jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Fatouma Mohamed Abdoul‐Latif | Ayoub Ainane | Touria Hachi | Rania Abbi | Meryem Achira | Abdelmjid Abourriche | Mathieu Brulé | Tarik Ainane
Source: Molecules (article, 2023-05-24)
Field: Chemistry — Organic Chemistry

Materials Derived from Olive Pomace as Effective Bioadsorbents for the Process of Removing Total Phenols from Oil Mill Effluents This work investigates olive pomace from olive mill factories as an adsorbent for the removal of total phenols from olive mill effluent (OME). This pathway of valorization of olive pomace reduces the environmental impact of OME while providing a sustainable and cost-effective wastewater treatment approach for the olive oil industry. Olive pomace was pretreated with water washing, drying (60 °C) and sieving (<2 mm) to obtain the raw olive pomace (OPR) adsorbent material. Olive pomace biochar (OPB) was obtained via carbonization of OPR at 450 °C in a muffle furnace. The adsorbent materials OPR and OPB were characterized using several basic analyzes (Scanning Electron Microscopy-Energy-Dispersive X-ray SEM/EDX, X-ray Diffraction XRD, thermal analysis DTA and TGA, Fourier transform infrared FTIR and Brunauer, Emmett and Teller surface BET). The materials were subsequently tested in a series of experimental tests to optimize the sorption of polyphenols from OME, investigating the effects of pH and adsorbent dose. Adsorption kinetics showed good correlation with a pseudo-second-order kinetic model as well as Langmuir isotherms. Maximum adsorption capacities amounted to 21.27 mg·g<sup>-1</sup> for OPR and 66.67 mg·g<sup>-1</sup> for OPB, respectively. Thermodynamic simulations indicated spontaneous and exothermic reaction. The rates of total phenol removal were within the range of 10-90% following 24 h batch adsorption in OME diluted at 100 mg/L total phenols, with the highest removal rates observed at pH = 10. Furthermore, solvent regeneration with 70% ethanol solution yielded partial regeneration of OPR at 14% and of OPB at 45% following the adsorption, implying a significant rate of recovery of phenols in the solvent. The results of this study suggest that adsorbents derived from olive pomace may be used as economical materials for the treatment and potential capture of total phenols from OME, also suggesting potential further applications for pollutants in industrial wastewaters, which can have significant implications in the field of environmental technologies. Pomace ; Adsorption ; Chemistry ; Phenols ; Langmuir adsorption model ; Biochar ; Nuclear chemistry ; Langmuir ; Wastewater ; Phenol ; Fourier transform infrared spectroscopy ; Pyrolysis ; Pulp and paper industry ; Organic chemistry ; Chemical engineering ; Waste management ; Food science Edible Oils Quality and Analysis ; Dye analysis and toxicity ; Adsorption and biosorption for pollutant removal
Authors: Xiuzhi Bai | Zhongxiang Liu | Pengfei Liu | Yijun Zhang | Linfeng Hu | Tongchao Su
Source: Polymers (article, 2023-05-17)
Field: Materials Science — Biomaterials

An Eco-Friendly Adsorbent Based on Bacterial Cellulose and Vermiculite Composite for Efficient Removal of Methylene Blue and Sulfanilamide In this work, a novel composite of bacterial cellulose (BC) and expanded vermiculite (EVMT) composite was used to adsorb dyes and antibiotics. The pure BC and BC/EVMT composite were characterized using SEM, FTIR, XRD, XPS and TGA. The BC/EVMT composite exhibited a microporous structure, providing abundant adsorption sites for target pollutants. The adsorption performance of the BC/EVMT composite was investigated for the removal of methylene blue (MB) and sulfanilamide (SA) from an aqueous solution. The adsorption capacity of BC/ENVMT for MB increased with increasing pH, while the adsorption capacity for SA decreased with increasing pH. The equilibrium data were analyzed using the Langmuir and Freundlich isotherms. As a result, the adsorption of MB and SA by the BC/EVMT composite was found to follow the Langmuir isotherm well, indicating a monolayer adsorption process on a homogeneous surface. The maximum adsorption capacity of the BC/EVMT composite was found to be 92.16 mg/g for MB and 71.53 mg/g for SA, respectively. The adsorption kinetics of both MB and SA on the BC/EVMT composite showed significant characteristics of a pseudo-second-order model. Considering the low cost and high efficiency of BC/EVMT, it is expected to be a promising adsorbent for the removal of dyes and antibiotics from wastewater. Thus, it can serve as a valuable tool in sewage treatment to improve water quality and reduce environmental pollution. Adsorption ; Langmuir adsorption model ; Composite number ; Methylene blue ; Aqueous solution ; Chemistry ; Nuclear chemistry ; Langmuir ; Freundlich equation ; Chemical engineering ; Materials science ; Organic chemistry ; Composite material ; Photocatalysis ; Catalysis Advanced Cellulose Research Studies ; Adsorption and biosorption for pollutant removal ; Graphene and Nanomaterials Applications
Authors: Shiva Dehghan | Amirhossein Naghipour | Fatemeh Zomorodi Anbaji | Pezhman Golshanrad | Hosein Mirazi | Hossein Adelnia | Mahdi Bodaghi | Bahareh Farasati Far
Source: International Journal of Pharmaceutics (article, 2023-04-29)
Field: Materials Science — Biomaterials

Enhanced in vitro and in vivo anticancer activity through the development of Sunitinib-Loaded nanoniosomes with controlled release and improved uptake This study aims to develop sunitinib niosomal formulations and assess their in-vitro anti-cancer efficiency against lung cancer cell line, A549. Sunitinib, a highly effective anticancer drug, was loaded in the niosome with high encapsulation efficiency. Collagen was coated on the surface of the niosome for enhanced cellular uptake and prolonged circulation time. Different formulations were produced, while response surface methodology was utilized to optimize the formulations. The stability of the formulations was evaluated over a 2-month period, revealing the importance of collagen coating. MTT assay demonstrated dose-dependent cytotoxicity for all formulations against lung cancer cells. Scratch assay test suggested antiproliferative efficacy of the formulations. The flow cytometry data confirmed the improved cytotoxicity with enhanced apoptosis rate when different formulations used. The 2D fluorescent images proved the presence of drug-containing niosomes in the tumor cells. The activation of the apoptotic pathway leading to protein synthesis was confirmed using an ELISA assay, which specifically evaluated the presence of cas3 and cas7. The results of this study indicated the antiproliferative efficacy of optimized niosomal formulations and their mechanism of action. Therefore, niosomes could be utilized as a suitable carrier for delivering sunitinib into lung cancer cells, paving the way for future clinical studies. Niosome ; Cytotoxicity ; In vivo ; Sunitinib ; Chemistry ; MTT assay ; Pharmacology ; In vitro ; Apoptosis ; Sunitinib malate ; Flow cytometry ; Cancer ; Vesicle ; Medicine ; Biochemistry ; Molecular biology ; Biology Nanoparticle-Based Drug Delivery ; Protein purification and stability ; RNA Interference and Gene Delivery
Authors: Xiaohong Wu | Fei He | Bin Wu | Shupeng Zeng | Chengyu He
Source: Foods (article, 2023-01-26)
Field: Chemistry — Analytical Chemistry

Accurate Classification of Chunmee Tea Grade Using NIR Spectroscopy and Fuzzy Maximum Uncertainty Linear Discriminant Analysis The grade of tea is closely related to tea quality, so the identification of tea grade is an important task. In order to improve the identification capability of the tea grade system, a fuzzy maximum uncertainty linear discriminant analysis (FMLDA) methodology was proposed based on maximum uncertainty linear discriminant analysis (MLDA). Based on FMLDA, a tea grade recognition system was established for the grade recognition of Chunmee tea. The process of this system is as follows: firstly, the near-infrared (NIR) spectra of Chunmee tea were collected using a Fourier transform NIR spectrometer. Next, the spectra were preprocessed using standard normal variables (SNV). Then, direct linear discriminant analysis (DLDA), maximum uncertainty linear discriminant analysis (MLDA), and FMLDA were used for feature extraction of the spectra, respectively. Finally, the k-nearest neighbor (KNN) classifier was applied to classify the spectra. The k in KNN and the fuzzy coefficient, m, were discussed in the experiment. The experimental results showed that when k = 1 and m = 2.7 or 2.8, the accuracy of the FMLDA could reach 98.15%, which was better than the other two feature extraction methods. Therefore, FMLDA combined with NIR technology is an effective method in the identification of tea grade. Linear discriminant analysis ; Pattern recognition (psychology) ; Artificial intelligence ; Mathematics ; k-nearest neighbors algorithm ; Principal component analysis ; Fuzzy logic ; Discriminant ; Feature extraction ; Classifier (UML) ; Statistics ; Computer science Spectroscopy and Chemometric Analyses ; Advanced Chemical Sensor Technologies ; Identification and Quantification in Food
Authors: Michael T. Bergman | Xingqing Xiao | Carol K. Hall
Source: The Journal of Physical Chemistry B (article, 2023-09-22)
Field: Materials Science — Biomaterials

In Silico Design and Analysis of Plastic-Binding Peptides Peptides that bind to inorganic materials can be used to functionalize surfaces, control crystallization, or assist in interfacial self-assembly. In the past, inorganic-binding peptides have been found predominantly through peptide library screening. While this method has successfully identified peptides that bind to a variety of materials, an alternative design approach that can intelligently search for peptides and provide physical insight for peptide affinity would be desirable. In this work, we develop a computational, physics-based approach to design inorganic-binding peptides, focusing on peptides that bind to the common plastics polyethylene, polypropylene, polystyrene, and poly(ethylene terephthalate). The PepBD algorithm, a Monte Carlo method that samples peptide sequence and conformational space, was modified to include simulated annealing, relax hydration constraints, and an ensemble of conformations to initiate design. These modifications led to the discovery of peptides with significantly better scores compared to those obtained using the original PepBD. PepBD scores were found to improve with increasing van der Waals interactions, although strengthening the intermolecular van der Waals interactions comes at the cost of introducing unfavorable electrostatic interactions. The best designs are enriched in amino acids with bulky side chains and possess hydrophobic and hydrophilic patches whose location depends on the adsorbed conformation. Future work will evaluate the top peptide designs in molecular dynamics simulations and experiment, enabling their application in microplastic pollution remediation and plastic-based biosensors. Peptide ; van der Waals force ; Rational design ; Molecular dynamics ; In silico ; Combinatorial chemistry ; Materials science ; Chemistry ; Nanotechnology ; Computational chemistry ; Molecule ; Organic chemistry ; Biochemistry Supramolecular Self-Assembly in Materials ; Advanced Proteomics Techniques and Applications ; Machine Learning in Materials Science
Authors: Sema Bayraktar | Cansu Üstün | S. Kehr
Source: Macromolecular Bioscience (review, 2023-11-30)
Field: Materials Science — Biomaterials

Oxygen Delivery Biomaterials in Wound Healing Applications Oxygen (O<sub>2</sub> ) delivery biomaterials have attracted great interest in the treatment of chronic wounds due to their potential applications in local and continuous O<sub>2</sub> generation and delivery, improving cell viability until vascularization occurs, promoting structural growth of new blood vessels, simulating collagen synthesis, killing bacteria and reducing hypoxia-induced tissue damage. Therefore, different types of O<sub>2</sub> delivery biomaterials including thin polymer films, fibers, hydrogels, or nanocomposite hydrogels have been developed to provide controlled, sufficient and long-lasting O<sub>2</sub> to prevent hypoxia and maintain cell viability until the engineered tissue is vascularized by the host system. These biomaterials are made by various approaches, such as encapsulating O<sub>2</sub> releasing molecules into hydrogels, polymer microspheres and 3D printed hydrogel scaffolds and adsorbing O<sub>2</sub> carrying reagents into polymer films of fibers. In this article, different O<sub>2</sub> generating sources such as solid inorganic peroxides, liquid peroxides, and photosynthetic microalgae, and O<sub>2</sub> carrying perfluorocarbons and hemoglobin are presented and the applications of O<sub>2</sub> delivery biomaterials in promoting wound healing are discussed. Furthermore, challenges encountered and future perspectives are highlighted. Self-healing hydrogels ; Wound healing ; Nanotechnology ; Tissue engineering ; Biomedical engineering ; Biomaterial ; Chemistry ; Viability assay ; Materials science ; Cell ; Polymer chemistry ; Surgery ; Medicine ; Biochemistry Electrospun Nanofibers in Biomedical Applications ; Wound Healing and Treatments ; Diabetic Foot Ulcer Assessment and Management
Authors: Benedict Terkula Iber | Donald Torsabo | Che Engku Noramalina Che Engku Chik | Fachrul Wahab | Siti Rozaimah Sheikh Abdullah | Hassimi Abu Hassan | Nor Azman Kasan
Source: Polymers (article, 2023-02-20)
Field: Materials Science — Biomaterials

Response Surface Methodology (RSM) Approach to Optimization of Coagulation-Flocculation of Aquaculture Wastewater Treatment Using Chitosan from Carapace of Giant Freshwater Prawn Macrobrachium rosenbergii The major sources of waste from aquaculture operations emanates from fish or shellfish processing and wastewater generation. A simple technique called coagulation/flocculation utilizes biowaste from aquaculture to produce chitosan coagulant for wastewater treatment. A chemical method was applied in the present study for chitin and chitosan extraction from carapace of <i>Macrobrachium rosenbergii</i> and subsequent application for removal of turbidity and salinity from shrimp aquaculture wastewater. Box-Behnken in RSM was used to determine the optimum operating conditions of chitosan dosage, pH, and settling time, after which quadratic models were developed and validated. Results show that 80 g of raw powder carapace yielded chitin and chitosan of 23.79% and 20.21%, respectively. The low moisture (0.38%) and ash (12.58%) content were an indication of good quality chitosan, while other properties such as water-binding capacity (WBC), fat-binding capacity (FBC), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscope (SEM) confirmed the structure and the α-group, as well as the rough morphology of chitosan. In addition, the high solubility (71.23%) and DDA (85.20%) suggested good coagulant potentials. It was recorded in this study that 87.67% turbidity was successfully removed at 20 mg/L of chitosan dosage and 6.25 pH after 30 min settling time, while 21.43% salinity was removed at 5 mg/L of chitosan dosage, 7.5 pH, and 30 min settling time. Therefore, the process conditions adopted in this study yielded chitosan of good quality, suitable as biopolymer coagulant for aquaculture wastewater treatment. Macrobrachium rosenbergii ; Chitosan ; Response surface methodology ; Flocculation ; Wastewater ; Turbidity ; Box–Behnken design ; Pulp and paper industry ; Salinity ; Materials science ; Chemistry ; Chromatography ; Fishery ; Prawn ; Biology ; Environmental engineering ; Environmental science ; Ecology Nanocomposite Films for Food Packaging ; Coagulation and Flocculation Studies
Authors: Lukáš Klein | Petr Žmij | Pavel Krömer
Source: IEEE Access (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Partial Discharge Detection by Edge Computing Edge computing is becoming a mainstream platform for practical applications of machine learning and in particular deep learning. Many systems capable of efficient execution of deep neural models in the context of edge computing are readily available or beginning to appear on the consumer market. The Jetson platform from NVIDIA, the Neural stick from Intel, and the Edge TPU designed by Google are examples of devices that enable the application of complex neural networks in edge computing. This work investigates the ability of selected edge devices to address a real-world classification problem from electrical power engineering. It consists of the detection of partial discharges (PDs) from covered conductors (CCs) on high-voltage power lines. The CCs are used in heavily forested and generally inaccessible areas where clearance zones cannot be maintained. Detection of PDs can prevent forest fires and other disasters potentially caused by prolonged contact of CCs with vegetation. The problem is suitable for an edge computing-based solution because Internet connectivity in remote areas is usually insufficient and a 2G (GSM) mobile network is available at best. Because such locations are difficult to access and usually without a suitable power supply, the proposed solution puts an emphasis also on PD detection latency and the associated power consumption. Two principal approaches to PD detection are considered. One is based on the classification of 1D time series (raw data). The second approach uses the signal transformed into a 2D spectrogram. In this case, two types of algorithms are evaluated. The first one is a novel custom stacking ensemble detector composed of 2D convolutional neural networks and a neural meta-learner on top of it. The second one uses the well-known and widely-used used ResNet deep neural model. Computer science ; Edge computing ; Deep learning ; Edge device ; Context (archaeology) ; Enhanced Data Rates for GSM Evolution ; Artificial neural network ; Convolutional neural network ; Edge detection ; Spectrogram ; Real-time computing ; Artificial intelligence ; Embedded system ; Cloud computing ; Image processing ; Operating system High voltage insulation and dielectric phenomena ; Geophysical Methods and Applications ; Fire Detection and Safety Systems
Authors: Xin Li | Jiandong Ding
Source: Regenerative Biomaterials (article, 2023-01-01)
Field: Materials Science — Materials Chemistry

Establishment of coverage-mass equation to quantify the corrosion inhomogeneity and examination of medium effects on iron corrosion Metal corrosion is important in the fields of biomedicine as well as construction and transportation etc. While most corrosion occurs inhomogeneously, there is so far no satisfactory parameter to characterize corrosion inhomogeneity. Herein, we employ the Poisson raindrop question to model the corrosion process and derive an equation to relate corrosion coverage and corrosion mass. The resultant equation is named coverage-mass equation, abbreviated as C-M equation. We also suggest corrosion mass at 50% coverage, termed as half-coverage mass <i>M</i> <sub>corro50%</sub>, as an inhomogeneity parameter to quantify corrosion inhomogeneity. The equation is confirmed and the half-coverage mass <i>M</i> <sub>corro50%</sub> is justified in our experiments of iron corrosion in five aqueous media, normal saline, phosphate-buffered saline, Hank's solution, deionized water and artificial seawater, where the former three ones are biomimetic and very important in studies of biomedical materials. The half-coverage mass <i>M</i> <sub>corro50%</sub> is proved to be more comprehensive and mathematically convergent than the traditional pitting factor. Iron corrosion is detected using visual observation, scanning electron microscopy with a build-in energy dispersive spectrometer, inductive coupled plasma emission spectrometry and electrochemical measurements. Both rates and inhomogeneity extents of iron corrosion are compared among the five aqueous media. The factors underlying the medium effects on corrosion rate and inhomogeneity are discussed and interpreted. Corrosion rates of iron in the five media differ about 7-fold, and half-coverage mass values differ about 300 000-fold. The fastest corrosion and the most significant inhomogeneity occur both in biomimetic media, but not the same one. The new equation (C-M equation) and the new quantity (half-coverage mass) are stimulating for dealing with a dynamic and stochastic process with global inhomogeneity including but not limited to metal corrosion. The findings are particularly meaningful for research and development of next-generation biodegradable materials. Corrosion ; Metallurgy ; Chemistry ; Materials science ; Computer science Corrosion Behavior and Inhibition ; Hydrogen embrittlement and corrosion behaviors in metals ; Material Properties and Failure Mechanisms
Authors: Anton Terentev | Vladimir Badenko | Е. L. Shaydayuk | D. V. Emelyanov | Danila Eremenko | Dmitriy Klabukov | Alexander Fedotov | В. И. Долженко
Source: Agriculture (article, 2023-06-02)
Field: Chemistry — Analytical Chemistry

Hyperspectral Remote Sensing for Early Detection of Wheat Leaf Rust Caused by Puccinia triticina Early crop disease detection is one of the most important tasks in plant protection. The purpose of this work was to evaluate the early wheat leaf rust detection possibility using hyperspectral remote sensing. The first task of the study was to choose tools for processing and analyze hyperspectral remote sensing data. The second task was to analyze the wheat leaf biochemical profile by chromatographic and spectrophotometric methods. The third task was to discuss a possible relationship between hyperspectral remote sensing data and the results from the wheat leaves, biochemical profile analysis. The work used an interdisciplinary approach, including hyperspectral remote sensing and data processing methods, as well as spectrophotometric and chromatographic methods. As a result, (1) the VIS-NIR spectrometry data analysis showed a high correlation with the hyperspectral remote sensing data; (2) the most important wavebands for disease identification were revealed (502, 466, 598, 718, 534, 766, 694, 650, 866, 602, 858 nm). An early disease detection accuracy of 97–100% was achieved from fourth dai (day/s after inoculation) using SVM. Hyperspectral imaging ; Remote sensing ; Rust (programming language) ; Stripe rust ; Computer science ; Environmental science ; Pattern recognition (psychology) ; Artificial intelligence ; Biology ; Geography ; Plant disease resistance Spectroscopy and Chemometric Analyses ; Remote Sensing in Agriculture ; Smart Agriculture and AI