This paper examines the linkage between working capital management and corporate performance for a sample of non-financial UK companies. In contrast to previous studies, the findings provide strong ...support for an inverted U-shaped relation between investment in working capital and firm performance, which implies the existence of an optimal level of investment in working capital that balances costs and benefits and maximizes a firm's value. The results suggest that managers should avoid negative effects on firm performance because of lost sales and lost discounts for early payments or additional financing expenses. The paper also analyzes whether the optimal working capital level is sensitive to alternative measures of financial constraints. The findings show that this optimum is lower for firms more likely to be financially constrained.
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•Survival prediction of HCC patients is modeled in a real and high complex scenario.•Its complexity is due to a small dataset with heterogeneous and missing input data.•We propose a ...new cluster-based oversampling method to overcome these drawbacks.•Neural networks and logistic regression are applied in the classification stage.•Experimental results show that our method outperforms previous existing approaches.
Liver cancer is the sixth most frequently diagnosed cancer and, particularly, Hepatocellular Carcinoma (HCC) represents more than 90% of primary liver cancers. Clinicians assess each patient’s treatment on the basis of evidence-based medicine, which may not always apply to a specific patient, given the biological variability among individuals. Over the years, and for the particular case of Hepatocellular Carcinoma, some research studies have been developing strategies for assisting clinicians in decision making, using computational methods (e.g. machine learning techniques) to extract knowledge from the clinical data. However, these studies have some limitations that have not yet been addressed: some do not focus entirely on Hepatocellular Carcinoma patients, others have strict application boundaries, and none considers the heterogeneity between patients nor the presence of missing data, a common drawback in healthcare contexts. In this work, a real complex Hepatocellular Carcinoma database composed of heterogeneous clinical features is studied. We propose a new cluster-based oversampling approach robust to small and imbalanced datasets, which accounts for the heterogeneity of patients with Hepatocellular Carcinoma. The preprocessing procedures of this work are based on data imputation considering appropriate distance metrics for both heterogeneous and missing data (HEOM) and clustering studies to assess the underlying patient groups in the studied dataset (K-means). The final approach is applied in order to diminish the impact of underlying patient profiles with reduced sizes on survival prediction. It is based on K-means clustering and the SMOTE algorithm to build a representative dataset and use it as training example for different machine learning procedures (logistic regression and neural networks). The results are evaluated in terms of survival prediction and compared across baseline approaches that do not consider clustering and/or oversampling using the Friedman rank test. Our proposed methodology coupled with neural networks outperformed all others, suggesting an improvement over the classical approaches currently used in Hepatocellular Carcinoma prediction models.
•FPH are promising alternative emulsifiers to stabilize fish oil-in-water emulsions.•Sardine hydrolysates with low DH, 3% and 4%, led to more physically stable emulsions.•The previous emulsions were ...also more oxidatively stable.•Small-spotted catshark hydrolysates showed poor emulsifying properties.
The emulsifying and antioxidant properties of fish protein hydrolysates (FPH) for the physical and oxidative stabilization of 5% (by weight) fish oil-in-water emulsions were investigated. Muscle proteins from sardine (Sardina pilchardus) and small-spotted catshark (Scyliorhinus canicula) were hydrolyzed to degrees of hydrolysis (DH) of 3-4-5-6% with subtilisin. Sardine hydrolysates with low DH, 3% and 4%, presented the most effective peptides to physically stabilize emulsions with smaller droplet size. This implied more protein adsorbed at the interface to act as physical barrier against prooxidants. This fact might also be responsible for the higher oxidative stability of these emulsions, as shown by their lowest peroxide value and concentration of volatiles such as 1-penten-3-one and 1-penten-3-ol. Among the hydrolysates prepared from small-spotted catshark only the hydrolysate with DH 3% yielded a physically stable emulsion with low concentration of unsaturated aldehydes. These results show the potential of FPH as alternative protein emulsifiers for the production of oxidatively stable fish oil-in-water emulsions.
The objective of this study was to investigate the influence of casein (0.3% w/w) and phospholipid (0.5% w/w) emulsifier combinations on the physical and oxidative stability of 10% fish oil-in-water ...emulsions at pH 7. For that purpose, three phospholipids were evaluated, namely, lecithin (LC), phosphatidylcholine (PC), and phosphatidylethanolamine (PE). The emulsion stabilized with LC showed the best physical stability having the most negative zeta potential and the lowest mean droplet size. In addition, this emulsion was also the least oxidized in terms of peroxide value and concentration of the volatile oxidation product 1-penten-3-ol. This finding is not explained by the antioxidant activity of LC because it showed similar DPPH scavenging activity and lower metal chelating activity than the other phospholipids. Therefore, these results suggested that other factors such as the combination of casein and lecithin, which could result in a favorable structure and thickness of the interfacial layer, prevented lipid oxidation in this emulsion.
Collinearity refers to the non independence of predictor variables, usually in a regression-type analysis. It is a common feature of any descriptive ecological data set and can be a problem for ...parameter estimation because it inflates the variance of regression parameters and hence potentially leads to the wrong identification of relevant predictors in a statistical model. Collinearity is a severe problem when a model is trained on data from one region or time, and predicted to another with a different or unknown structure of collinearity. To demonstrate the reach of the problem of collinearity in ecology, we show how relationships among predictors differ between biomes, change over spatial scales and through time. Across disciplines, different approaches to addressing collinearity problems have been developed, ranging from clustering of predictors, threshold-based pre-selection, through latent variable methods, to shrinkage and regularisation. Using simulated data with five predictor-response relationships of increasing complexity and eight levels of collinearity we compared ways to address collinearity with standard multiple regression and machine-learning approaches. We assessed the performance of each approach by testing its impact on prediction to new data. In the extreme, we tested whether the methods were able to identify the true underlying relationship in a training dataset with strong collinearity by evaluating its performance on a test dataset without any collinearity. We found that methods specifically designed for collinearity, such as latent variable methods and tree based models, did not outperform the traditional GLM and threshold-based pre-selection. Our results highlight the value of GLM in combination with penalised methods (particularly ridge) and threshold-based pre-selection when omitted variables are considered in the final interpretation. However, all approaches tested yielded degraded predictions under change in collinearity structure and the ‘ folk lore ’ -thresholds of correlation coefficients between predictor variables of |r| > 0.7 was an appropriate indicator for when collinearity begins to severely distort model estimation and subsequent prediction. The use of ecological understanding of the system in pre-analysis variable selection and the choice of the least sensitive statistical approaches reduce the problems of collinearity, but cannot ultimately solve them.
Beyond species loss Valiente-Banuet, Alfonso; Aizen, Marcelo A.; Alcántara, Julio M. ...
Functional ecology,
March 2015, Letnik:
29, Številka:
3
Journal Article
Recenzirano
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Summary
The effects of the present biodiversity crisis have been largely focused on the loss of species. However, a missed component of biodiversity loss that often accompanies or even precedes ...species disappearance is the extinction of ecological interactions.
Here, we propose a novel model that (i) relates the diversity of both species and interactions along a gradient of environmental deterioration and (ii) explores how the rate of loss of ecological functions, and consequently of ecosystem services, can be accelerated or restrained depending on how the rate of species loss covaries with the rate of interactions loss.
We find that the loss of species and interactions are decoupled, such that ecological interactions are often lost at a higher rate. This implies that the loss of ecological interactions may occur well before species disappearance, affecting species functionality and ecosystems services at a faster rate than species extinctions. We provide a number of empirical case studies illustrating these points.
Our approach emphasizes the importance of focusing on species interactions as the major biodiversity component from which the ‘health’ of ecosystems depends.
Lay Summary
This paper studies the effect of growth opportunities, financial constraints and financial distress on the speed of adjustment of small and medium-sized enterprises (SMEs) to their target cash ...holdings. We use a sample of Spanish SMEs from the period of 1998 to 2012. The results support the existence of a target cash holding level to which small firms attempt to converge. Additionally, consistent with the precautionary motive for cash holdings, the results show that SMEs with greater growth opportunities adjust more quickly to their target cash holding level to preserve their financial flexibility and to be able to take advantage of profitable investment opportunities when they arise. Moreover, for SMEs in financial difficulties, the adjustment speed of cash is higher to avoid financial distress costs. Finally, we observe a faster speed of adjustment for cash holding in the crisis period for all firms, as a possible response to the credit restrictions faced by SMEs.
Oxidation and oxidative stability in emulsions Ghelichi, Sakhi; Hajfathalian, Mona; Yesiltas, Betül ...
Comprehensive reviews in food science and food safety,
20/May , Letnik:
22, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Emulsions are implemented in the fabrication of a wide array of foods and therefore are of great importance in food science. However, the application of emulsions in food production is restricted by ...two main obstacles, that is, physical and oxidative stability. The former has been comprehensively reviewed somewhere else, but our literature review indicated that there is a prominent ground for reviewing the latter across all kinds of emulsions. Therefore, the present study was formulated in order to review oxidation and oxidative stability in emulsions. In doing so, different measures to render oxidative stability to emulsions are reviewed after introducing lipid oxidation reactions and methods to measure lipid oxidation. These strategies are scrutinized in four main categories, namely storage conditions, emulsifiers, optimization of production methods, and antioxidants. Afterward, oxidation in all types of emulsions, including conventional ones (oil‐in‐water and water‐in‐oil) and uncommon emulsions in food production (oil‐in‐oil), is reviewed. Furthermore, the oxidation and oxidative stability of multiple emulsions, nanoemulsions, and Pickering emulsions are taken into account. Finally, oxidative processes across different parent and food emulsions were explained taking a comparative approach.
Dietary antioxidants are an important preservative in food and have been suggested to help in disease prevention. With consumer demands for less synthetic and safer additives in food products, the ...food industry is searching for antioxidants that can be marketed as natural. Peptides derived from natural proteins show promise, as they are generally regarded as safe and potentially contain other beneficial bioactivities. Antioxidative peptides are usually obtained by testing various peptides derived from hydrolysis of proteins by a selection of proteases. This slow and cumbersome trial-and-error approach to identify antioxidative peptides has increased interest in developing computational approaches for prediction of antioxidant activity and thereby reduce laboratory work. A few antioxidant predictors exist, however, no tool predicting the antioxidative properties of peptides is, to the best of our knowledge, currently available as a web-server. We here present the AnOxPePred tool and web-server ( http://services.bioinformatics.dtu.dk/service.php?AnOxPePred-1.0 ) that uses deep learning to predict the antioxidant properties of peptides. Our model was trained on a curated dataset consisting of experimentally-tested antioxidant and non-antioxidant peptides. For a variety of metrics our method displays a prediction performance better than a k-NN sequence identity-based approach. Furthermore, the developed tool will be a good benchmark for future predictors of antioxidant peptides.
This paper analyzes the relation between working capital management and profitability for small and medium-sized enterprises (SMEs) by controlling for unobservable heterogeneity and possible ...endogeneity. Unlike previous studies, we examine a non-linear relation between these two variables. Our results show that there is a nonmonotonic (concave) relationship between working capital level and firm profitability, which indicates that SMEs have an optimal working capital level that maximizes their profitability. In addition, a robustness check of our results confirms that firms' profitability decreases as they move away from their optimal level.
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