jablonkagroup/rise_ai_scientists huggingface dataset:
Authors: Alexander Schlaich | Sandeep Tyagi | Stefan Kesselheim | Marcello Sega | Christian Holm
Source: The European Physical Journal E (article, 2023-09-01)
Field: Chemistry — Physical and Theoretical Chemistry

Renormalized charge and dielectric effects in colloidal interactions: a numerical solution of the nonlinear Poisson–Boltzmann equation for unknown boundary conditions The Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, introduced more than 70 years ago, is a hallmark of colloidal particle modeling. For highly charged particles in the dilute regime, it is often supplemented by Alexander's prescription (Alexander et al. in J Chem Phys 80:5776, 1984) for using a renormalized charge. Here, we solve the problem of the interaction between two charged colloids at finite ionic strength, including dielectric mismatch effects, using an efficient numerical scheme to solve the nonlinear Poisson-Boltzmann (NPB) equation with unknown boundary conditions. Our results perfectly match the analytical predictions for the renormalized charge by Trizac and coworkers (Aubouy et al. in J Phys A 36:5835, 2003). Moreover, they allow us to reinterpret previous molecular dynamics (MD) simulation results by Kreer et al. (Phys Rev E 74:021401, 2006), rendering them now in agreement with the expected behavior. We furthermore find that the influence of polarization becomes important only when the Debye layers overlap significantly. DLVO theory ; Poisson–Boltzmann equation ; Nonlinear system ; Physics ; Poisson's equation ; Charge (physics) ; Dielectric ; Boundary value problem ; Statistical physics ; Molecular dynamics ; Debye ; Boltzmann equation ; Polarization (electrochemistry) ; Colloid ; Classical mechanics ; Condensed matter physics ; Quantum mechanics ; Ion ; Chemistry Electrostatics and Colloid Interactions ; Spectroscopy and Quantum Chemical Studies ; Material Dynamics and Properties
Authors: Manzoor Koyakutty | Greeshma Devassy | Devika Das | Shantikumar V. Nair
Source: Precision Nanomedicine (article, 2023-09-23)
Field: Materials Science — Biomaterials

Injectable nanogel systems for brain drug delivery &lt;img src=” https://s3.amazonaws.com/production.scholastica/article/88217/large/prnano_912023ga.jpg?1695507286”&gt; The central nervous system (CNS) controls many critical functions, such as intelligence, emotion, sense, and memory, and modulates many other functions of the entire human body. Diseases affecting the CNS are challenging to treat because of the CNS’s sensitive functional and structural features and limited accessibility. The brain is secured from the systemic circulation by a unique biological fence, the blood-brain barrier (BBB), that limits molecular exchange between the peripheral and CNS systems. Most drugs used for treating CNS diseases fail to reach the brain in effective therapeutic concentrations due to the presence of BBB. During the last decade, specifically engineered drug delivery systems (DDS) have offered the opportunity to overcome systemic barriers in brain drug delivery. However, even with the best-engineered nano-carriers, delivering sufficient drug doses into the brain through systemic circulation remains challenging. Here, we review various systems for ‘direct’ drug delivery to the brain using im-plantable or injectable intracranial nano-drug delivery systems (nDDS), which can ensure 100% release of drug to the brain in a sustained or controlled fashion for prolonged periods, bypassing the BBB, thereby radically improving the therapeutic efficacy while minimizing systemic toxicity. Brain injectable nanogels or nanoparticle systems can be considered superior compared to other local drug-delivery systems because they possess better diffusivity of drugs. The nanogels can be injected through minimally invasive procedures, precisely delivering drugs to specific target sites. This review covers a detailed discussion about locally injectable DDS and various nanogel-based drugs, oligonucleotide, and theragnostic delivery systems used for treating brain malignancies, infections, and neurodegenerative diseases. Drug delivery ; Systemic circulation ; Medicine ; Nanogel ; Drug ; Blood–brain barrier ; Central nervous system ; Drug delivery to the brain ; Systemic administration ; Blood circulation ; Pharmacology ; Neuroscience ; Nanotechnology ; Biology ; Internal medicine ; In vivo Nanoparticle-Based Drug Delivery ; Advanced Drug Delivery Systems ; Graphene and Nanomaterials Applications
Authors: Banu Özgen Keleş
Source: TEKSTİL VE KONFEKSİYON (article, 2023-06-22)
Field: Materials Science — Polymers and Plastics

Application of Neural Network for the Prediction of Loss in Mechanical Properties of Aramid Fabrics After Thermal Aging Aramid fabrics are used to produce most of the flame resistant protection clothes to fulfil the protection requirements. Even though aramid fibers have good thermal stability and flame resistance properties, fabrics used in protective clothing age and loss some of their essential functions under various environmental and operational conditions during their lifetime. These conditions cause serious limitations in the use of clothing. In this study, various woven fabrics produced from aramid (Nomex, Kevlar) fabrics were exposed to accelerated aging tests under varying temperature and time period in order to construct Neural Network models to predict weight loss and tensile strength loss percentages of the fabrics. The results of Artificial Neural Network models demonstrate that regression values are 0.98405 for weight loss percentages and 0.99935 for tensile strength loss percentages of the fabrics. Accordingly, the proposed Artificial Neural Network models are correctly constituted and the losses in determined fabric properties is successfully predicted. Aramid ; Ultimate tensile strength ; Materials science ; Composite material ; Kevlar ; Artificial neural network ; Weight loss ; Tear resistance ; Structural engineering ; Computer science ; Engineering ; Composite number ; Artificial intelligence ; Fiber ; Medicine Textile materials and evaluations
Authors: Ahmed Sameer Khan Mohammed | R. Sidharth | Wael Abuzaid | Hiroshi Akamine | Minoru Nishida | Hüseyin Şehitoğlu
Source: Shape Memory and Superelasticity (article, 2023-08-24)
Field: Materials Science — Materials Chemistry

Orientation Relationships in FeMnNiAl Governed by Martensitic Substructure Substructure ; Martensite ; Materials science ; Stacking ; Austenite ; Shape-memory alloy ; Crystallography ; Condensed matter physics ; Transmission electron microscopy ; Phase (matter) ; Metallurgy ; Microstructure ; Physics ; Structural engineering ; Chemistry ; Nuclear magnetic resonance ; Nanotechnology Shape Memory Alloy Transformations
Authors: Hongtao Lin | Maoliang Wei | Kai Xu | Bo Tang | Junying Li | Yiting Yun | Peng Zhang | Yingchun Wu | Kangjian Bao | Kunhao Lei | Zequn Chen | Hui Ma | Chunlei Sun | Ruonan Liu | Ming Li | Lan Li
Source: Research Square (preprint, 2023-10-20)
Field: Materials Science — Materials Chemistry

“Zero change” platform for monolithic back-end-of-line integration of phase change materials in silicon photonics Photonics ; Zero (linguistics) ; Silicon ; Phase (matter) ; Line (geometry) ; Silicon photonics ; Materials science ; Phase change ; Zero emission ; Optoelectronics ; Engineering ; Engineering physics ; Electrical engineering ; Physics ; Mathematics ; Geometry Phase-change materials and chalcogenides ; Photonic and Optical Devices ; Thin-Film Transistor Technologies
Source: International Research Journal of Modernization in Engineering Technology and Science (article, 2023-04-04)
Field: Materials Science — Polymers and Plastics

ARTIFICIAL INTELLIGENCE FOR CHILD DROWNING PREVENTION IN SWIMMING POOLS USING FACE RECOGNITION Every year, many individuals, including kids under the age of 5 drown in the deeps of the swimming pool, and the lifeguards are not well trained enough to handle these situations.The current systems expected to address the problem of ensuring safety at swimming pools have significant problems due to their technical aspects, such as cameras and methodological aspects such as the need for human intervention in the rescue mission.Thus, arises the requirement for having a system that will consequently detect the drowning individuals and alarm the life guard at such risk.Swimming pool surveillance systems plays an essential role in safeguarding the premises.The use of an automated visual-based monitoring system can help to reduce drownings and assure pool safety effectively.This study introduces a revolutionary technology that identifies drowning victims in a minimum amount of time.Using convolutional neural network (CNN) models, it can detect a drowning person.Drowning is not like what we see in movies, the real features of drowning don't include shouting for help, but what is really present in drowning behavior is having a vertical body resurfacing up and down on the water surface.In this project the children's details are recorded in the system prior to swimming.The recorded details are saved in the databases.The facial recognition of the kids in the swimming pool are continuously monitored.Using Open cv, threshold values for water depth level are defined in the system and any person detected beyond this depth are considered drowning and the image is captured instantly.The captured image is compared with the details in database and the kid drowned is identified.The details of the kid drowning are sent to the rescuer immediately through SMTP and alarm sound alert is generated using speech synthesizer.This helps in quick rescue of drowning kids. Face (sociological concept) ; Medical emergency ; Injury prevention ; Artificial intelligence ; Poison control ; Psychology ; Computer science ; Computer security ; Medicine ; Sociology Textile materials and evaluations
Authors: SM Bargeen Alam Turzo | Justin T. Seffernick | Sergey Lyskov | Steffen Lindert
Source: ChemRxiv (preprint, 2023-02-27)
Field: Chemistry — Spectroscopy

Predicting Ion Mobility Collision Cross Sections using Projection Approximation with ROSIE-PARCS Webserver Ion mobility (IM) coupled to mass spectrometry informs on the shape and size of protein structures in the form of a collision cross section (CCSIM). While there are several computational methods for predicting CCSIM based on protein structures, including our previously developed PARCS, the process usually requires prior experience with the command-line interface (CLI). To overcome this challenge, here we present a web application on the ROSIE webserver to predict CCSIM from protein structure using projection approximation with PARCS. In this web interface, the user is only required to provide one or more PDB files as input. Results from our case studies suggest that CCSIM predictions (with ROSIE-PARCS) are highly accurate with an average error of 6.12%. Furthermore, the absolute difference between CCSIM and CCSPARCS can help in distinguishing accurate from inaccurate AlphaFold2 protein structure predictions. ROSIE-PARCS is designed with a user-friendly interface, is available publicly, and is free to use. The ROSIE-PARCS web interface is supported by all major web browsers and can be accessed via this link (https://rosie.graylab.jhu.edu). Computer science ; Interface (matter) ; Collision ; Web server ; Process (computing) ; Cross section (physics) ; Simulation ; Physics ; Operating system Mass Spectrometry Techniques and Applications ; Advanced Proteomics Techniques and Applications ; Metabolomics and Mass Spectrometry Studies
Authors: Samadi Samadi | Indra Wahyudi | Sitti Wajizah | Zulfahrizal Zulfahrizal | Agus Arip Munawar
Source: International Journal of Design & Nature and Ecodynamics (article, 2023-08-31)
Field: Chemistry — Analytical Chemistry

Rapid and Non-Destructive Prediction of Animal Feed Nutritive Parameters Using Near Infrared Spectroscopy and Multivariate Analysis This study elucidates the application of near-infrared spectroscopy (NIRS) and multivariate analysis for the rapid, non-destructive determination of animal feed nutritive parameters, specifically pH, NH3, and volatile fatty acid (VFA) values.NIRS spectra within the 1000-2500 nm range, coupled with reference methods, were employed for parameter determination.To enhance prediction accuracy, spectral pre-processing was undertaken using multiplicative scatter correction (MSC), Savitzky-Golay (SG) smoothing, and first-derivative methods.Simultaneous determination of nutritive parameters was achieved through the establishment of prediction models employing three multivariate analyses: principal component regression (PCR), partial least squares regression (PLSR), and support vector machine regression (SVMR).The results indicated superior pH (r=0.993) and NH3 (r=0.987)predictions using SVMR, while PLSR yielded the lowest root mean square error (RMSE) for VFA (r=0.998).These findings suggest that with appropriate spectral corrections and regression methodologies, NIRS can be effectively utilized for the rapid, simultaneous determination of animal feed nutritive parameters. Partial least squares regression ; Multivariate statistics ; Principal component analysis ; Mean squared error ; Principal component regression ; Mathematics ; Smoothing ; Statistics ; Regression analysis ; Second derivative ; Multivariate analysis ; Analytical Chemistry (journal) ; Biological system ; Chemistry ; Chromatography ; Biology Spectroscopy and Chemometric Analyses ; Spectroscopy Techniques in Biomedical and Chemical Research ; Water Quality Monitoring and Analysis
Authors: О. П. Черкасова | Maria Konnikova | М. М. Назаров | Denis A. Vrazhnov | Yury V. Kistenev | A. P. Shkurinov
Source: Journal of Biomedical Photonics & Engineering (article, 2023-08-15)
Field: Chemistry — Physical and Theoretical Chemistry

Terahertz Spectroscopy of Mouse Blood Serum in the Dynamics of Experimental Glioblastoma In this study terahertz (THz) absorption spectra of mouse blood serum in the dynamics of experimental U87 glioblastoma were investigated. Decrease of THz absorption with glioma growth was demonstrated. A two-component Debye model was used to analyze the experimental data. Analysis of the complex dielectric permittivity parameters of blood serum indicates an increase in the proportion of bound water in the samples in the dynamics of tumor growth. Terahertz radiation ; Dynamics (music) ; Permittivity ; Glioblastoma ; Absorption (acoustics) ; Materials science ; Glioma ; Spectral line ; Spectroscopy ; Terahertz spectroscopy and technology ; Nuclear magnetic resonance ; Chemistry ; Dielectric ; Medicine ; Cancer research ; Optoelectronics ; Physics thermodynamics and calorimetric analyses ; Terahertz technology and applications
Authors: Xiaoyu Han | Lu Jin | Zhimin Zhao | Xinjun Xu | Shiyi Liu | Yuquan Huang | Xiaoli Liu | Yuehong Xu | Depo Yang | Wei Huang | Li Wang
Source: Pharmaceuticals (article, 2023-01-10)
Field: Chemistry — Organic Chemistry

Combining the In Silico and In Vitro Assays to Identify Strobilanthes cusia Kuntze Bioactives against Penicillin-Resistant Streptococcus pneumoniae Leaves of <i>Strobilanthes cusia</i> Kuntze (<i>S. cusia</i>) are a widely used alexipharmic Traditional Chinese Medicine (TCM) in southern China for the prevention of cold and respiratory tract infectious diseases. One of the most common bacterial pathogens in the respiratory tract is the gram-positive bacterium <i>Streptococcus pneumoniae</i>. The antibiotic resistance of colonized <i>S. pneumoniae</i> makes it a more serious threat to public health. In this study, the leaves of <i>S. cusia</i> were found to perform antibacterial effects on the penicillin-resistant <i>S. pneumoniae</i> (PRSP). Confocal assay and Transmission Electron Microscopy (TEM) monitored the diminished cell wall integrity and capsule thickness of the PRSP with treatment. The following comparative proteomics analysis revealed that the glycometabolism-related pathways were enriched for the differentially expressed proteins between the samples with treatment and the control. To further delve into the specific single effective compound, the bio-active contents of leaves of <i>S. cusia</i> were analyzed by UPLC-UV-ESI-Q-TOF/MS, and 23 compounds were isolated for anti-PRSP screening. Among them, Tryptanthrin demonstrated the most promising effect, and it possibly inhibited the N-glycan degradation proteins, as suggested by reverse docking analysis in silico and further experimental verification by the surface plasmon resonance assay (SPR). Our study provided a research foundation for applications of the leaves of <i>S. cusia</i> as a TCM, and supplied a bio-active compound Tryptanthrin as a candidate drug skeleton for infectious diseases caused by the PRSP. Streptococcus pneumoniae ; Microbiology ; In silico ; Respiratory tract infections ; Chemistry ; Biology ; Traditional medicine ; Antibiotics ; Medicine ; Biochemistry ; Respiratory system ; Gene Quinazolinone synthesis and applications ; Phenothiazines and Benzothiazines Synthesis and Activities ; Cancer therapeutics and mechanisms
Authors: Priya Palanichamy | Rajesh Krishnasamy | M. Ulaganathan | Senthil Muthu Kumar Thiagamani | R.A. Ilyas | Ahmed M. Hassan
Source: Heliyon (article, 2023-11-27)
Field: Materials Science — Materials Chemistry

A practical green synthesis method of Ag NPs using rosy periwinkle plant leaves for solar panel coating Coated silver nanoparticles (Ag NPs) are currently receiving interest because of their numerous uses in various fields of electronics, antimicrobials, manufacturing sectors, optical science, and pharmaceuticals. Among others, it gained significant attention in the power electronic system. The goal of the proposed study is to use a cost-effective coating material for solar panels; to accomplish this, silver nanoparticles were synthesized from the leaves of the <i>Rosy Periwinkle</i> plants. Green synthesis and characterization, such as Ultraviolet Visible Spectrometer (UV-Vis) analysis, Scanning Electron Microscopy (SEM), Energy Dispersive X-ray Spectroscopy (EDX), and Fourier Transform Infrared Spectroscopy (FTIR), were carried out after the silver nanoparticles have been collected prior coating. As a consequence, the effectiveness is determined based on the conductivity test, and the resulting Ag NPs are then applied to the c-si layer of the solar panel. Additionally, a modelling and experimental analysis are performed in this study to ascertain the suggested framework's ability to measure energy before and after coating panels with Ag NPs. Specifically, the Voltage Current (VI) and Power Voltage (PV) characteristics were validated in this study for analyzing the effectiveness and the obtained results revealed that the coating of green synthesized Ag NPs generated 2 % more power than the reference solar panel under the same conditions. Further, hardware testing and simulation were both used to confirm the outcomes and effectiveness of the suggested method. The open circuit voltage (V<sub>oc</sub>), short circuit current (I<sub>sc</sub>), maximum peak voltage (V<sub>mp</sub>), maximum peak current (I<sub>mp</sub>), and efficiency are taken into account when assessing how well the suggested system performs at tracking. Moreover, the current density characteristics were evaluated with respect to various irradiation conditions for both the typical solar as well as Ag NPs coated panels. From the observation, it is noted that the efficiency level of coated panel was improved up to 19.20 %, 18 %, and 17.20 % for the irradiations of 200 W/m<sup>2</sup>, 500 W/m<sup>2</sup>, and 1000 W/m<sup>2</sup> respectively. Coating ; Fourier transform infrared spectroscopy ; Materials science ; Silver nanoparticle ; Spectroscopy ; Spectrometer ; Nanotechnology ; Voltage ; Open-circuit voltage ; Nanoparticle ; Analytical Chemistry (journal) ; Optoelectronics ; Process engineering ; Chemical engineering ; Electrical engineering ; Chemistry ; Optics ; Engineering ; Physics ; Chromatography Nanoparticles: synthesis and applications
Authors: Irina V. Lebedeva | Alberto Garcı́a | Emilio Artacho | Pablo Ordejón
Source: Royal Society Open Science (article, 2023-04-01)
Field: Materials Science — Materials Chemistry

Modular implementation of the linear- and cubic-scaling orbital minimization methods in electronic structure codes using atomic orbitals We present a code modularization approach to design efficient and massively parallel cubic- and linear-scaling solvers for electronic structure calculations using atomic orbitals. The modular implementation of the orbital minimization method, in which linear algebra and parallelization issues are handled via external libraries, is demonstrated in the SIESTA code. The distributed block compressed sparse row (DBCSR) and scalable linear algebra package (ScaLAPACK) libraries are used for algebraic operations with sparse and dense matrices, respectively. The MatrixSwitch and libOMM libraries, recently developed within the Electronic Structure Library, facilitate switching between different matrix formats and implement the energy minimization. We show results comparing the performance of several cubic-scaling algorithms, and also demonstrate the parallel performance of the linear-scaling solvers, and their supremacy over the cubic-scaling solvers for insulating systems with sizes of several hundreds of atoms. Linear scale ; Scaling ; Linear algebra ; Computer science ; Computational science ; Parallel computing ; Minification ; Benchmark (surveying) ; Sparse matrix ; Atomic orbital ; Modular design ; Energy minimization ; Algorithm ; Mathematics ; Physics ; Geometry ; Quantum mechanics Machine Learning in Materials Science ; Advanced Chemical Physics Studies ; Semiconductor materials and devices
Authors: Markéta Tichotová | Lucie Tučková | Hugo Kocek | Aleš Růžička | Michal Straka | Eliška Procházková
Source: Physical Chemistry Chemical Physics (article, 2023-12-13)
Field: Chemistry — Spectroscopy

Exploring the impact of alignment media on RDC analysis of phosphorus-containing compounds: a molecular docking approach Residual dipolar couplings (RDCs) are employed in NMR analysis when conventional methods, such as <i>J</i>-couplings and nuclear Overhauser effects (NOEs) fail. Low-energy (optimized) conformers are often used as input structures in RDC analysis programs. However, these low-energy structures do not necessarily resemble conformations found in anisotropic environments due to interactions with the alignment medium, especially if the analyte molecules are flexible. Considering interactions with alignment media in RDC analysis, we developed and evaluated a molecular docking-based approach to generate more accurate conformer ensembles for compounds in the presence of the poly-γ-benzyl-L-glutamate alignment medium. We designed chiral phosphorus-containing compounds that enabled us to utilize <sup>31</sup>P NMR parameters for the stereochemical analysis. Using P3D/PALES software to evaluate diastereomer discrimination, we found that our conformer ensembles outperform moderately the standard, low-energy conformers in RDC analysis. To further improve our results, we (i) averaged the experimental values of the molecular docking-based conformers by applying the Boltzmann distribution and (ii) optimized the structures through normal mode relaxation, thereby enhancing the Pearson correlation factor <i>R</i> and even diastereomer discrimination in some cases. Nevertheless, we presume that significant differences between <i>J</i>-couplings in isotropic and in anisotropic environments may preclude RDC measurements for flexible molecules. Therefore, generating conformer ensembles based on molecular docking enhances RDC analysis for mildly flexible systems while flexible molecules may require applying more advanced approaches, in particular approaches including dynamical effects. Diastereomer ; Conformational isomerism ; Docking (animal) ; Chemistry ; Helix (gastropod) ; Computational chemistry ; Crystallography ; Stereochemistry ; Organic chemistry ; Molecule ; Biology Molecular spectroscopy and chirality ; Advanced NMR Techniques and Applications ; Various Chemistry Research Topics