A Bound on Peak Age of Information Distribution

This paper presents a study on peak age of information (AoI), focusing on its distribution that is more important for AoI guarantees than the mean. Specifically, the relation of peak AoI to the underlying information generation and transmission processes is explicitly formulated. Based on this formulation and by exploring the independence information between the information generation and transmission processes, a general bound on the distribution of peak AoI is derived. To showcase the use of the derived bound, it is applied to two representative cases, which are characterized by the M/M/1 and D/M/1 queuing models. Numerical results obtained from the proposed bound analysis are finally introduced and discussed in comparison with exact results, validating the bound.acceptedVersio

1.7 MV Tandem Accelerator Beam Tuning Optimization

To augment the inherent efficiency and enhance the quality of the conventional manual beam-tuning methodology, this paper presented an innovative approach through the incorporation of a differential evolution (DE) algorithm. Initially, the architectural framework of the DE algorithm was meticulously delineated, serving as the bedrock of the methodological paradigm. The DE algorithm, renowned for its robust optimization capabilities, is implemented utilizing the versatile Python programming language. This implementation leverages Python’s computational prowess and inherent flexibility, enabling the development of a sophisticated algorithmic solution. A resilient connection with the experimental physics and industrial control system (EPICS) was established via the pyEPICS interface. This integration facilitates seamless communication and precise control between the advanced DE algorithm and the intricate accelerator system. The pyEPICS interface acted as a conduit, ensuring real-time data exchange and enabling dynamic adjustments to be made based on the algorithm’s outputs. Furthermore, to augment user operation and monitoring capabilities, an intuitive control system studio (CSS) interface was devised. This interface empowered efficient upper-level control and real-time monitoring functions, thereby significantly bolstering the usability and practicality of the system. The CSS interface features a user-friendly graphical user interface (GUI) that allows operators to monitor and adjust parameters in real-time with ease, enhancing the overall user experience and operational efficiency. Using the 1.7 MV tandem accelerator platform as a testbed, rigorous experiments were conducted to ascertain the feasibility and efficacy of the DE algorithm in beam optimization. These experiments were designed to comprehensively evaluate the algorithm’s performance under various conditions and constraints. During these trials, this paper not only scrutinized the algorithm’s performance but also implemented optimizations and enhancements based on empirical findings. These refinements notably elevate the optimization capabilities of the algorithm, culminating in an impressive beam transfer efficiency of 80%. The methodology encompassed several pivotal steps. Firstly, the DE algorithm using Python was implemented, capitalizing on its robust computational capabilities and inherent flexibility. This implementation allowed for the development of a sophisticated and adaptable algorithmic solution. Subsequently, the algorithm was seamlessly integrated with the EPICS system via the pyEPICS interface, enabling precise control and monitoring of the accelerator beam. The CSS interface was meticulously developed to offer an intuitive and user-friendly graphical interface, facilitating real-time monitoring and adjustment of parameters by operators. The experimental results underscore that the exceptional performance of the DE algorithm in beam tuning. The optimized beam transfer efficiency of 80% constitutes a substantial improvement over traditional manual methods, highlighting the algorithm’s efficacy in enhancing beam-tuning processes. Furthermore, the DE algorithm’s adaptability and robustness were evident in its proficiency to handle a diverse array of beam conditions and constraints, demonstrating its versatility and practical utility. In conclusion, this study highlights the superior performance of the DE algorithm in beam tuning and proposes a novel approach for the development of intelligent beam-tuning technology. By achieving beam-modulation intelligentization, this paper strives to further enhance the efficiency and stability of accelerator systems. This research not only contributes to the advancement of beam-tuning techniques but also holds considerable promise for related fields of study and practical applications. The findings presented in this paper have the potential to stimulate further research and development in this domain, ultimately culminating in the creation of more efficient and reliable accelerator systems. This work underscores the importance of leveraging advanced algorithmic solutions and robust control systems to enhance the performance and operational efficiency of accelerator facilities

Yap1 Hydroxylation Suppress Prostate Cancer Metastasis

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Hexokinase1: A glucose sensor involved in drought stress response and sugar metabolism depending on its kinase activity in strawberry

Hexokinase1 (HXK1) is a bifunctional enzyme that plays indispensable roles in plant growth, nitrogen utilization, and stress resistance. However, information on the HXK family members of strawberries and their functions in glucose sensing and metabolic regulation is scarce. In the present study, four HXKs were firstly identified in the genome of Fragaria vesca and F. pentaphylla. The conserved domains of the HXK1s were confirmed, and a site-directed mutation (S177A) was introduced into the FpHXK1. FpHXK1, which shares the highest identity with the AtHXK1 was able to restore the glucose sensitivity and developmental defects of the Arabidopsis gin2-1 mutant, but not its kinase-activity-impaired mutant (FpHXK1S177A). The transcription of FpHXK1 was dramatically up-regulated under PEG-simulated drought stress conditions. The inhibition of the HXK kinase activity delayed the strawberry plant’s responses to drought stress. Transient overexpression of the FpHXK1 and its kinase-impaired mutant differentially affected the level of glucose, sucrose, anthocyanins, and total phenols in strawberry fruits. All these results indicated that the FpHXK1, acting as a glucose sensor, was involved in drought stress response and sugar metabolism depending on its kinase activity

New Landscapes and Horizons in Hepatocellular Carcinoma Therapy

Hepatocellular carcinoma (HCC), is the sixth most frequent form of cancer and leads to the fourth highest number of deaths each year. HCC results from a combination of environmental factors and aging as there are driver mutations at oncogenes which occur during aging. Most of HCCs are diagnosed at advanced stage preventing curative therapies. Treatment in advanced stage is a challenging and pressing problem, and novel and well-tolerated therapies are urgently needed. We will discuss further advances beyond sorafenib that target additional signaling pathways and immune checkpoint proteins. The scenario of possible systemic therapies for patients with advanced HCC has changed dramatically in recent years. Personalized genomics and various other omics approaches may identify actionable biochemical targets, which are activated in individual patients, which may enhance therapeutic outcomes. Further studies are needed to identify predictive biomarkers and aberrantly activated signaling pathways capable of guiding the clinician in choosing the most appropriate therapy for the individual patient

Impact of digital transformation on corporate sustainability: evidence from China’s carbon emissions

Abstract Climate change has become an increasingly pressing issue, underscoring the urgent global need for energy conservation and emission reduction. As one of the largest emitters, China is actively advancing comprehensive efforts to reduce emissions in pursuit of sustainable development, with enterprises playing a key role in aligning economic growth with environmental sustainability. Digital Transformation (DT) has emerged as a crucial enabler of low-carbon economic development. This study utilizes data from publicly listed companies in China, spanning the period from 2000 to 2021, and employs a two-way fixed-effects model to assess the impact of corporate DT on Carbon Emissions (CE). The findings reveal that: First, DT significantly contributes to the reduction of CE; Second, the impact of DT on CE varies across regions, industries, and firm characteristics; Third, the positive effect of DT on CE is driven by mechanisms such as technological advancement, innovation promotion, resource optimization, and improved output efficiency. These results provide both theoretical insights and empirical evidence supporting the role of DT in fostering green, low-carbon enterprise development