| 1. |
- Ilyas, Muhammad Tasaduq, et al.
(author)
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Substantial performance of copper sulfide nanotubes at high current densities for energy storage applications
- 2024
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In: Journal of Energy Storage. - : Elsevier. - 2352-152X .- 2352-1538. ; 85
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Journal article (peer-reviewed)abstract
- This study presents the direct growth of CuS nanotubes (NTs) on nickel foam using a facile solution synthesis route. The structural, elemental and morphological analyses of CuS NTs grown Ni foam were conducted through X-ray diffraction, energy dispersive X-ray spectroscopy, scanning electron microscope, and field emission scanning electron microscope. The electrochemical performance of the prepared electrodes was comprehensively characterized by cyclic voltammetry (CV), galvanostatic charge discharge and electrochemical impedance spectroscopy. The CuS NTs grown electrodes delivered a specific capacitance of 1539 Fg−1 at 1 mVs−1 and 1365 Fg−1 at 5 Ag−1, demonstrating a remarkable rate capability of 66 % at an extremely high current density of 25 Ag−1. Notably, the CuS NTs electrode demonstrated good cyclic stability, as evidenced by a charge retention of 75.5 % after 3000 cycles at a high current density of 20 Ag−1. The charge storage mechanism was predominantly diffusion controlled, accomplished by analyzing CV data. Overall, this work evinces that the as-synthesized CuS NTs hold a significant promise as electrode materials for high-performance electrochemical energy storage applications.
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| 2. |
- Mansha, Saira, et al.
(author)
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Development of pH-Responsive, Thermosensitive, Antibacterial, and Anticancer CS/PVA/Graphene Blended Hydrogels for Controlled Drug Delivery
- 2024
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In: Gels. - : MDPI. - 2310-2861. ; 10:3
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Journal article (peer-reviewed)abstract
- Drug delivery techniques based on polymers have been investigated for their potential to improve drug solubility, reduce systemic side effects, and controlled and targeted administration at infection site. In this study, we developed a co-polymeric hydrogel composed of graphene sheets (GNS), polyvinyl alcohol (PVA), and chitosan (CS) that is loaded with methotrexate (MTX) for in vitro liver cancer treatment. Fourier transform infrared spectroscopy (FTIR) and atomic force microscopy (AFM) was employed to check the structural properties and surface morphology. Moreover, tests were conducted on the cytotoxicity, hemolytic activity, release kinetics, swelling behaviour and degradation of hydrogels. A controlled release of drug from hydrogel in PBS at pH 7.4 was examined using release kinetics. Maximal drug release in six hours was 97.34%. The prepared hydrogels did not encourage the HepG2 growth and were non-hemolytic. The current study highlights the potential of GNS-based hydrogel loaded with MTX as an encouraging therapy for hepatocellular carcinoma. HepG2 cell viability of MTX-loaded CS-PVA-GNS hydrogel was (IC50 5.87 mu g/200 mL) in comparison to free MTX (IC50 5.03 mu g/200 mL). These outcomes recommend that hydrogels with GNS ensure improved drug delivery in cancer microenvironment while lessening adverse consequences on healthy cells.
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| 3. |
- Qadri, Azam Mehmood, et al.
(author)
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Heart failure survival prediction using novel transfer learning based probabilistic features
- 2024
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In: PeerJ Computer Science. - : PEERJ INC. - 2376-5992. ; 10
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Journal article (peer-reviewed)abstract
- Heart failure is a complex cardiovascular condition characterized by the heart's inability to pump blood effectively, leading to a cascade of physiological changes. Predicting survival in heart failure patients is crucial for optimizing patient care and resource allocation. This research aims to develop a robust survival prediction model for heart failure patients using advanced machine learning techniques. We analyzed data from 299 hospitalized heart failure patients, addressing the issue of imbalanced data with the Synthetic Minority Oversampling (SMOTE) method. Additionally, we proposed a novel transfer learning-based feature engineering approach that generates a new probabilistic feature set from patient data using ensemble trees. Nine fine-tuned machine learning models are built and compared to evaluate performance in patient survival prediction. Our novel transfer learning mechanism applied to the random forest model outperformed other models and state-of-the-art studies, achieving a remarkable accuracy of 0.975. All models underwent evaluation using 10-fold crossvalidation and tuning through hyperparameter optimization. The findings of this study have the potential to advance the field of cardiovascular medicine by providing more accurate and personalized prognostic assessments for individuals with heart failure.
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| 4. |
- Raza, Mohsin Ali, et al.
(author)
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Synthesis and characterization of zinc aluminate electrodes for supercapacitor applications
- 2024
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In: Electrochimica Acta. - : Elsevier. - 0013-4686 .- 1873-3859. ; 475
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Journal article (peer-reviewed)abstract
- We report, for the first time, the thorough electrochemical characterization of zinc aluminate spinel. Four different stoichiometric composition of zinc aluminate (ZnAl1.5O3.25, ZnAl2O4, ZnAl2.87O5.30, and ZnAl4O7) were prepared by solution combustion method. The obtained powders after calcination at 1000 °C were characterized through scanning electron microscope (SEM), energy dispersive x-ray spectroscopy (EDX) and x-ray diffraction to analyze the morphology, elemental composition and structure, respectively, of the zinc aluminate compositions. The electrodes were prepared by coating slurry of zinc aluminate, carbon black and polyvinylidene fluoride on nickel foam in a ratio of 8:1:1. The electrochemical characterization was carried out by cyclic voltammetry (CV), galvanostatic charge discharge (GCD) and electrochemical impedance spectroscopy (EIS). ZnAl1.5O3.25 exhibited the highest specific capacity of 546 C/g at 1 mV/s and 336 C/g at 1 A/g, as appraised by CV and GCD analysis, respectively. EIS test revealed that ZnAl1.5O3.25 had the modest impedance value. The energy density value for ZnAl1.5O3.25 sample was 16.79 Wh/kg at 1 A/g with a power density of 179.9 W/kg. The as developed electrodes showed predominantly pseudo-capacitive charge storage mechanism.
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| 5. |
- Tariq, Imran, et al.
(author)
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Ameliorative delivery of docetaxel and curcumin using PEG decorated lipomers : A cutting-edge in-vitro/ in-vivo appraisal
- 2024
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In: Journal of Drug Delivery Science and Technology. - : Elsevier. - 1773-2247. ; 97
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Journal article (peer-reviewed)abstract
- The development of a PEG-decorated lipid-polymer hybrid system camouflaged with natural and synthetic chemotherapeutic moieties is an influential approach melding the biomimetic properties of long-circulating vesicles to utilize different mechanisms to dwindle the tumor growth. Therefore, a safe and efficient lipid-coated nano-particulate system (LCNPs) was proposed to investigate the in-vitro, ex-vivo and in-vivo demeanors of such amalgamation.Docetaxel loaded PLGA nanoparticles (DTX-NPs) were prepared by solvent evaporation while curcumin liposomes were mapped out using the film hydration method. Physicochemical characterizations were executed in terms of size, surface morphology, differential scanning calorimetry (DSC) and fourier-transform infrared spectroscopy (FTIR). In-vitro cytotoxicity was effectuated using MCF-7 cell line. Hemolysis, erythrocyte aggregation and acute in-vivo toxicity were carried out to establish the biocompatibility. The hydrodynamic diameters of samples were in the nano-range and corresponded to the findings of scanning electron microscopy (SEM) and atomic force microscopy (AFM). The absence of distinctive peaks of DTX-NPs in FTIR and DSC analysis of LCNPs depicts the shielding of the lipid bilayer over the nanoparticle. Cytotoxicity induced by the LCNPs represented the efficient delivery of cargo to the tumor cells. LCNPs also exhibited the least toxicity under ex-vivo and in-vivo circumstances compared to free drugs. Additionally, histological studies showed no evidence of substantial necrosis. Additionally, histological studies showed no evidence of notable necrosis.
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| 6. |
- Al-Qadri, Ali A., et al.
(author)
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A review of hydrogen generation through gasification and pyrolysis of waste plastic and tires : Opportunities and challenges
- 2024
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In: International journal of hydrogen energy. - : Elsevier. - 0360-3199 .- 1879-3487. ; 77, s. 1185-1204
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Research review (peer-reviewed)abstract
- The global annual production of plastics and tires exceeds 6.5 billion tons, with only 10% being recycled, leading to significant environmental problems. Thermochemical gasification of these waste materials offers a potential avenue for producing renewable hydrogen while harnessing underutilized carbon-based waste streams. This review highlights the research on thermochemical conversion of plastics and tires, providing key inferences regarding yield optimization, technical hurdles, and techno-economic viability. It indicates that strategic catalyst design and optimized integrated system configurations can significantly improve the hydrogen yields from plastic and tire pyrolysis/gasification. The key results of this work are that catalyzed gasification reactions show the most potential for maximizing hydrogen yield from plastic and tire waste. The related studies demonstrated that catalysts like Ni, Fe and Ce-doped mixtures can significantly increase hydrogen yield from plastic waste pyrolysis and gasification by suppressing coke formation and promoting reforming/shift reactions. Optimization of temperature, steam ratio and residence time also improves yield. Feedstock synergies exhibiting multiple reaction pathways likewise maximize yield. Computational modeling plays a valuable role by providing mechanistic insights through equilibrium and kinetic simulations. Integrated gasification with carbon/methane reforming shows potential to improve efficiency and lower costs. Techno-economic analyses indicate plastic/tire gasification may achieve cost parity with steam methane reforming through optimized integrated designs incorporating heat recovery. Integrated processes combining multiple conversion steps could further boost efficiency but require additional modeling and testing. A deeper understanding of reaction mechanisms, achieved through advanced modeling approaches, coupled with comprehensive lifecycle analyses of integrated solutions, can pinpoint optimized processing conditions and system designs capable of matching or surpassing the economic and environmental performance of conventional fossil fuel-based hydrogen production. The recommendations provided aim to guide future research prioritization, facilitating the realization of the large-scale potential inherent in waste-derived renewable hydrogen pathways.
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| 7. |
- Jiao, Yiping, et al.
(author)
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LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset
- 2024
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In: IEEE journal of biomedical and health informatics. - : IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC. - 2168-2194 .- 2168-2208. ; 28:3, s. 1161-1172
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Journal article (peer-reviewed)abstract
- We introduce LYSTO, the Lymphocyte Assessment Hackathon, which was held in conjunction with the MICCAI 2019 Conference in Shenzhen (China). The competition required participants to automatically assess the number of lymphocytes, in particular T-cells, in images of colon, breast, and prostate cancer stained with CD3 and CD8 immunohistochemistry. Differently from other challenges setup in medical image analysis, LYSTO participants were solely given a few hours to address this problem. In this paper, we describe the goal and the multi-phase organization of the hackathon; we describe the proposed methods and the on-site results. Additionally, we present post-competition results where we show how the presented methods perform on an independent set of lung cancer slides, which was not part of the initial competition, as well as a comparison on lymphocyte assessment between presented methods and a panel of pathologists. We show that some of the participants were capable to achieve pathologist-level performance at lymphocyte assessment. After the hackathon, LYSTO was left as a lightweight plug-and-play benchmark dataset on grand-challenge website, together with an automatic evaluation platform.
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| 8. |
- Kazmi, Bilal, et al.
(author)
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Towards a sustainable future : Bio-hydrogen production from food waste for clean energy generation
- 2024
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In: Process Safety and Environmental Protection. - : Institution of Chemical Engineers. - 0957-5820 .- 1744-3598. ; 183, s. 555-567
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Journal article (peer-reviewed)abstract
- To address climate change, energy security, and waste management, new sustainable energy sources must be developed. This study uses Aspen Plus software to extract bio-H2 from food waste with the goal of efficiency and environmental sustainability. Anaerobic digestion, optimised to operate at 20–25 °C and keep ammonia at 3%, greatly boosted biogas production. The solvent [Emim][FAP], which is based on imidazolium, had excellent performance in purifying biogas. It achieved a high level of methane purity while consuming a minimal amount of energy, with a solvent flow rate of 13.415 m³ /h. Moreover, the utilization of higher temperatures (600–700 °C) during the bio-H2 generation phase significantly enhanced both the amount and quality of hydrogen produced. Parametric and sensitivity assessments were methodically performed at every stage. This integrated method was practicable and environmentally friendly, according to the economic assessment. H2 generation using steam reforming results in a TCC of 1.92 × 106 USD. The CO2 separation step has higher costs (TCC of 2.15 ×107 USD) due to ionic liquid washing and CO2 liquefaction. Compressor electricity consumption significantly impacts total operating cost (TOC), totaling 4.73 × 108 USD. showing its ability to reduce greenhouse gas emissions, optimize resource utilization, and promote energy sustainability. This study presents a sustainable energy solution that addresses climate and waste challenges.
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| 9. |
- Khan, Abdul Ahad, et al.
(author)
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Algal biochar : A natural solution for the removal of Congo red dye from textile wastewater
- 2024
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In: Journal of the Taiwan Institute of Chemical Engineers / Elsevier. - : Elsevier. - 1876-1070 .- 1876-1089.
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Journal article (peer-reviewed)abstract
- The present study was aimed at synthesizing algae-derived biochar to examine its effectiveness and adsorption capacity to remove Congo red dye. The independent variables such as dye concentration, adsorbent dose, and adsorption time were optimized by using a central composite design (CCD). An adsorption experiment was conducted to evaluate equilibrium using a detailed experimental design and characterized through XRD, TGA, SEM, EDX, and FTIR analysis. This paper also focuses on evaluating non-linear adsorption isotherm and kinetics to describe the adsorption mechanism along with applying an Artificial neural network to validate the removal efficiency. The maximum Congo red removal efficiency (96.14 %) and maximum adsorption capacity of algal biochar (186.94 mg/g) were achieved with the optimized parameters of 1 mg/L of dye concentration, 0.1 g of adsorbent dose, and 240 min of contact time. Adsorption behavior was well described by Langmuir isotherm and Pseudo-nth order. A multilayer perceptron (MLP) MLP 2–5–1 structure best validates the response. Overall, the study sheds light that Algal-derived biochar is a potential material for the elimination of Congo red dye and contributes to achieving sustainable development goals.
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| 10. |
- Khan, Arslan, et al.
(author)
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Comprehensive investigation of almond shells pyrolysis using advance predictive models
- 2024
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In: Renewable energy. - : Elsevier. - 0960-1481 .- 1879-0682. ; 227
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Journal article (peer-reviewed)abstract
- This research focused on comprehensive characterization and assessment of almond shells pyrolysis for bioenergy potential through thermogravimetric analysis from ambient temperature to 900 °C at different heating rates of 10, 15, and 20 °C/min in inert environment. Iso-conversional model-free methods like Friedman, Ozawa-Flynn-Wall (OFW), and Kissinger-Akahira-Sunose (KAS) were used for kinetic analysis. Average activation energies (Ea) evaluated using Friedman, OFW, and KAS methods were 198.45 kJ mol−1, 204.43 kJ mol−1, and 204.97 kJ mol−1, respectively. The evaluation of thermodynamic parameters, including ΔH‡, ΔG‡, and ΔS‡, was also assessed. The average values of ΔH‡, ΔG‡, and ΔS‡, were found to be 199.4 kJ mol−1, 172.17 kJ mol−1 and 42.60 kJ mol−1 respectively. The reaction mechanism was obtained from combined kinetics. A high R2 value of 0.9933 demonstrates strong agreement between the combined kinetic analysis results and the experimental data. The distribution activation energy model was assessed employing four pseudo elements identified as PC1, PC2, PC3, and PC4. Artificial Neural Network (ANN) and Boosting regression trees (BRT) were used for the prediction of Ea of almond shells pyrolysis. The detailed understanding of thermokinetics and creating customized predictive and innovative modelling techniques like ANN and BRT sets a new benchmark for developing customized models for thermochemical conversion of varieties of almond shells.
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