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Cellulose/reduced graphene oxide (rGO)/Fe3O4 aerogels exhibiting strong electromagnetic wave absorption were prepared by a green, simple, and scalable coprecipitation process. With rGO loading of 8...

Biofoam materials are attractive alternatives for petroleum-based foams to be used to solve environmental problems. Inspired by steamed bread, we report herein a novel utilization of wheat flour (WF) with the introduction of carbon nanotubes (CNTs) to form an environmentally friendly WF/CNT composite foam. This foam displayed a high elasticity (nearly 100% shape recovery), recyclable (5000 cycles), fast (100 ms), and superstability pressure-sensing response. It could serve as a new pressure sensor to detect the tiny pressure (1.76 Pa) and acoustic vibrations from piano notes. As an acoustic sensor, WF/CNT foam detected and recognized different volumes and frequencies of piano sounds. As an electromagnetic interference (EMI) shielding switch, the EMI shielding effectiveness (SE) of the foam could be easily regulated under self-fixable compression-recovery cycles. In addition, the WF/CNT foam could be converted into the WF/CNT film by a hot-compress process. This flexible film was applied as a multifunctional sensing device for detecting various motions. Therefore, wheat flour as a renewable resource could be designed into various WF-based biofoams with new functionalities and outstanding mechanical properties through a simple process.

The influence of surface modification of zirconia (ZrO2) membrane with tethered poly(vinyl pyrrolidone) (PVP) chains was evaluated with respect to the impact of pH and ionic strength on hydraulic resistance and fouling resistance in the filtration of bovine serum albumin (BSA) and lysozyme (Lys) as model protein foulants. The tethered PVP surface layer led to membrane permeability and fouling propensity that were responsive to both pH and ionic strength. The PVP-modified membrane (PVP-ZrO2) hydraulic resistance increased by up to ~48% over a pH range of 6–11, but with no discernible impact at lower pH. Membrane hydraulic resistance was virtually unaffected by ionic strength over the 0.001–1 M range. However, reversible foulant cake resistance in BSA and Lys solution filtration increased with elevated ionic strength, owing in part to the weakening of protein–protein repulsion. Irreversible BSA and Lys fouling was affected by the operational pH relative to the protein isoelectric point (IEP) and reduced under conditions of chain swelling. Irreversible membrane fouling resistance for both proteins was significantly lower, by ~11–49% and 18–74%, respectively, for the PVP-ZrO2 membrane relative to the unmodified ZrO2 membrane. The present results suggest the merit of further exploration of fouling reduction and improvement of membrane cleaning effectiveness via tuning pH and ionic strength triggered conformational responsiveness of the tethered target polymer layer.

This paper first proposes a high-strength (HS) steel-moment frame structure with replaceable damage-control fuses, which utilized the very large elastic deformation capacity of HS steel and...

Lignin valorization has been scarcely considered in the form of liquid crystalline polymer blends. Recently, a stabilizing effect of organosolv lignin (OSL) on the oriented mesophase of hydroxypropyl cellulose (HPC) was observed and related to drastic improvements in tensile properties of the blends. With a view to elucidating this relaxation phenomenon, different molecular weight fractions and derivatives of organosolv lignin are synthesized, blended in solution with the liquid crystalline cellulosic polymer and analyzed in regard to their effect on the microstructural evolution of shear-aligned HPC chains. The rheological and rheo-optical investigations suggest a crucial contribution of the lower molecular weight oligomers and the phenolic hydroxy functionalities to the stabilization of the oriented cellulosic mesophase. The results provide an indication of the molecular origin and mechanism and might be of special interest for the production of anisotropic materials from liquid crystalline cellulosic polymers.

PurposeThe purpose of this paper is to gain a deeper insight on how education boosts economic progress in key emerging economies. This project is aimed at exploring the interactive dynamics between the tertiary education sector and economic development in BRICS countries. The author also aims to examine how the structure of higher education contributes to economic expansion.Design/methodology/approachThe author uses the time series data of BRICS countries across approximately two decades to determine the statistical causality between the size of tertiary enrollment and economic development. The linear regression model is then used to figure out the different impact levels of academic and vocational training programs at the tertiary level to economic development.FindingsData from all BRICS countries exhibited a unidirectional statistical causality relationship, except the Brazilian data. The national economic expansion Granger Caused increased tertiary enrollment in Russia and India, while in China and South Africa, higher education enrollment Granger Caused economic progress. The impact from tertiary academic training is found to be positive for all BRICS nations, while tertiary vocation training is shown to have impaired the Russian and South African economy.Research limitations/implicationsThis project is based on a rather small sample size, and the stationary feature of the time series could be different should a larger pool of data spanning a longer period of time is used. In addition, the author also neglects other control variables in the regression model. Therefore, the impact level could be distorted due to possible omitted variable bias.Practical implicationsTertiary academic study is found to have a larger impact level to all countries’ economic advancement, except for China, during the time frame studied. There is a statistical correlation between the education and economic progress. This is particularly true for BRICS countries, especially China. But the exception is Brazil.Social implicationsThe government should provide education up to the certain level, as there is a direct correlation to the job creation and economic progress. Furthermore, the government should also work closely with industry to ensure growth of industry and creation of new jobs.Originality/valueThe comparative analysis and evaluation of the dynamic interaction of tertiary enrollment and economic output across all five BRICS nations is unique, and it deepens the understanding of the socioeconomic development in these countries from a holistic management perspective.

Cellulose/graphene nanocomposite films are prepared by dispersing graphene oxide (GO) and dissolving cellulose homogeneously in alkaline–urea aqueous solution followed by in situ chemical reduction of GO to rGO. The efficient and eco-friendly reduction process renders these novel composites high electrical conductivity as well as good mechanical properties. As demonstrated on composites with 5 wt% rGO, the rGO/cellulose composite films can be applied as multifunctional sensor materials responding to different external stimuli, such as temperature, humidity, stress/strain, and liquids by electrical resistance changes.

Sulfated nanocellulose (SNC) is used as a dispersant instead of poly(styrene sulfonate) (PSS) to prepare poly(3,4-ethylenedioxythiophene) (PEDOT) dispersion by in-situ polymerization. Due to the excellent electronegativity provided by the sulfate groups on the cellulose chain and the colloidal stability of nanocellulose, the obtained PEDOT:SNC dispersions exhibit controllable conductivity, high stability with less dispersant and even good redispersibility. In addition, these dispersions show excellent printing suitability on a variety of substrates, proving their great potential to be applied as conductive ink for electronic circuit printing. Based on the outstanding forming ability of SNC, high performance PEDOT/SNC nanocomposite film can be fabricated from the PEDOT:SNC dispersion directly, which can serve as high-performance multifunctional sensors to external stimuli.

The rational design of high-performance, flexible, transparent, electrically conducting sensor attracts considerable attention. However, these designed devices predominantly utilize glass and plastic substrates, which are expensive and not environmentally friendly. Here, novel transparent and conductive woods (TCWs) were fabricated by using renewable wood substrates and low-cost conductive polymers. Polymerizable deep eutectic solvents (PDES), acrylic-acid (AA)/choline chloride (ChCl), were used as backfilling agents and in situ photopolymerized in the delignified wood, which endowed the materials with high transparency (transmittance of 90%), good stretchability (strain up to 80%), and high electrical conductivity (0.16 S m-1). The retained cellulose orientation and strong interactions between the cellulose-rich template and poly(PDES) endow TCWs with excellent mechanical properties. Moreover, TCWs exhibited excellent sensing behaviors to strain/touch, even at low strain. Therefore, these materials can be used to detect weak pressure such as human being's subtle bending-release activities. This work provides a new route to fabricate functional composite materials and devices which have promising potential for electronics applications in flexible displays, tactile skin sensors, and other fields.

Hydraulic permeability and molecular weight cutoff (MWCO) performance tuning of polysulfone (PSf) ultrafiltration (UF) membrane was attained via surface modification with a tethered layer of poly(acrylic acid) (PAA). Surface nano-structured (SNS) PAA layer was synthesized onto base PSf UF membranes by atmospheric pressure plasma (APP) surface activation followed by graft polymerization (GP) of acrylic acid (AA). Through a systematic study, it was shown that effective SNS-PAA-PSf UF membrane performance tuning was feasible by adjustments of APP and graft polymerization conditions. It was shown, for the first time, that SNS-PAA-PSf membranes can be synthesized with a range of hydraulic permeability (spanning a factor of 1.1–2.6 in magnitude) for a given MWCO, or a range of MWCO (spanning a factor of 1.5–2.3 in magnitude) for a given hydraulic permeability, thereby overcoming the hydraulic permeability-MWCO tradeoff.

This paper presents the role of global Industry 4.0 technology management in the growth of the wind turbine industry. The article begins with a brief overview of the Industry 4.0 wind turbine industry development, focusing on factors shaping this development. The legal policies are identified as one of the significant factors, especially in PR China and Germany. A detailed secondary data analysis of the country-specific systems is presented, followed by the analysis of patents and companies in both countries to understand better how the development, management and transfer of technology affected the different factors and the global patterns. An effective approach of acquiring technology for local enterprises as well as market development entry mode for the foreign technology holding companies are both identified. Accessing technology through licensing, entering joint ventures, or acquiring knowledge-intensive companies can be identified as common and often successful industry approaches. To develop, obtain, or maintain competitive advantages in the wind turbine industry, we suggest that the governments issue relevant legislation and regulations to support the upgrading of the industry, and the enterprises can access and manage the technology through the approaches mentioned above.

The monograph, electrical conductivity, and rheological behaviors of isotactic polypropylene /carbon black (CB)/multiwalled carbon nanotubes (MWCNTs) composites were studied. Ternary composites including MWCNTs and CB revealed an electrical property similar to the binary MWCNTs composites. This work showed that a synergistic effect result in preserved electrical behavior with a simultaneous effective reduced of the MWCNTs amount. Moreover, the combination of conductive fillers also resulted in a decreased rheological percolation threshold, an accelerated formation of rheological network and a delay in the destruction of the filler network. The similar value of the activation energy for CB/MWCNTs and MWCNTs verified the existence of a co-supporting networked formed by MWCNTs and CB. Two strain-softening processes are found in a strain sweep for the ternary composite melt with high filler loading. The low-strain-softening process may be an indication that the MWCNTs filler network is broken into separated aggregated structures, while the high-strain-softening process should be related to the breakdown of the temporary network structure. POLYM. COMPOS., 2016. © 2016 Society of Plastics Engineers

This paper firstly developed a new type of moment frame using high strength steel (HSS) members and fuse-equipped joints. In this structure, the beams and columns were made of S690 HSS whilst replaceable fuses near the welded beam-to-column joints were used to prevent damage. Cyclic tests on T-joints with fuses were then carried out. A three-dimensional solid-element based finite element model (FEM) was developed to simulate structural behaviours of beam-to-column joints. The FEM was validated by the reported cyclic test results. FE parametric studies were then performed to investigate the influences of different parameters on seismic behaviours of fuse-equipped T-joint. These studied parameters included the slenderness ratio of fuse plate, gap size in fuse joints, yield strength of fuse plate, and pre-arching of fuse plates. The FE parametric studies showed that for HSS fuse-equipped T-joint increasing slenderness ratio of fuse plate reduced its energy dissipation capacity; increasing the gap size in fuse joints and pre-arching of fuse plate exhibited marginal influences on its seismic resistance; using higher strength fuse plates improved its seismic resistance.

The feasibility of wellhead water treatment in small communities for nitrate removal and salinity reduction via a flexible high recovery RO system was evaluated through analysis of treatment options, laboratory and onsite field tests. In small remote communities that rely on septic systems for residential wastewater treatment, discharge of the RO residual stream (containing nitrate) to the community septic tank is shown to be a feasible option. It is demonstrated that RO treatment with a system that employs partial concentrate recycle, integrated with a pressure intensifier, enabled the use of a relatively low-pressure feed pump while allowing high recovery operation. The approach of integrating RO treatment into existing community small water systems is demonstrated to be suitable for providing effective nitrate removal and salinity reduction over wide range of nitrate and salinity levels, while meeting community water demand and regulatory water quality requirements.

With the popularization of music streaming services, millions of songs can be accessed easily. The effectiveness of music access can be further enhanced by making the labels of a music playlist more indicative of the theme of the playlist. However, manually classifying playlists is laborious and often requires domain knowledge. In this paper, we propose a novel multi-label model for playlist classification based on a convolutional neural network. The network is trained in an end-to-end manner to jointly learn song embedding and convolutional filters without the need of feature extraction from audio signals. Specifically, the song embedding vectors are concatenated as a matrix to represent a playlist, and the convolutional filters for playlist classification are applied to the playlist matrix. We also propose two augmentation techniques to prevent over-fitting of playlist data and to improve the training of the proposed model. Experimental results show that the proposed model performs significantly better than the support vector machine and k-nearest neighbors models.

This paper proposed a framework FINS to identify the niche singers by using the listening history from online music streaming services. First of all, we show that the distribution of frequency of songs listen follows the power law. Then, the approach of selecting candidates for niche singers is designed based on Pareto principle. Secondly, the approach to inferring and ranking niche singers is proposed where the users with strong preference are found. Based on the fact that the niche singers are usually supported by a group of loyal fans, the niche singers with lots of loyal fans could be discovered. Finally, based on the number of loyal fans and their listening behavior, the hotness of niche singers could be defined so that the niche singers with top-k hotness score can be derived as our output. Finally, the experimental results show that FINS could effectively identified the niche singers.

Online streaming services are prevalent. Major service providers, such as Netflix (for movies) and Spotify (for music), usually have a large customer base. More often than not, users may share an account. This has attracted increasing attention recently, as account sharing not only compromises the service provider's financial interests but also impairs the performance of recommendation systems and consequently the quality of service provided to the users. To address this issue, this paper focuses on the problem of user identification in shared accounts. Our goal is three-fold: (1) Given an account, along with its historical session logs, we identify a set of users who share such account; (2) Given a new session issued by an account, we find the corresponding user among the identified users of such account; (3) We aim to boost the performance of item recommendation by user identification. While the mapping between users and accounts is unknown, we propose an unsupervised learning-based framework, Session-based Heterogeneous graph Embedding for User Identification (SHE-UI), to differentiate and model the preferences of users in an account, and to group sessions by these users. In SHE-UI, a heterogeneous graph is constructed to represent items such as songs and their available metadata such as artists, genres, and albums. An item-based session embedding technique is proposed using a normalized random walk in the heterogeneous graph. Our experiments conducted on two large-scale music streaming datasets, Last.fm and KKBOX, show that SHE-UI not only accurately identifies users, but also significantly improves the performance of item recommendation over the state-of-the-art methods.

Excellent recommendation system facilitates users retrieving contents they like and, what»s much more important - the contents they might like but they are not aware of yet. It will further increase the satisfaction of users and increase the retention rate and conversion rate indirectly. While the public's now listening to all kinds of music, recommendation algorithms still struggle in key areas. Without enough historical data, how would an algorithm know if listeners will like a new song or a new artist? And, how would it know what songs to recommend brand new users? In WSDM Cup 2018, the first task is to solve the abovementioned challenges to build a better music recommendation system. The 2nd task in the Cup focuses on churn prediction. For a subscription business, accurately predicting churn is critical to long-term success. Even slight variations in churn can drastically affect profits. In this task, participants are asked to build an algorithm that predicts whether a user will churn after their subscription expires. The competition data and award are provided by KKBOX, a leading music streaming service in Taiwan.