Reuse Capability Research Articles

Preparation of hydrophilic PVDF membranes through in situ assembly of phytate-polyethyleneimine-Fe3+ for efficient separation of herbal volatile oil from oily water.

In the realm of oil-water separation technologies, membrane-based separation emerges as an efficacious approach. Nevertheless, crafting a hydrophilic membrane capable of effectively segregating herbal volatile oil remains a formidable challenge. Our study introduces a facile in situ assembly strategy for fabricating a double-crosslinked composite coating comprising phytate (PA)-polyethyleneimine (PEI) polyelectrolyte complexes and PA-Fe3⁺ assemblies. The PA within the PA-PEI/Fe3⁺ coatings form a double cross-linking layer through interactions with amine groups and metal ions, thereby enhancing interfacial interactions and structural integrity of the membranes. Consequently, the resultant PVDF/PA-PEI/Fe3⁺ membranes exhibit improved coating stability, pronounced hydrophilicity, and exceptional antifouling capabilities, rendering them highly suitable for the separation of diverse herbal volatile oil-in-water emulsions. Furthermore, they possess the capability for reuse with an average retention ratio exceeding 90% and a pure water flux reaching up to 3200 L·m⁻2·h⁻1. Additionally, they demonstrate long-term stability and resistance to corrosion. With a simplistic yet efficient preparation process, the PVDF/PA-PEI/Fe3⁺ membrane holds significant potential for the extraction of oils from herbal volatile oil-in-water emulsions.

Green heterogeneous catalyst based on cross-linked carrageenans for direct conversion of fructose to ethyl levulinate

Ethyl levulinate (EL) is a biomass-derived compound, capable of being converted to an array of costly compounds and therefore is attracted by many researchers. In the present study, κ and ι-carrageenan grafted methylenebisacrylamide (MBA) catalysts (κC-g-MBA and ιC-g-MBA) were prepared and applied to convert fructose to EL. FT-IR spectroscopy, XRD of both low-angle and wide-angle, N2 adsorption-and-desorption, FESEM, and TGA were used to identify the catalysts. From the catalysts, κC-g-MBA and ιC-g-MBA revealed the desirable results for EL with 80 and 82 % yields, respectively. The various parameters like reaction temperature, time, catalyst quantity, and the original fructose quantity were studied. Furthermore, experimental design was employed to create the ideal conditions for the reaction temperature 180 °C for the reaction, 5 h for the duration of the reaction, and 50 mg of catalyst for EL chosen. In addition, the catalyst's capability for reuse was explored and the catalyst was used repeatedly without a significant change in the catalyst activity.

Well-designed chitosan-based cationic porous polymer: A robust material for effective adsorption of endocrine disrupting chemicals

There is an immediate need for meticulous design of easily accessible, cost-effective, chemically stable and eco-friendly materials for effectively removal of water contaminant. Herein, targeting typical water contaminants, endocrine disrupting chemicals (EDCs), three cationic hyper-cross-linked porous polymers (ciHCP-1, ciHCP-2, ciHCP-3) with multiple adsorption sites were designed with 2-hydroxypropyltrimethyl ammonium chloride chitosan (HACC) as precursor. The ciHCP-3 with large surface area (806 m2 g−1) exhibited high sorption capacity (137–366 mg g−1), and fast adsorption kinetics (5 min) for the EDCs, which is superior to the reported sorbents. The adsorption mechanisms can be attributed to the synergistic effect of physisorption and chemisorption. The high preparation reproducibility, physicochemical stability, and reuse capability of ciHCP highlights its great potential in practical water remediation applications.

Deep Quasi-Recurrent Self-Attention with Dual Encoder-Decoder in Biomedical CT Image Segmentation.

Developing deep learning models for accurate segmentation of biomedical CT images is challenging due to their complex structures, anatomy variations, noise, and unavailability of sufficient labeled data to train the models. There are many models in the literature, but the researchers are yet to be satisfied with their performance in analyzing biomedical Computed Tomography (CT) images. In this article, we pioneer a deep quasi-recurrent self-attention structure that works with a dual encoder-decoder. The proposed novel deep quasi-recurrent self-attention architecture evokes parameter reuse capability that offers consistency in learning and quick convergence of the model. Furthermore, the quasi-recurrent structure leverages the features acquired from the previous time points and elevates the segmentation quality. The model also efficiently addresses long-range dependencies through a selective focus on contextual information and hierarchical representation. Moreover, the dynamic and adaptive operation, incremental and efficient information processing of the deep quasi-recurrent self-attention structure leads to improved generalization across different scales and levels of abstraction. Along with the model, we innovate a new training strategy that fits with the proposed deep quasi-recurrent self-attention architecture. The model performance is evaluated on various publicly available CT scan datasets and compared with state-of-the-art models. The result shows that the proposed model outperforms them in segmentation quality and training speed. The model can assist physicians in improving the accuracy of medical diagnoses.

Enhancing Small Object Detection in Aerial Images: A Novel Approach with PCSG Model

Generalized target detection algorithms perform well for large- and medium-sized targets but struggle with small ones. However, with the growing importance of aerial images in urban transportation and environmental monitoring, detecting small targets in such imagery has been a promising research hotspot. The challenge in small object detection lies in the limited pixel proportion and the complexity of feature extraction. Moreover, current mainstream detection algorithms tend to be overly complex, leading to structural redundancy for small objects. To cope with these challenges, this paper recommends the PCSG model based on yolov5, which optimizes both the detection head and backbone networks. (1) An enhanced detection header is introduced, featuring a new structure that enhances the feature pyramid network and the path aggregation network. This enhancement bolsters the model’s shallow feature reuse capability and introduces a dedicated detection layer for smaller objects. Additionally, redundant structures in the network are pruned, and the lightweight and versatile upsampling operator CARAFE is used to optimize the upsampling algorithm. (2) The paper proposes the module named SPD-Conv to replace the strided convolution operation and pooling structures in yolov5, thereby enhancing the backbone’s feature extraction capability. Furthermore, Ghost convolution is utilized to optimize the parameter count, ensuring that the backbone meets the real-time needs of aerial image detection. The experimental results from the RSOD dataset show that the PCSG model exhibits superior detection performance. The value of mAP increases from 97.1% to 97.8%, while the number of model parameters decreases by 22.3%, from 1,761,871 to 1,368,823. These findings unequivocally highlight the effectiveness of this approach.

Bio-carbon coil aerogels from tea waste: A sustainable solution for efficient oil-water separation

Discharging wastewater containing oils, fats, and organic solvents into water bodies poses a significant threat to the already limited freshwater resources. In recent years, three-dimensional (3D) porous adsorbent materials, such as aerogel materials, have gained attention for their high separation effectiveness in adsorption technology. However, the poor mechanical strength of existing aerogel materials limits their application in oil–water separation. To address this challenge, this study proposes to use carbon coils obtained from tea waste as a template for producing low-cost, ultra-light, elastic, and highly recyclable bio-carbon coil aerogels (BCCA). The BCCA, featuring high porosity and a hierarchical porous structure, demonstrated exceptional performance in oil–water separation applications. Specifically, it exhibited a high adsorption capacity for organic solutions (39 ∼ 117 g/g) and oils (32 ∼ 41 g/g), respectively, along with excellent selectivity, rapid adsorption time of approximately 30s, and good reuse capability, maintaining an adsorption efficiency of 85 %. These remarkable properties can be attributed to the exceptional hydrophobicity of the BCCA, with a contact angle of 134°, and the rapid capillary action facilitated by the helical network structure. The use of tea waste-derived carbon coils as a precursor for producing efficient and sustainable carbon coil aerogels presents a promising solution for environmental remediation, particularly in oil–water separation applications. This research addresses the issue of wastewater contamination and contributes to the utilization of tea waste, a readily available and abundant biomass resource, in the development of value-added materials for environmental sustainability.

Efficient removal of U(VI) from aqueous solution using poly(amidoxime-hydroxamic acid) functionalized graphene oxide.

The efficient development of selective materials for uranium recovery from wastewater and seawater is crucial for the utilization of uranium resources and environmental protection. The potential of graphene oxide (GO) as an effective adsorbent for the removal of environmental contaminants has been extensively investigated. Further modification of the functional groups on the basal surface of GO can significantly enhance its adsorption performance. In this study, a novel poly(amidoxime-hydroxamic acid) functionalized graphene oxide (pAHA-GO) was synthesized via free radical polymerization followed by an oximation reaction, aiming to enhance its adsorption efficiency for U(VI). A variety of characterization techniques, including SEM, Raman spectroscopy, FT-IR, and XPS, were employed to demonstrate the successful decoration of amidoxime and hydroxamic acid functional groups onto GO. Meanwhile, the adsorption of U(VI) on pAHA-GO was studied as a function of contact time, adsorbent dosage, pH, ionic strength, initial U(VI) concentration, and interfering ions by batch-type experiments. The results indicated that the pAHA-GO exhibited excellent reuse capability, high stability, and anti-interference ability. Specially, the U(VI) adsorption reactions were consistent with pseudo-second-order and Langmuir isothermal adsorption models. The maximum U(VI) adsorption capacity was evaluated to be 178.7mg/g at pH 3.6, displaying a higher U(VI) removal efficiency compared with other GO-based adsorbents in similar conditions. Regeneration of pAHA-GO did not significantly influence the adsorption towards U(VI) for up to four sequential cycles. In addition, pAHA-GO demonstrated good adsorption capacity stability when it was immersed in HNO3 solution at different concentrations (0.1-1.0mol/L) for 72h. pAHA-GO was also found to have anti-interference ability for U(VI) adsorption in seawater with high salt content at near-neutral pH condition. In simulated seawater, the adsorption efficiency was above 94% for U(VI) across various initial concentrations. The comprehensive characterization results demonstrated the involvement of oxygen- and nitrogen-containing functional groups in pAHA-GO in the adsorption process of U(VI). Overall, these findings demonstrate the feasibility of the pAHA-GO composite used for the capture of U(VI) from aqueous solutions.

Estimation of the Optimal Storage Capacity of Rainwater Harvesting System Considering Regional Climate Characteristics

Due to the influence of climate change, the frequency and intensity of droughts in the Korean Peninsula regions are increasing. Moreover, regional rainfall deviations are increasing, increasing the severity of localized droughts. Accordingly, it is necessary to enhance water resource utilization through recycling and establishing a robust safety net for water supply. This necessitates the implementation of rainwater harvesting systems to augment water reuse capabilities. When planning the storage capacity of a rainwater harvesting system, it is important to calculate the appropriate capacity. Therefore, we created an Excel tool for water balance analysis in this study. It incorporates diverse rainwater uses, their respective usage conditions, and daily usage quantities. A water balance analysis was performed, applying the climate characteristics of different regions. A cost-benefit analysis was applied to the economic feasibility analysis, and a B/C regression curve by region and catchment area was derived based on the results of the water balance analysis. The tool is believed to be an effective support measurement to help decision-makers to calculate the appropriate storage capacity of rainwater harvesting systems in the relevant regions.

Sensing property of TM (Ti, Mn, Mo) doped Janus WSSe monolayer upon vented gases of lithium-ion battery thermal runaway

This paper employs density functional theory to investigate transition metal-doped WSSe(Ti–WSSe, Mn–WSSe, Mo–WSSe) gas-sensitive devices, exploring their adsorption and sensing properties towards three characteristic gases of thermal runaway in Li-ion battery, namely H2, CO, and CO2. Results indicate that Ti, Mn, and Mo dopants preferentially anchor to the S-surface of the pristine WSSe monolayer, exhibiting binding energies of −3.145, −1.282, and −3.376 eV, respectively. All three monolayers present significantly improved sensing characteristics, showing chemisorption towards CO. Band structure and density of states analyses reveals the potential of Ti–WSSe monolayer as a resistive CO detection sensor. Furthermore, recovery time calculations are performed to assess the reuse capabilities of the three gas-sensitive devices. Regarding high sensitivity and tunable detection, Mn–WSSe monolayer emerges as potential candidate for H2 detection, while Mo–WSSe monolayer is more suitable for CO2 detection. This work lays the foundation for the potential gas-sensitive applications of WSSe monolayer in the field of thermal runaway scenarios, which is expected to advance research in gas sensing domains.

Knowledge Transfer and Reuse: A Case Study of Ai-Enabled Resource Management in RAN Slicing

An efficient resource management scheme is critical to enable network slicing in 5G networks and in envisioned 6G networks, and artificial intelligence (AI) techniques offer promising solutions. Considering the rapidly emerging new machine learning techniques, such as graph learning, federated learning, and transfer learning, a timely survey is needed to provide an overview of resource management and network slicing techniques of AI-enabled wireless networks. This article provides such a survey along with an application of knowledge transfer in radio access network (RAN) slicing. In particular, we first provide some background on resource management and network slicing, and review relevant state-of-the-art AI and machine learning (ML) techniques and their applications. Then, we introduce our AI-enabled knowledge transfer and reuse-based resource management (AKRM) scheme, where we apply transfer learning to improve system performance. Compared with most existing works, which focus on the training of standalone agents from scratch, the main difference of AKRM lies in its knowledge transfer and reuse capability between different tasks. Our paper aims to be a roadmap for researchers to use knowledge transfer schemes in AI-enabled wireless networks, and we provide a case study over the resource allocation problem in RAN slicing.

Agile Software Development and Reuse Approach with Scrum and Software Product Line Engineering

Agile methods and software product line engineering (SPLE) are widely recognized as practical approaches for delivering high-quality software, adapting to evolving stakeholder needs, and tackling complex problems. This study proposes a hybrid agile software development and reuse approach called SPLE-Scrum based on the activities of software product line engineering and Scrum. Within the SPLE process, we incorporate requirement engineering and design practices to create a reference architecture with reusable components called core assets by introducing a product management meeting. The core assets are reused to build a series of applications with various product lines. The product increments are delivered in each Sprint with the review and retrospective meetings based on Scrum lifecycle and practices. We present a case study involving a blockchain online store to demonstrate the practical application of SPLE-Scrum, highlighting the benefits of integrating Scrum and software product line engineering. The research hypotheses of the proposed approach were validated through a study of structured interviews with 5 experts and 44 software practitioners, showing that the key factors of product management, project requirements, and product architecture in the SPLE-Scrum approach have a beneficial impact on project success. The SPLE-Scrum approach provides valuable insights and practical guidance for organizations seeking to optimize their software engineering practices while incorporating agile development and software reuse capabilities.

Genetic algorithm-assisted artificial neural network modelling for remediation and recovery of Pb (II) and Cr(VI) by manganese and cobalt spinel ferrite super nanoadsorbent

MnFe2O4 and CoFe2O4 nanoparticles were hydrothermally synthesized to examine their capability in adsorption of Pb (II) and Cr (VI). The adsorbents exhibited a high rate of adsorption, reaching 90% of their adsorption capacity in less than 30 min. Furthermore, the adsorption capability of the Magnetic Nanoparticles (MNPs) was noticeably greater at initial pollutant concentrations smaller than 40 mg/L. Maximum adsorption capacity on MnFe2O4 and CoFe2O4 nanoparticles were 40 and 25.38 mg/g for Cr (VI) and 523.32 and 476.19 mg/g for Pb (II), respectively. A data-driven model of Artificial Neural Network was used for prediction of adsorption capacity at both equilibrium and non-equilibrium condition. The model parameters including the numbers of neuron (n = 7) and data portioning for training (49.5%), validation (40.5%), and testing (10%) were obtained using Genetic Algorithm. The results indicated that the model could predict the data with high accuracy (R2 = 0.998). The input parameters were initial concentration, time, pH, temperature, adsorbent dosage, and other parameters that is dependent to the physico-chemical properties of ions and adsorbents’ surface (ε, α1, α2). The mechanism involved in Cr(VI) and Pb(II) adsorption are electrostatic physisorption and a combination of ion exchange chemisorption and electrostatic physisorption, respectively. Desorption capability and adsorbent reuse capability were also examined.

Graphene oxide electrode for unusual water softening in capacitive deionization

With the depleting freshwater resources and increasing demand for potable water, brackish water sources are potential sources for obtaining potable water due to their availability and low salt concentration. Various technologies are employed to treat the brackish water among which the Capacitive deionization (CDI) is an energy-efficient technique to achieve this due to its high regeneration and reuse capability, low voltage requirement, no pressure requirement, and scalability. The major bottlenecks in this pursuit involve limited desalination capacities and high costs. Here, we demonstrate the use of graphene oxide (GO) as an efficient and inexpensive electrode material for CDI. The hydrophilic nature of GO enables the interaction of hydrolyzed ions in water with the GO surface and reduces electrode-water resistance. The oxygen-containing groups in GO store pseudo charge making it useful for CDI. GO electrodes show a desalination capacity of ∼ 230 mg/g, which is the highest among all carbon-based materials at a high flow rate of ∼ 720 ml/min for 1000 ppm sodium chloride feed solution operating at a cell potential of 1 V. The salt adsorption capacity of GO increases with increasing ionic charges as Na+ < Mg2+ < Fe3+. Excellent recyclability and complete regeneration of electrodes along with high salt adsorption capacity underline the potential of GO electrodes to achieve high capacity, high rate, and efficient CDI.

A novel bionanocomposite from doped lipase enzyme into magnetic graphene oxide-immobilized-cellulose for efficient removal of methylene blue and malachite green dyes

Immobilized biosorbents with enzymes have become a topic of interest in the fields of environmental and energy science owing to their numerous advantages such as ease of separation, non-toxicity, biocompatiblity, high activity, and regeneration capability for further reuse. In this respect, lipase fromCandida rugose was selected to covalently immobilize ontoa supporting matrix of magnetic graphene oxide-immobilized-cellulose via glutaraldehyde to produce a magnetic bionanocomposite (MGO@Cellulose@Lipase) for the effective removal of methylene blue (MB) and malachite green (MG) from water as two target cationic pollutants. The as-synthesized bionanocomposite was characterized by various techniques to confirm the structure composition, surface morphology, thermal and magnetic properties. The SEM and HR-TEM examinations referred to good homogeneity and surface porosity with 23.80–32.69 nm as the identified particle size. Based on the BET analysis, MGO@Cellulose@Lipase exhibited a mesoporous structure with a mean pore size 11.56 nm, while the VSM results showed that the prepared bionanocomposite particles exhibited a saturation magnetization value 14.78 emu/g. To evaluate the adsorption performance of the newly designed bionanocomposite, batch adsorption experiments was carried out, under the influence and impact of various experimental controlling parameters. The adsorption correlations of MB and MG pollutants were fitted to Langmuir isotherm and pseudo-second order kinetics. The maximum computed adsorption capacity (qmax) for MB and MG were 66.79 and 51.87 mg/g, respectively. Thermodynamic studies confirmed the spontaneity and the endothermic nature of the adsorption process. Moreover, excellent removal efficiency of MB and MG by MGO@Cellulose@Lipase after five consecutive adsorption–desorption cycles were confirmed as 97.43% and 87.60%, respectively. The validity and applicability of MGO@Cellulose@Lipase in removal of MB and MG pollutants from real water samples were characterized in the range 95.09–96.24% and 91.01–92.58%, respectively. Therefore, the outlined results prove that the MGO@Cellulose could be used as a promising carrier alternative for enzymes immobilization and the assembled MGO@Cellulose@Lipase bionanocomposite was also characterized as an innovative green material for solving the environmental dye pollution.

An Automated Data Desensitisation System Based on the Middle Platform

Built on top of a big data platform, the Middle Platform develops data through abstraction, sharing, and reuse capabilities to provide data products and data services for upper-level business development. While fully analysing and mining the intrinsic value of data, privacy and sensitive information in the data must also be protected, so the Middle Platform needs a data desensitisation system to ensure the safe and open use of data. In order to solve the problems of high usage costs, low efficiency, and lack of standardised results of desensitisation that exist in conventional data desensitisation systems, an automated desensitisation system with data assets, access control, and desensitisation strategies as the main modules is established using an adaptive method of generating dynamic desensitisation rules, combined with a security monitoring mechanism of sensitivity classification and two-level permissions. The system optimises the configuration structure to obtain stable and reliable desensitisation results and efficiently respond to diverse business needs. Users are able to get rid of complex rule management and focus on the data usage itself.

Assessment and optimization of As(V) adsorption on hydrogel composite integrating chitosan-polyvinyl alcohol and Fe3O4 nanoparticles and evaluation of their regeneration and reusable capabilities in aqueous media

A modified chitosan-polyvinyl alcohol (PVA) hydrogel was developed by incorporating Fe3O4 nanoparticles. Four chitosan-Fe3O4 (ChFe) hydrogel types were developed based on chitosan:Fe3O4 ratio as 1:0, 1:1, 1:0.5 and 1:0.25. Batch sorption experiments were conducted with different pH, dosage, kinetics, and isotherms. The exhausted ChFe hydrogels were evaluated for their regeneration and reuse capability with different acids and bases. The best hydrogel for arsenic (V) [As(V)] adsorption was 1:0.5 ratio ChFe hydrogel. The highest As(V) adsorption (89 %) was at pH 4 and the adsorption capacity gradually decreased with increasing solution pH. Within the pH 4–6 range, the hydrogel surface became positively charged due to protonation of NH2 and OH groups in the polymer chain and the positive surface attracted H2AsO4− and HAsO42− oxyanions. The experimental kinetic data was well-fitted to the Elovich model (R2 of 0.99) while the Freundlich isotherm model best described the isotherm data (R2 of 0.97). The models predicted chemisorption mechanisms on ChFe hydrogel composites. Electrostatic attractions with NH3+ and OH2+, ligand-exchange inner-sphere complexes formation and bidentate corner-sharing (2C) and bidentate edge-sharing (2E) trimetric surface complexes formation have been proposed as the adsorption mechanism of As(V) into ChFe hydrogel. 0.1 M CH3COOH showed the best regeneration pattern with 75, 96, 81, 53 and 43 % of 1st, 2nd, 3rd, 4th and 5th adsorption respectively. Because of this re-usable capability, the As(V) adsorption capacity is not a single value from one adsorption cycle, but a cumulative value of several adsorption cycles and it was 17.39 mg/g for five adsorption cycles. Open for regeneration and reuse, no post-treatment is needed for adsorbent-water separation, allow applications of the ChFe hydrogel composite in a wide range of applications such as water filtration and purification systems. The modification with ChFe further expands the application capacity since the ChFe can remove other contaminants as well.

Iodine adsorption isotherms on Matamba fruit shell stemmed biochar for wastewater re-use strategy in rural areas owing to climate change.

Remote communities in developing countries are facing ever-increasing water scarcities, due to cumulative demand induced by the climate change and global warming impacts. For the socio-economic and health well-being of the local communities, sufficient, efficient, and affordable water supply is fundamental from local-based adsorbents. Matamba Fruit shell was obtained and pyrolyzed to obtain well-transformed biochar, which exhibited enough capacity to remove Iodine from aqueous solution. The maximum capacity of adsorption of the Matamba Fruit shell was 2.122mmolL-1 and 2.12mmolL-1 from conventional and Bayesian statistics correspondingly. The difference was insignificant. The surface morphology was evaluated by the Field Emission Scanning Electron Microscopy with Energy Dispersive X-Ray Spectroscopy (FESEM-EDX) which revealed porous structures with irregular openings enough to purge wastewater pollutants. The material surface area was 267.0m2g-1, as estimated by both approaches, making the Matamba Fruit shell an emerging potential candidate for environmental pollution control and use in bioremediation practices. The Fourier-transform infrared spectroscopy (FTIR) revealed that surface functional groups of Matamba Fruit shell biochar have enough peak variations in intensity and position due to vibration variations of the surface. The Fruit shell has different functional groups including the hydroxyl (-OH) and the carbonyl groups (CO), CC stretches of aromatic rings, and the carboxylate (C-O-O-) groups. The biochar understudy unveiled its capability for wastewater-treatment reuse in local and urban communities of developing countries to safeguard their health and access to water-supply as the climate change reverberations are affecting the developing countries more pronounced than before.

Facilitating Software Reuse Through Design Characteristics in Object-Oriented Paradigm

Software are used to increases quality as well as productivity that could be associated with lower costs. Implementing software with capability for reuse is difficult without sufficient support. This paper includes tutorial represents four important design characteristics in object-oriented paradigm for facilitating the production of more reusable software. It reviews the concepts of modularity, cohesion, coupling and information hiding and provides a discussion about their effect on software reuse. Object-oriented approach is having wide attention both in research environments and in industry. This tutorial is prepared for newbie developers of reusable software assets and for everyone else interested in the subject.

Self-floating capsule of algicidal bacteria Bacillus sp. HL and its performance in the dissolution of Microcystis aeruginosa

Algicidal bacteria is considered as an efficient and environmentally friendly approach to suppress Microcystis aeruginosa (M. aeruginosa). However, algicidal bacteria in natural water is limited during the practical application due to the interference of external factors and the low reuse capability. In this study, a bio-degradation capsule for M. aeruginosa is prepared by bio-compatible sodium alginate (SA) compositing with eco-friendly ethyl cellulose (EC) to improve the property and reuse capability of algicidal bacteria. Bacterial strain HL was well immobilized and the capsule was obtained with 2% of SA, 3% of calcium chloride (CaCl2) and 3% of EC. It has been proved that capsules immobilizing bacteria HL shows considerable advantage over traditional bio-treatment systems (free-living bacteria) and good reusable performance. A better algicidal rate of 77.67% ± 1.14% at 7th day was obtained with the use of capsule embedding 50 mL of algicidal bacteria, enhanced by 11.05% comparing with same amount of free-living bacteria. Moreover, the algicidal rate of M. aeruginosa still reached 68.57% ± 2.88% after three times repetitive use. The effect of capsules on the fluorescence and antioxidant system of M. aeruginosa indicated that the photosystems were irreversibly damaged and the antioxidant response of superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT) were significantly induced. Overall, capsules prepared in this study can provide a desirable environment for algicidal bacteria HL and ensure algicidal bacteria to in-situ work well in inhibiting booms of algae.

EFFECTS OF NON-REDUNDANCY AMONG TIES ON RECOMBINANT CAPABILITIES

This study explores the impacts of non-redundancy among ties in collaboration and knowledge networks on diverse recombinant capabilities by examining the moderating effects of both knowledge similarity and knowledge complementarity. By using 3,293 patent data in the graphene field of China, we found that non-redundancy among ties in a collaboration network positively affected both recombinant creation capability and recombinant reuse capability. However, non-redundancy among ties in a knowledge network was found to favour recombinant creation capability but hinder recombinant reuse capability. Moreover, the effects of non-redundancy among ties in different networks on recombinant capabilities depended on knowledge similarity and knowledge complementarity. These findings not only reveal the role of non-redundancy among ties on recombinant capabilities, but also highlight the significance of knowledge similarity and knowledge complementarity in the relationship between non-redundancy among ties and recombinant capabilities, thereby providing fresh insights into how to improve organisational recombinant capabilities