Analysis of Ω(2012)\Omega(2012) as a molecule in the chiral quark model

Inspired by the updated information on $\Omega(2012)$ by the Belle Collaboration, we conduct a study of all possible $S$-wave pentaquark systems with quark contents $sssq\bar{q},q=u,d$ in a chiral quark model with the help of Gaussian expansion method. Channel coupling is also considered. The real-scaling method (stabilization method) is employed to identify and check the bound states and the genuine resonances. In addition, the decay widths of all resonances are given. The results show that $\Omega(2012)$ can be interpreted as a $\Xi^*K$ molecular state with quantum number of $IJ^P=0(\frac{3}{2})^-$. Other resonances are obtained: $\Xi^* K^*$ with $IJ^P=0(\frac{1}{2})^-$ and$0(\frac{3}{2})^-$, $\Omega\pi$ with $IJ^P=1(\frac{3}{2})^-$. These pentaquark states is expected to be further verified in future experiments.Comment: 10 pages, 5 figures. arXiv admin note: text overlap with arXiv:2109.0997

Developing Low Carbon Supply Networks: Influence, Measurement, and Improvement

Climate change has emerged as one of the most serious challenges faced by human beings. As manufacturing globalisation involves more and more emerging nations, a greater proportion of CO2 emissions is generated from developing countries. The dilemma between fast industrial development and carbon reduction makes firms in developing nations reluctant to take serious commitment and actions in CO2 emission reduction in their global manufacturing practices. From a theoretical perspective, low-carbon supply networks research is also still in its infant stage and needs more explorations and development. Therefore this research aims to address the research question: “How can supply networks in developing countries be developed to reduce carbon emission?” Especially it focuses on: • An influence process to engage companies in developing countries to reduce carbon emission • A typology of carbon emission assessments in supply networks • An initial process of implementing carbon-reduction projects in supply network The research adopts theory building approach based on multiple case studies. The units of analysis are carbon reduction project of focal firms and initiatives of Non-Government Organizations (NGO). Drawing upon the cases, this research develops a general framework for developing low-carbon supply network, including three parts namely network influence, network CO2 measurement, and network CO2 improvement (IMI), with the three process models accordingly proposed. In the ‘influence’ process, based on resource dependence theory (RDT), this research illustrates a categorization of influence choices and a typology of influence pathways, which both underpin the four-step influence procedure proposed later. In the ‘measurement’ process, this research proposes a goal-oriented carbon footprint measurement guideline. In the “improvement’ process, an initial framework to classify carbon reduction projects and implementation process model of these projects are both built based on the analysis of primary case studies and Carbon Disclosure Project (CDP) database which contains corporates’ carbon reduction practices. Overall this research makes contributions in the following aspects: (1) this research advocates IMI framework as a pathway to de-carbonize supply networks, contributing to manufacturing system’s evolution to sustainable paradigm; (2) It integrates the institutional, stakeholder and network theory in the context of de-carbonization, and extends the research scope of operations management; (3) The research contributes to life cycle assessment (LCA) literature by exploring supply network coordination during the LCA procedure; (4) The research also contributes to green supply chain literature by providing insights from firms’ de-carbonization projects in supply network. (5) In practice, the IMI three-process models can help practitioners to implement de-carbonization management, serving as a preliminary guideline to follow. The potential audience of this research can be MNCs, NGOs, government bodies, consultants, and any organization or individual who aim to change industrial system in the pursuit of climate change mitigation

Do green practices really attract customers? The sharing economy from sustainable supply chain management perspective

The notion of the sharing economy has been introduced in many sectors and provided significant benefits to consumers and asset owners. Despite the remarkable improvement of the sharing economy in recent years, its relationship with sustainability remains insufficiently researched. This study adopts a sustainable supply chain management (SSCM) perspective. A large-scale survey with 420 participants showed that investment recovery (IR) practices and corporate social responsibility (CSR) conducted by sharing economy platforms significantly and positively affect customers’ intention to use sharing economy-based services/products, whereas internal green management (IGM), supplier green management (SGM), eco-design (ECD) and customer green management (CGM) practices do not. A follow-up qualitative study with ten participants provided further explanations and supported the findings of the survey. This study links the sharing economy and sustainability by testing the effectiveness of sharing economy platforms’ sustainable practices and proposes the best practices for sharing economy platforms to maintain a long-term sustainable marketplace

Molecular state interpretation of charmed baryons in the quark model

Stimulated by the observation of $\Lambda_c(2910)^+$ by the Belle Collaboration, the $S$-wave $qqq\bar{q}c~(q=u~\text{or}~d)$ pentaquark systems with $I$ = 0, $J^P$ = $\frac{1}{2}^-,~\frac{3}{2}^- and~\frac{5}{2}^-$ are investigated in the framework of quark delocalization color screening model(QDCSM). The real-scaling method is utilized to check the bound states and the genuine resonance states. The root mean square of cluster spacing is also calculated to study the structure of the states and estimate if the state is resonance state or not. The numerical results show that $\Lambda_{c}(2910)$ cannot be interpreted as a molecular state, and $\Sigma_{c}(2800)$ cannot be explained as the $ND$ molecular state with $J^P=1/2^-$. $\Lambda_{c}(2595)$ can be interpreted as the molecular state with $J^P=\frac{1}{2}^-$ and the main component is $\Sigma_{c}\pi$. $\Lambda_{c}(2625)$ can be interpreted as the molecular state with $J^P=\frac{3}{2}^-$ and the main component is $\Sigma_{c}^{*}\pi$. $\Lambda_{c}(2940)$ is likely to be interpreted as a molecular state with $J^P=3/2^-$, and the main component is $ND^{*}$. Besides, two new molecular states are predicted, one is the $J^P=3/2^-$ $\Sigma_{c}\rho$ resonance state with the mass around 3140 MeV, another one is the $J^P=\frac{5}{2}^-$ $\Sigma_{c}^*\rho$ with the mass of 3188.3 MeV.Comment: 12 pages, 3 figure

A106: Aerobic Exercise Modulates GPCR/cAMP/PKA Signaling Pathway and Complement-Microglia Axis to Prevent Synaptic Loss in APP/PS1 Mice

Purpose: Synaptic failure serves as a primary contributor to memory dysfunction in Alzheimer\u27s disease (AD). Physical exercise has demonstrated the potential to thwart and delay degenerative alterations in memory functions linked to AD. Investigating the underlying mechanisms may unveil crucial insights into early pathological changes, offering breakthroughs for both understanding and treating AD. Methods: We utilized 3-month-old APP/PS1 mice and subjected them to a 12-week aerobic exercise intervention. The spatial learning and memory functions of the mice were assessed using the Morris water maze test, while Golgi staining was employed to determine dendritic spine density in each mouse group. To analyze the potential mechanisms mediating the effects of exercise intervention in the AD brain, we conducted RNA sequencing. Subsequently, pathway enrichment analysis, immunofluorescence, real-time quantitative PCR, and western blotting were employed to elucidate the impact of regular aerobic exercise on the GPCR/cAMP/PKA signaling pathway and complement-microglia axis. Results: Our findings reveal that a 12-week aerobic exercise intervention significantly enhanced spatial learning and memory function in APP/PS1 mice. Moreover, it led to a substantial increase in dendritic spine density and elevated expression of postsynaptic density protein 95 (PSD-95) in the cortex and hippocampus. Aerobic exercise demonstrated the ability to improve the expression of certain genes and enhance synaptic pathways in the brains of APP/PS1 mice. This suggests that aerobic exercise facilitates synaptic growth in APP/PS1 mice by modulating G protein-coupled receptors (GPCRs) and activating the cAMP signaling pathway, with significant alterations observed in the expressions of Hcar1 and Vipr2 genes. Furthermore, exercise intervention resulted in the significant down-regulation (P \u3c 0.05 or P \u3c 0.01) of cAMP, p-PKA/PKA, GluA1, and CaMKII protein expressions in the brain tissue of APP/PS1 mice, which were subsequently up-regulated after exercise (P \u3c 0.01). Notably, regular aerobic exercise effectively suppressed the activation of IBA-1+ microglia cells (P \u3c 0.01), reversed changes in M1 phenotype markers (Cd86 and iNOS) and M2 phenotype markers (Arg-1) of microglia cells (P \u3c 0.05), reduced the production of promoters C1q and central factor C3 in the macrosomatic cascade (P \u3c 0.05), and prevented the colocalization of microglia and PSD-95 (P \u3c 0.01). Conclusion: In conclusion, our results indicate that physical exercise plays a pivotal role in fostering early synaptic growth and averting synaptic loss in Alzheimer\u27s disease (AD). This effect may be attributed to the regulation of the G protein-coupled receptors (GPCRs)/cAMP/PKA signaling pathway and the suppression of complement-mediated microglial phagocytosis of synapses. This mechanistic insight underscores the inherent contribution of exercise to health promotion, offering potential avenues for synaptic-focused interventions in the early stages of AD treatment

Industrialisation, ecologicalisation and digitalisation (IED): building a theoretical framework for sustainable development

Purpose In the past two decades, manufacturing has witnessed significant transformations alongside ecological challenges. Meanwhile, industrial 4.0 digital technologies have accelerated industrialisation with potentials of innovation in the context of circular economy. However, current concepts and models are fragmented and impractical. This paper aims to develop a holistic view integrating the three bodies of knowledge – industrialisation, ecologicalisation and digitalisation (IED) – in order to achieve sustainable development. Design/methodology/approach Critical literature review is conducted across three bodies of knowledge. Key themes are summarised with the identification of research gaps. A theoretical framework is synthesised and developed aiming to achieve synergy from IED with the modules, integration architecture, mechanism and dynamic paths. Findings First, the authors review and develop three conceptual models of ecologicalised industrialisation (IE3), industrial system digitalisation (D1) and digital technology industrialisation (D2) separately. Second, the authors propose a theoretical framework seeking to synthesise the above three conceptual models together to form the IED. Third, the authors design a process orientated abductive approach to improve and validate the IED framework. Originality/value This study contributes to the limited literature addressing the linkage of IED by integration different perspectives to develop theory in a novel way. Practically, it provides important tools for organisations to consider resource cascading in combination with digitalisation during the industrial system design

Research on large-scale clean energy optimal scheduling method based on multi-source data-driven

With the large-scale growth and grid connection of intermittent renewable energy such as wind and solar, the problem of increasing renewable energy curtailment rate and system backup flexibility has become increasingly prominent. In order to solve the problem of high proportion of renewable energy scientific consumption and flexible and stable operation of energy system. We propose a flexible and economical dispatch method based on data-driven multi-regional power system. For the problem of economic dispatch of multi-area power system, a mathematical calculation model is established to satisfy the constraints of unit output, system power balance, unit ramp rate, and valve point effect, and to consider the requirement of minimizing the cost of multi-area power load comprehensively. Based on data-driven, this paper adopts an improved fruit fly optimization algorithm to quickly find the global optimal solution. The calculations are performed by IEEE6 simulation test system, and the results verify the feasibility of the proposed algorithm. The improved fruit fly optimization algorithm is compared and analyzed with other algorithms considering the quality of the obtained solutions. The results show the effectiveness and superiority of the proposed algorithm in solving multi-area economic dispatching problems in real power systems