This study is an attempt to examine the application and usefulness of social media and mobile devices in transferring the resources and interaction with academicians in higher education institutions ...across the boundary wall, a hitherto unexplained area of research. This empirical study is based on the survey of 360 students of a university in eastern India, cognising students’ perception on social media and mobile devices through collaborative learning, interactivity with peers, teachers and its significant impact on students’ academic performance. A latent variance-based structural equation model approach was followed for measurement and instrument validation. The study revealed that online social media used for collaborative learning had a significant impact on interactivity with peers, teachers and online knowledge sharing behaviour.
Additionally, interactivity with teachers, peers, and online knowledge sharing behaviour has seen a significant impact on students’ engagement which consequently has a significant impact on students’ academic performance. Grounded to this finding, it would be valuable to mention that use of online social media for collaborative learning facilitate students to be more creative, dynamic and research-oriented. It is purely a domain of knowledge.
Drying sago pith waste in a fluidized bed dryer Rosli, Masli Irwan; Abdul Nasir, Abdul Mu’im; Takriff, Mohd Sobri ...
Food and bioproducts processing,
September 2020, 2020-09-00, 20200901, Volume:
123
Journal Article
Peer reviewed
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•Effects of the densities on the moisture content of sago pith waste.•Drying profiles of sago pith waste.•Drying rate and drying time of sago pith waste.•Fluidization profiles of the ...sago pith waste drying process.•Transformation from fixed bed to turbulent and followed by turbulent fluidization.
Sago pith waste produced in largely during the manufacturing process of sago flour and causes serious environmental pollution. Once SPW is dried, it can be stored and further exploited for its high starch content. SPW has an original moisture content of 90% wet basis but can be dried to 10% wet basis. This study evaluated the effects of the bulk and tapped densities on the moisture content of SPW and used the compressibility index and Hausner ratio to characterize the flow of SPW in a fluidized bed dryer at wet basis. The temperature (50–80 °C) and velocity (1.5–2.1 m/s) of the air supplied into the fluidized bed dryer were considered in terms of the loss of moisture content, drying rate, and fluidization profile of the drying process. The effective moisture diffusivity were estimated to determine the optimum drying condition. The experimental results showed that the drying process took less time and reached a higher drying rate as the air temperature and velocity increased. Increasing the air temperature increased the heat transfer between SPW and dry air and accelerated the movement of moisture to the surface. The air velocity had a less significant effect on the drying process and was more important for fluidization of the SPW. The profile showed a fixed bed during early fluidization, followed by a bubbling state and then turbulent condition. Increasing the air temperature reduced the time for SPW to reach turbulent situation. Increasing the air velocity increased the bubbling fluidization density and accelerated the turbulent fluidization. Based on the effective moisture diffusivity analysis, it showed that the optimum drying process of SPW could be achieved at air velocity of 1.50 m/s with 80 °C of air temperature and at air temperature of 70 °C with 2.10 m/s of air velocity. Meanwhile, dry sieve analysis was performed to obtain the particle size distribution and percentage of fines in SPW with the sieve sizes of 3.35, 2.00, 1.70, 1.00, 0.85, 0.60, and 0.43 mm. Then, SPW was classified and characterized according to each particle size range. Visually, SPW was found to have three categories of particles: sand, gravel, and fibrous wood.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Photocatalytic water splitting is considered one of the most important and appealing approaches for the production of green H2 to address the global energy demand. The utmost possible form of ...artificial photosynthesis is a two‐step photoexcitation known as “Z‐scheme”, which mimics the natural photosystem. This process solely relies on the effective coupling and suitable band positions of semiconductors (SCs) and redox mediators for the purpose to catalyze the surface chemical reactions and significantly deter the backward reaction. In recent years, the Z‐scheme strategies and their key role have been studied progressively through experimental approaches. In addition, theoretical studies based on density functional theory have provided detailed insight into the mechanistic aspects of some breathtakingly complex problems associated with hydrogen evolution reaction and oxygen evolution reaction. In this context, this critical review gives an overview of the fundamentals of Z‐scheme photocatalysis, including both theoretical and experimental advancements in the field of photocatalytic water splitting, and suggests future perspectives.
Solar‐driven water splitting has attracted substantial attention over the past decades as it not only provides a clean and sustainable fuel but also promises to dramatically reduce CO2 emissions. The utmost possible form of artificial photosynthesis is a two‐step photoexcitation known as “Z‐scheme”, which mimics the natural photosystem, and considerably enhances the stability and efficiency of overall water splitting.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
The effective treatment of industrial wastewater to protect freshwater reserves for the survival of life is a primary focus of current research. Herein, a multicomponent Eleocharis-manganese ...peroxidase enzyme (Eleocharis@MnPE) layered hybrid with high surface area (1200 m2/m3), with a strong synergistic adsorption and catalytic biodegradation (SACB), has been developed through a facile method. A combination of outer porous (Eleocharis) and inner catalytically active (MnPE) components of the hybrid resulted in highly efficient SACB system, evidenced by high removal rate of 15 kg m–3 day–1 (100%) and complete degradation of toxic Orange II (OR) azo dye into nontoxic products (gases and weak acids). The Eleocharis@MnPE layered hybrid efficiently degraded both OR in synthetic wastewater and also other azo dyes (red, pink, and yellow dyes) present in three different textile industrial effluents. For the industrial effluents, these were evidenced by the color disappearance and reduction in biological oxygen demand (BOD), chemical oxygen demand (COD), and total organic carbon (TOC) of up to 97%, 92%, and 76%, respectively. Furthermore, reduced toxicity of treated wastewater was confirmed by decreased cell toxicity to 0.1%–1% and increased cell viability to 90%. We believe that designing a hybrid system with strong ability of SACB could be highly effective for industrial-scale treatment of wastewater.
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•Top-down etching strategy was used to get hollow ZIF-67(HZIF-67).•HZIF-67 was used as a precursor for the fabrication of hollow Co3O4/C by heat treatment.•Hollow Co3O4/C was used for ...peroxymonosulfate (PMS) activation.•Enhanced catalytic performance was observed on hollow Co3O4/C as compared with solid structure.
Concurrently rational optimization and design of the structure and composition of catalysts are significant for improving its catalytic performance. In this report, a novel hollow carbon supported ultrafine Co3O4 nanoparticles (HCo3O4/C) with a diameter of 6–12 nm were prepared as an active catalyst for peroxymonosulfate (PMS) activation. Initially, the zeolitic-imidazole-framework (ZIF-67) was synthesized followed by top-down etching strategy to get the hollow structure. Finally, as prepared hollow ZIF-67 was used as a precursor to fabricate HCo3O4/C. To understand the effects of structure and final composition on catalytic performance, another material, solid carbon supported Co3O4 nanoparticles (SCo3O4/C) was synthesized for comparison. The catalytic efficiency in control experiments between HCo3O4/C and SCo3O4/C was identified; in which HCo3O4/C demonstrated more than two times improved catalytic efficiency as compared to a solid structure. Interestingly, the HCo3O4/C catalyst exhibits better efficiency for PMS activation to generate sulfate radicals (SO4−) and the results show that degradation rate of targeted pollutant bisphenol A (BPA) was achieved up to 97% in 4 min, which is higher than other reported catalysts. The other factors which could influence PMS activation were also analyzed as well, for instance, the solution pH, catalyst loading, pollutant (BPA) concentration, system temperature and effect of organic molecules. Moreover, the Liquid chromatography-mass spectrometry (LC–MS) was used to identify the BPA degraded intermediate products. This work provides a new prospect into the synthesis of high-performance metal-organic framework (MOF) derived catalysts with exceptional properties, which may encourage the employ of hollow MOF materials in more practical applications.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Over the past few years, considerable attention has been paid to biomedical applications of copper sulfide nanostructures owing to their enhanced physiochemical and pharmacokinetics characteristics ...in comparison to gold, silver, and carbon nanomaterials. The small-sized Cu
S
nanoparticles have the advantage to absorb efficiently in the near-infrared region (NIR) above 700 nm and the absorption can be tuned by altering their stoichiometries. Moreover, their easy removal through the kidneys overpowers the issue of toxicity caused by many inorganic substances. The low cost and selectivity further add to the advantages of Cu
S
nanostructures as electrode materials in comparison to relatively expensive materials such as silver and gold nanoparticles. This review is mainly focused on the synthesis and biomedical applications of Cu
S
nanostructures. The first part summarizes the various synthetic routes used to produce Cu
S
nanostructures with varying morphologies, while the second part targets the recent progress made in the application of small-sized Cu
S
nanostructures as biosensors, and their analysis and uses in the cure of cancer. Photoacoustic imaging and other cancer treatment applications are discussed. Research on Cu
S
nanostructures will continue to increase over the next few decades, and great opportunities lie ahead for potential biomedical applications of Cu
S
nanostructures.
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•Modification strategies of metal oxides for photocatalysis.•Preparation mechanism of metal oxides with different morphologies,•Types of photocatalysis and its reaction ...pathways,•Analysis of stability and the structure-property relationship.•Durability and reusability of metal oxide photocatalyst.•Application of metal oxide photocatalyst.
In the modern world, the industrial revolution to meet consumer demand increases the need for clean energy production and a sustainable environment. Photocatalysis is envisioned among the promising strategies to fulfill the preceding global demands in an eco-friendly way. Among photocatalysts, metal oxides (MOs) are considered promising candidates owing to their efficiency, low cost, and environment-friendliness. In addition, sufficient availability, ease of fabricating method, and high surface area make MOs suitable for extensive use in a vast domain. However, certain limitations such as wide band-gap, the high recombination rate of photo-generated electron-hole pairs, and catalyst deactivation hamper their practical applications. In this review, various strategies mainly employed to address the challenging issues associated with MOs are comprehensively highlighted. Likewise, the preparation mechanism of MOs with different morphologies, types of photocatalysis and its reaction pathways, detailed analysis of stability and the structure-property relationship, and challenges about the issue of durability and reusability of MO photocatalysts are discussed in detail. In addition, the use of MOs as an effective photocatalyst for CO2 reduction, hydrogen generation, and pollutant degradation is also discussed in detail.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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•Simultaneous sensing of multiple gases with Superluminescent diode.•Selective sensing of CO2 and CH4with a low-resolution spectrometer using a FP etalon.•Development of a technique ...that can monitor biogas from different feed-stocks.
Monitoring of methane (CH4) and carbon dioxide (CO2) in biogas from different feed-stocks using superluminescent diode (SLED) is proposed and demonstrated. The SLED has a broadband spectrum (1540 nm–1640nm) and this allows for the detection of CO2 at 1570nm and CH4 at 1600nm range simultaneously. Experiments were performed on biogas collected from various biomass like food waste, sewage waste and cattle dung. CO2 and CH4 concentration levels were monitored on each source of biogas. The etalon based sensing system provides the opportunity to select absorption lines with a low resolution spectrometer. Further, measurements on CH4 and CO2 concentration changes depending on the food-waste input to the plant are demonstrated.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Understanding factors associated with flood incidence could facilitate flood disaster control and management. This paper assesses flood susceptibility of Perlis, Malaysia for reducing and managing ...their impacts on people and the environment. The study used an integrated approach that combines geographic information system (GIS), analytic network process (ANP), and remote sensing (RS) derived variables for flood susceptibility assessment and mapping. Based on experts’ opinion solicited via ANP survey questionnaire, the ANP mathematical model was used to calculate the relative weights of the various flood influencing factors. The ArcGIS spatial analyst tools were used in generating flood susceptible zones. The study found zones that are very highly susceptible to flood (VHSF) and those highly susceptible to flood (HSF) covering 38.4% (30,924.6 ha) and 19.0% (15,341.1 ha) of the study area, respectively. The results were subjected to one-at-a-time (OAT) sensitivity analysis to verify their stability, where 6 out of the 22 flood scenarios correlated with the simulated spatial assessment of flood susceptibility. The findings were further validated using real-life flood incidences in the study area obtained from satellite images, which confirmed that most of the flooded areas were distributed over the VHSF and HSF zones. This integrated approach enables network model structuring, and reflects the interdependences among real-life flood influencing factors. This accurate identification of flood prone areas could serve as an early warning mechanism. The approach can be replicated in cities facing flood incidences in identifying areas susceptible to flooding for more effective flood disaster control.
•A thorough review of techniques, algorithms, datasets, and tasks for fake news detection.•An overview of text processing deep learning architectures for handling fake news detection as a text ...classification task.•A novel, hybrid CNN-RNN model for the task.•An extensive evaluation on benchmark datasets with very positive results.
The explosion of social media allowed individuals to spread information without cost, with little investigation and fewer filters than before. This amplified the old problem of fake news, which became a major concern nowadays due to the negative impact it brings to the communities. In order to tackle the rise and spreading of fake news, automatic detection techniques have been researched building on artificial intelligence and machine learning. The recent achievements of deep learning techniques in complex natural language processing tasks, make them a promising solution for fake news detection too. This work proposes a novel hybrid deep learning model that combines convolutional and recurrent neural networks for fake news classification. The model was successfully validated on two fake news datasets (ISO and FA-KES), achieving detection results that are significantly better than other non-hybrid baseline methods. Further experiments on the generalization of the proposed model across different datasets, had promising results.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
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