Construction of a grading model based on the quality characteristics of different grades of chicken wooden breast

The deterioration of wooden breast myofibrillar protein (WBMP) increases with the increase in wooden breast grades. In order to quickly and conveniently classify wooden breast to prevent waste of raw materials and unsuitable processing. Different grades of wooden breasts that exhibited mild, moderate, and severe degrees were collected, and correlation analysis was employed for the quality and WBMP functional characteristic indicators. The indicators were further classified into two components according to the principal component analysis method. Based on the correlation and variation coefficients, two main indicators were selected to represent the quality level of wooden breasts (redness (a*) and pH value (P)). The weights of the two indicators were 0.353 and 0.219 for a* and P, respectively, using the weighted coefficient method. Therefore, a formula for calculating the comprehensive evaluation score (y) of different grades of wooden breast meat was obtained: y = 0.353a* + 0.219P. Based on regression analysis, the fitting equation y = 2.407 1x + 0.0343 (R2 = 0.9883) was obtained, for the comprehensive quality score (y) and sensory evaluation score (x) through regression analysis, with a fitting coefficient ˃ 0.8. This equation can accurately predict sensory evaluation scores, effectively reflect the quality differences of different grades of wooden breasts, and accurately and rapidly grade wooden breasts

Blockchain-enabled Wireless IoT Networks with Multiple Communication Connections

Blockchain-enabled wireless network has been recognized as an emerging network architecture to be widely employed into the Internet of Things (IoT) ecosystems for establishing trust and consensus mechanisms without the involvement of a third party. However, the uncertainty and vulnerability of wireless channels among the IoT nodes may pose a serious challenge to facilitate the deployment of blockchain in wireless networks. In this paper, we first present a generic system model for blockchain enabled wireless networks with multiple communication connections, where the number of communication connections between a client IoT node and the blockchain full nodes can be any arbitrary positive integer to satisfy different security requirements. Based on the proposed spatial-temporal network model, we theoretically calculate the transmission successful probability and the required communication throughput to support a wireless blockchain network. Finally, simulation results validate the accuracy of our theoretical analysis

Global gross primary productivity and water use efficiency changes under drought stress

Drought can affect the structure, composition and function of terrestrial ecosystems, yet drought impacts and post-drought recovery potentials of different land cover types have not been extensively studied at a global scale. We evaluated drought impacts on gross primary productivity (GPP), evapotranspiration (ET), and water use efficiency (WUE) of different global terrestrial ecosystems, as well as the drought-resilience of each ecosystem type during the period of 2000 to 2011. Using GPP as biome vitality indicator against drought stress, we developed a model to examine ecosystem resilience represented by the length of recovery days (LRD). LRD presented an evident gradient of high (\u3e60 days) in mid-latitude region and low (\u3c60 days) in low (tropical area) and high (boreal area) latitude regions. As average GPP increased, the LRD showed a significantly decreasing trend, indicating readiness to recover after drought, across various land cover types (R 2 = 0.68, p \u3c 0.0001). Moreover, zonal analysis revealed that the most dramatic reduction of the drought-induced GPP was found in the mid-latitude region of the Northern Hemisphere (48% reduction), followed by the low-latitude region of the Southern Hemisphere (13% reduction). In contrast, a slightly enhanced GPP (10%) was evident in the tropical region under drought impact. Additionally, the highest drought-induced reduction of ET was found in the Mediterranean area, followed by Africa. Water use efficiency, however, showed a pattern of decreasing in the Northern Hemisphere and increasing in the Southern Hemisphere. Drought induced reductions of WUE ranged from 0.96% to 27.67% in most of the land cover types, while the increases of WUE found in Evergreen Broadleaf Forest and savanna were about 7.09% and 9.88%, respectively. These increases of GPP and WUE detected during drought periods could either be due to water-stress induced responses or data uncertainties, which require further investigation

Purchase or rent? Optimal pricing for 3D printing capacity sharing platforms

Online sharing platforms have attracted considerable research and management attention across a number of industries, including travel, real estate, and cloud computing. They also have great potential for the 3D printing (3DP) industry, offering users the choice between owning or renting 3DP capacity. For matching supply and demand, capacity pricing is crucial. In this paper we consider two fundamental questions concerning pricing: (i) What is the optimal pricing strategy for a 3DP capacity sharing platform? (ii) How do usage level and printer heterogeneity affect consumers’ choice between in-house printing (owning) and outsourcing (renting)? Using queuing analysis, we derive the structural properties of the solutions to the problems. Furthermore, we conduct numerical studies using real-world data to generate managerial insights from the analytical findings. A key finding is that governments should focus on encouraging technological progress to lower the printers’ prices in order to improve the well-being of the industry. When considering two types of printers, we find that it is more beneficial for the platform if the high capacity printer dominates the market, as the platform then retains the prominent role in “redistributing” the 3DP capacity.</p

Hepatoprotective mechanism of Silybum marianum on nonalcoholic fatty liver disease based on network pharmacology and experimental verification

The study aimed to identify the key active components in Silybum marianum (S. marianum) and determine how they protect against nonalcoholic fatty liver disease (NAFLD). TCMSP, DisGeNET, UniProt databases, and Venny 2.1 software were used to identify 11 primary active components, 92 candidate gene targets, and 30 core hepatoprotective gene targets in this investigation, respectively. The PPI network was built using a string database and Cytoscape 3.7.2. The KEGG pathway and GO biological process enrichment, biological annotation, as well as the identified hepatoprotective core gene targets were analyzed using the Metascape database. The effect of silymarin on NAFLD was determined using H&E on pathological alterations in liver tissues. The levels of liver function were assessed using biochemical tests. Western blot experiments were used to observe the proteins that were expressed in the associated signaling pathways on the hepatoprotective effect, which the previous network pharmacology predicted. According to the KEGG enrichment study, there are 35 hepatoprotective signaling pathways. GO enrichment analysis revealed that 61 biological processes related to the hepatoprotective effect of S. marianum were identified, which mainly involved in response to regulation of biological process and immune system process. Silymarin was the major ingredient derived from S. marianum, which exhibited the hepatoprotective effect by reducing the levels of ALT, AST, TC, TG, HDL-C, LDL-C, decreasing protein expressions of IL-6, MAPK1, Caspase 3, p53, VEGFA, increasing protein expression of AKT1. The present study provided new sights and a possible explanation for the molecular mechanisms of S. marianum against NAFLD

Do Emotional Faces Affect Inhibition of Return? An ERP Study

Inhibition of Return (IOR) refers to an individual’s slowed localization or discrimination performance for targets that appear in previously cued versus uncued location after a relatively long delay after cue (∼300–500 ms). The current study adopted a cue-target paradigm and used behavioral and event-related potential (ERP) measures to investigate whether IOR would be modulated by emotional faces during an emotion recognition task. For reaction time measure, we found IOR effect and the magnitude of IOR effect were comparable for fearful face target and neutral face target. For ERP measures, valid cues were associated with smaller P1 and larger N1 waveform than that for invalid cues. Fearful faces were associated with a larger N170 than neutral faces. The onset latency of the stimulus-locked lateralised readiness potential (LRP) in the valid cue condition was longer than that in the invalid cue condition, while there was no significant difference on the onset latency of the response-locked LRP between the valid cue and invalid cue condition. These results support the notion that, regardless the emotion component of the stimulus, the inhibitory bias of attention to previous visited location before response contributes to the IOR

Dickeya fangzhongdai was prevalent and caused taro soft rot when coexisting with the Pectobacterium complex, with a preference for Araceae plants

Bacterial soft rot caused by coinfection with Dickeya spp. and Pectobacterium spp. in hosts can cause successive changes in fields, and it is difficult to prevent the spread of and control the infection. Pectobacterium spp. are prevalent in the growing areas of tuberous crops, including taro and potato. Recently, Dickeya fangzhongdai has emerged as a virulent pathogen in taro. To determine the prevalence status of the causal agents and evaluate the potential spreading risks of D. fangzhongdai, screening and taxonomic classification were performed on phytopathogenic bacteria collected from different taro-growing areas in Guangdong Province, China, and biological and genomic characteristics were further compared among typical strains from all defined species. The causative agents were verified to be phytobacterial strains of D. fangzhongdai, Pectobacterium aroidearum and Pectobacterium colocasium. P. aroidearum and P. colocasium were found to form a complex preferring Araceae plants and show intensive genomic differentiation, indicating their ancestor had adapted to taro a long time prior. Compared with Pectobacterium spp., D. fangzhongdai was more virulent to taro corms under conditions of exogenous infection and more adaptable at elevated temperatures. D. fangzhongdai strains isolated from taro possessed genomic components of additional T4SSs, which were accompanied by additional copies of the hcp-vgrG genes of the T6SS, and these contributed to the expansion of their genomes. More gene clusters encoding secondary metabolites were found within the D. fangzhongdai strains than within the Pectobacterium complex; interestingly, distinct gene clusters encoding zeamine and arylpolyene were both most similar to those in D. solani that caused potato soft rot. These comparisons provided genomic evidences for that the newly emerging pathogen was potentially equipped to compete with other pathogens. Diagnostic qPCR verified that D. fangzhongdai was prevalent in most of the taro-growing areas and coexisted with the Pectobacterium complex, while the plants enriching D. fangzhongdai were frequently symptomatic at developing corms and adjacent pseudostems and caused severe symptoms. Thus, the emerging need for intensive monitoring on D. fangzhongdai to prevent it from spreading to other taro-growing areas and to other tuberous crops like potato; the adjustment of control strategies based on different pathopoiesis characteristics is recommended

Load shifting of a supplier-based demand response of multi-class subscribers in smart grid

We propose a demand response (DR) solution approach for a real-time pricing model with multi-class users to determine the electricity supply mix. The model aims to address the problem of power consumption overloading in peak hours using the real-time information obtained from the interaction between suppliers and users in a smart grid. The proposed DR algorithm allocates the overloaded demand assigned to a supplier to other electricity suppliers in order to satisfy all users’ demand while the supplier ensures to maximize the utility or reserved demand of users. Furthermore, a priority approach based on different user groups is developed for allocating the extra demand to other suppliers. Numerical experiments have been conducted to analyze the performance of the algorithm and compare the real-time electricity price with the fixed price