Search Results (19)

Packing food into lunch boxes requires the correct portion to be selected. Food items such as fried chicken, eggs, and sausages are straightforward to manipulate when packing. In contrast, deformable objects like spaghetti can give challenges to lunch box packing due to their fragility and tendency to break apart, and the fluctuating weight of noodles. Furthermore, achieving the correct amount is crucial for lunch box packing. This research focuses on self-learned grasping by a robotic arm to enable the ability to autonomously predict and grasp deformable objects, specifically spaghetti, to achieve the correct amount within specified ranges. We utilize deep reinforcement learning as the core learning. We developed a custom environment and policy network along a real-world scenario that was simplified as in a food factory, incorporating multi-sensors to observe the environment and pipeline to work with a real robotic arm. Through the study and experiments, our results show that the robot can grasp the spaghetti within the desired ranges, although occasional failures were caused by the nature of the deformable object. Addressing the problem under varying environmental conditions such as data augmentation can partially help model prediction. The study highlights the potential of combining deep learning with robotic manipulation for complex deformable object tasks, offering insight for applications in automated food handling and other industries. Full article

As a crucial characteristic waterfowl breed, the egg-laying performance of Lion-Headed Geese serves as a core indicator for precision breeding. Under large-scale flat rearing and selection practices, high phenotypic similarity among individuals within the same pedigree coupled with traditional manual observation and existing automation systems relying on fixed nesting boxes or RFID tags has posed challenges in achieving accurate goose–egg matching in dynamic environments, leading to inefficient individual selection. To address this, this study proposes YOLO-Goose, an improved YOLOv8s-based method, which designs five high-contrast neck rings (DoubleBar, Circle, Dot, Fence, Cylindrical) as individual identifiers. The method constructs a lightweight model with a small-object detection layer, integrates the GhostNet backbone to reduce parameter count by 67.2%, and employs the GIoU loss function to optimize neck ring localization accuracy. Experimental results show that the model achieves an F1 score of 93.8% and mAP50 of 96.4% on the self-built dataset, representing increases of 10.1% and 5% compared to the original YOLOv8s, with a 27.1% reduction in computational load. The dynamic matching algorithm, incorporating spatiotemporal trajectories and egg positional data, achieves a 95% matching rate, a 94.7% matching accuracy, and a 5.3% mismatching rate. Through lightweight deployment using TensorRT, the inference speed is enhanced by 1.4 times compared to PyTorch-1.12.1, with detection results uploaded to a cloud database in real time. This solution overcomes the technical bottleneck of individual selection in flat rearing environments, providing an innovative computer-vision-based approach for precision breeding of pedigree Lion-Headed Geese and offering significant engineering value for advancing intelligent waterfowl breeding. Full article

Probiotics like Lactobacillus rhamnosus GG (LRGG) offer health benefits but face reduced viability under harsh gastrointestinal (GI) conditions. Encapsulation improves stability, yet most studies rely on static GI models with a simplified environment that may overestimate survival. This study assessed LRGG survival using chitosan-coated alginate beads under both static and dynamic GI models, including peristaltic flow and continuous juice replenishment. Food matrices (casein, corn starch, and soybean oil) were tested in static models. Beads were prepared via extrusion and subjected to simulated gastric and intestinal digestion. After 2 and 4 h of digestion, casein preserved LRGG viability at 8.50 ± 0.11 Log CFU/g, compared to 5.81 ± 0.44 with starch and undetectable levels with soybean oil. Casein’s protective effect was attributed to its pH-buffering capacity, raising gastric pH from 2.5 to 4.6. Starch offered moderate protection, while soybean oil led to bead dissolution due to destabilization of the egg-box structure. Dynamic GI models showed greater reductions in LRGG viability than static models, emphasizing the need for physiologically relevant simulations. The results highlight the importance of selecting appropriate food matrices and digestion models for accurate probiotic assessment, supporting improved encapsulation strategies in functional food development. Full article

The routine culling of male chicks in the laying hen industry raises significant ethical, animal welfare, and sustainability concerns. Current methods to determine chick embryo sex before hatching are costly, time-consuming, and invasive. This study aimed to develop a low-cost, non-invasive solution to predict chick embryo sex before hatching using the morphological features of eggs. A custom imaging apparatus was created using a smartphone and light box, enabling consistent image capture of chicken eggs. Egg length, width, area, eccentricity, and extent were measured, and machine learning models were trained to predict chick embryo sex. The wide neural network model achieved the highest accuracy of 88.9% with a mean accuracy of 81.5%. Comparison of the imaging apparatus to a high-cost industrial 3D scanner demonstrated comparable accuracy in capturing egg morphology. The findings suggest that this method can contribute to the prevention of up to 6.2 billion male chicks from being culled annually by destroying male embryos before they develop the capacity to feel pain. This approach offers a feasible, ethical, and scalable alternative to current practices, with potential for further improvements in accuracy and adaptability to different industry settings. Full article

Artificial light at night (ALAN) and noise pollution are two important stressors associated with urbanisation that can have a profound impact on animal behaviour and physiology, potentially disrupting biological rhythms. Although the influence of ALAN and noise pollution on daily activity patterns of songbirds has been clearly demonstrated, studies often focus on males, and the few that examined females have not included the potential influence of males on female activity patterns. Using free-living pairs of great tits (Parus major) as a model, we examined for the first time the effects of ALAN and noise pollution and their interaction on the onset of (vocal) activity in both members of a pair. We focused on the egg-laying phase, when both sexes are most vocally active. The onset of male dawn song, female emergence time from the nest box and the onset of female calling in the nest box were measured and used as a proxy for the chronotype. The repeatabilities for all chronotype proxies were high, with higher repeatabilities for males. Consistent with previous studies, ALAN advanced the onset of male dawn song, while it did not elicit a strong response in female emergence time. Additionally, our results suggest an indirect effect of ALAN on the onset of female vocal activity via acoustic interaction with the male. Noise pollution advanced the emergence time in females, while an interaction between ALAN and noise pollution was found for the onset of female calling. In agreement with previous studies, several covariables were shown to have an influence on the activity onset. Taking several proxies for chronotype into account, this study has provided robust evidence of effects of ALAN on male and female cavity-nesting songbirds during the egg-laying period. Full article

Salted duck egg yolk, a key ingredient in various specialty foods in China, frequently contains broken eggshell fragments embedded in the yolk due to high-speed shell-breaking processes, which pose significant food safety risks. This paper presents an online detection method, YOLOv7-SEY-DeepSORT (salted egg yolk, SEY), designed to integrate an enhanced YOLOv7 with DeepSORT for real-time and accurate identification of salted egg yolks with impurities on production lines. The proposed method utilizes YOLOv7 as the core network, incorporating multiple Coordinate Attention (CA) modules in its Neck section to enhance the extraction of subtle eggshell impurities. To address the impact of imbalanced sample proportions on detection accuracy, the Focal-EIoU loss function is employed, adaptively adjusting bounding box loss values to ensure precise localization of yolks with impurities in images. The backbone network is replaced with the lightweight MobileOne neural network to reduce model parameters and improve real-time detection performance. DeepSORT is used for matching and tracking yolk targets across frames, accommodating rotational variations. Experimental results demonstrate that YOLOv7-SEY-DeepSORT achieves a mean average precision (mAP) of 0.931, reflecting a 0.53% improvement over the original YOLOv7. The method also shows enhanced tracking performance, with Multiple Object Tracking Accuracy (MOTA) and Multiple Object Tracking Precision (MOTP) scores of 87.9% and 73.8%, respectively, representing increases of 17.0% and 9.8% over SORT and 2.9% and 4.7% over Tracktor. Overall, the proposed method balances high detection accuracy with real-time performance, surpassing other mainstream object detection methods in comprehensive performance. Thus, it provides a robust solution for the rapid and accurate detection of defective salted egg yolks and offers a technical foundation and reference for future research on the automated and safe processing of egg products. Full article

More than 40 hypotheses predict associations between features of nest architecture and at least one measure of reproductive success. However, quantitative studies of reproductive consequences of nest characteristics remain scarce. In addition, most studies were conducted on model species of which nests can be easily monitored with artificial nest-boxes. Here, we review the replicability of research protocols and findings in model species, with many repeat studies focusing mainly on nest-size components, animal-derived nest material, or fresh greenery in model species of secondary hole-nesting birds: Blue Tits (Cyanistes caeruleus), Great Tits (Parus major), Tree Swallows (Tachycineta bicolor), and Starlings (Sturnus spp.). The studies looked for correlations between nest traits and aspects of breeding performance that can be easily quantified in the field, such as clutch size, brood size at hatching or fledging, the percentage of eggs that hatch or fledge, or nestling characteristics assumed to reflect qualities associated with survival probabilities (e.g., morphometry, body condition, blood profiles). We discuss the consequences of poor replicability of research methodologies and provide explanations for why many of these studies reported poor associations between nest design and breeding success at different spatiotemporal scales. We also make suggestions for future research. Full article

This study considers the potential of elemental analysis of polysaccharide ionotropic gels in elucidating the junction zones for different divalent cations. The developed algorithm ensures the correct separation of contributions from physically adsorbed and structure-forming ionic compounds, with the obtained results scaled to alginate C₁₂ block. Possible versions of chain association into dimers and their subsequent integration into flat junction zones were analyzed within the framework of the “egg-box” model. The application of combinatorial analysis made it possible to derive theoretical relations to find the probability of various types of egg-box cell occurrences for alginate chains with arbitrary monomeric units ratio μ = M/G, which makes it possible to compare experimental data for alginates of different origins. Based on literature data and obtained chemical formulas, the possible correspondence of concrete biopolymer cells to those most preferable for filling by alkaline earth cations was established. The identified features of elemental composition suggest the formation of composite hydrated complexes with the participation of transition metal cations. The possibility of quantitatively assessing ordered secondary structures formed due to the physical sorption of ions and molecules from environment, correlating with the sorption capabilities of Me²⁺ alginate, was established. Full article

Structure and reversibility of cross-link junctions play pivotal roles in determining the nature of thermoreversible gelation and dynamic mechanical properties of the produced polymer networks. We attempt to theoretically explore new types of sol–gel transitions with mechanical sharpness by allowing cross-links to grow without upper bound. We consider thermoreversible gelation of the primary molecules R{A${}_f$} carrying the number f of low molecular weight functional groups (gelators) A. Gelators A are assumed to form supramolecular assemblies. Some examples are: telechelic polymers ($f=2$) carrying $\pi$–$\pi$ stacking benzene derivatives at their both ends, and trifunctional star molecules ($f=3$) bearing multiple hydrogen-bonding gelators. The sol–gel transition of the primary molecules becomes sharper with the cooperativity parameter of the stepwise linear growth of the cross-links. There is a polymerization transition (crossover without singularity) of the junctions in the postgel region after the gel point is passed. If the gelator A tends to form supramolecular rings competitively with linear chains, there is another phase transition in the deep postgel region where the average molecular weight of the rings becomes infinite (Bose–Einstein condensation of rings). As a typical example of binary cross-links where gelators A and B form mixed junctions, we specifically consider metal-coordinated binding of ligands A by metal ions B. Two types of multi-nuclear supramolecular complexes are studied: (i) linear stacking (ladder) of the sandwich A${}_2$B units, and (ii) linear train of egg-box A${}_4$B units. To find the strategy towards experimental realization of supramolecular cross-links, the average molecular weight, the gel fraction, the average length of the cross-link junctions are numerically calculated for all of these models as functions of the functionality f, the concentration of the solute molecules, and the temperature. Potential candidates for the realization of these new types of thermoreversible gelation are discussed. Full article

The identification of a chicken’s sex is a massive task in the poultry industry. To solve the problems of traditional artificial observation in determining sex, such as time-consuming and laborious, a sex identification method of chicken embryos based on blood vessel images and deep learning was preliminarily investigated. In this study, we designed an image acquisition platform to capture clear blood vessel images with a black background. 19,748 images of 3024 Jingfen No. 6 breeding eggs were collected from days 3 to 5 of incubation in Beijing Huadu Yukou Poultry Industry. Sixteen thousand seven hundred sixty-one images were filtered via color sexing in 1-day-old chicks and constructed the dataset of this study. A sex identification model was proposed based on an improved YOLOv7 deep learning algorithm. An attention mechanism CBAM was introduced for YOLOv7 to improve the accuracy of sex identification of chicken eggs; the BiFPN feature fusion was used in the neck network of YOLOv7 to fuse the low-level and high-level features efficiently; and α-CIOU was used as the bounding box loss function to accelerate regression prediction and improve the positioning accuracy of the bounding box of the model. Results showed that the mean average precision (mAP) of 88.79% was achieved by modeling with the blood vessel data on day 4 of incubation of chicken eggs, with the male and female reaching 87.91% and 89.67%. Compared with the original YOLOv7 network, the mAP of the improved model was increased by 3.46%. The comparison of target detection model results showed that the mAP of our method was 32.49%, 17.17%, and 5.96% higher than that of SSD, Faster R-CNN, and YOLOv5, respectively. The average image processing time was 0.023 s. Our study indicates that using blood vessel images and deep learning has great potential applications in the sex identification of chicken embryos. Full article

Pectate and alginate are among the most important biopolymers able to give rise to ionotropic gelation upon the addition of di- or multivalent counterions. The two ionic polysaccharides exhibit several common aspects of the gelation mechanism with calcium ions, the physiologically and commercially most relevant counterion type. The first one pertains to the role that specific Ca²⁺/polyion interactions play in the establishment of the ion-mediated chain/chain cross-links. Such interactions include both a specific affinity of the territorially condensed Ca²⁺ counterions for the polyuronate(s) and the formation of long-lasting chemical bonding (inner ion–sphere complex) of specific interchain sites accompanied by high conformational ordering. As to the first mechanism, it is dominated by the strong desolvation of the interacting ionic species, with concomitant positive variations in both enthalpy and entropy, the contribution of the latter prevailing over the former due to the favorable liberation of a very large number of water molecules of hydration. Both dilatometric and microcalorimetric data point to the higher affinity of Ca²⁺ for pectate than for alginate. The selective accumulation of calcium ions close to the polyanion(s) favors the onset of the second—chemical bonding—mode, which is associated with charge neutralization at the bonding site. This mode coincides with the largely accepted “egg-box” model for the calcium-mediated interchain junction of pectate and alginate. A new approach was devised for the calculation of the fraction of chemically bound divalent ions; it was based on the available circular dichroism data (further supported by scattering and viscosity results) and successfully tested by comparison with an independently determined fraction in the case of pectate. In detail, the strong bonding mode manifests in two sequential bonding modes. The first one (at low concentrations of added Ca²⁺ ions) entails a cross-link in which only one calcium ions is bracketed in a “twisted” egg-box between two chains; upon further counterion addition, a series of nearest-neighboring “perfect” egg-box structures develops. Both dilatometric and microcalorimetric changes associated with the latter chemical bonding modes are quantitatively larger for pectate than for alginate; clearly the latter polyuronate suffers from the relevant presence of the weakly calcium-binding mannuronic acid repeating units. Light-scattering experiments provided a clear-cut demonstration of the intermolecular bonding of calcium ions from the very beginning of the linker addition. Full article

Europe calls for a transition to the circular economy model based on recycling, reuse, the proper design of products, and repair. Recycling requires energy and chemical products for waste processing; on the contrary, reusing reduces the impact of transportation and expands the life of materials that cannot be recycled. This article highlights the characteristics of selected end-of-life materials; it aims to raise awareness among manufacturers to consider products’ conscious design to facilitate their reuse in different sectors. Panels 7 cm thick, realized by assembling cardboard packaging, egg boxes, bulk polyester, and felt, have been experimentally tested to understand whether they can be installed indoors to improve thermal and acoustic comfort. The panels’ equivalent thermal conductivity ${\lambda }_{eq}$ measured through the guarded hot plate method is 0.071 W/mK. Acoustic tests have been performed in a sound transmission room and a reverberation room. The weighted sound reduction index $R_w$ is 19 dB, the weighted sound absorption coefficient ${\alpha }_w$ is 0.30, and the noise reduction coefficient $NRC$ is 0.64. The measured properties have been compared to those of commercial materials, and the results show that the panels have interesting properties from the thermal and acoustic points of view. They could be employed in the building sector and in disadvantaged contexts where low-income people cannot afford commercial insulating materials. Although other factors, such as fire resistance, need to be evaluated, these results show that the proposed approach is feasible. Full article

Schistosomiasis is a chronic helminthic disease of both humans and animals and the second most prevalent parasitic disease after malaria. Through a complex migration process, schistosome eggs trapped in the liver can lead to the formation of granulomas and subsequent schistosome-induced liver damage, which results in high mortality and morbidity. Although praziquantel can eliminate mature worms and prevent egg deposition, effective drugs to reverse schistosome-induced liver damage are scarce. High mobility group box 1 (HMGB1) is a multifunctional cytokine contributing to liver injury, inflammation, and immune responses in schistosomiasis by binding to cell-surface Toll-like receptors and receptors for advanced glycation end products. HMGB1 is increased in the serum of patients with schistosomiasis and enables hepatic stellate cells to adopt a proliferative myofibroblast-like phenotype, which is crucial to schistosome-induced granuloma formation. Inhibition of HMGB1 was found to generate protective responses against fibrotic diseases in animal models. Clinically, HMGB1 presents a potential target for treatment of the chronic sequelae of schistosomiasis. Here, the pivotal role of HMGB1 in granuloma formation and schistosome-induced liver damage, as well the potential of HMGB1 as a therapeutic target, are discussed. Full article

Enzymatic acidolysis of egg-yolk phosphatidylcholine (PC) with 3-methoxycinnamic acid (3-OMe-CA) was investigated to produce biologically active 3-methoxycinnamoylated phospholipids. Four commercially available lipases were screened for their ability to incorporate 3-OMe-CA into PC. The results showed that Novozym 435 is the most effective biocatalyst for this process, while during the examination of organic solvents, heptane was found propriate reaction medium. The other reaction parameters including the substrate molar ratio, enzyme load and reaction time were designed using an experimental factorial design method. According to three-level-3-factor Box-Behnken model it was shown that all of studied parameters are crucial variables for the maximization of the synthesis of structured PLs. The optimum conditions derived via response surface methodology (RSM) were: 30% of lipase of the total weight of substrates, 1:15 molar ration of PC/3-OMe-CA and reaction time 4 days. The process of acidolysis performed on the increased scale at optimized parameters afforded two products. The major product, 3-methoxycinnamoylated lysophosphatidylcholine (3-OMe-CA-LPC) was isolated in high 48% yield, while 3-methoxycinnamoylated phosphatidylcholine (3-OMe-CA-PC) was produced in trace amount only in 1.2% yield. Obtained results indicate that presented biotechnological method of synthesis of 3-methoxycinnamoylated lysophosphatidylcholine is competitive to the previously reported chemical one. Full article

Chitin oligosaccharides (COs) hold high promise as organic fertilizers in the ongoing agro-ecological transition. Short- and long-chain COs can contribute to the establishment of symbiotic associations between plants and microorganisms, facilitating the uptake of soil nutrients by host plants. Long-chain COs trigger plant innate immunity. A fine investigation of these different signaling pathways requires improving the access to high-purity COs. Here, we used the response surface methodology to optimize the production of COs by enzymatic hydrolysis of water-soluble chitin (WSC) with hen egg-white lysozyme. The influence of WSC concentration, its acetylation degree, and the reaction time course were modelled using a Box–Behnken design. Under optimized conditions, water-soluble COs up to the nonasaccharide were formed in 51% yield and purified to homogeneity. This straightforward approach opens new avenues to determine the complex roles of COs in plants. Full article