Solid phase extraction and preconcentration of uranium(VI) and thorium(IV) on Duolite XAD761 prior to their inductively coupled plasma mass spectrometric determination

A simple and effective method is presented for the separation and preconcentration of thorium(IV) and uranium(VI) by solid phase extraction on Duolite XAD761 adsorption resin. Thorium(IV) and uranium(VI) 9-phenyl-3-fluorone chelates are formed and adsorbed onto the Duolite XAD761. Thorium(IV) and uranium(VI) are quantitatively eluted with 2 mol L⁻¹ HCl and determined by inductively coupled plasma-mass spectrometry (ICP-MS). The influences of analytical parameters including pH, amount of reagents, amount of Duolite XAD761 and sample volume, etc. were investigated on the recovery of analyte ions. The interference of a large number of anions and cations has been studied and the optimized conditions developed have been utilized for the trace determination of uranium and thorium. A preconcentration factor of 30 for uranium and thorium was achieved. The relative standard deviation (N = 10) was 2.3% for uranium and 4.5% for thorium ions for 10 replicate determinations in the solution containing 0.5 μg of uranium and thorium. The three sigma detection limits (N = 15) for thorium(IV) and uranium(VI) ions were found to be 4.5 and 6.3 ng L⁻¹, respectively. The developed solid phase extraction method was successively utilized for the determination of traces thorium(IV) and uranium(VI) in environmental samples by ICP-MS.     

Synthesis and characterization of new 4,5-dihydropyrazol-1-yl derivatives

In this study, first, a series of chalcone compounds S1–S6 were synthesized from various acetophenone derivatives (acetophenone, p-methyl acetophenone, and p-methoxy acetophenone) and aromatic aldehyde derivatives (benzaldehyde, p-methyl benzaldehyde, and p-methoxy benzaldehyde) by the Claisen–Schmidt condensation reaction. These S1–S6 compounds were then used in the preparation of 4,5-dihydropyrazol-1-yl derivatives S7–S15. Finally, four new compounds S16–S19 were synthesized from compound (S7, S8, S9, and S12) and 2,4-dinitrophenylhydrazine. Therefore, three known and ten new heterocyclic compounds were synthesized and completely characterized using ¹H NMR, ¹³C NMR, IR, and elemental analysis.     

Lipase biosensor for tributyrin and pesticide detection

Potentiometric biosensors based on Candida rugosa lipase was described for the detection of organophosphorus pesticide; methyl-parathion and tributyrin. Lipase was immobilized on the glass electrode by means of a gelatin membrane, which is then cross-linked with glutaraldehyde. The principle of the biosensor is based on the measurement of pH variation which was recorded in millivolts due to the enzymatic hydrolysis of tributyrin to butyric acid. For the inhibitor detection, biosensor responses were measured after pesticide treatment, which caused a drop in enzyme activity because of the irreversible inhibition. Reactivation conditions of the reused enzyme electrodes were also investigated by pyridine-2-aldoxime methiodide (2-PAM). The limit of detection for tributyrin was estimated as 93?µM for lipase sensor within the linear range of 65–455?µM.     

A Comparison of Four Different Electrode Matrices on the Performance of Amperometric Hydrogen Peroxide (Bio)Sensors

A comparison of the analytical performances of four different (bio)sensor designs in H₂O₂ determination is discussed. The (bio)sensor designs developed were based on the use of (i) multiwalled carbon nanotubes (MWCNT), zinc oxide nanoparticles (ZnONP), prussian blue (PB); (ii) MWCNT, ZnONP, PB and ionic liquid (IL); (iii) MWCNT, ZnONP and horseradish peroxidase (HRP) and (iv) MWCNT, ZnONP, HRP and IL modified glassy carbon electrode (GCE). A performance comparison of (bio)sensors showed that the one based on HRP/IL-MWCNT-ZnONP/GCE showed the best analytical characteristics with a linear dynamic range of 9.99×10⁻⁸–7.55×10⁻⁴ M, detection limit of 1.37×10⁻⁸ M and sensitivity of 17.00 μA mM⁻¹.     

Microstructural properties and local atomic structures of cobalt oxide nanoparticles synthesised by mechanical ball-milling process

In this study, facile preparation of pure and nano-sized cobalt oxides particles was achieved using low-cost mechanical ball-milling synthesis route. Microstructural and morphological properties of synthesised products were characterised by X-ray diffraction (XRD) and transmission electron microscopy (TEM) techniques. XRD results indicated that the fabricated samples composed of cubic pure phase CoO and Co₃O₄ nanocrystalline particles with an average crystallite size of 37.2 and 31.8 nm, respectively. TEM images showed that the resulting samples consisted of agglomerates of particles with average diameter of about 37.6 nm for CoO and 31.9 nm for Co₃O₄. Phase purity of the prepared samples was further investigated due to their promising technological applications. Local atomic structure properties of the prepared nanoparticles were probed using synchrotron radiation-based X-ray absorption spectroscopy (XAS) including X-ray absorption near-edge structure (XANES) and extended X-ray absorption fine structure (EXAFS). EXAFS data analysis further confirmed the formation of single-phase CoO and Co₃O₄ nanoparticles. In addition, structural properties of cobalt oxide nanoparticles were investigated by performing density functional theory calculations at B3LYP/TZVP level and Born–Oppenheimer molecular dynamics. Theoretical calculations for both prepared samples were found to be consistent with the experimental results derived from EXAFS analysis. Obtained results herein reveals that highly crystalline and pure phase CoO and Co₃O₄ nanoparticles can be synthesised using simple, inexpensive and eco-friendly ball-milling method for renewable energy applications involving fuel cells and water splitting devices.     

Spectral characterization and antibacterial effect of 2-methyl-6-(5-H-Me-Cl-NO <Subscript>2</Subscript>-1<Emphasis Type="Italic">H</Emphasis>-benzimidazol-2-yl)-phenols and some transition metal complexes

2-Methyl-6-(5-H-methyl-chloro-nitro-1H-benzimidazol-2-yl)-phenols( HL _x :x= 1-4)ligands and HL₁ complexes with Fe(NO₃)₃, Cu(NO₃)₂, AgNO₃, Zn(NO₃)₂ have been synthesized and characterized. The structures of the compounds were confirmed on the basis of elemental analysis, molar conductivity, magnetic moment, FT-IR, ¹H-and ¹³C-NMR. Antibacterial activity of the free ligands, their hydrochloride salts and the complexes were evaluated using the disk diffusion method in dimethyl sulfoxide as well as the minimum inhibitory concentration dilution method, against nine bacteria. While HL₁ ligand has not any activity, it’s Ag(I) complex show antibacterial effect toward almost to all the bacteria. Zn(II) complex has antibacterial effect on especially K. pneumoniae, S. epidermidis and S. aureus bacteria.     

A Districtwide Study of Automaticity When Included in Concept‐Based Elementary School Mathematics Instruction

While conceptual understanding of properties, operations, and the base‐ten number system is certainly associated with the ability to access math facts fluently, the role of math fact memorization to promote conceptual understanding remains contested. In order to gain insight into this question, this study looks at the results when one of three elementary schools in a school district implements mandatory automaticity drills for 10 minutes each day while the remaining two elementary schools, with the same curriculum and very similar demographics, do not. This study looks at (a) the impact that schoolwide implementation of automaticity drills has on schoolwide computational math skills as measured by the ITBS and (b) the relationship between automaticity and conceptual understanding as measured by statewide standardized testing. The results suggest that while there may be an association between automaticity and higher performance on standardized tests, caution should be taken before assuming there are benefits to promoting automaticity drills. These results are consistent with those that support a process‐driven approach to automaticity based on familiarity with properties and strategies associated with the base‐ten number system; they are not consistent with those that support an answer‐driven approach to automaticity based on memorization of answers.     

A step toward the wet surface chemistry of glycine and alanine on Cu{110}: destabilization and decomposition in the presence of near-ambient water vapor

The coadsorption of water with organic molecules under near-ambient pressure and temperature conditions opens up new reaction pathways on model catalyst surfaces that are not accessible in conventional ultrahigh-vacuum surface-science experiments. The surface chemistry of glycine and alanine at the water-exposed Cu{110} interface was studied in situ using ambient-pressure photoemission and X-ray absorption spectroscopy techniques. At water pressures above 10(-5) Torr a significant pressure-dependent decrease in the temperature for dissociative desorption was observed for both amino acids, accompanied by the appearance of a new CN intermediate, which is not observed for lower pressures. The most likely reaction mechanisms involve dehydrogenation induced by O and/or OH surface species resulting from the dissociative adsorption of water. The linear relationship between the inverse decomposition temperature and the logarithm of water pressure enables determination of the activation energy for the surface reaction, between 213 and 232 kJ/mol, and a prediction of the decomposition temperature at the solid-liquid interface by extrapolating toward the equilibrium vapor pressure. Such experiments near the equilibrium vapor pressure provide important information about elementary surface processes at the solid-liquid interface, which can be retrieved neither under ultrahigh vacuum conditions nor from interfaces immersed in a solution.     

The long term impact of a coherence based model for mathematics intervention

This article presents a large-scale longitudinal study of hundreds of students across the state of Kentucky that participated in a dual-focus mathematics intervention initiative when they were in the third grade. Rather than an exclusive focus on intervention, this initiative focused on both (i) high quality pull-out intervention and (ii) coherence between pull-out intervention and classroom instruction. The study found that over half of the third grade intervention students that participated in this initiative were classified as “novice” (the lowest possible performance category) on state standardized mathematics assessments at the end of the third grade. However, over the course of the following four years, the novice reduction rate of these students was significantly (p < .01) greater than other novices in Kentucky that did not participate in the initiative. These findings indicate that when implementing intervention initiatives to help students that are struggling with mathematics, it may be important to establish coherence between pull-out intervention and classroom instruction. The long term impact of this approach among traditionally underrepresented minorities suggest that this publication may provide insight into important equity issues where long-term analyses may sometimes be needed to capture the full impact of intervention initiatives.     

A Confidence Region Approach to Tuning for Variable Selection

We develop an approach to tuning of penalized regression variable selection methods by calculating the sparsest estimator contained in a confidence region of a specified level. Because confidence intervals/regions are generally understood, tuning penalized regression methods in this way is intuitive and more easily understood by scientists and practitioners. More importantly, our work shows that tuning to a fixed confidence level often performs better than tuning via the common methods based on Akaike information criterion (AIC), Bayesian information criterion (BIC), or cross-validation (CV) over a wide range of sample sizes and levels of sparsity. Additionally, we prove that by tuning with a sequence of confidence levels converging to one, asymptotic selection consistency is obtained, and with a simple two-stage procedure, an oracle property is achieved. The confidence-region-based tuning parameter is easily calculated using output from existing penalized regression computer packages. Our work also shows how to map any penalty parameter to a corresponding confidence coefficient. This mapping facilitates comparisons of tuning parameter selection methods such as AIC, BIC, and CV, and reveals that the resulting tuning parameters correspond to confidence levels that are extremely low, and can vary greatly across datasets. Supplemental materials for the article are available online.