Search

The global telecom industry is carrying out research and exploration of potential 6G technical architectures and key techs, of which it has become a consensus in the industry to further realize the vision of 6G smart inclusion by better enabling all new 6G network technologies and services through joint communication ＆amp; computing (JC＆amp;C).Therefore, how to realize the deep integration and real-time collaboration of communication and computing to meet the needs of ultra-low latency and real-time response of new services in dynamic and complex network environments has become the challenge and key of JC＆amp;C.A computing native network (CNN) driven by JC＆amp;C was proposed, which realized the decoupling of communication and computing of base station or multiple base stations, computing pooling and intelligent JC＆amp;C scheduling through computing time division multiplexing and intelligent JC＆amp;C scheduling, thus realizing the base station to support communication and computation services simultaneously.The technology has been technically verified and piloted, and the experimental and pilot results demonstrate that CNN can effectively improve the computing utilization rate of wireless networks and realize the base station to support communication and computing services simultaneously, facilitating the evolution of 6G JC＆amp;C.

Abstract Lactiplantibacillus plantarum is a probiotic bacterium widely used in food and health industries, but its gene regulatory information is limited in existing databases, which impedes the research of its physiology and its applications. To obtain a better understanding of the transcriptional regulatory network of L. plantarum, independent component analysis of its transcriptomes was used to derive 45 sets of independently modulated genes (iModulons). Those iModulons were annotated for associated transcription factors and functional pathways, and active iModulons in response to different growth conditions were identified and characterized in detail. Eventually, the analysis of iModulon activities reveals a trade‐off between regulatory activities of secondary and primary metabolism in L. plantarum.

Abstract The steel sector currently accounts for 7% of global energy-related CO2 emissions and requires deep reform to disconnect from fossil fuels. Here, we investigate the market competitiveness of one of the widely considered decarbonisation routes for primary steel production: green hydrogen-based direct reduction of iron ore followed by electric arc furnace steelmaking. Through analysing over 300 locations by combined use of optimisation and machine learning, we show that competitive renewables-based steel production is located nearby the tropic of Capricorn and Cancer, characterised by superior solar with supplementary onshore wind, in addition to high-quality iron ore and low steelworker wages. If coking coal prices remain high, fossil-free steel could attain competitiveness in favourable locations from 2030, further improving towards 2050. Large-scale implementation requires attention to the abundance of suitable iron ore and other resources such as land and water, technical challenges associated with direct reduction, and future supply chain configuration.

An enhanced customer-user-account (eCUA) model was proposed.Based on the traditional three-household (customer, user, account) model in telecom industry, an enhanced customer-user-account model and its information framework was constructed by means of virtual digital human and decentralized identity technology, combined with the service demand of task-based computing power.With the globally unique identity, eCUA enables the traditional three-household model to have distributed and decentralized sharing capability.eCUA can solve the problem of information inconsistency in multi-account management, multi-source data synchronization, and multi-channel display of same-origin data.It can effectively support the closed-loop management of the whole process of computing power network business, such as computing power subscription, experience, ordering, and transaction operation.Therefore, the eCUA model proposed can be used as the main data reference frame of the integrated telecommunications service support system.

With the enrichment and diversification of business types, low latency, high bandwidth, data privacy and high reliability have become common requirements.Edge computing, fog computing, distributed cloud, computing power network and other solutions have been proposed, and have triggered in-depth research and exploration in industry, academia and research.There is a consensus within and outside the industry on the view that “multi-level computing power distribution and collaboration of computing power will be the mainstream of computing power structure in the future”.The problems related to resource scheduling optimization, such as computing power management, allocation, scheduling, have also become the current research hotspot and key research direction.Therefore, for the future computing power supply structure, focuses on the latest progress of resource scheduling optimization in academia and industry, the current main methodology and engineering implementation architecture was summarized.And then, for the two typical cloud edge collaboration scenarios, the analysis was carried out from the perspective of scene splitting, scheduling objectives, and solutions in turn, and the resource scheduling optimization reference schemes that adapted to the characteristics of the scenarios were analyzed and discussed respectively.

In microorganisms, different from primary metabolism for cellular growth, secondary metabolism is for ecological interactions and stress responses and an important source of natural products widely used in various areas such as pharmaceutics and food additives. With advancements of sequencing technologies and bioinformatics tools, a large number of biosynthetic gene clusters of secondary metabolites have been discovered from microbial genomes. However, due to challenges from the difficulty of genome-scale pathway reconstruction and the limitation of conventional flux balance analysis (FBA) on secondary metabolism, the quantitative modeling of secondary metabolism is poorly established, in contrast to that of primary metabolism. This review first discusses current efforts on the reconstruction of secondary metabolic pathways in genome-scale metabolic models (GSMMs), as well as related FBA-based modeling techniques. Additionally, potential extensions of FBA are suggested to improve the prediction accuracy of secondary metabolite production. As this review posits, biosynthetic pathway reconstruction for various secondary metabolites will become automated and a modeling framework capturing secondary metabolism onset will enhance the predictive power. Expectedly, an improved FBA-based modeling workflow will facilitate quantitative study of secondary metabolism and in silico design of engineering strategies for natural product production.

It has been an exciting journey since the mobile communications and artificial intelligence (AI) were conceived in 1983 and 1956. While both fields evolved independently and profoundly changed communications and computing industries, the rapid convergence of 5th generation mobile communication technology (5G) and AI is beginning to significantly transform the core communication infrastructure, network management, and vertical applications. The paper first outlined the individual roadmaps of mobile communications and AI in the early stage, with a concentration to review the era from 3rd generation mobile communication technology (3G) to 5G when AI and mobile communications started to converge. With regard to telecommunications AI, the progress of AI in the ecosystem of mobile communications was further introduced in detail, including network infrastructure, network operation and management, business operation and management, intelligent applications towards business supporting system (BSS) & operation supporting system (OSS) convergence, verticals and private networks, etc. Then the classifications of AI in telecommunication ecosystems were summarized along with its evolution paths specified by various international telecommunications standardization organizations. Towards the next decade, the prospective roadmap of telecommunications AI was forecasted. In line with 3rd generation partnership project (3GPP) and International Telecommunication Union Radiocommunication Sector (ITU-R) timeline of 5G & 6th generation mobile communication technology (6G), the network intelligence following 3GPP and open radio access network (O-RAN) routes, experience and intent-based network management and operation, network AI signaling system, intelligent middle-office based BSS, intelligent customer experience management and policy control driven by BSS & OSS convergence, evolution from service level agreement (SLA) to experience level agreement (ELA), and intelligent private network for verticals were further explored. The paper is concluded with the vision that AI will reshape the future beyond 5G (B5G)/6G landscape, and we need pivot our research and development (R&D), standardizations, and ecosystem to fully take the unprecedented opportunities.

With the development of information and communication technologies, traditional telecom business support systems (BSS) are facing the challenge of agilely meeting the flexible needs from business.Application scenarization, service standardization, technology componentization and resource sharing have gradually become the consensual features among the evolution of telecom BSS architectures.A business function virtualization (BFV)-based BSS architecture, which is based on cloud-native, micro-services, containers, and DevOps technologies, was proposed.By embedding four components into the architecture, including standardized virtual network functions, modular design orchestrator, micro-service management framework, and multi-plane elastic computing controller, the system is able to deploy unitized system and distributed cloud.Therefore, the requirements of flexible telecom business development and frequent evolution of the system could be satisfied by the proposed BFV-based BSS architecture.In other words, the lightweight delivery of IT technologies and agile business support could be fulfilled by using the proposed BFV-based BSS architecture, and the proposed architecture will eventually become the standard architecture of next generation telecom BSS.

Microbes communicate with each other by Quorum sensing (QS) languages. Here the authors construct a QS database and the QS communication network to decipher intricate QSbased communications and form one of the key knowledge maps for human gut microbiota.

With the development of the mobile communication and Internet technology, the traditional communication business has been developed from voice communication services to diversified and personalized information services, and the value chain structure of the communication industry has been changed from the mobile network operator (MNO)-centered mode to the user experience-centered mode.With the concept of “content-driven”, Internet content providers update their products actively to satisfy the users’ needs, which results in a rapid increase in the market share, while the MNOs are gradually being “pipelined” in the industry value chain.In the process of the digital transformation, MNOs have achieved the on-demand scheduling, flexible adaptation, and rapid deployment by reconfiguring and abstracting 5G network functions, and have enhanced the user experience using a user centric operation model based on the business support system (BSS)/operation support system(OSS)(BO) consolidation to ultimately achieve the enhancement in the value chain.On the basis of reviewing the development of the communication industry’s value chain, the challenges for MNOs to promote their values were analyzed.Meanwhile, a 5G value plane architecture based on embedded services in 5G networks was proposed, and the typical application scenarios were given.Path suggestions for the evolution of the 5G value plane were provided, which help MNOs to build the next generation of BSS/ OSS consolidation.

As consumers’ demands for mobile services have become more abundant and diversified, the architecture and functions of mobile network have become more complex.With the development of 5G technology, 5G mobile network could realize on-demand orchestration and flexible exposure of network capabilities, which made higher requirements for network lifecycle management.Digital twins technology could be used to assist the network lifecycle management, so as to improve the network management quality, reduce network risks and costs, and achieve the visual perception and the real-time closed-loop control.The network digital twin platform and application cases show that the proposed network digital twins platform can realize visual monitoring and analysis of mobile network operation key performance indicators and quickly diagnosis of network faults.

Abstract Background The rising consensus that the cell can dynamically allocate its resources provides an interesting angle for discovering the governing principles of cell growth and metabolism. Extensive efforts have been made in the past decade to elucidate the relationship between resource allocation and phenotypic patterns of microorganisms. Despite these exciting developments, there is still a lack of explicit comparison between potentially competing propositions and a lack of synthesis of inter-related proposals and findings. Results In this work, we have reviewed resource allocation-derived principles, hypotheses and mathematical models to recapitulate important achievements in this area. In particular, the emergence of resource allocation phenomena is deciphered by the putative tug of war between the cellular objectives, demands and the supply capability. Competing hypotheses for explaining the most-studied phenomenon arising from resource allocation, i.e. the overflow metabolism, have been re-examined towards uncovering the potential physiological root cause. The possible link between proteome fractions and the partition of the ribosomal machinery has been analysed through mathematical derivations. Finally, open questions are highlighted and an outlook on the practical applications is provided. It is the authors’ intention that this review contributes to a clearer understanding of the role of resource allocation in resolving bacterial growth strategies, one of the central questions in microbiology. Conclusions We have shown the importance of resource allocation in understanding various aspects of cellular systems. Several important questions such as the physiological root cause of overflow metabolism and the correct interpretation of ‘protein costs’ are shown to remain open. As the understanding of the mechanisms and utility of resource application in cellular systems further develops, we anticipate that mathematical modelling tools incorporating resource allocation will facilitate the circuit-host design in synthetic biology.

Abstract Xuan-bai-cheng-qi decoction (XCD), a traditional Chinese medicine (TCM) prescription, has been widely used to treat a variety of respiratory diseases in China, especially to seriously infectious diseases such as acute lung injury (ALI). Due to the complexity of the chemical constituent, however, the underlying pharmacological mechanism of action of XCD is still unclear. To explore its protective mechanism on ALI, firstly, a network pharmacology experiment was conducted to construct a component-target network of XCD, which identified 46 active components and 280 predicted target genes. Then, RNA sequencing (RNA-seq) was used to screen differentially expressed genes (DEGs) between ALI model rats treated with and without XCD and 753 DEGs were found. By overlapping the target genes identified using network pharmacology and DEGs using RNA-seq, and subsequent protein–protein interaction (PPI) network analysis, 6 kernel targets such as vascular epidermal growth factor (VEGF), mammalian target of rapamycin (mTOR), AKT1, hypoxia-inducible factor-1α (HIF-1α), and phosphoinositide 3-kinase (PI3K) and gene of phosphate and tension homology deleted on chromsome ten (PTEN) were screened out to be closely relevant to ALI treatment. Verification experiments in the LPS-induced ALI model rats showed that XCD could alleviate lung tissue pathological injury through attenuating proinflammatory cytokines release such as tumor necrosis factor (TNF)-α, interleukin (IL)-6, and IL-1β. Meanwhile, both the mRNA and protein expression levels of PI3K, mTOR, HIF-1α, and VEGF in the lung tissues were down-regulated with XCD treatment. Therefore, the regulations of XCD on PI3K/mTOR/HIF-1α/VEGF signaling pathway was probably a crucial mechanism involved in the protective mechanism of XCD on ALI treatment.

It has been an exciting journey since the mobile communications and AI were conceived 37 years and 64 years ago.While both fields evolved independently and profoundly changed communications and computing industries, the rapid convergence of 5G and AI is beginning to significantly transform the core communication infrastructure, network management and vertical applications.The individual roadmaps of mobile communications and artificial intelligence in the early stage were firstly outlined, with a concentration to review the era from 3G to 5G when AI and mobile communications started to converge.With regard to telecommunications artificial intelligence, the progress of AI in the ecosystem of mobile communications was further introduced in detail, including network infrastructure, network operation and management, business operation and management, intelligent applications towards BSS ＆amp; OSS convergence, verticals and private networks etc.Then the classifications of AI in telecom ecosystems were summarized along with its evolution paths specified by various international telecommunications standardization bodies.Towards the next decade, the prospective roadmap of telecommunications artificial intelligence was forecasted.In line with 3GPP and ITU-R’s timeline of 5G ＆amp; 6G, the network intelligence following 3GPP and O-RAN routes, experience and intention driven network management and operation, network AI signaling system, intelligent middle-office based BSS, intelligent customer experience management and policy control driven by BSS＆amp; OSS convergence, evolution from SLA to ELA, and intelligent private network for verticals were further explored.It concludes that with the vision AI will reshape the future B5G/6G landscape, and we need fully take the unprecedented opportunities.

At the end of November 2019,China officially implemented the number portability policy (MNP) that has been in trial for 9 years.The policy will strengthen the liquidity and competitiveness of the telecommunication market,making the problem of subscriber churn more prominent.A game theory-assisted machine learning methodology was proposed,verified and commercialized timely,which could help mobile network operator (MNO) actively respond to competition in the MNP market.The proposed methodology provides MNO with a machine learning model to detect subscriber portability and give differentiated treatment.Experimental results show that the proposed methodology can guide MNOs to make a targeted MNP strategy,and precisely identify “abnormal” subscribers who tend to churn-out and potential new subscribers who may churn-in.In addition,the proposed methodology has been successfully commercialized,greatly improving the marketing efficiency of operators,increasing user satisfaction,and reducing the loss of users by about 50% for a tier-1 MNO in China.

Chemical production using renewable energies is an important element on the roadmap of industry decarbonisation. This work investigates the optimisation of renewable power supply for a fully electrified methanol process, with a focus on the interplay between renewable fix, storage sizing and the use of backup dispatchable power source. The analysis is performed using the meteorological data obtained from two locations, i.e. Kramer Junction (US) and Norderney (Germany), which have excellent solar and wind source, respectively. The minimum levelised energy cost, which is optimised in terms of renewable power generation, renewable mix and storage size, is found to be 106$/MWh and 103$/MWh for operations in Kramer Junction and Norderney, respectively, based on a dispatchable energy price of 230$/MWh. This leads to a levelised methanol cost of 1490$/tonne and 1459$/tonne with a respective renewable penetration of 81% and 96% in the production. The correlation between renewable penetration and dispatchable energy price in the most economical scenario exhibits a two-regime behaviour: the renewable penetration increases dramatically at the beginning and then slowly approaches 100% when the dispatchable energy price is above a critical point. For a fully renewable operation, the optimised levelised energy cost is found to increase to 167$/MWh and 114$/MWh for Kramer Junction and Norderney, respectively. The results show the importance of the dual functionality of hydrogen in the energy storage system, which improves the overall energy efficiency.

Introduction Following recent regulatory approvals of two chimeric antigen receptor T-cell (CAR-T) therapies, the field now faces a number of post-approval challenges. These challenges are in some respects defined and, in others, uncertain due to the nascence of the field. At present, information pertaining to such post-approval challenges are scattered in various previous reviews or raised in singular papers reporting experience in working with the therapy. This systematic review is designed to evaluate and summarise the post-approval challenges for robust delivery of CAR-T therapies to inform future work on the optimisation of CAR-T delivery to patients.Methods and analysis We will search Medline, EMBASE (OvidSP), BIOSIS & Web of Science, Cochrane Library, ICER database, NICE Evidence Search, CEA Registry, WHOLIS WHO Library and Scopus for studies published between 2014 and the present. In addition, a Google search for grey literature such as bioprocess blog posts, opinion pieces, press releases and listed companies involved in CAR-T development annual reports will be conducted. Two authors will independently screen the titles and abstracts identified from the search and accept or reject the studies according to the study inclusion criteria and any discrepancies will be discussed and resolved. The quality of the selected literature will be assessed using the Critical Appraisal Skills Programme(CASP) Systematic Review checklist and grey literature will be assessed using the Authority, Accuracy, Coverage, Objectivity, Date, Significance (AACODS) checklist. Data from eligible publications will be categorised using a flowchart and extracted using a data abstraction form. Qualitative and quantitative analysis of the post-approval challenges of CAR-T therapies will be conducted based on the results attained.Ethics and dissemination The executed study will be published in a peer-reviewed journal in accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The findings from this review will be used to inform the development of an optimisation model for robust delivery of CAR-T therapies using a systems engineering approach.Trial registration number CRD42018109756.

Current emission scenarios envisage the potential draw-down of around 810 Gt CO2 from the atmosphere by 2100. This would require some 110×1012 kWh of reversible work, and the energy needed to drive the CO2 capture processes would approach, and may even exceed, the energy gained in burning the fossil fuel in the first place. Negative Emission Technologies (NETs) would be needed at huge scale, motivating a search for novel, highly energy-efficient approaches. Separation processes such as CO2 capture involve dissipation of energy in diffusion, the losses being greater when higher transfer rates are utilised to reduce equipment size. A process for generating power for air capture by humidifying dry air is analysed using an equivalent reversible process, which yields minimum utility requirements and maximum (reversible) efficiency. Comprehensive socio-economic and environmental assessments of NETs are needed. The Process Analysis Method provides a triple-bottom line sustainability assessment, but results are dependent on uncertain external factors such as the introduction of flue gas-CCS and the growth rate of renewables. The challenge for NETs becomes easier the faster the transition to a low-carbon economy occurs.

Enhancer trap Arabidopsis thaliana plants were screened for genes up-regulated by virus infection. The plants carried T-DNA insertions comprising a minimal -60-bp Cauliflower mosaic virus 35S promoter fused to the β-glucuronidase (GUS) reporter gene. Approximately 12,000 plants were assayed for GUS activity before and after rub-inoculation with Tobacco rattle virus (TRV) tagged with the green fluorescent protein (GFP). One plant and its progeny consistently showed upregulation of GUS activity in response to TRV-GFP infection, indicating that a virus-responsive enhancer element was “tagged” by the T-DNA in this line. Other viruses, bacteria, and oomycetes, but not wounding, up-regulated GUS activity in the enhancer trap line, indicating that the response was not specific to TRV-GFP infection. A pathogen-inducible, alternatively spliced gene was identified, which we have termed TRI for TRV-induced gene. A pathogen-responsive element was localized to a 1.1-kb region upstream of the T-DNA insertion, and two different cis-acting elements, both implicated in defense responses, were found in the sequence upstream of TRI. Sequence analyses revealed that TRI is similar to ACRE169, a gene that is up-regulated in Cf-9-expressing tobacco when treated with Avr-9, the Cladosporium fulvum elicitor of the Cf-9 resistance response.