect of the camera is largest when the selectivity of the pretrained model between these object classes is small. The effect of camera choice is also demonstrated quantitatively by examining Cohen’s Kappa (κ) statistic. Finally, we make recommendations on mitigating the effect of the camera on image-classification inference. Full article

The Murciano-Granadina goat (MUG) is a renowned dairy breed, known for its adaptability and resilience, as well as for its exceptional milk traits characterized by high protein and fat content, along with low somatic cell counts. These traits are governed by complex biological processes, crucial in shaping phenotypic diversity. Thus, it is imperative to explore the factors regulating milk production and lactation for this breed. In this study, we investigated the genetic architecture of seven milk traits in MUGs, employing a two-step computational analysis to examine genotype–phenotype associations. Initially, a random forest algorithm identified the relative importance of each single-nucleotide polymorphism (SNP) in determining the traits of interest. The second step applied an information theory-based approach to exploring the complex genetic architecture of quantitative milk traits, focusing on epistatic interactions that may have been overlooked in the first step. These approaches allowed us to identify an almost distinct set of candidate genes for each trait. In contrast, by analyzing the promoter regions of these genes, we revealed common regulatory networks among the milk traits under study. These findings are crucial for understanding the molecular mechanisms underlying gene regulation, and they highlight the pivotal role of transcription factors (TFs) and their preferential interactions in the development of these traits. Notably, TFs such as DBP, HAND1E47, HOXA4, PPARA, and THAP1 were consistently identified for all traits, highlighting their important roles in immunity within the mammary gland and milk production during lactation. Full article

A traditional mug shot is a front and side view of a person from the shoulder up, taken by law enforcement. Forensic science is exploring the benefit of working with 3D data offered by new technologies, and there is an increasing need to work with 3D mug shots. Among the various available techniques, a multi-view photogrammetric approach achieves the highest accuracy in the shortest acquisition time. In this work, a multi-view photogrammetric system for facial reconstruction based on low-cost cameras is developed with the aims of verifying the performance of such cameras for the production of a 3D mug shot with submillimetre accuracy and assessing the improvement of facial matching using a 3D mug shot over traditional 2D mug shots. The tests were carried out in both a virtual and a real-world environment, using either a virtual or a 3D-printed 3D model. The outcome is a point cloud, which describes the face. The quantitative analysis of the errors was realized through the distances between the mesh of the acquired 3D model and the point cloud. A total of 80% of the points with a distance of less than ±1 mm was obtained. Finally, the performance on facial recognition of the 3D mug shot is evaluated against the traditional 2D mug shot using the NeoFace Watching software (NeoFACE) with a score increment of up to 0.42 points, especially in scenarios where the suspect is not captured from a frontal view. Full article

Plant seedling morphogenesis is considerably related to photosynthesis, pigment synthesis, and circadian periodicity during seedling development. We identified and cloned a maize zebra or crossbanding leaves mutant wk3735, which produces pale white kernels and was identified and plays a role in the equilibrium of the Redox state the in/out of ETC by active oxygen scavenging. Interestingly, it produces the zebra leaves during the production of the first seven leaves, which is apparently different from the mutation of homologs AtPTOX in Arabidopsis. It is intriguing to investigate how and why yellow crossbands (zebra leaf phenotype) emerge on leaves. As expected, chlorophyll concentration and photosynthetic efficiency both significantly declined in the yellow sector of wk3735 leaves. Meanwhile, we observed the circadian expression pattern of ZmPTOX1, which was further validated by protein interaction assays of the circadian clock protein TIM1 and ZmPTOX1. The transcriptome data of yellow (muW) and green (muG) sectors of knock-out lines and normal leaves of overexpression lines (OE) at the 5th-leaf seedling stage were analyzed. Zebra leaf etiolated sections exhibit a marked defect in the expression of genes involved in the circadian rhythm and rhythmic stress (light and cold stress) responses than green sections. According to the analysis of co-DEGs of muW vs. OE and muG vs. OE, terms linked to cell repair function were upregulated while those linked to environmental adaptability and stress response were downregulated due to the mutation of ZmPTOX1. Further gene expression level analyses of reactive oxygen species (ROS) scavenging enzymes and detection of ROS deposition indicated that ZmPTOX1 played an essential role in plant stress resistance and ROS homeostasis. The pleiotropic roles of ZmPTOX1 in plant ROS homeostasis maintenance, stress response, and circadian rhythm character may collectively explain the phenotype of zebra leaves during wk3735 seedling development. Full article

Species-unique genes that encode specific proteins and have no homologs in other species play certain roles in the evolution of species and adaptations to external environments. Nevertheless, the biological roles of unique genes in plant pathogenic fungi remain largely unknown. Here, four Magnaporthe-unique genes (MUG1–MUG4), which were highly expressed during the early infection stages, were functionally characterized in the rice blast fungus Magnaporthe oryzae. Subcellular localization assays revealed that Mug1, Mug2, and Mug4 were localized to the cytoplasm and that Mug3 was localized into the nuclei. Furthermore, through gene knockout and phenotypic analysis, only MUG1 was found to be indispensable for fungal virulence and conidiation. Detailed microscopic analysis revealed that the deletion mutants of MUG1 clearly exhibited reduced appressorial turgor pressure and invasive hyphal development. Taken together, our findings indicate that the Magnaporthe-unique gene MUG1 plays a vital role in infection-related morphogenesis and virulence in rice blast fungi and suggest the specific and important roles of species-unique genes. Full article

Neutron diffraction instruments offer a platform for materials science and engineering studies at extended temperature ranges far from ambient. As one of the widely used neutron sample environment types, cryogenic furnaces are usually bulky and complex, and they may need hours of beamtime overhead for installation, configuration, cooling, and sample change, etc. To reduce the overhead time and expedite experiments at the state-of-the-art high-flux neutron source, we developed a low-cost, miniature, and easy-to-use cryogenic environment (77–473 K) for in situ neutron diffraction. A travel-size mug serves for the environment where the samples sit inside. Immediate cooling and an isothermal dwell at 77 K are realized on the sample by direct contact with liquid N₂ in the mug. The designed Al inserts serve as the holder of samples and heating elements, alleviate the thermal gradient, and clear neutron pathways. Both a single-sample continuous measurement and multi-sample high-throughput measurements are demonstrated in this environment. High-quality and refinable in situ neutron diffraction patterns are acquired on model materials. The results quantify the orthorhombic-to-cubic phase transformation process in LiMn₂O₄ and differentiate the anisotropic lattice thermal expansions and bond length evolutions between rhombohedral perovskite oxides with composition variation. Full article

The quality of urban green space has an impact on the health and well-being of populations. Previous studies have shown that consideration of crowd activity characteristics is the key premise of landscape space design and planning. However, there is limited research on the correlation between features of the spatial layout of Mini Urban Green Spaces (MUGS) and the behavior of people, and it is difficult to take into account the possible distribution of people and their activity characteristics during the design phase of MUGS. This study aims to construct a technical workflow utilizing the AnyLogic platform and agent-based simulation methods for analyzing the characteristics of landscape spatial layouts considering dynamic human behavior. One MUGS, named 511 Park in Nanjing, China, was selected as the case for the application of the method and exploration of the impacts of spatial elements and layout on crowd activity types and density. We investigated the impact of four types of spatial elements—paths, facilities, nodes, and entrances—on human activities in MUGS. The results showed that path layout emerged as the most significant influencing factor. Changes in nodes and the number of facilities have a relatively minor impact on people’s activities. There was an apparent impact of changes in path orientation around nodes on the dynamics of the flow of people. This study could provide valuable insights for landscape designers, aiding informed decision-making during the construction, renovation, and management of MUGS. Full article