IOT-enabled Quality Management Process Innovation and Analytics in China’s Dairy Industry: A Data Flow Modeling Perspective

Since the melamine incident was reported in China, China’s dairy industry attracts more and more attention, leading some scholars to conduct research on quality management and safety monitoring issues of China’s dairy industry. The technology of the Internet of Things (IOT) is viewed as one of the best ways to solve the safety problems of China’s dairy industry by supporting the development of dairy traceability systems. This paper firstly analyses the current situation of China’s dairy industry supply chain to get at the root of the problem. We then propose an IOT-enabled quality management framework which is an innovation mode of quality management in China’s dairy industry supply chain. To further highlight the important role of IOT technology, we employ a business process modeling approach based on data flow perspective to describe this innovation management mode. The artifacts we design, especially the matrix of dairy products and process information, can help the practitioners to efficiently monitor the quality information of dairy products

Differential Expression Analysis of Olfactory Genes Based on a Combination of Sequencing Platforms and Behavioral Investigations in Aphidius gifuensis

Aphidius gifuensis Ashmead is a dominant endoparasitoid of aphids, such as Myzus persicae and Sitobion avenae, and plays an important role in controlling aphids in various habitats, including tobacco plants and wheat in China. A. gifuensis has been successfully applied for the biological control of aphids, especially M. persicae, in green houses and fields in China. The corresponding parasites, as well as its mate-searching behaviors, are subjects of considerable interest. Previous A. gifuensis transcriptome studies have relied on short-read next-generation sequencing (NGS), and the vast majority of the resulting isotigs do not represent full-length cDNA. Here, we employed a combination of NGS and single-molecule real-time (SMRT) sequencing of virgin females (VFs), mated females (MFs), virgin males (VMs), and mated males (MMs) to comprehensively study the A. gifuensis transcriptome. Behavioral responses to the aphid alarm pheromone (E-β-farnesene, EBF) as well as to A. gifuensis of the opposite sex were also studied. VMs were found to be attracted by female wasps and MFs were repelled by male wasps, whereas MMs and VFs did not respond to the opposite sex. In addition, VFs, MFs, and MMs were attracted by EBF, while VMs did not respond. According to these results, we performed a personalized differential gene expression analysis of olfactory gene sets (66 odorant receptors, 25 inotropic receptors, 16 odorant-binding proteins, and 12 chemosensory proteins) in virgin and mated A. gifuensis of both sexes, and identified 13 candidate genes whose expression levels were highly consistent with behavioral test results, suggesting potential functions for these genes in pheromone perception

Unveiling the role of Zn dopants in NiFe phosphide nanosheet for oxygen evolution reaction

Transition metal phosphides have been recognized as promising electrocatalysts for oxygen evolution reaction (OER) due to their low cost and high activity. However, the insufficient exposed active region limited the OER performance. Recently, the introduction of sacrificial dopants has been considered an effective strategy to enlarge the surface area. Herein, the Zn dopants are introduced in NiFe phosphide (NiFeZnP) nanosheet, which work as the sacrificial dopants to generate more exposed active NiFe sites and promote the formation of the NiFeOOH active phase during OER process. The optimized Zn-doped NiFeP catalyst shows an overpotential of ≈203 ​mV to reach a current density of 10 ​mA ​cm−2 in 1 ​M KOH, and a stability of 100 ​h at 1000 ​mA ​cm−2. Overall, this work provides a sacrificial Zn doping strategy to prepare highly efficient OER electrocatalysts

Influence of the Built Environment on Older Adults’ Travel Time: Evidence from the Nanjing Metropolitan Area, China

The built environment is among the critical factors in older adults’ travel behavior, and a favorable built environment can encourage them to travel and engage in various activities. Existing studies have mostly focused on exploring the correlation between the built environment and travel behavior, ignoring the heterogeneity between the two at different times of the day. In this study, we conducted structured, face-to-face interviews in the Nanjing (China) metropolitan area to investigate the time consumed per trip by older adults using various travel modes and used the structural equation and random forest models to explore the relationship between the built environment and older adults’ travel time. The results demonstrated that older adults had different perspectives on travel during different time periods. Different environments and the convenience of destinations affected their overall satisfaction during travel. We found a nonlinear relationship between the built environment and travel time. Metropolitan street connectivity initially had a positive effect on travel time until a certain threshold or peak, whereafter a gradual decline ensued. This nonlinear relationship also existed between the proportion of green space and the distance to subway stations. These results can guide the retrofitting and construction of age-friendly metropolitan infrastructure facilities that promote older adults’ mobility

Possibility generalized labeled multi-Bernoulli filter for multi-target tracking under epistemic uncertainty

This paper presents a flexible modeling framework for multi-target tracking based on the theory of Outer Probability Measures (OPMs). The notion of labeled uncertain finite set is introduced and utilized as the basis to derive a possibilistic analog of the δ-Generalized Labeled Multi-Bernoulli (δ-GLMB) filter, in which the uncertainty in the multi-target system is represented by possibility functions instead of probability distributions. The proposed method inherits the capability of the standard probabilistic δ-GLMB filter to yield joint state, number, and trajectory estimates of multiple appearing and disappearing targets. Beyond that, it is capable to account for epistemic uncertainty due to ignorance or partial knowledge regarding the multi-target system, e.g., the absence of complete information on dynamical model parameters (e.g., probability of detection, birth) and initial number and state of newborn targets. The features of the developed filter are demonstrated using two simulated scenarios

Multiple metallic dopants in nickel nanoparticles for electrocatalytic oxygen evolution

Developing efficient oxygen evolution reaction (OER) electrocatalysts is of great importance for sustainable energy conversion and storage. Ni-based catalysts have shown great potential as OER electrocatalysts, but their performance still needs to be improved. Herein, we report the multiple metal doped nickel nanoparticles synthesized via a simple oil phase strategy as efficient OER catalysts. The FeMnMoV–Ni exhibits superior OER performance with an overpotential of 220 ​mV at 10 ​mA ​cm−2 and a long-term stability of 250 ​h in 1 ​M KOH solution. In situ Raman analysis shows that the NiOOH site works as the active center and multiple metallic dopants facilitate the formation of NiOOH. Mo and V dopants promote the formation of high-valence state of Ni sites, and Mn dopants increase the electrochemical active surface area and expose more active sites. This work provides a novel strategy for catalyst design, which is critical for developing multiple metal doped catalysts

Metal-organic framework derived copper catalysts for CO2 to ethylene conversion

The electrochemical reduction of CO2 to ethylene provides a carbon-neutral avenue for the conversion of CO2 to value-added fuels and feedstocks, so contributing to the storage of intermittent renewable electricity. The exploration of efficient electrocatalysts with high ethylene selectivity and productivity is highly desirable but remains challenging. Here, we present a Cu-based catalyst derived from a metal-organic framework (Cu-MOF) which shows enhanced performance due to its porous morphology, complex oxidation states and strong lattice strain. X-ray diffraction, X-ray photoelectron spectroscopy, and X-ray absorption spectroscopy are utilized to track the evolution of the crystal structure and oxidation states during the reaction, and the results reveal that Cu2+ ions are rapidly reduced to Cu+ and then slowly to Cu-0, resulting in a Cu@CuxO core@shell structure. The tensile strain caused by the distorted grain is beneficial for the activation of CO2. Cu+/Cu-0 interfaces formed through stabilized Cu+ facilitate *CO-CO dimerization, promoting conversion to C2+ products and suppressing conversion to C-1 products. The optimized catalyst exhibits a 51% Faraday efficiency (FE) for ethylene and a 70% FE for C2+ products, with 20 h operational stability in an H-cell configuration, and a partial ethylene current density of 150mA cm(-2) in a flow-cell configuration