Interaction Plots Research Articles

Factors Associated with the Year of Admission and The IQ of Engineering Students at A Public University in Peru

This study investigates the evolution of intelligence quotient (IQ) among students in the Faculty of Industrial Engineering at the Universidad Nacional Mayor de San Marcos. The aim is to determine the influence of three factors on IQ: age, year of study, and month of university enrollment. Data was collected from a group of students using the Wechsler Adult Intelligence Scale (WAIS-IV), a standardized instrument for assessing general intelligence in individuals aged 16 to 90. An orthogonal experimental design was employed to compare mean IQ scores across different groups defined by age, year of study, and their combinations, using a three-way analysis of variance and interaction plots. Results confirm the influence of both age and year of study on IQ, as well as the existence of an interaction effect between both variables. These findings suggest that both natural cognitive development and exposure to academic training contribute to changes in IQ throughout the university trajectory. Additionally, an opportunity is identified for future research to delve deeper into the underlying mechanisms of these changes and explore strategies to optimize students' intellectual development.

Locuszoomr: an R package for visualising publication-ready regional gene locus plots

Abstract Summary Locuszoomr is an R package for visualising and creating publication-ready regional gene locus plots similar to those produced by the original web interface ‘LocusZoom’, but running locally in R. Genetic or genomic data with gene annotation tracks are plotted via R base graphics or ‘ggplot2’, allowing flexibility and easy customisation. Modular plotting functions enable layering of multiple GWAS plots such as for PheWAS, comparing GWAS with eQTL signals, and aligning multiple locus plots on the same page. Interactive plots can be visualised using ‘plotly’ enabling quick identification of data points for labelling. The ‘LDlink’ API (https://ldlink.nih.gov/) can be programmatically queried to obtain linkage disequilibrium (LD) data from the 1000 Genomes Project which is overlaid on plots. The package allows users to query Ensembl databases from Bioconductor or AnnotationHub for genomic information, so it can be used to show gene track information for any species available in Ensembl. Helper functions enable recombination rate data from UCSC to be overlaid on plots. The package has a detailed vignette and includes embedded example GWAS data to allow users to try out different features. Locuszoomr is also fast: identifying 50 peaks in a GWAS of around 8 million SNPs takes around 0.6 seconds. Exporting 50 locus plots with 1Mbp window with recombination rate takes around 30 seconds on Intel 9th gen CPU or 14 seconds on Apple ARM M3. Availability and implementation The R package locuszoomr is open-source and available from CRAN: https://cran.r-project.org/package=locuszoomr and GitHub: https://github.com/myles-lewis/locuszoomr

Synthesis and machining characteristics study of agro-waste coconut shell powder incorporated aluminium alloy composite via the squeeze cast technique

ABSTRACT The present research synthesizes the aluminium alloy (Al7075) composite with 0-6% agro-waste coconut shell powder (CSP) via squeeze stir casting and evaluates its microstructural and mechanical properties. Effective processing influences uniform particle dispersion without agglomeration. The 6vol% of CSP featured Al7075 alloy composite is found an optimum tensile strength (242MPa) and hardness (83HV), which is subjected to drilling process via MTAB –Fanuc operated CNC drilling machine configured with CBN coated tool with different process parameters like speed (250-750rpm), diameter of drill (4- 8mm), and feed rate (5-15 mm/min) under 20mm depth with minimum quantity of lubricant on surface roughness (Ra), tool wear (TW) and time to drill (t) is calculated and optimized through analysis of variance. Interaction plot revealed that the S7 (750rpm/4mm/15mm/min) and S9 (750rpm/8mm/15mm/min) sequences are found to perform better machining operations like lower Ra, TW, and t between 0.00018 and 0.00019µm, 0.62-0.61m3/m and 75 and 112 sec.

Profile and outcomes of retinal artery occlusion: The underrealized need to expedite presentation.

To evaluate the clinical profile of retinal artery occlusion (RAO) and impact of presentation on visual outcomes. A retrospective analysis of case files of 3070 patients with RAO was performed using electronic medical records. Demographic data were analyzed using descriptive statistics. The differential distribution of risk factors of RAO with age was studied. Time to presentation and treatment effects were assessed using multivariate regression. Interaction plots were drawn to assess the impact of risk factors on outcomes. Central RAO was the most common type (n = 2443, 77.11%), followed by branch RAO (n = 500, 15.78%), while combined retinal vascular occlusion and cilio-RAO were rare. Most of the patients (71.40%) were male and had unilateral (96.81%) affliction. Almost half presented within the fifth (24.85%) and sixth (21.4%) decades of life. Hyperhomocysteinemia had a higher association (1.95, P = 0.0019) with younger patients (<40 years), while hypertension (3.64, P < 0.001), diabetes mellitus (DM; 4.18, P < 0.001), and coronary artery disease (CAD) (4.26, P = 0.002) were significantly commoner in older patients. CAD (5.1%) and cerebrovascular disease (0.6%) were detected after ocular presentation in some patients. Embolus, though detected rarely (1%), was associated (60%) with serious systemic disorders. Early presentation (<6 h) was associated with better visual outcomes (mean log of minimum angle of resolution 1.8 ± 1.3 vs. 2.1 ± 1.3, P = 0.032). Neovascular glaucoma (2.14% overall) was twice more common in DM (P < 0.0004) and led to further vision loss. Visual improvement occurred in 10% of patients over follow-up. RAO occurs slightly earlier compared to coronary and cerebrovascular disorders and can precede their detection. Associated risk factors vary with the age of presentation. Presentation within 6 h needs facilitation for better outcomes and management.

ENHANCING FORMABILITY OF AA6061 IN INCREMENTAL SHEET FORMING: EXPLORING PARAMETER EFFECTS ON FRACTURE DEPTH

AA6061's high strength and strain rate sensitivity in Incremental Sheet Forming (ISF) demand precise parameter control to prevent early fractures, especially at steep wall angles. Tool diameter influences the distribution of deformation forces, while spindle speed, step depth, and feed rate control the rate and extent of material deformation, collectively impacting the forming. This paper investigates the effect of these process parameters on the formability in terms of fracture depth. A statistical analysis is performed to identify the significant factors affecting forming depth. The main effect plot suggests that except the spindle speed, all three process parameters influence forming depth. However, the interaction plot reveals a more complex relationship, where step depth has a stronger effect on fracture depth, particularly at higher feed rates. These findings indicate that the interplay between these factors is crucial for determining optimal process parameters, where nearly 10% of increase in forming depth was achieved.

Development and validation of interpretable machine learning models for postoperative pneumonia prediction.

Postoperative pneumonia, a prevalent form of hospital-acquired pneumonia, poses significant risks to patients' prognosis and even their lives. This study aimed to develop and validate a predictive model for postoperative pneumonia in surgical patients using nine machine learning methods. Our study aims to develop and validate a predictive model for POP in surgical patients using nine machine learning algorithms. By evaluating the performance differences among these machine learning models, this study aims to assist clinicians in early prediction and diagnosis of POP, providing optimal interventions and treatments. Retrospective data from electronic medical records was collected for 264 patients diagnosed with postoperative pneumonia and 264 healthy control surgical patients. Through correlation screening, chi-square tests, and feature importance ranking, 47 variables were narrowed down to 5 potential predictive factors based on the main cohort of 528 patients. Nine machine learning models, including k-nearest neighbors, support vector machine, random forest, decision tree, gradient boosting machine, adaptive boosting, naive bayes, general linear model, and linear discriminant analysis, were developed and validated to predict postoperative pneumonia. Model performance was evaluated using the area under the receiver operating curve, sensitivity, specificity, accuracy, precision, recall, and F1 score. A distribution plot of feature importance and feature interaction was obtained to interpret the machine learning models. Among 17,190 surgical patients, 264 (1.54%) experienced postoperative pneumonia, which resulted in adverse outcomes such as prolonged hospital stay, increased ICU admission rates, and mortality. We successfully established nine machine learning models for predicting postoperative pneumonia in surgical patients, with the general linear model demonstrating the best overall performance. The AUC of the general linear model on the testing set was 0.877, with an accuracy of 0.82, specificity of 0.89, sensitivity of 0.74, precision of 0.88, and F1 score of 0.80. Our study revealed that the duration of bed rest, unplanned re-operation, end-tidal CO2, postoperative albumin, and chest X-ray film were significant predictors of postoperative pneumonia. Our study firstly demonstrated that the general linear model based on 5 common variables might predict postoperative pneumonia in the general surgical population.

Effects of Polyethylene Glycol and Chloride Ion on Copper Electroplating at High Current Density

To determine the effect of Polyethylene Glycol(PEG) and Chloride ions(Cl-) as additives during electroplating, this study used interaction plots of various characteristics of the electroplated Cu foils for analyses. Crystals of about 2 µm in size were observed on the surface of Cu electroplated in the electrolyte without PEG. When 30-100 ppm PEG was added, the crystal size and surface roughness decreased in relation to the amount of PEG. However, there were lots of dented areas, which became fewer as Chloride ions were increased from 20 ppm to 40 ppm. When 300 ppm PEG was added, the dented areas were not observed. Nevertheless, the surface morphology was very irregular and rough. In the group with 30-100 ppm PEG added, the resistivity decreased due to the increase in grain size. Moreover, the tendency of crystals to grow preferentially in the direction of the (111) plane led to an increased resistance to EM(electro-migration). When 40 ppm of chloride ions and 100 ppm of PEG were added, the yield strength increased by 22.4%, the tensile strength increased by 28.7%, and the elongation increased by 293.5% compared to the group without additives. This study showed that a combination of appropriate additives and amounts was required to form copper foils with low surface roughness, excellent electrical properties, and EM resistance and low corrosion rate. Therefore, with 100 ppm added PEG, it is necessary to add 20 ppm of chloride ions to ensure a low corrosion rate and 40 ppm of chloride ions for high mechanical properties.

Unconventional C-Hlg···H-C (Hlg = Cl, Br, and I) Interactions Involving Organic Halides: A Theoretical Study.

In this study, unconventional C-Hlg···H-C (Hlg = Cl, Br, and I) interactions involving sp, sp2, and sp3 organic halides were investigated at the RI-MP2/aug-cc-pVQZ level of theory. Energy Decomposition Analyses (EDA) and Natural Bonding Orbital (NBO) studies showed that these intermolecular contacts are mainly supported by orbital and dispersion contributions, which counteracted the unfavorable/slightly favorable electrostatics due to the halogen-hydrogen σ-hole facing. In addition, the Bader's Quantum Theory of Atoms in Molecules (QTAIM) and the Noncovalent Interaction plot (NCIplot) visual index methodologies were used to further characterize the interactions discussed herein. We expect that the results reported herein will be useful in the fields of supramolecular chemistry, crystal engineering, and rational drug design, where the fine tuning of noncovalent interactions is crucial to achieve molecular recognition or a specific solid-state architecture.

Revisiting Metal Dihalide Complexes with Phosphine Ligands: Isostructurality, Steric Effects, Anagostic Interactions, Crystal Voids, and Energetic Calculations

AbstractThe crystal structures of seven metal dihalide complexes with triphenylphosphine (PPh₃) and two with tribenzylphosphine (PBz₃) have been reanalyzed. The studied complexes include [FeCl₂(PPh₃)₂], [CoCl₂(PPh₃)₂], [CoBr₂(PPh₃)₂], [NiCl₂(PPh₃)₂], [NiBr₂(PPh₃)₂], [NiI₂(PPh₃)₂], [ZnCl₂(PPh₃)₂], [NiCl₂(PBz₃)₂], and [NiBr₂(PBz₃)₂]. A detailed geometric analysis revealed high isostructurality among several pairs. Ligand steric effects were assessed using cone angles and percentage surface coverage. Crystal packing is stabilized by weak C─H⋯π and C─H⋯X (X = Cl, Br, and I) interactions. Notably, [NiCl₂(PBz₃)₂] and [NiBr₂(PBz₃)₂] feature rare intramolecular C─H⋯Ni anagostic interactions. Reduced density gradient (RDG) and noncovalent interaction (NCI) plots confirmed weakly attractive C─H⋯π contacts in all complexes. Void‐volume analysis assessed the mechanical strength of the crystals, while pixel energy and energy frameworks clarified structural stability and dominant interactions. Density Functional Theory (DFT) calculations, along with QTAIM/NCIplot and NBO analyses, as well as electron density (ED) versus electrostatic potential (ESP) plots, were performed to better understand the C─H···Ni interactions and distinguish between agostic and anagostic interactions.

Exploration of Hydrogen Storage Exhibited by Rh‐Decorated Pristine and Defective Graphenes: A First‐Principles Study

ABSTRACTWe utilized density functional theory (DFT) to ascertain the storage of hydrogen in Rh‐decorated pristine (PG) and defective graphenes, primarily graphitic‐N (GNG) and pyridinic‐N (PNG). The binding energy of a single Rh atom on PG, GNG, and PNG was found to be −1.87, −2.18, and −4.01 eV, respectively. PG exhibits a weak adsorption energy of hydrogen molecules (−0.06 eV/H2). On the other hand, Rh‐decorated pristine and defective graphenes show incredibly higher hydrogen adsorption energy. As per the latest guidelines of the U.S. Department of Energy (DOE), the Rh‐decorated GNG (Rh@GNG) is found to be the best hydrogen storage material out of the three systems investigated here. The single Rh atom‐decorated GNG adsorbs up to 4H2. Uniform decoration of graphene surfaces with Rh atoms is necessary to improve hydrogen storage performance. Both sides of GNG surfaces are decorated with 8Rh atoms, which can adsorb up to 24H2 molecules, with an average adsorption energy of −0.33 eV/H2. The mechanism of H2 adsorption on the host system has been explored based on DFT‐evaluated deformation of charge density, partial density of states (PDOS), and non‐covalent interaction (NCI) plots. For a better understanding of the adsorption process, the diffusion energy barrier of Rh metal is computed using the climbing image nudged elastic band (CI‐NEB) method, and the thermal stability has been evaluated through ab initio molecular dynamics (AIMD) simulations.

Technical note: Effects of chemical, radiational, and thermal treatment of bone tissue on material stiffness and anisotropy.

We evaluated the effects of four treatments for pathogen inactivation in bone tissue (ethanol storage, formalin fixation, gamma irradiation, and heat treatment via autoclave) on stiffness and anisotropy values in bone samples. Cortical bone samples from the humerus of 14 bovine specimens were subjected to Knoop microindentation analysis in longitudinal and transverse planes of section and four indenter orientations within each section. From each specimen, individual samples were assigned to one of five treatment conditions: 50% ethanol-saline solution, formalin immersion, gamma irradiation, autoclave, and buffered saline (controls). Each sample was microindented 100 times and the resultant stiffness data were analyzed by a resampled factorial analysis of variance. First- and second-order interactions as well as main effects of indenter orientation, treatment, and specimen were significant for both transverse and longitudinal sections, with the sole exception that indenter orientation-treatment interaction was nonsignificant for longitudinal sections. Interaction plots reveal that thermal (autoclave) and irradiation treatments depress stiffness values the most, while patterns of indentation stiffness at different orientations are relatively unaffected. Patterns of anisotropy are relatively unaffected by preservative treatments, but elastic modulus changes are consistent and unambiguous. Formalin and ethanol treatments are most comparable to controls and represent the best preservative media for mechanical testing. These options, however, are likely to be the least effective for ensuring the inactivation or sterilization of potentially contaminated samples.

Aluminum Fluorides as Noncovalent Lewis Acids in Proteins: The Case of Phosphoryl Transfer Enzymes.

The Protein Data Bank (PDB) was scrutinized for the presence of noncovalent O ⋅ ⋅ ⋅ Al Triel Bonding (TrB) interactions, involving protein residues (e. g. GLU and GLN), adenosine/guanine diphosphate moieties (ADP and GDP), water molecules and two aluminum fluorides (AlF3 and AlF4 -). The results were statistically analyzed, revealing a vast number of O ⋅ ⋅ ⋅ Al contacts in the active sites of phosphoryl transfer enzymes, with a marked directionality towards the Al σ-/π-hole. The physical nature of the TrBs studied herein was analyzed using Molecular Electrostatic Potential (MEP) maps, the Quantum Theory of Atoms in Molecules (QTAIM), the Non Covalent Interaction plot (NCIplot) visual index and Natural Bonding Orbital (NBO) studies. As far as our knowledge extends, it is the first time that O ⋅ ⋅ ⋅ Al TrBs are analyzed within a biological context, participating in protein trapping mechanisms related to phosphoryl transfer enzymes. Moreover, since they are involved in the stabilization of aluminum fluorides inside the protein's active site, we believe the results reported herein will be valuable for those scientists working in supramolecular chemistry, catalysis and rational drug design.

Interfacial adsorption of ionic liquids (ILs) on graphitic carbon nitride (g-C3N4) nanosheets: A DFT study

The adsorption of nine common ionic liquids (ILs) on two well-known structures of graphitic carbon nitride (g-C3N4) nanosheets, including Triazine-g-C3N4 and Heptazine-g-C3N4 has been investigated using density functional theory (DFT) method in gas phase and water solvent. The interactions between the ILs and the nanosheets are characterized by several techniques, such as quantum theory of atoms in molecules (QTAIM) analysis, noncovalent interaction (NCI) plots, and energy decomposition analysis (EDA) method. Interestingly, the obtained results showed that electrostatic interactions have the highest contributions to the interaction energies between the ILs and the surfaces, followed by dispersion interactions and orbital interactions (ΔEelec > ΔEdisp > ΔEorb) The most important Van der Waals (vdW) interactions between the ILs and the surfaces include π–π, CH…N, CH…π (CN), and CN…X (X = F, N, O) interactions. On the other hand, the adsorption of ILs is accompanied by charge transfer from the surfaces to the ILs. The calculated adsorption energy (Eads) showed that the [Bmim][PF6] IL has the highest adsorption affinity on the Triazine-g-C3N4 (−28.28 kcal/mol) and Heptazine-g-C3N4 (−26.68 kcal/mol) surfaces. Thermochemistry calculations showed that the Eads, ΔHads, and ΔGads values of IL@surface complexes decrease on moving from gas phase to water media. However, our results showed that the adsorption of ILs on the surfaces is still exothermic and proceeds spontaneously. Upon adsorption of ILs, a decrease in the HOMO–LUMO energy gap (Eg) is observed and is accompanied by an increase in the reactivity and electrophilic character of the surfaces. TD-DFT calculations showed that the weak adsorption of ILs leads to small red or blue shifts in the absorption bands of the Triazine-g-C3N4 and Heptazine-g-C3N4 surfaces. However, no significant changes are observed in the shape of the absorption spectra of the surfaces. Furthermore, the transition density matrix (TDM) heat maps of the IL@surface complexes showed that the electrons and holes are generally concentrated on the Triazine-g-C3N4 and Heptazine-g-C3N4 surfaces in the IL@surface complexes, signifying that the electronic transitions occur mainly on the surfaces.

Ab Initio Molecular Dynamics Studies of Stacked Adenine–Thymine and Guanine–Cytosine Nucleic Acid Base Pairs in Aqueous Solution

Ab initio MD studies have been performed on stacked adenine–thymine (A–T) and guanine–cytosine (G–C) nucleobase pairs solvated in water using Born–Oppenheimer molecular dynamics. These two systems have been analyzed using RDF, SDF, angle–distance CDF (combined distribution functions), plane projection analysis, hydrogen bond analysis, and non–covalent interaction (NCI) plots. The stacking property studies have shown that the molecular orientation of the A–T pair is completely opposite to that of the G–C pair though the center of mass distance between the two molecules is similar. The G–C pair shows significantly more stability in water than the A–T system does. RDF analyses show that the –NH– group and carbonyl groups show predominant interaction with water molecules. Water molecules are found to be most in numbers around the cytosine molecule and least around the adenine molecule. Hydrogen bonding studies show that the guanine molecule forms the highest number of hydrogen bonds with water molecules. On the other hand, the hydrogen atom attached to the –NH– group of adenine molecule shows the longest mean H–bond lifetime with water oxygen atoms. NCI interactions calculated through the ab initio method help us to visualize the [Formula: see text]-electron stacking and H–bonding between aromatic nucleobases and water molecules. A great shift in bond polarity and interaction intensity in different functional groups is observed for the nucleobases going from individually solvated molecules to paired states.

Evaluation of albumin and lactate dehydrogenase in comparison with cytokeratin 19 fragments and neuron‐specific enolase as diagnostic biomarkers for non‐small cell lung cancer

AbstractBackgroundThe diagnosis of non‐small cell lung cancer (NSCLC) is a clinical issue that requires attention, and more practical and effective biomarkers need to be selected to assist in diagnosis. This study aimed to examine the diagnostic value of serum albumin (ALB), lactate dehydrogenase (LDH), cytokeratin 19 fragments (CYFRA21‐1), and neuron‐specific enolase (NSE) for NSCLC.MethodsThe clinical data of 1048 NSCLC patients and 1125 healthy subjects were extracted from electronic medical records. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic significance of ALB, LDH, CYFRA21‐1, and NSE for NSCLC. The Cancer Genome Atlas (TCGA) data, which included mRNA profiles for ALB and LDH expression, were acquired from TCGA Program. Finally, interactive survival scatter plots and survival analyses for NSCLC patients were evaluated using the Human Protein Atlas and Kaplan–Meier Plotter.ResultsSignificant differences were noted in the levels of ALB and LDH between NSCLC patients and healthy controls. The areas under the ROC curves (AUCs) for ALB and LDH were 0.754 (95% CI: 0.734–0.774) and 0.681 (95% CI: 0.658–0.704), respectively. Moreover, the combination of ALB and LDH raised the AUC to 0.804 (95% CI: 0.785–0.823), and the incorporation of CYFRA21‐1 and NSE further increased the AUC to 0.903 (95% CI: 0.890–0.916). Notably, ALB and LDH might be related to the overall survival of NSCLC patients.ConclusionThis study revealed that ALB and LDH in NSCLC patient serum could improve the diagnostic accuracy of conventional biomarkers for NSCLC.

Unusual Metal–organic Multicomponent Ni(II) and Mononuclear Zn(II) Compounds Involving Pyridine dicarboxylates: Supramolecular Assemblies and Theoretical Studies

In the present work, we reported the synthesis and characterization [single crystal X-ray diffraction technique, spectroscopic, etc.] of two new Ni(II) and Zn(II) coordination compounds, viz. [Ni(2,6-PDC)2]2[Ni(en)2(H2O)2]2[Ni(en)(H2O)4]·4H2O (1) and [Zn(2,6-PDC)(Hdmpz)2] (2) (where 2,6-PDC = 2,6-pyridinedicarboxylate, en = ethylene-1,2-diamine, and Hdmpz = 3,5-dimethyl pyrazole). Compound 1 is found to crystallize as a multicomponent Ni(II) compound with five discrete complex moieties, whereas compound 2 is isolated as a mononuclear Zn(II) compound. A deep analysis of the crystal structure of 1 unfolds unusual dual enclathration of guest complex cationic moieties within the supramolecular host cavity stabilized by anion–π, π-stacking, N–H⋯O, C–H⋯O, and O–H⋯O hydrogen bonding interactions. Again, the crystal structure of compound 2 is stabilized by the presence of unconventional C–H⋯π(chelate ring) interactions along with C–H⋯O, C–H⋯N hydrogen bonding, π-stacking, and C–H⋯π(pyridyl) interactions. These non-covalent interactions were further studied theoretically using density functional theory (DFT) calculations, molecular electrostatic potential (MEP) surfaces, non-covalent interaction (NCI) plot index, and quantum theory of atoms in molecules (QTAIM) computational tools. The computational study displays that π-stacking or H bonds greatly tune the directionality of compound 1, although non-directional electrostatic forces dominate energetically. For compound 2, a combined QTAIM/NCI plot analysis confirms the presence of unconventional C–H⋯π(chelate ring) interactions along with other weak interactions obtained from the crystal structure analysis. Further, the individual energy contributions of these weak yet significant non-covalent interactions have also been determined computationally.

Advanced synthesis and forensic application of CoPr(x)Cr(2-x)O4 nanoparticles for latent fingerprint detection

The production, characterisation, and use of CoPr(x)Cr(2-x)O4 (x = 0.00, 0.01, 0.03, and 0.05) nanoparticles for improved latent fingerprint (LFP) detection are investigated in this study. CoCr2O4 containing different amounts of Praseodymium(Pr3+) were prepared by solution combustion process using 1:1 M ratio of oxidizer and fuel. X-ray diffraction (XRD) was used to examine the structural characteristics of these nanoparticles, and the results showed that the crystallite sizes and lattice parameters varied while the spinel structure remained constant. The effective synthesis of the intended nanoparticles was indicated by the confirmation of CoCr2O4 presence in the spinel structure by Fourier Transform Infrared Spectroscopy, or FTIR. In particular, the study showed how these nanoparticles can be used in forensic science to identify LFP on a variety of surfaces, including steel, paper, and OHP sheets. In daylight, the CoPr0.03Cr1.97O4 (CoPr-3)variation with x = 0.05 performed better, allowing for a clear viewing of Level I–III fingerprint features. 3D interactive plots and high-resolution images demonstrated that the nanoparticles stuck to fingerprint remnants, improving visibility and detail. The study also looked at how stable these nanoparticles were under UV irradiation and aging, and it discovered that CoPr-3 phosphor was remarkably resistant to UV degradation and retained its efficacy for 60 days. These results demonstrate the potential of CoPr(x)Cr(2-x)O4 nanoparticles as a reliable and effective material for forensic fingerprint analysis, providing notable enhancements in LFP detection sensitivity and resolution.

Role of Intermolecular Interactions in Deep Eutectic Solvents for CO2 Capture: Vibrational Spectroscopy and Quantum Chemical Studies.

Recent research and reviews on CO2 capture methods, along with advancements in industry, have highlighted high costs and energy-intensive nature as the primary limitations of conventional direct air capture and storage (DACS) methods. In response to these challenges, deep eutectic solvents (DESs) have emerged as promising absorbents due to their scalability, selectivity, and lower environmental impact compared to other absorbents. However, the molecular origins of their enhanced thermal stability and selectivity for DAC applications have not been explored before. Therefore, the current study focuses on a comprehensive investigation into the molecular interactions within an alkaline DES composed of potassium hydroxide (KOH) and ethylene glycol (EG). Combining Fourier transform infrared (FT-IR) and quantum chemical calculations, the study reports structural changes and intermolecular interactions induced in EG upon addition of KOH and its implications on CO2 capture. Experimental and computational spectroscopic studies confirm the presence of noncovalent interactions (hydrogen bonds) within both EG and the KOH-EG system and point to the aggregation of ions at higher KOH concentrations. Additionally, molecular electrostatic potential (MESP) surface analysis, natural bond orbital (NBO) analysis, quantum theory of atoms-in-molecules (QTAIM) analysis, and reduced density gradient-noncovalent interaction (RDG-NCI) plot analysis elucidate changes in polarizability, charge distribution, hydrogen bond types, noncovalent interactions, and interaction strengths, respectively. Evaluation of explicit and hybrid models assesses their effectiveness in representing intermolecular interactions. This research enhances our understanding of molecular interactions in the KOH-EG system, which are essential for both the absorption and desorption of CO2. The study also aids in predicting and selecting DES components, optimizing their ratios with salts, and fine-tuning the properties of similar solvents and salts for enhanced CO2 capture efficiency.

Magnetization Processes of Exchange Coupled Nd2(Fe,Co)14B Alloys in Various Demagnetized States

Processes of magnetization in exchange-coupled rapidly quenched nanocrystalline alloys Nd2(Fe1-xCox)14B, where x = 0, 0.07, 0.2, 0.5, have been studied. Initial magnetization curves and interaction plots δM(H) for various demagnetized states were obtained. Based on comparison of measurement results, influence of the pinning type mechanism on magnetization process in the Nd2(Fe1-xCox)14B melt-spun ribbons is shown. Using δM(H) plots, change in intergrain exchange interaction depending on cobalt concentration in rapidly quenched Nd2(Fe1-xCox)14B nanocrystalline alloys was investigated.

PerturBase: a comprehensive database for single-cell perturbation data analysis and visualization.

Single-cell perturbation (scPerturbation) sequencing techniques, represented by single-cell genetic perturbation (e.g. Perturb-seq) and single-cell chemical perturbation (e.g. sci-Plex), result from the integration of single-cell toolkits with conventional bulk screening methods. These innovative sequencing techniques empower researchers to dissect perturbation effects in biological systems at an unprecedented resolution. Despite these advancements, a notable gap exists in the availability of a dedicated database for exploring scPerturbation data. To address this gap, we present PerturBase, the most comprehensive database designed for the analysis and visualization of scPerturbation data (http://www.perturbase.cn/). PerturBase curates 122 datasets from 46 publicly available studies, covering 115 single-modal and 7 multi-modal datasets that include 24254 genetic and 230 chemical perturbations from approximately 5 million cells. The database, comprising the 'Dataset' and 'Perturbation' modules, provides insights into various results, encompassing quality control, denoising, differential gene expression analysis, functional analysis of perturbation effectsand characterization of relationships between perturbations. All the datasets and results are presented on user-friendly, easy-to-browse web pages and can be visualized through intuitive and interactive plot and table formats. In summary, PerturBase stands as a pioneering, high-content database intended for searching, visualizingand analyzing scPerturbation datasets, contributing to a deeper understanding of perturbation effects.