Unraveling the Rheology of Nanocellulose Aqueous Suspensions:A Comprehensive Study on Biomass-Derived Nanofibrillated Cellulose

The rheological properties of nanocellulose aqueous suspensions play a critical role in the development of nanocellulose-based bulk materials.High-crystalline,high-aspect ratio,and slender nanofibrillated cellulose(NFC)were extracted from four biomass resources.The cellulose nanofibrils and nanofibril bundles formed inter-connected networks in the NFC aqueous suspensions.The storage moduli of the suspensions with different concentrations were higher than their corresponding loss moduli.As the concentration increased,the storage and loss modulus of NFC dispersion increased.When the shear rate increased to a certain value,there were differences in the changing trend of the rheological behavior of NFC aqueous suspensions derived from different biomass resources and the suspensions with different solid concentrations.NFC dispersion’s storage and loss modulus increased when the temperature rose to nearly 80℃.We hope this study can deepen the understanding of the rheological properties of NFC colloids derived from different biomass resources.

Different Resistance Exercise Interventions for Handgrip Strength in Apparently Healthy Adults: A Systematic Review

Background: Although handgrip strength is a biomarker for morbidity/mor-tality, there is lack of evidence on the effects of resistance training on handgrip strength in healthy adults of all ages. Objective: The aim of this systematic review was to assess the impact of resistance training on handgrip strength in healthy adults. Methods: Five databases/search engines were searched. Studies comparing different types of resistance exercise interventions versus a non-exercised control group on handgrip strength were included. The available data did not allow us to conduct the pre-planned meta-analyses;therefore, only descriptive statistics were performed to summarize the data. Results: Twenty studies (17 randomized and three non-randomized controlled trials) were included, most of which were conducted in older adults. Twelve studies reported no significant difference in the change in handgrip strength between the resistance training and control groups. Two studies showed increases in handgrip strength in the resistance training group compared with the control group. Other studies included results for multi-training groups or left/right hands and found increasing handgrip strength compared to controls, but only in one training group or one hand. Overall, the randomized and non-ran-domized clinical trials presented moderate risk of bias. Conclusions: Due to the lack of low risk-of-bias randomized controlled trials of young and middle-aged adults, different training protocols, and small sample sizes, the existing evidence appears insufficient to support resistance training for increasing handgrip strength in healthy adults. Future studies may seek to discern the optimal way to develop and employ resistance training to improve hand-grip strength.

米歇尔·福柯与现代史学思潮变化之渊源

在现代世界,法国思想家米歇尔·福柯(Michel Foucault,1926—1984)对当代史学的主导观念、书写内容和研究方法均有重要的影响。首先,福柯改变了近代历史学的主旨,摒弃了启蒙运动思想家希图探究历史规律的所谓"大写的历史"。其次,福柯为"它者"写史,将历史研究的对象从中心转移到了边缘,譬如疯狂、疾病、身体、性等,引发了史学界的诸多新潮——医疗史、性别史、身体史、儿童史、情感史等等。再次,福柯改造了历史研究的方法,指出史家不能仅仅依赖文献,而需要扩大史料的范围,将建筑、机构、规则、技术、物品、习俗等能承载记忆的东西都包含进来。复次,福柯提倡用话语取代语言,提出"考古学"和"系谱学"的概念来考察话语的构成和网络,直接导致了历史学中的"语言学转向"。最后,福柯指出了知识与权力的关系,揭橥了近代理性主义、科学主义所建构的知识体系背后的权力架构和网络。

超越东西:博古学、考据学以及近代早期历史学发展的全球性

从比较的角度考察了18世纪清代考据学的兴起历程及其对近代中国思想发展的深远影响。与欧洲近代早期的人文主义者和博古学者相似的是,清代中后期的考据学者对儒学要义的探寻也有着复古主义的兴趣。他们通过综合运用文字学、音韵学、训诂学从而完善考证的方法,以期将儒家经典恢复到在他们看来更为准确可信的早期版本。正如他们的欧洲同行在推进人文主义和博古学研究时所形成的文人圈一样,这些考据学者为了共同的学术兴趣组成了一个活跃的学术团体,交流研究心得并相互切磋。在对儒家经典产生的历史语境进行重构的过程中,他们也认识到历史学与金石学的重要性,并以历史学的取径诠释经典。在二十世纪初中国近代史学家将历史学研究塑造成现代学科的努力中,清代考据学的学术遗产留下了深刻的印记。考据学的遗产表明,那些在塑造欧洲现代历史学科的过程中通常被认为是独一无二的先例也存在于东亚,很可能也存在于世界的其他地方。我们应当将历史观念以及史学研究的方法论作为一种全球现象加以分析与看待,从而超越东西方二元的方法论。

Energy Consumption Prediction of a CNC Machining Process With Incomplete Data

Energy consumption prediction of a CNC machining process is important for energy efficiency optimization strategies.To improve the generalization abilities,more and more parameters are acquired for energy prediction modeling.While the data collected from workshops may be incomplete because of misoperation,unstable network connections,and frequent transfers,etc.This work proposes a framework for energy modeling based on incomplete data to address this issue.First,some necessary preliminary operations are used for incomplete data sets.Then,missing values are estimated to generate a new complete data set based on generative adversarial imputation nets(GAIN).Next,the gene expression programming(GEP)algorithm is utilized to train the energy model based on the generated data sets.Finally,we test the predictive accuracy of the obtained model.Computational experiments are designed to investigate the performance of the proposed framework with different rates of missing data.Experimental results demonstrate that even when the missing data rate increases to 30%,the proposed framework can still make efficient predictions,with the corresponding RMSE and MAE 0.903 k J and 0.739 k J,respectively.

Characterization of gut microbiome and metabolome in Helicobacter pylori patients in an underprivileged community in the United States

BACKGROUND Helicobacter pylori(H.pylori),a bacterium that infects approximately half of the world’s population,is associated with various gastrointestinal diseases,including peptic ulcers,non-ulcer dyspepsia,gastric adenocarcinoma,and gastric lymphoma.As the burden of antibiotic resistance increases,the need for new adjunct therapies designed to facilitate H.pylori eradication and reduce negative distal outcomes associated with infection has become more pressing.Characterization of the interactions between H.pylori,the fecal microbiome,and fecal fatty acid metabolism,as well as the mechanisms underlying these interactions,may offer new therapeutic approaches.AIM To characterize the gut microbiome and metabolome in H.pylori patients in a socioeconomically challenged and underprivileged inner-city community.METHODS Stool samples from 19 H.pylori patients and 16 control subjects were analyzed.16S rRNA gene sequencing was performed on normalized pooled amplicons using the Illumina MiSeq System using a MiSeq reagent kit v2.Alpha and beta diversity analyses were performed in QIIME 2.Non-targeted fatty acid analysis of the samples was carried out using gas chromatography-mass spectrometry,which measures the total content of 30 fatty acids in stool after conversion into their corresponding fatty acid methyl esters.Multi-dimensional scaling(MDS)was performed on Bray-Curtis distance matrices created from both the metabolomics and microbiome datasets and a Procrustes test was performed on the metabolomics and microbiome MDS coordinates.RESULTS Fecal microbiome analysis showed that alpha diversity was lowest in H.pylori patients over 40 years of age compared to control subjects of similar age group.Beta diversity analysis of the samples revealed significant differences in microbial community structure between H.pylori patients and control subjects across all ages.Thirty-eight and six taxa had lower and higher relative abundance in H.pylori patients,respectively.Taxa that were enriched in H.pylori patients included Atopobium,Gemellaceae,Micrococcaceae,Gemellales and Rothia(R.mucilaginosa).Notably,relative abundance of the phylum Verrucomicrobia was decreased in H.pylori patients compared to control subjects.Procrustes analysis showed a significant relationship between the microbiome and metabolome datasets.Stool samples from H.pylori patients showed increases in several fatty acids including the polyunsaturated fatty acids(PUFAs)22:4n6,22:5n3,20:3n6 and 22:2n6,while decreases were noted in other fatty acids including the PUFA 18:3n6.The pattern of changes in fatty acid concentration correlated to the Bacteroidetes:Firmicutes ratio determined by 16S rRNA gene analysis.CONCLUSION This exploratory study demonstrates H.pylori-associated changes to the fecal microbiome and fecal fatty acid metabolism.Such changes may have implications for improving eradication rates and minimizing associated negative distal outcomes.

Ion Recognition and Analytical Application of a Fibroin Modified Electrode

A novel fibroin modified electrode with ion recognition was reported. The membranewith isoelectric point of pH 4.5, was modified on graphite and carbon fiber electrodes. ThepH-responsive ion recognition of the modified electrode was investigated by use of someneurocompounds. The fibroin carbon fiber electrode has been used for in-vivo determination.

Kite Modeling for Higher Altitude Wind Energy

Among the renewable energy sources, high altitude wind power is gaining increased attention for its better strength, steadiness, and coverage compared to the traditional ground-based wind power with wind turbines. However, unlike the latter, the technology for high altitude wind is still immature and the works on the field are mostly empirical. In our research, we try to set up a framework about force analysis and provide a stepping stone for other kite energy researchers and engineers to develop more efficient systems. In this paper, we analyzed and experimentally verified the effects of acting aerodynamic forces at different angles of attack ranging from 0° to 90°. We also studied the power potentials of a kite corresponding to these varying forces. The work will enable a researcher or engineer to design a more feasible and more efficient kite power system with better understanding of the kite dynamics.

Flexible Nanopaper Composed of Wood-Derived Nanofibrillated Cellulose and Graphene Building Blocks

Nanopaper has attracted considerable interest in the fields of films and paper research.However,the challenge of integrating the many advantages of nanopaper still remains.Herein,we developed a facile strategy to fabricate multifunctional nanocomposite paper(NGCP)composed of wood-derived nanofibrillated cellulose(NFC)and graphene as building blocks.NFC suspension was consisted of long and entangled NFCs(10–30 nm in width)and their aggregates.Before NGCP formation,NFC was chemically modified with a silane coupling agent to ensure that it could interact strongly with graphene in NGCP.The resulting NGCP samples were flexible and could be bent repeatedly without any structural damage.Within the NGCP samples,the high aspect ratio of NFC made a major contribution to its high mechanical strength,whereas the sheet-like graphene endowed the NGCP with electrical resistance and electrochemical activity.The mechanical strength of the NGCP samples decreased as their graphene content increased.However,the electrical resistance and electrochemical activity of the NGCP samples both rose with increasing content of graphene.The NGCPs still kept advantageous mechanical properties even at high temperatures around 300℃ because of the high thermal stability of NFCs and their strong entangled web-like structures.In view of its sustainable building blocks and multifunctional characteristics,the NGCP developed in this work is promising as low-cost and high-performance nanopaper.

The Making of Japanese Femininity： Women, Civilization, and War, from 1868 to 1945

This article traces the development of modem Japanese femininity from the Meiji Restoration （1868） to the end of the Asia Pacific War （1945）. It explores how modem Japanese femininity was constructed in relation to ＂civilization＂ （bunmei） and war. With the introduction of the Western notion of ＂civilization＂, the Meiji state tried to ＂civilize＂ its views on women to become on par with the West. As the status of women became a major national issue in the late 19th century, women began to regard themselves as important members of the nation through their involvement in patriotic activities. During the Second Sino-Japanese War and Asia Pacific War, women strengthened their ties to the nation by supporting the wars on the home front as mothers, wives, laborers, and members of women＇s association. This made patriotism, frugality, and selflessness essential to the definition of the Japanese woman. In addition to these qualities, chastity was central to the idealized image of the Japanese woman. Through the examination of the historical development of Japanese femininity, this article offers insight into the image of ＂good Japanese woman＂.

Contemporary Designs for Long-Term Care (LTC) Facilities

In addition to experiencing shortage in LTC workforce, some existing facilities are unable to provide quality service, since they were designed and built decades ago. Thus, the renovation of outdated LTC facilities is currently an unavoidable issue. In this paper, some contemporary practices are presented related to renovating old LTC facilities to improve the quality of service. The most important concept is the person-centered design. Some other elements include the importance of natural lighting for residents, proper practices of flooring and picking doors, some details in home-like design, new guidelines for resident rooms’ design, and other miscellaneous issues. Furthermore, the latest Americans with Disabilities Act (ADA) compliance protocols are reviewed, and some crucial elements are discussed to ensure the renovations will make the facilities compliant with the current standards.

Recent advances in artificial intelligence generated content

Artificial intelligence generated content(AIGC)has been a research hotspot in the field of artificial intelligence in recent years.It is expected to replace humans in performing some of the work of content generation at a low cost and a high volume,such as music,painting,multimodal content generation,news articles,summary reports,stock commentary summaries,and even content and digital people generated in the meta-universe.AIGC provides a new technical path for the development and implementation of AI in the future.

Photonic analog signal processing and neuromorphic computing[Invited]

In this review paper,we discuss the properties and applications of photonic computing and analog signal processing.Photonic computational circuits have large operation bandwidth,low power consumption,and fine frequency control,enabling a wide range of application-specific computational techniques that are impossible to implement using traditional electrical and digital hardware alone.These advantages are illustrated in the elegant implementation of optical steganography,the real-time blind separation of signals in the same bandwidth,and the efficient acceleration of artificial neural network inference.The working principles and use of photonic circuits for analog signal processing and neuromorphic computing are reviewed and notable demonstrated applications are highlighted.

Approximating Special Social Influence Maximization Problems

Social Influence Maximization Problems(SIMPs)deal with selecting k seeds in a given Online Social Network(OSN)to maximize the number of eventually-influenced users.This is done by using these seeds based on a given set of influence probabilities among neighbors in the OSN.Although the SIMP has been proved to be NP-hard,it has both submodular(with a natural diminishing-return)and monotone(with an increasing influenced users through propagation)that make the problem suitable for approximation solutions.However,several special SIMPs cannot be modeled as submodular or monotone functions.In this paper,we look at several conditions under which non-submodular or non-monotone functions can be handled or approximated.One is a profit-maximization SIMP where seed selection cost is included in the overall utility function,breaking the monotone property.The other is a crowd-influence SIMP where crowd influence exists in addition to individual influence,breaking the submodular property.We then review several new techniques and notions,including double-greedy algorithms and the supermodular degree,that can be used to address special SIMPs.Our main results show that for a specific SIMP model,special network structures of OSNs can help reduce its time complexity of the SIMP.

In vitro evaluation of 3D printed polycaprolactone scaffolds with angle-ply architecture for annulus fibrosus tissue engineering

Tissue engineering of the annulus fibrosus(AF)is currently being investigated as a treatment for intervertebral disc degeneration,a condition frequently associated with low back pain.The objective of this work was to use 3D printing to generate a novel scaffold for AF repair that mimics the structural and biomechanical properties of the native tissue.Multi-layer scaffolds were fabricated by depositing polycaprolactone struts in opposing angular orientations,replicating the angle-ply arrangement of the native AF tissue.Scaffolds were printed with varied strut diameter and spacing.The constructs were characterized morphologically and by static and dynamic mechanical analyses.Scaffold surfaces were etched with unidirectional grooves and the influence on bovine AF cell metabolic activity,alignment,morphology and protein expression was studied in vitro.Overall,the axial compressive and circumferential tensile properties of the scaffolds were found to be in a similar range to the native AF tissue.Confocal microscopy images indicated that cells were able to attach and spread on the smooth polycaprolactone scaffolds,but the surface texture induced cellular alignment and proliferation.Furthermore,immunofluorescence analysis demonstrated the aligned deposition of collagen type I,aggrecan and the AF-specific protein marker tenomodulin on the etched scaffolds.Overall,results demonstrated the potential for using the scaffolds as a template for AF regeneration.

A Two-stage Peer-to-peer Energy Trading Model for Distribution Systems with Participation of Utility

With the growing penetration of distributed energy resources(DER)in distribution systems,the traditional utility dominated tariff-based business model may no longer meet the need for further development.As a result,the transformation from the traditional tariff-based business model to the emerging peer-to-peer energy trading model has been acknowledged by researchers and policy makers.In this paper,a two-stage peer-to-peer energy trading model is proposed while considering the role of the utility.Specifically,energy transactions between buyers and sellers are optimized in the first stage;the cleared transactions are submitted to the utility for approval in the second stage,which solves a transaction approval model to verify the transactions from the perspective of secure system operations.Indeed,certain transactions mav be disapproved to ensure that all network constraints,such as voltage and line flow limitations,are satisfied.In addition,a comprehensive trading tariff is designed to recover the hidden costs of the utility,such as those associated with network usage,system losses,and ancillary service provision.A modified 33-bus distribution system is adopted to verify the proposed model.

Energy efficient cutting parameter optimization

Mechanical manufacturing industry consumes substantial energy with low energy efficiency. Increasing pressures from energy price and environmental directive force mechanical manufacturing industries to implement energy efficient technologies for reducing energy consumption and improving energy efficiency of their machining processes. In a practical machining process, cutting parameters are vital variables set by manufacturers in accordance with machining requirements of workpiece and machining condition. Proper selection of cutting parameters with energy consideration can effectively reduce energy consumption and improve energy efficiency of the machining process. Over the past 10 years, many researchers have been engaged in energy efficient cutting parameter optimization, and a large amount of literature have been published. This paper conducts a comprehensive literature review of current studies on energy efficient cutting parameter optimization to fully understand the recent advances in this research area. The energy consumption characteristics of machining process are analyzed by decomposing total energy consumption into electrical energy consumption of machine tool and embodied energy of cutting tool and cutting fluid. Current studies on energy efficient cutting parameter optimization by using experimental design method and energy models are reviewed in a comprehensive manner. Combined with the current status, future research directions of energy efficient cutting parameter optimization are presented.

Field cracking performance of airfield rigid pavements

This paper discusses cracking in airport pavements as studied in Construction Cycle 6 of testing carried out at the National Airport Pavement Testing Facility by the Federal Aviation Administration. Pavements of three different flexural strengths as well as two different subgrades, a soft bituminous layer and a more rigid layer known as econocrete, were tested. In addition to this, cracking near two types of isolated transition joints, a reinforced edge joint and a thickened edge joint, was considered. The pavement sections were tested using a moving load simulating that of an aircraft. It has been determined that the degree of cracking was reduced as the flexural strength of the pavement was increased and that fewer cracks formed over the econocrete base than over the bituminous base. In addition, the thickened edge transition joint was more effective in preventing cracking at the edges compared to the reinforced edge joint.

Accelerating DAG-Style Job Execution via Optimizing Resource Pipeline Scheduling

The volume of information that needs to be processed in big data clusters increases rapidly nowadays. It is critical to execute the data analysis in a time-efficient manner. However, simply adding more computation resources may not speed up the data analysis significantly. The data analysis jobs usually consist of multiple stages which are organized as a directed acyclic graph (DAG). The precedence relationships between stages cause scheduling challenges. General DAG scheduling is a well-known NP-hard problem. Moreover, we observe that in some parallel computing frameworks such as Spark, the execution of a stage in DAG contains multiple phases that use different resources. We notice that carefully arranging the execution of those resources in pipeline can reduce their idle time and improve the average resource utilization. Therefore, we propose a resource pipeline scheme with the objective of minimizing the job makespan. For perfectly parallel stages, we propose a contention-free scheduler with detailed theoretical analysis. Moreover, we extend the contention-free scheduler for three-phase stages, considering the computation phase of some stages can be partitioned. Additionally, we are aware that job stages in real-world applications are usually not perfectly parallel. We need to frequently adjust the parallelism levels during the DAG execution. Considering reinforcement learning (RL) techniques can adjust the scheduling policy on the fly, we investigate a scheduler based on RL for online arrival jobs. The RL-based scheduler can adjust the resource contention adaptively. We evaluate both contention-free and RL-based schedulers on a Spark cluster. In the evaluation, a real-world cluster trace dataset is used to simulate different DAG styles. Evaluation results show that our pipelined scheme can significantly improve CPU and network utilization.