Handicraft Technique for Making Liansi Paper

Liansi paper is a kind of traditional handmade bamboo paper produced in Yanshan County,Jiangxi Province,whose handicraft technique is listed as a national intangible cultural heritage protection project.This study conducted a field survey in Shangrao,and the main survey areas included Guangxin District and the Hekou,Goose Lake,Gexian Mountain,Tianzhu Mountain,Chenfang,and Shitang townships.Field investigators communicated with a group of intangible cultural heritage inheritors,and with their assistance,clarified the steps and processes involved in the production of Liansi paper.The handicraft technique of Liansi paper consists of five steps:chopping bamboo to make bamboo filaments,steaming bamboo filaments to make bamboo pulp,interweaving fibers into wet paper,drying wet paper,and package processing.A total of 13 processes are involved:chopping bamboo,fermentation,making bamboo filaments,soaking bamboo filaments,steaming bamboo filaments,natural bleaching,pounding bamboo filaments to make bamboo pulp,stirring pulp,adding plant mucilage,interweaving bamboo fibers into wet paper,pressing paper,drying wet paper,and package processing.

Call for Papers from Journal of Future Foods

Journal of Future Foods(ISSN 2772-5669.Owner:Beijing Academy of Food Sciences.Production and Hosting:Elsevier B.V.on behalf of KeAi Communications Co.,Ltd.)is an international,peer-reviewed open access journal belonging to the discipline of food science and technology.The aim of the journal is to report latest research results of high-tech in food science.We welcome submissions that drive the field of food science towards whole food nutrition,intelligence and high technology.

Call for Papers

Geodesy and Geodynamics mainly publishes the newest research in the Geodesy and Geodynamics.The journal has been indexed by Ei Compendex,Scopus,ESCI,CSCD,NASA ADS,Geobase,GeoRef Preview database,Ulrich's Periodical Directory,VINITI databse.All the papers accepted by the journal are open access on the ScienceDirect with free charge(ttp://ww.sciencedirect.com/science/journa/6749847.)

Method for triangular fuzzy multiple attribute decision making based on two-dimensional density operator method

Aiming at the triangular fuzzy(TF)multi-attribute decision making(MADM)problem with a preference for the distribution density of attribute(DDA),a decision making method with TF number two-dimensional density(TFTD)operator is proposed based on the density operator theory for the decision maker(DM).Firstly,a simple TF vector clustering method is proposed,which considers the feature of TF number and the geometric distance of vectors.Secondly,the least deviation sum of squares method is used in the program model to obtain the density weight vector.Then,two TFTD operators are defined,and the MADM method based on the TFTD operator is proposed.Finally,a numerical example is given to illustrate the superiority of this method,which can not only solve the TF MADM problem with a preference for the DDA but also help the DM make an overall comparison.

Call for Papers

Geodesy and Geodynamics mainly publishes the newest research in the Geodesy and Geodynamics.The journal has been indexed by Ei Compendex,Scopus,ESCl,CSCD,NASA ADS,Geobase,GeoRef Preview database,Ulrich's Periodical Directory,VINITI databse.All the papers accepted by the journal are open access on the ScienceDirect with free charge(http://www.sciencedirect.com/science/journal/16749847).

Call for Papers

Geodesy and Geodynamics mainly publishes the newest research in the Geodesy and Geodynamics.The journal has been indexed by Ei Compendex,Scopus,ESCl,CSCD,NASA ADS,Geobase,GeoRef Preview database,Ulrich's Periodical Directory,VINITI databse.All the papers accepted by the journal are open access on the ScienceDirect with free charge(http://www.sciencedirect.com/science/journal/16749847).

Call for Papers from Journal of Future Foods

Journal of Future Foods(ISSN 2772-5669.Owner:Beijing Academy of Food Sciences.Production and Hosting:Elsevier B.V.on behalf of KeAi Communications Co.,Ltd.)is an international,peer-reviewed open access journal belonging to the discipline of food science and technology.The aim of the journal is to report latest research results of high-tech in food science.We welcome submissions that drive the field of food science towards whole food nutrition,intelligence and high technology.

Call for Papers from Journal of Future Foods

FoodsJournal of Future Foods(ISSN 2772-5669.Owner:Beijing Academy of Food Sciences.Production and Hosting:Elsevier B.V.on behalf of KeAi Communications Co.,Ltd.)is an international,peer-reviewed open access journal belonging to the discipline of food science and technology.The aim of the journal is to report latest research results of high-tech in food science.We welcome submissions that drive the field of food science towards whole food nutrition,intelligence and high technology.

Call for Papers from Journal of Future Foods

Journal of Future Foods(ISSN 2772-5669.Owner:Beijing Academy of Food Sciences.Production and Hosting:Elsevier B.V.on behalf of KeAi Communications Co.,Ltd.)is an international,peer-reviewed open access journal belonging to the discipline of food science and technology.The aim of the journal is to report latest research results of high-tech in food science.We welcome submissions that drive the field of food science towards whole food nutrition,intelligence and high technology.

Call for Papers from Journal of Future Foods

Journal of Future Foods(ISSN 2772-5669.Owner:Beijing Academy of Food Sciences.Production and Hosting:Elsevier B.V.on behalf of KeAi Communications Co.,Ltd.)is an international,peer-reviewed open access journal belonging to the discipline of food science and technology.The aim of the journal is to report latest research results of high-tech in food science.We welcome submissions that drive the field of food science towards whole food nutrition,intelligence and high technology.

Call for Papers from Journal of Future Foods

Journal of Future Foods(ISSN 2772-5669.Owner:Beijing Academy of Food Sciences.Production and Hosting:Elsevier B.V.on behalf of KeAi Communications Co.,Ltd.)is an international,peer-reviewed open access journal belonging to the discipline of food science and technology.The aim of the journal is to report latest research results of high-tech in food science.We welcome submissions that drive the field of food science towards whole food nutrition,intelligence and high technology.

Call for Papers from Journal of Future Foods

Journal of Future Foods(ISSN 2772-5669.Owner:Beijing Academy of Food Sciences.Production and Hosting:Elsevier B.V.on behalf of KeAi Communications Co.,Ltd.)is an international,peer-reviewed open access journal belonging to the discipline of food science and technology.The aim of the journal is to report latest research results of high-tech in food science.We welcome submissions that drive the field of food science towards whole food nutrition,intelligence and high technology.

Call for Papers from Journal of Future FoodsJournal of Future Foods

Journal of Future Foods(ISSN 2772-5669.Owner:Beijing Academy of Food Sciences.Production and Hosting:Elsevier B.V.on behalf of KeAi Communications Co.,Ltd.)is an international,peer-reviewed open access journal belonging to the discipline of food science and technology.The aim of the journal is to report latest research results of high-tech in food science.We welcome submissions that drive the field of food science towards whole food nutrition,intelligence and high technology.

Call for Papers from Journal of Future Foods

Journal of Future Foods(ISSN 2772-5669.Owner:Beijing Academy of Food Sciences.Production and Hosting:Elsevier B.V.on behalf of KeAi Communications Co.,Ltd.)is an international,peer-reviewed open access journal belonging to the discipline of food science and technology.The aim of the journal is to report latest research results of high-tech in food science.We welcome submissions that drive the field of food science towards whole food nutrition,intelligence and high technology.

Call for Papers from Journal of Future Foods

Journal of Future Foods(ISSN 2772-5669.Owner:Beijing Academy of Food Sciences.Production and Hosting:Elsevier B.V.on behalf of KeAi Communications Co.,Ltd.)is an international,peer-reviewed open access journal belonging to the discipline of food science and technology.The aim of the journal is to report latest research results of high-tech in food science.We welcome submissions that drive the field of food science towards whole food nutrition,intelligence and high technology.

Research on Carbon Peak and Carbon Neutrality Technological Pathways in the Chinese Papermaking Industry

Against the backdrop of the dual carbon goals,the papermaking industry in China faces significant pressure to reduce emissions and lower carbon intensity.Based on historical data of energy consumption in the pulp and paper industry in China from 2000 to 2020,this study analyzed the current status of paper production and energy consumption in China.Two methods were employed to predict the growth trend of paper production in China,and three carbon dioxide emission accounting methods were compared.The study used an accounting method based on the industry’s overall energy consumption and predicted the carbon dioxide(CO_(2))emissions of the Chinese papermaking industry from 2021 to 2060 under three scenarios.The study identified the timing for achieving carbon peak and proposed the measures for carbon neutrality.The results indicated that:(1)the CO_(2)emissions of the Chinese papermaking industry in 2020 were 111.98 million tons.(2)Under low-demand,high-demand,and baseline scenarios,the papermaking industry is expected to achieve carbon peak during the“14th Five-Year Plan”period.(3)In 2060,under the three scenarios,CO_(2)emissions from the papermaking industry will decrease by 11%-31%compared to the baseline year.However,there will still be emissions of 72-93 million tons,requiring reductions in fossil energy consumption at the source,increasing forestry carbon sequestration and utilization of Carbon Capture,Utilization and Storage(CCUS)technology,and taking measures such as carbon trading to achieve carbon neutrality.

Novelty of Different Distance Approach for Multi-Criteria Decision-Making Challenges Using q-Rung Vague Sets

In this article,multiple attribute decision-making problems are solved using the vague normal set(VNS).It is possible to generalize the vague set(VS)and q-rung fuzzy set(FS)into the q-rung vague set(VS).A log q-rung normal vague weighted averaging(log q-rung NVWA),a log q-rung normal vague weighted geometric(log q-rung NVWG),a log generalized q-rung normal vague weighted averaging(log Gq-rung NVWA),and a log generalized q-rungnormal vagueweightedgeometric(logGq-rungNVWG)operator are discussed in this article.Adescription is provided of the scoring function,accuracy function and operational laws of the log q-rung VS.The algorithms underlying these functions are also described.A numerical example is provided to extend the Euclidean distance and the Humming distance.Additionally,idempotency,boundedness,commutativity,and monotonicity of the log q-rung VS are examined as they facilitate recognizing the optimal alternative more quickly and help clarify conceptualization.We chose five anemia patients with four types of symptoms including seizures,emotional shock or hysteria,brain cause,and high fever,who had either retrograde amnesia,anterograde amnesia,transient global amnesia,post-traumatic amnesia,or infantile amnesia.Natural numbers q are used to express the results of the models.To demonstrate the effectiveness and accuracy of the models we are investigating,we compare several existing models with those that have been developed.

Two-Stage IoT Computational Task Offloading Decision-Making in MEC with Request Holding and Dynamic Eviction

The rapid development of Internet of Things(IoT)technology has led to a significant increase in the computational task load of Terminal Devices(TDs).TDs reduce response latency and energy consumption with the support of task-offloading in Multi-access Edge Computing(MEC).However,existing task-offloading optimization methods typically assume that MEC’s computing resources are unlimited,and there is a lack of research on the optimization of task-offloading when MEC resources are exhausted.In addition,existing solutions only decide whether to accept the offloaded task request based on the single decision result of the current time slot,but lack support for multiple retry in subsequent time slots.It is resulting in TD missing potential offloading opportunities in the future.To fill this gap,we propose a Two-Stage Offloading Decision-making Framework(TSODF)with request holding and dynamic eviction.Long Short-Term Memory(LSTM)-based task-offloading request prediction and MEC resource release estimation are integrated to infer the probability of a request being accepted in the subsequent time slot.The framework learns optimized decision-making experiences continuously to increase the success rate of task offloading based on deep learning technology.Simulation results show that TSODF reduces total TD’s energy consumption and delay for task execution and improves task offloading rate and system resource utilization compared to the benchmark method.

Enhancing the Decomposition of Paper Cups Using Galleria Mellonella and Eisenia Fetida

The composition of paper cups creates a challenge for the recycling industry,as the paperboard–plastic film composite is hard to separate.Therefore,paper cups are sent to landfills or waste incinerators.This study explores the combined use of red worms(Eisenia fetida)and Greater wax moth(Galleria mellonella)in the biodegradation of paper cups.The study investigates the conditions and combinations that promote using Eisenia fetida and Galleria mellonella for degrading paper cups.The study considered the influence of environmental temperature,the presence of food waste,varying the number of Eisenia fetida worms,and the presence of a Galleria mellonella growth-slowing agent on the degradation process.To achieve the study objectives,the study followed a quantitative approach.The study monitored the degradation of paper cup cuts that were placed in jars containing different combinations of Eisenia fetida worms,Galleria mellonella larvae,food waste,bedding material,and Galleria mellonella growth-slowing agents.The study found that the best operating temperature is 30oC.The study found that using food waste improves the performance of Eisenia fetida worms and Galleria mellonella larvae significantly.The study found that adding a Galleria mellonella growth-slowing agent slightly enhances the degradation of the paper cup.Finally,a numerical model was obtained to simulate the paper cup degradation efficiency.

A Large-Scale Group Decision Making Model Based on Trust Relationship and Social Network Updating

With the development of big data and social computing,large-scale group decisionmaking(LGDM)is nowmerging with social networks.Using social network analysis(SNA),this study proposes an LGDM consensus model that considers the trust relationship among decisionmakers(DMs).In the process of consensusmeasurement:the social network is constructed according to the social relationship among DMs,and the Louvain method is introduced to classify social networks to form subgroups.In this study,the weights of each decision maker and each subgroup are computed by comprehensive network weights and trust weights.In the process of consensus improvement:A feedback mechanism with four identification and two direction rules is designed to guide the consensus of the improvement process.Based on the trust relationship among DMs,the preferences are modified,and the corresponding social network is updated to accelerate the consensus.Compared with the previous research,the proposedmodel not only allows the subgroups to be reconstructed and updated during the adjustment process,but also improves the accuracy of the adjustment by the feedbackmechanism.Finally,an example analysis is conducted to verify the effectiveness and flexibility of the proposed method.Moreover,compared with previous studies,the superiority of the proposed method in solving the LGDM problem is highlighted.