The F-measure for Research Priority Rousseau, Ronald
Journal of data and information science (Warsaw, Poland),
3/2018, Letnik:
3, Številka:
1
Journal Article
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Abstract Purpose In this contribution we continue our investigations related to the activity index ( AI ) and its formal analogs. We try to replace the AI by an indicator which is better suited for ...policy applications. Design/methodology/approach We point out that fluctuations in the value of the AI for a given country and domain are never the result of that country’s policy with respect to that domain alone because there are exogenous factors at play. For this reason we introduce the F -measure. This F -measure is nothing but the harmonic mean of the country’s share in the world’s publication output in the given domain and the given domain’s share in the country’s publication output. Findings The F -measure does not suffer from the problems the AI does. Research limitations The indicator is not yet fully tested in real cases. R&D policy management In policy considerations, the AI should better be replaced by the F -measure as this measure can better show the results of science policy measures (which the AI cannot as it depends on exogenous factors). Originality/value We provide an original solution for a problem that is not fully realized by policy makers.
Abstract Purpose New developments in the study of delayed recognition are discussed. Design/methodology/approach Based on these new developments a method is proposed to characterize delayed ...recognition as a fuzzy concept. Findings A benchmark value of 0.333 corresponding with linear growth is obtained. Moreover, a case is discovered in which an expert found delayed recognition several years before citation analysis could discover this phenomenon. Research limitations As all citation studies also this one is database dependent. Practical implications Delayed recognition is turned into a fuzzy concept. Originality/value The article presents a new way of studying delayed recognition.
The scientific foundation for the criticism on the use of the Journal Impact Factor (JIF) in evaluations of individual researchers and their publications was laid between 1989 and 1997 in a series of ...articles by Per O. Seglen. His basic work has since influenced initiatives such as the San Francisco Declaration on Research Assessment (DORA), the Leiden Manifesto for research metrics, and The Metric Tide review on the role of metrics in research assessment and management. Seglen studied the publications of only 16 senior biomedical scientists. We investigate whether Seglen's main findings still hold when using the same methods for a much larger group of Norwegian biomedical scientists with more than 18,000 publications. Our results support and add new insights to Seglen's basic work.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Both primary and secondary nucleation rates are considered in a model developed for unseeded batch crystallization. A carefully designed strategy was employed to minimize the effects of the ...stochastic nature of induction time; nucleation was induced at designed supersaturations on known temperature plateaus. Crystallization kinetics of paracetamol from ethanolic solutions were extracted from measurements of in situ solute concentrations and combined with sieve (ex situ) data on the final product. Parameters in models for primary and secondary nucleation and for crystal growth rate were estimated by fitting a full population balance model to the measurements, and the evolution of the crystal size distribution was compared against in situ estimation from focused-beam reflectance measurements using the technique that we previously developed. The resulting models suggest that primary nucleation produces fewer surviving crystals than had been expected and that most of the product crystals from the process involving a temperature plateau result from secondary nucleation.
The multiphase nature of slurries can make them difficult to process and monitor in real time. For example, the nuclear waste slurries present at the Hanford site in Washington State are ...multicomponent, multiphase, and inhomogeneous. Current analytical techniques for analyzing radioactive waste at Hanford rely on laboratory results from an on-site analytical laboratory, which can delay processing speed and create exposure risks for workers. However, in-line probes can provide an alternative route to collect the necessary composition information. In the present work, Raman spectroscopy and attenuated total reflectance–Fourier transform infrared (ATR-FTIR) spectroscopy are tested on simulants of nuclear waste slurries containing up to 23.2 wt % solids. We observe ATR-FTIR spectroscopy to be effective in measuring the solution phase of the studied slurry systems (3.52% mean percent error), while Raman spectroscopy provides information about the suspended solids in the slurry system (18.21% mean percent error). In-line measurement of multicomponent solids typical of nuclear waste processing has been previously unreported. The composition of both the solution and solid phases is vital in ensuring stable glass formulation and effective disposal of nuclear waste at Hanford. Raman and ATR-FTIR spectroscopies can provide a safer and faster alternative for acquiring compositional information on nuclear waste slurries.
The online detection of a trace amount of an undesired solid phase within a crystal slurry can enable feedback control to improve product purity, decrease batch rejection, and increase process ...performance. Systems involving the production of one crystalline solid while suppressing the nucleation of a second solid are common, with applications to polymorphs, hydrates/solvates, chiral resolution, and byproducts. Several process analytical technologies (PATs) have already been established for system-specific detection of an undesired solid phase; this study adds to that PAT suite an image-based technique with greater generality and sensitivity than common tools such as Raman spectroscopy and focused beam reflectance measurement. In situ microscope images are analyzed with a convolutional neural network (CNN) to extract image features and classify cropped regions obtained by a sliding window as containing a single particle type or multiple particle types. As an experimental case study, the performance of the technique is evaluated using a system involving contamination of reactive crystallization of cephalexin with phenylglycine, the sparingly soluble byproduct in the enzymatic synthesis of cephalexin. A CNN, ResNet, was retrained for the classification task at hand and showed >98% accuracy on the test data, highlighting the distinct features of different crystal classes used as the basis of process monitoring.
The empirical model developed in the present work allows estimation of crystal size distributions from focused beam reflectance measurements (FBRM) of chord length distributions. The model is ...constructed from purposely varied crystal size distributions and the corresponding measured chord length distributions, which allows construction of a transformation matrix relating the two distributions. Experimental results show advantages over more complex phenomenological models, presumably because the transformation matrix implicitly embodies such phenomena. The ability of the model to address varying crystal concentration and selectively added size fractions is demonstrated with experimental results. Finally, the simplicity of the approach allows rapid (of order 0.1s) estimation of crystal size distributions from FBRM, which is a promising outcome for potentially using the approach in an on-line control scheme.
► A model relates focused beam reflectance measurements to crystal size distribution. ► The model is constructed empirically using known crystal size distributions. ► Experimental results demonstrate the practicality of the method. ► Two inversion methods estimating crystal size distribution are studied and applied.
The kinetics of cephalexin synthesis and hydrolysis of the activated acyl‐donor precursor phenylglycine methyl ester (PGME) were characterized under a broad range of substrate concentrations. A ...previously developed model by Youshko‐Svedas involving the formation of the acyl‐enzyme complex followed by binding of the nucleophilic β‐lactam donor does not fully estimate the maximum reaction yields for cephalexin synthesis at different concentrations using initial‐rate data. 7‐aminodesacetoxycephalosporanic acid (7‐ADCA) was discovered to be a potent inhibitor of cephalexin hydrolysis, which may account for the deviation from model predictions. Three kinetic models were compared for cephalexin synthesis, with the model incorporating competitive inhibition due to 7‐ADCA yielding the best fit. Additionally, the βF24A variant and Assemblase® did not exhibit significantly different kinetics for the synthesis of cephalexin compared to the wild‐type, for the concentration range evaluated and for both initial‐rate experiments and time‐course synthesis experiments. Lastly, a continuous stirred‐tank reactor for cephalexin synthesis was simulated using the model incorporating competitive inhibition by 7‐ADCA, with clear tradeoffs observed between productivity, fractional yield, and PGME conversion.
(Left)—Inhibition of substrate binding by 7‐aminodesacetoxycephalosporanic acid (7‐ADCA). (Right)—Models investigated for the synthesis of cephalexin catalyzed by penicillin G acylase (PGA) with parity plot of best fit model. All models include acyl‐enzyme formation and nucleophilic attack by 7‐ADCA or water. Models 2 and 3 include competitive inhibition by 7‐ADCA or separate binding of 7‐ADCA, respectively.
One of the challenges associated with multicomponent mixture analysis using chemometrics models is collecting calibration data. Depending upon the number of constituents, the size of the calibration ...set can be quite large. In some cases, the mixtures may contain numerous species, but only a small subset is central to the process for which quantification is being undertaken. For example, nuclear waste at the Hanford site contains a large number of radioactive and non-radioactive species, which complicates remediation efforts. However, only the concentrations of a few target species may need to be quantified in real time to facilitate operation of the cleanup process. In this paper, we introduce a preprocessing procedure that reduces the need for extensive model calibration. The preprocessing framework uses blind source separation (BSS) to identify the independent components in the mixture, which is followed by a correlation to classify them as either target species (part of the critical quality attributes that need to be measured during waste processing) or non-target species. The classification is used to preprocess the original mixture data: the signals of the target components are retained, while those of the non-target components are removed. Since the preprocessed spectra only contain the target components, the spectra-to-concentration regression model can be trained with a smaller calibration set. The approach is tested for Raman and infrared spectroscopy using simulated and experimental data sets based on simulant mixtures of nuclear waste.
•Reactive crystallization can be employed to increase the selectivity of ampicillin.•New pH-sensitive model predicts concentrations for non-pH-stat batch reactions.•Experiments confirm model ...predictions of better selectivity towards ampicillin.•Using Assemblase® selectivity is increased 50% by parallel reaction/crystallization.•Yield is improved 20% over the theoretical maximum not considering crystallization.
The enzyme penicillin G acylase (PGA) catalyzes the condensation of phenylglycine methyl ester (PGME) with 6-aminopenicillanic acid (6-APA) to form ampicillin. We improved the selectivity of ampicillin synthesis with PGA by running simultaneous reaction and crystallization. However, the enzyme also catalyzes two undesirable side reactions: the hydrolysis of PGME to phenylglycine and the hydrolysis of ampicillin to phenylglycine and 6-APA. We demonstrate that a fifty percent improvement in selectivity for ampicillin over phenylglycine is achieved by combining reaction and crystallization in batch at pH value of 6 with saturated 6-APA and equimolar PGME. The enhancement in selectivity is mainly attributed to the decreased rates of enzymatic ampicillin hydrolysis; however, the course of the pH value during the reaction also has an effect on enzyme activity that improved selectivity. In addition to showing experimental results, we developed a new kinetic process model that predicts the observed improvement. The new model accounts for the solubility limits of different species as functions of pH value as well as the large change in pH value at high conversion. Previous work does not account for changes in activity with conversion. The pH-dependent activity for the specific enzyme used in this system, Assemblase® from DSM-Sinochem, is well-realized by the model and generalization to other PGAs is possible within the model framework; the selectivity parameters α, β0, and γ for Assemblase® are compared to PGA from E. coli as evidence.
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