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Rechargeable Mg batteries are promising candidates for achieving considerable high-energy-density. Enhancing the energy density can be achieved by integrating metallic Mg anodes with conversion-type cathode materials, which are characterized by multi-electron transfer process and elevated specific capacities in contrast to intercalation-type materials. Despite these advantages, the conversion-type cathodes still have some challenges of substantial volume expansion, sluggish diffusion kinetics and intricate mesophase evolution during repeated electrochemical reactions. Herein, first-principles calculations were performed to probe into the electronic properties, Mg2+ dynamical properties, Bader charge and electrochemical mechanism of spinel-type sulfides (M3S4, M = Co and Ni). The band gap values of Co3S4 and Ni3S4 are 0.28 and 0 eV, respectively, showing their superior electrical conductivity. The preferential order of Mg intercalation sites is 16c > 48f > 8b. Computational predictions of the formation energy and discharge voltage indicate that spinel Ni3S4 can exhibit a relatively high specific discharge capacity of 220.8 mA h g−1 and an average voltage of ∼1.6 V vs. Mg2+/Mg with an energy density of 353.3 W h kg−1 at a Mg intercalation concentration of x 2+Mg = 1.25, surpassing those of Co3S4 and Mo6S8. According to the principle of the lowest barrier, the diffusion pathway "oct → tet → oct" of spinel sulfides Co3S4 and Ni3S4 has low Mg migration barrier values of 1.10 and 0.67 eV, respectively. The Bader charge and AIMD results revealed that the spinel M3S4 (M = Co and Ni) underwent conversion reactions to the rock-salt phase especially at deep discharge. These insights significantly advance the rational design of spinel sulfides with a conversion reaction mechanism, providing great potential for the development of Mg batteries with high energy density. [ABSTRACT FROM AUTHOR]

Lighting is crucial for the development of broilers as it affects their growth performance, oxidative stress, and overall health. This study investigates the impact of full-spectrum light, infrared light, and LED white light exposure on the growth performance, oxidative stress markers, and cecal microbiota of medium-growth yellow-feathered broilers. A total of 216 medium-growth yellow-feathered chicks (Yuhuang No. 5), five days old, were randomly divided into three groups: 72 chicks in each group, with three replicates of 24 chicks. The birds were raised under different lighting conditions, including LED infrared light (II), full-spectrum therapy light (FB), and LED white light (CG) until day 87. This experiment comprised the early growth phase and measured critical hormones such as Melatonin (Mel), Growth Hormone (GH), and Growth Hormone Releasing Hormone (GHRH), as well as Malondialdehyde (MDA), Superoxide Dismutase (SOD), and Catalase (CAT). Additionally, this study examined the differences in microbiota diversity and composition. The results demonstrated that LED infrared and full-spectrum light exposure significantly (p < 0.05) increased broiler body weight. Particularly, full-spectrum light was effective in comb redness and reducing final comb length and oxidative stress. Furthermore, full-spectrum light improved microbial prosperity and diversity compared with the other lighting conditions. Overall, the findings suggest that full-spectrum lighting is more beneficial for broiler growth, reducing oxidative stress, and promoting gut health compared with LED infrared lighting. These insights can be applied to optimizing broiler farming practices, thereby improving productivity and animal welfare. [ABSTRACT FROM AUTHOR]

Eggs are a rich food source of proteins, fats, vitamins, minerals, and other nutrients. However, the egg industry faces some challenges such as microbial invasion due to environmental factors, leading to damage and reduced usability. Therefore, detecting the freshness of raw eggs using various technologies, including traditional and non-destructive methods, can overcome these challenges. As the traditional methods of assessing egg freshness are often subjective and time-consuming, modern non-destructive technologies, including near-infrared (NIR) spectroscopy, Raman spectroscopy, fluorescence spectroscopy, computer vision (color imaging), hyperspectral imaging, electronic noses, and nuclear magnetic resonance, have offered objective and rapid results to address these limitations. The current review summarizes and discusses the recent advances and developments in applying non-destructive technologies for detecting raw egg freshness. Some of these technologies such as NIR spectroscopy, computer vision, and hyperspectral imaging have achieved an accuracy of more than 96% in detecting egg freshness. Therefore, this review provides an overview of the current trends in the state-of-the-art non-destructive technologies recently utilized in detecting the freshness of raw eggs. This review can contribute significantly to the field of emerging technologies in this research track and pique the interests of both food scientists and industry professionals. [ABSTRACT FROM AUTHOR]

This study investigates the geometrical and mechanical properties of two cassava varieties: 'Newly Elected No. 48' and 'Jin Yue HRMUS'. We analyzed various properties, including width, length, geometric diameter, thickness, compression firmness, shape ratio, surface area, shear strength, rupture force, and shear rupture force (SRF), at different moisture content (MC) levels ranging from 35.0 to 80.0% wet basis. Our findings indicate that all mechanical properties of cassava (MPC) were significantly influenced by moisture content within this range. Specifically, as moisture content decreases, the compression rupture force (CRF) increases linearly in the vertical direction, while a quadratic relationship is observed in the horizontal direction, characterized by an initial increase followed by a decrease. Additionally, a quadratic relationship was established between moisture content and firmness. In contrast, shear fracture force and strength exhibited a quadratic relationship that decreased initially and then increased with rising moisture content. Furthermore, both compression and shear fracture forces were significantly higher in the vertical loading direction compared to the horizontal direction. Notably, the 'Jin Yue HRMUS' variety demonstrated greater mechanical strength than the 'Newly Elected No. 48'. These findings provide valuable insights for developing, optimizing, and evaluating cassava harvesting and processing machinery. [ABSTRACT FROM AUTHOR]

Meta‐analysis produces a quantitative synthesis of evidence‐based knowledge, shaping not only research trends but also policies and practices in biology. However, two statistical issues, selective reporting and statistical dependence, can severely distort meta‐analytic parameter estimation and inference.Here, we re‐analyse 448 meta‐analyses to demonstrate a new two‐step procedure to deal with two common challenges in biological meta‐analyses that often occur simultaneously: publication bias and non‐independence. First, we employ bias‐robust weighting schemes under the generalized least square estimator to obtain average effect sizes that are more robust to selective reporting. We then use cluster‐robust variance estimation to account for statistical dependence, reducing bias in estimating standard errors and ensuring valid statistical inference.The first step of our approach demonstrates comparable performance in estimating average effect sizes to the existing publication‐bias adjustment methods in the presence of selective reporting. This equivalence holds across two publication bias selection processes. The second step achieves estimates of standard errors consistent with the multilevel meta‐analytic model, a benchmark method with adequate control of Type I error rates for multiple, statistically dependent effect sizes. Re‐analyses of 448 meta‐analyses show that ignoring these two issues tends to overestimate effect sizes by an average of 110% and underestimate standard errors by 120%.To facilitate implementation, we have developed a website including a step‐by‐step tutorial. Complementing current meta‐analytic workflows with the proposed method as a sensitivity analysis can facilitate a transition to a more robust approach in quantitative evidence synthesis. [ABSTRACT FROM AUTHOR]

Simple Summary: The poultry industry is advancing through a focus on nutrition, management practices, and technology to enhance productivity by improving feed conversion ratios, disease control, lighting management, and exploring antibiotic; alternatives. Infrared (IR) radiation, with wavelengths ranging from 760 to 10,000 nm, is being used to improve the well-being of humans, animals, and poultry. IR applications like heating, spectroscopy, beak trimming, and other therapies offer health benefits such as improved skin health, wound healing, and enhanced immune responses. In poultry production, IR radiation positively impacts growth performance, gut health, blood profiles, and food safety. Despite its benefits, applications of IR in poultry are limited but show promise for wider adoption. This innovative approach has the potential to revolutionize traditional practices in the industry by optimizing productivity and efficiency while improving animal welfare. The poultry industry is dynamically advancing production by focusing on nutrition, management practices, and technology to enhance productivity by improving feed conversion ratios, disease control, lighting management, and exploring antibiotic alternatives. Infrared (IR) radiation is utilized to improve the well-being of humans, animals, and poultry through various operations. IR radiation occurs via electromagnetic waves with wavelengths ranging from 760 to 10,000 nm. The biological applications of IR radiation are gaining significant attention and its utilization is expanding rapidly across multiple sectors. Various IR applications, such as IR heating, IR spectroscopy, IR thermography, IR beak trimming, and IR in computer vision, have proven to be beneficial in enhancing the well-being of humans, animals, and birds within mechanical systems. IR radiation offers a wide array of health benefits, including improved skin health, therapeutic effects, anticancer properties, wound healing capabilities, enhanced digestive and endothelial function, and improved mitochondrial function and gene expression. In the realm of poultry production, IR radiation has demonstrated numerous positive impacts, including enhanced growth performance, gut health, blood profiles, immunological response, food safety measures, economic advantages, the mitigation of hazardous gases, and improved heating systems. Despite the exceptional benefits of IR radiation, its applications in poultry production are still limited. This comprehensive review provides compelling evidence supporting the advantages of IR radiation and advocates for its wider adoption in poultry production practices. [ABSTRACT FROM AUTHOR]

The characteristics of chicken droppings are closely linked to their health status. In prior studies, chicken droppings recognition is treated as an object detection task, leading to challenges in labeling and missed detection due to the diverse shapes, overlapping boundaries, and dense distribution of chicken droppings. Additionally, the use of intelligent monitoring equipment equipped with edge devices in farms can significantly reduce manual labor. However, the limited computational power of edge devices presents challenges in deploying real-time segmentation algorithms for field applications. Therefore, this study redefines the task as a segmentation task, with the main objective being the development of a lightweight segmentation model for the automated monitoring of abnormal chicken droppings. A total of 60 Arbor Acres broilers were housed in 5 specific pathogen-free cages for over 3 wk, and 1650 RGB images of chicken droppings were randomly divided into training and testing sets in an 8:2 ratio to develop and test the model. Firstly, by incorporating the attention mechanism, multi-loss function, and auxiliary segmentation head, the segmentation accuracy of the DDRNet was enhanced. Then, by employing the group convolution and an advanced knowledge-distillation algorithm, a lightweight segmentation model named DDRNet-s-KD was obtained, which achieved a mean Dice coefficient (mDice) of 79.43% and an inference speed of 86.10 frames per second (FPS), showing a 2.91% and 61.2% increase in mDice and FPS compared to the benchmark model. Furthermore, the DDRNet-s-KD model was quantized from 32-bit floating-point values to 8-bit integers and then converted to TensorRT format. Impressively, the weight size of the quantized model was only 13.7 MB, representing an 82.96% reduction compared to the benchmark model. This makes it well-suited for deployment on the edge device, achieving an inference speed of 137.51 FPS on Jetson Xavier NX. In conclusion, the methods proposed in this study show significant potential in monitoring abnormal chicken droppings and can provide an effective reference for the implementation of other agricultural embedded systems. [ABSTRACT FROM AUTHOR]

Poultry are sensitive to red objects, such as comb and blood on the body surface, likely inducing injurious pecking in flocks. Light is an important factor that affects the pecking behavior of poultry. A wooden box was built to investigate the effects of Light Emitting Diode (LED) light color (warm white and cold white) and intensity (5 and 50 lux) of background light on the discrimination of red objects in broilers. A piece of red photographic paper (Paper 1) was used to simulate a red object and paired with another piece of paper (Paper 2 to 8) with a different color. Bigger number of the paired paper indicated greater color difference. The experiment consisted of three phases: adaptation, training, and test. In the adaptation phase, birds were selected for the adaptation to reduce the stress from the box. In the training phase, birds were trained to discriminate and peck at Paper 1 when paired with Paper 8 under one type of background light. Twenty-three birds were tested when the paired paper was changed from Paper 7 to 2. Each pair of paper included 12 trials for every bird, and response time to peck and proportion of choices of Paper 1 in the last 10 trials were collected. The results showed that broilers tested under 5 lux light had longer response times than broilers tested under 50 lux light (P < 0.05). When Paper 1 was paired with paper 7, broilers tested under warm white light had lower proportion of choices of Paper 1 than those tested under cold white light (P < 0.05). Color difference had a significant effect on response time of broilers (P < 0.05). Moreover, the proportion of choices of Paper 1 decreased to 50% (chance-level performance) when color of the paired paper was gradually similar to Paper 1. Conclusively, rearing broilers in warm white rather than cold white light with appropriate light intensity should be recommended to reduce damaging pecking behavior in broiler production. [ABSTRACT FROM AUTHOR]

Simple Summary: Feather coverage reflects the production efficiency and animal welfare of poultry. Monitoring the feather-cover condition of chickens is of great significance. Infrared thermography can be used to evaluate the probable existence of inflammatory or tissue damage processes due to the variation in skin temperature, which can be used to objectively determine the depth of the feather damage. In this study, a 3D reconstruction pipeline of chicken monitoring was developed, with color, depth and thermal information for the comprehensive feather damage monitoring of chickens. The results demonstrated that the proposed method can better assess the feather damage compared to a 2D color image or thermal infrared image. The depth of chicken feather damage can be assessed by the 3D model. The method provided ideas for automation and intelligent feather-damage monitoring in poultry farming. Feather damage is a continuous health and welfare challenge among laying hens. Infrared thermography is a tool that can evaluate the changes in the surface temperature, derived from an inflammatory process that would make it possible to objectively determine the depth of the damage to the dermis. Therefore, the objective of this article was to develop an approach to feather damage assessment based on visible light and infrared thermography. Fusing information obtained from these two bands can highlight their strengths, which is more evident in the assessment of feather damage. A novel pipeline was proposed to reconstruct the RGB-Depth-Thermal maps of the chicken using binocular color cameras and a thermal infrared camera. The process of stereo matching based on binocular color images allowed for a depth image to be obtained. Then, a heterogeneous image registration method was presented to achieve image alignment between thermal infrared and color images so that the thermal infrared image was also aligned with the depth image. The chicken image was segmented from the background using a deep learning-based network based on the color and depth images. Four kinds of images, namely, color, depth, thermal and mask, were utilized as inputs to reconstruct the 3D model of a chicken with RGB-Depth-Thermal maps. The depth of feather damage can be better assessed with the proposed model compared to the 2D thermal infrared image or color image during both day and night, which provided a reference for further research in poultry farming. [ABSTRACT FROM AUTHOR]

The traditional direct torque control system of permanent magnet synchronous motor has many problems, such as large torque ripple and variable switching frequency. In order to improve the dynamic and static performance of the control system, a new torque control idea and speed sensorless control scheme are proposed in this paper. First, by deriving the equation of torque change rate, an improved torque controller is designed to replace the torque hysteresis controller of the traditional direct torque control. The improved direct torque control strategy can significantly reduce the torque ripple and keep the switching frequency constant. Then, based on the improved direct torque control and considering the sensitivity of the stator resistance to temperature change, a speed estimator based on the model reference adaptive method is designed. This method realizes the stator resistance on-line identification and further improves the control precision of the system. The performance of the traditional direct torque control and the improved direct torque control are compared by simulation and experiment under different operating conditions. The simulation and experimental results are presented to support the validity and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]