A Bayesian Approach for Extracting Fluorescence Lifetimes from Sparse Data Sets and Its Significance for Imaging Experiments

The measurement of fluorescence lifetimes, especially in small sample volumes, presents the dual challenge of probing a small number of fluorophores and fitting the concomitant sparse data set to the appropriate excited‐state decay function. A common method of analysis, such as the maximum likelihood (ML) technique, assumes a uniform probability distribution of the parameters describing the fluorescence decay function. An improvement is thus suggested by implementing a suitable nonuniform distribution, as is provided by a Bayesian framework, where the distribution of parameters is obtained from both their prior knowledge and the evidence‐based likelihood of an event for a given set of parameters. We have also considered the Dirichlet prior distribution, whose mathematical form enables analytical solutions of the fitting parameters to be rapidly obtained. If Gaussian and exponential prior distributions are judiciously chosen, they reproduce the experimental target lifetime to within 20% with as few as 20 total photon counts for the data set, as does the Dirichlet prior distribution. But because of the analytical solutions afforded by the Dirichlet prior distribution, it is proposed to employ a Dirichlet prior to search parameter space rapidly to provide, if necessary, appropriate parameters for subsequent employment of a Gaussian or exponential prior distribution.     

X‐ray photoelectron spectroscopy and the pattern recognition method—their application to surface studies in CoPd alloys

In the present work, polycrystalline CoPd alloys in varying range of bulk atomic percent composition (Co30Pd70, Co50Pd50 and Co70Pd30) are investigated by means of X‐ray photoelectron spectroscopy (XPS). The results of conventional XPS quantitative multiline (ML) approach are compared to the results obtained on the basis of XPS lines shape analysis, where the selected XPS or X‐ray induced Auger electron (XAES) transitions, are processed using the pattern recognition method known as the fuzzy k‐nearest neighbour (fkNN) rule. The fkNN rule is applied to the following spectra line shapes: Pd MNV, Co 2p, Co LMM, Pd 3d and valence band, analysing electrons in a varying range of selected kinetic energies. Both methods showed the surface segregation of Pd in Co30Pd70 and Co50Pd50 alloys. The results of the ML, the binding energy shift (ΔBE) analysis and the fkNN rule remained in agreement. Discrepancies in quantitative results obtained using different approaches are discussed within the accuracy of the applied methods, differences due to mean escape depth (MED) of electrons in considered transitions, their depth distribution function, the sensitivity of electron transition line shape on the environmental change (weaker effect for the inner shell transitions, and stronger effect for the outer shell transitions and Auger electron spectroscopy (AES) electrons transitions) and the non‐uniform depth profile concentrations. Copyright © 2005 John Wiley & Sons, Ltd.     

Establishing a Robust and Reliable Response from a Potent Osmium-Based Photosensitizer Via Lipid Nanoformulation†

Osmium (Os) based photosensitizers (PSs) are a unique class of nontetrapyrrolic metal-containing PSs that absorb red light. We recently reported a highly potent Os(II) PS, rac-[Os(phen)₂(IP-4T)](Cl)₂, referred to as ML18J03 herein, with light EC₅₀ values as low as 20 pm . ML18J03 also exhibits low dark toxicity and submicromolar light EC₅₀ values in hypoxia in some cell lines. However, owing to its longer oligothiophene chain, ML18J03 is not completely water soluble and forms 1–2 μm sized aggregates in PBS containing 1% DMSO. This aggregation causes variability in PDT efficacy between assays and thus unreliable and irreproducible reports of in vitro activity. To that end, we utilized PEG-modified DPPC liposomes (138 nm diameter) and DSPE-mPEG₂₀₀₀ micelles (10.2 nm diameter) as lipid nanoformulation vehicles to mitigate aggregation of ML18J03 and found that the spectroscopic properties important to biological activity were maintained or improved. Importantly, the lipid formulations decreased the interassay variance between the EC₅₀ values by almost 20-fold, with respect to the unformulated ML18J03 when using broadband visible light excitation (P = 0.0276). Herein, lipid formulations are presented as reliable platforms for more accurate in vitro photocytotoxicity quantification for PSs prone to aggregation (such as ML18J03) and will be useful for assessing their in vivo PDT effects.     

Quantitative Analysis of Solar Photovoltaic Panel Performance with Size-Varied Dust Pollutants Deposition Using Different Machine Learning Approaches

In this paper, the impact of dust deposition on solar photovoltaic (PV) panels was examined, using experimental and machine learning (ML) approaches for different sizes of dust pollutants. The experimental investigation was performed using five different sizes of dust pollutants with a deposition density of 33.48 g/m² on the panel surface. It has been noted that the zero-resistance current of the PV panel is reduced by up to 49.01% due to the presence of small-size particles and 15.68% for large-size (ranging from 600 µ to 850 µ). In addition, a significant reduction of nearly 40% in sunlight penetration into the PV panel surface was observed due to the deposition of a smaller size of dust pollutants compared to the larger size. Subsequently, different ML regression models, namely support vector machine (SVMR), multiple linear (MLR) and Gaussian (GR), were considered and compared to predict the output power of solar PV panels under the varied size of dust deposition. The outcomes of the ML approach showed that the SVMR algorithms provide optimal performance with MAE, MSE and R² values of 0.1589, 0.0328 and 0.9919, respectively; while GR had the worst performance. The predicted output power values are in good agreement with the experimental values, showing that the proposed ML approaches are suitable for predicting the output power in any harsh and dusty environment.     

Effects of coverage and solvent on H2S adsorption on the Cu(100) surface: A DFT study

Density functional theory is used to investigate the effects of coverage and solvent on the adsorption of H₂S on the Cu(100) surface. In this work, the adsorption energies, structural parameters and Mulliken charges of the adsorbed H₂S are calculated. The results show that when the coverage of H₂S is high (1 ML), H₂S molecule cannot adsorb on the Cu(100) surface spontaneously, and the decomposition of H₂S preferentially occurs at the bridge site. When the coverage decreases to 1/4 ML coverage, H₂S molecule does not exhibit the decomposition, but bonds to the top Cu atom with the tilted adsorption. Furthermore, when the coverage is 1/9, 1/16 and 1/25 ML, H₂S adsorption remains stable. In addition, the stability of H₂S adsorption on the Cu(100) surface improves rapidly when the solvent dielectric constant (ε) increases from 1 to 12.3 corresponding to the vacuum and pyridine, respectively. For the higher ε (≥24.3), the effect of the solvent on the H₂S adsorption was greatly reduced. In this work, both coverage and solvent are shown to have an important effect on the H₂S adsorption on the Cu(100) surface, which might be useful to improve the future similar simulations. Copyright © 2015 John Wiley & Sons, Ltd.     

Impact of updating the MALDI‐TOF MS database on the identification of nontuberculous mycobacteria

Conventional identification of mycobacteria species is slow, laborious and has low discriminatory power. Matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry (MALDI‐TOF MS) has proved highly effective for identifying conventional bacteria, and it may also be useful for identifying mycobacteria. The aim of this study was to evaluate and compare MALDI‐TOF MS with currently recommended molecular methods for the identification of nontuberculous mycobacteria (NTM), applying Mycobacteria Libraries v3.0 (ML3.0) and v2.0 (ML2.0). A total of 240 clinical isolates of 41 NTM species grown on solid media were analysed: 132 isolates of slow‐growing mycobacteria and 108 of rapid‐growing mycobacteria. MALDI‐TOF MS, using ML3.0, identified 192 (80%) NTM isolates with a score ≥1.7, encompassing 35 (85.4%) different species, that is, 17 (7.1%; p  = 0.0863) isolates and 15 (36.6%; p  = 0.0339) species more than currently recommended molecular techniques (polymerase chain reaction reverse hybridization). All these isolates were correctly identified according to molecular identification methods. The application of ML3.0 also identified 15 (6.2%) NTM isolates more than ML2.0 (p  < 0.01). The scores obtained with MALDI‐TOF MS using ML3.0 (mean score: 1.960) were higher in 147 (61.2%) isolates than when using ML2.0 (mean score: 1.797; p  < 0.01). Three of the species analysed were not included in either database, so they were not recognized by this system. In conclusion, MALDI‐TOF MS identified more isolates and species than the recommended polymerase chain reaction reverse hybridization assays. Although the new ML3.0 is not the definitive database, it yielded better results than ML2.0. This shows that the updating of the MALDI‐TOF MS database plays an essential role in mycobacterial identification. Copyright © 2017 John Wiley & Sons, Ltd.     

Sorption of Lead(II) on Two Chelating Resins: From the Exchange Coefficient to the Intrinsic Complexation Constant

The sorption of inorganic lead(II) on two cationic resins containing different complexing groups, the iminodiacetic Chelex 100 and the carboxylic Amberlite CG-50, was investigated. The Gibbs-Donnan model was used to describe and predict the sorption through the determination of the intrinsic complexation constants. These quantities, even though non-thermodynamic, characterize the sorption as being independent of experimental conditions. The sorption mechanism for metals on complexing resins was also studied by adding a competitive soluble ligand that shifts the sorption curves to higher pH. The ligand competes with the resin for complexation with the metal ion. Lead(II) is strongly sorbed on Chelex 100 through the formation of two complexes in the resin phase: MHL with log ₁₀ β _111i =−0.3 and ML with log ₁₀ β _111i =−3.7. The presence of the competitive ligand in solution allows for the determination of a third complex. Furthermore, on Amberlite CG-50 the sorption is rather strong and involves the formation of the complex ML, in more acidic solution, with log ₁₀ β _110i =−2.0. In the presence of the ligand PyDA, the ML(OH) complex was characterized by log ₁₀ β _11−1i =−5.6. In all the experiments the hydrolysis reactions in the aqueous phase are considered quantitatively.     

Enhanced Nanostructure Dynamics on Au(111) with Adsorbed Sulfur due to Au−S Complex Formation

Chemisorbed species can enhance the fluxional dynamics of nanostructured metal surfaces which has implications for applications such as catalysis. Scanning tunneling microscopy studies at room temperature reveal that the presence of adsorbed sulfur (S) greatly enhances the decay rate of 2D Au islands in the vicinity of extended step edges on Au(111). This enhancement is already significant at S coverages, θ_S, of a few hundredths of a monolayer (ML), and is most pronounced for 0.1–0.3 ML where the decay rate is increased by a factor of around 30. For θ_S close to saturation at about 0.6 ML, sulfur induces pitting and reconstruction of the entire surface, and Au islands are stabilized. Enhanced coarsening at lower θ_S is attributed to the formation and diffusion across terraces of Au−S complexes, particularly AuS₂ and Au₄S₄, with some lesser contribution from Au₃S₄. This picture is supported by density functional theory analysis of complex formation energies and diffusion barriers.     

The preparation and characterization of some new nickel(II), copper(II), zinc(II) and cadmium(II) complexes of the pyrrole-2-carboxaldehyde Schiff bases ofS-alkyl esters of dithiocarbazic acid

Summary New complexes of general formulae [Ni(HL)₂], [ML]·H₂O and [Cu(HL)X] (H₂L = pyrrole-2-aldehyde Schiff bases ofS-methyl- andS-benzyldithiocarbazates; X = Cl or Br; M = Ni^II, Cu^II, Zn^II or Cd^II) were prepared and characterized by a variety of physicochemical techniques. The Schiff bases coordinate as NS bidentate chelating agents in [Ni(HL)₂] and [Cu(HL)X], and as tridentate NNS chelates in [ML] (M = Ni^II, Cu^II, Zn^II or Cd^II). Both the [Ni(HL)₂] and [NiL] complexes are diamagnetic and square-planar. Based on magnetic and spectroscopic evidence, thiolate sulphur-bridged dimeric square-planar structures are assigned to the [Cu(HL)X] and [ML] (M = Ni^II or Cu^II) complexes. The complexes ML (M = Zn^II or Cd^II) are polymeric and octahedral.     

Dielectric Characteristics of Sol-Gel-Derived BST/BSLaT/BST Multilayer

BST/BSLaT/BST multiplayer (ML) films were prepared by sol-gel method on the Pt/Ti/SiO₂/Si substrate. X-ray diffraction analysis and atomic force microscopy showed that dopant La causes decreased grain size of BST thin films obviously, and ML films were similar to BST films in size. The dielectric constant versus temperature curve of ML films becomes sharper comparing with that of BST films near the phase transition point, which indicated that the pyroelectric coefficient is propitious to be enhanced. The ML films also improve the leakage current characteristics of BST thin films and the linear relationship of the log J versus E^1/2 curves shows in a good agreement with the Schottky thermionic emission model. This work clearly reveals the highly promising potential of BST/BSLaT/BST multiplayer films compared with BST films for application in uncooled infrared focal plane arrays system.     

CO Blocking of D2 Dissociative Adsorption on Ru(0001)

The influence of pre‐adsorbed CO on the dissociative adsorption of D₂ on Ru(0001) is studied by molecular‐beam techniques. We determine the initial dissociation probability of D₂ as a function of its kinetic energy for various CO pre‐coverages between 0.00 and 0.67 monolayers (ML) at a surface temperature of 180 K. The results indicate that CO blocks D₂ dissociation and perturbs the local surface reactivity up to the nearest‐neighbour Ru atoms. Non‐activated sticking and dissociation become less important with increasing CO coverage, and vanish at θ_CO≈0.33 ML. In addition, at high D₂ kinetic energy (>35 kJ mol^?1) the site‐blocking capability of CO decreases rapidly. These observations are attributed to a CO‐induced activation barrier for D₂ dissociation in the vicinity of CO molecules.     

Retention modeling under organic modifier gradient conditions in ion-pair reversed-phase chromatography. Application to the separation of a set of underivatized amino acids

The combined effect of the ion-pairing reagent concentration, C _ipr, and organic modifier content, φ, on the retention under φ-gradient conditions at different constant C _ipr was treated in this study by using two approaches. In the first approach, the prediction of the retention time of a sample solute is based on a direct fitting procedure of a proper retention model to 3-D φ-gradient retention data obtained under the same φ-linear variation but with different slope and time duration of the initial isocratic part and in the presence of various constant C _ipr values in the eluent. The second approach is based on a retention model describing the combined effect of C _ipr and φ on the retention of solutes in isocratic mode and consequently analyzes isocratic data obtained in mobile phases containing different C _ipr values. The effectiveness of the above approaches was tested in the retention prediction of a mixture of 16 underivatized amino acids using mobile phases containing acetonitrile as organic modifier and sodium dodecyl sulfate as ion-pairing reagent. From these approaches, only the first one gives satisfactory predictions and can be successfully used in optimization of ion-pair chromatographic separations under gradient conditions. The failure of the second approach to predict the retention of solutes in the gradient elution mode in the presence of different C _ipr values was attributed to slow changes in the distribution equilibrium of ion-pairing reagents caused by φ-variation.     

Anionic syntheses of terminally functionalized ethylene oligomers

Synthetic procedures for preparation of terminally functionalized linear ethylene oligomers are described. The preferred synthetic method is anionic oligomerization of ethylene with n-butyllithium–tetramethylethylenediamine and electrophilic substitution of the living oligomer so-formed. Conditions and procedures for subsequent chemistry to elaborate the end groups of these oligomers are described. These procedures afford strictly linear ethylene oligomers which contain a wide variety of end groups and which range in molecular weight from 1000 to 4500 (M_n). The product oligomers were characterized spectroscopically as toluene-d₈ solutions at 110°C using multinuclear NMR, FT-IR, fluorescence, and UV-visible spectroscopies as appropriate. Alternative stepwise approaches to such oligomers are also discussed.     

The determination of an accepted reference value from proficiency data with stated uncertainties

Proficiency data with stated uncertainties represent a unique opportunity for testing that the reported uncertainties are consistent with the Guide to the expression of uncertainty in measurement (GUM). In most proficiency tests, however, this opportunity is forfeited, because proficiency data are processed without regard to their uncertainties. In this paper we present alternative approaches for determining a reference value as the weighted mean of all mutually consistent results and their stated uncertainties. Using an accepted reference value each reported uncertainty estimate can be expressed as an E _n number, but a value of confirms its validity only if the uncertainty of the reference value is negligible in comparison.Reference values calculated for results from an International Measurement Evaluation Programme (IMEP-9) by “bottom up” as well as “top down” methods were practically identical, although the first strategy yielded the lowest uncertainty. A plot of individual coefficients of variation (CV) versus E _n numbers helps interpretation of the proficiency data, which could be used to validate relative uncertainties down to <1%.     

A benchmark spike‐in data set for biomarker identification in metabolomics

The development and the validation of innovative approaches for biomarker selection are of paramount importance in many ‐omics technologies. Unfortunately, the actual testing of new methods on real data is difficult, because in real data sets, one can never be sure about the “true” biomarkers. In this paper, we present a publicly available metabolomic ultra performance liquid chromatography–mass spectrometry spike‐in data set for apples. The data set consists of 10 control samples and three spiked sets of the same size, where naturally occurring compounds are added in different concentrations. In this sense, the data set can serve as a test bed to assess the performance of new algorithms and compare them with previously published results. We illustrate some of the possibilities provided by this spike‐in data set by comparing the performance of two popular biomarker‐selection methods, the univariate t‐test and the multivariate variable importance in projection. To promote a widespread use of the data, raw data files as well as preprocessed peak lists are made available. Copyright © 2012 John Wiley & Sons, Ltd.     

Electrochemical formation of a III–V compound semiconductor superlattice: InAs/InSb

We report on the use of electrochemical atomic-layer epitaxy (EC-ALE) to grow thin-films of the III–V compounds InAs, InSb, and an InAs_xSb_1−x superlattice. EC-ALE is a method for forming compound semiconductors with improved control, compared to other electrodeposition methodologies. It involves the use of surface limited reactions to form deposits an atomic layer at a time, in a cycle. The EC-ALE cycle uses underpotential deposition (upd) to form atomic layers of each of the component elements. One cycle ideally produces one monolayer (ML) of the desired compound. Studies to optimize the InAs cycle are reported, specifically the dependence on the In and As deposition potentials. These studies show that the potentials must be adjusted for each of the first 25 or more cycles, as a contact potential between the Au substrate and the growing semiconductor develops. After deposition of this initial ‘buffer layer’, steady state conditions are reached, and the same potentials can be used without change, for the remaining cycles. The formation of InSb has also been investigated, and the EC-ALE growth of InSb deposits is reported for the first time. Due to a 6% lattice mismatch, and a less than fully optimized cycle, the InSb deposits on Au appear composed of 70 nm particles. By combining the InAs and InSb programs, a superlattice was formed with 41 periods, where each period involved ten cycles of InAs followed by ten cycles of InSb. X-ray diffraction (XRD) indicated a period of 5.5 nm, whereas a 7.4 nm period was expected, based on 1 ML/cycle and the (111) interplanar spacing, derived from the lattice constants for InAs and InSb. Given the stoichiometry of the resulting deposit, and the shorter periodicity observed, it appears that 1 ML/cycle of InAs was formed, while only a 1/2 ML/cycle of InSb was obtained. IR absorption measurements indicate that the deposit was red shifted relative to the lower bandgap compound, InSb (0.17 eV), which is consistent with a type II superlattice. If an alloy had been formed, the bandgap should have been a linear function of the bandgaps and relative mole fractions of InAs and InSb, or about 0.31 eV, twice the observed bandgap.     

Use of cluster expansion techniques in quantum chemistry. A linear response model for calculating energy differences

In this paper we have reviewed the theoretical framework of the coupled-cluster (cc) based linear response model as a tool for directly calculating energy differences of spectroscopic interest like excitation energy (ee), ionisation potential (ip) or electron affinity (ea). In this model, the ground state of a many-electron system is described as in a coupled cluster theory for closed shells. The electronic ground state is supposed to interact with an external photon field of frequencyw, and the poles of the linear response function as a function ofw furnish with the elementary excitations of the system. Depending on the general form of the coupling term chosen, appropriate difference energies like ee, ip or EA may be generated. Pertinent derivations of the general working equations are reviewed, and specific details as well as approximations for ee, ip or ea are indicated. It is shown that the theory bears a close resemblance to the equation of motion (eom) method but is superior to the latter in that the ground state correlation is taken to all orders and may be looked upon as essentially a variant of renormalisedtda. A perturbative analysis elucidating the underlying perturbative structure of the formulation is also given which reveals that the theory has a hybrid structure: the correlation terms are treated akin to an open shellmbpt, while the relaxation terms are treated akin to a Green function theory. A critique of the methodvis-a-vis other cc-based approaches for difference energies forms the concluding part of our review.