Miracle-dz/UniFAR-FTUs huggingface dataset:
The nutritional value of leaves of selected berry species

Although the medicinal properties of berry fruit are well known, there is relatively little information available concerning the applications of other parts of berry plants. Thus, in this study we determined the nutritional value of the leaves of selected berry species and their possible application in health promoting diets. The levels of nutrients, and macro- and microelements in the leaves of four species collected from allotment gardens in the city of Szczecin, Poland (53°26′17″ N, 14°32′32″ E; altitude 7 m a.s.l.) were identified: raspberry (Rubus idaeus L.), blackberry (Rubus fruticosus L.), chokeberry (Aronia melanocarpa L.), and sea buckthorn (Hippophae rhamnoides L.). Sea buckthorn leaves were the richest source of protein, raspberry leaves had the highest levels of lipids, and the leaves of all four species studied were a rich source of crude fibre and dietary fibre fractions. Desirable Ca:P and Na:K ratios indicated their potential as a good source of minerals essential to bone formation and the treatment of hypertension. Sea buckthorn leaves contained high but also safe Fe levels (within recommended WHO limits) and, therefore, may become an alternative rich source of this element.
Convolutional Neural Network-based Automatic Prediction of Judgments of the European Court of Human Rights

In the past few years, predictive modelling has brought revo-lutionary changes in the way various industries function. Advancements in the areas of Deep Learning (DL) and Natural Language Processing (NLP) have made their application to diﬀerent problem areas highly promising. In the legal domain, positive results have been obtained in predicting the judgements of various Courts of diﬀerent countries using DL and NLP. However, not much research has been carried out in the area of legal judgement forecasting for the European Court of Human Rights (ECHR). The models designed in the previous research employ only one Machine Learning algorithm namely a Support Vector Machine (SVM) to solve such problem. This study applies DL and NLP to the problem of automatic prediction of judgements for ECHR. Extensive experiments are conducted which compare the performance of models trained on SVM with linear kernel as part of previous research (Medvedeva, Vols & Wieling, 2018) with the models trained on Convolutional Neural Networks (CNN) as proposed in this study. To implement this, state-of-the-art NLP techniques are applied to the text data. Moreover, pre-trained and custom trained Word Embedding text representations are considered. Statistical tests are performed to gather suﬃcient statistical evidence to determine which algorithm performs better at providing a solution to this problem. Based on the results obtained, it is established that overall, CNN models outperform SVM models as the former achieves an average accuracy of 82% whereas the latter achieves 75%. Speciﬁcally, CNN models for four Articles out of nine achieve statistically signiﬁcant higher accuracy than SVM models.
University of Southern Denmark Dimensional testing for reverse k-nearest neighbor search

Given a query object q, reverse k-nearest neighbor (RkNN) search aims to locate those objects of the database that have q among their k-nearest neighbors. In this paper, we propose an approximation method for solving RkNN queries, where the pruning operations and termination tests are guided by a characterization of the intrinsic dimensionality of the data. The method can accommodate any index structure supporting incremental (forward) nearest-neighbor search for the generation and verification of candidates, while avoiding impractically-high preprocessing costs. We also provide experimental evidence that our method significantly outperforms its competitors in terms of the tradeoff between execution time and the quality of the approximation. Our approach thus addresses many of the scalability issues surrounding the use of previous methods in data mining.
Parallel Gaussian Processes for Optimal Sensor Placement

Optimal sensor placement is of vital importance to many complex systems. However, despite its importance, existing algorithms that optimize sensor placements have scalability issues and therefore do not work with the big data generated by computational simulations. Instead, they use small-scale data collected by existing sensors, which is expensive and leads to imprecise results for large domains. This thesis attempts to provide a solution by parallelizing computations of a Gaussian process (GP) based sensor placement algorithm. By doing so, it provides unprecedented use of GP’s with big data to solve this important problem in spatial statistics. As an example, sensor placements are optimized for part of the test-side around the London South Bank University. Instead of running the algorithm for the whole domain, our approach only considers relevant sub-domains of the test-side that were obtained by Fluidity’s native domain decomposition. For computations on these, a mixture of multi-processing and multi-threading is used to fully utilize all available resources. The results are validated by comparison of the pollution levels predicted by the posterior GP to the real pollution levels, and measurement of performance in data assimilation. According to both measures, our algorithm leads to near-perfect sensor placements. For instance, for one sub-domain, our mean estimation is off by only 6.15e−3 while random placement is off by over 1.93.
Extending an international lexical framework for Asian languages, the case of Mandarin, Taiwanese, Cantonese, Bangla and Malay

This paper describes the experiments we are currently conducing at Academia Sinica for extending a proposed international standard for lexical framework (Lexical Markup Framework) and shows the relevance of this work for the Digital Archives Program. Although this framework is very rich and powerful, it originally has been developed for European languages. Hence some important extensions are needed to ensure the robustness of this framework to cope with Asian languages. The issues addressed include: (i) the need for derivational morphology, (ii) the interface between morphology, syntax and semantics with the problem of classifiers, and (iii) representational issues with the richness of the writing systems in Asian languages. In this paper we propose prospective solutions for these issues and explain how lexicon meta-models are useful for digital archives.
Cheap But Flighty: How Global Imbalances Create Financial Fragility

Can a wealth shift to emerging countries explain instability in developed countries? Investors exposed to political risk seek safety in countries with better property right protection. This induces private intermediaries to offer safety via inexpensive demandable debt, and increases lending into marginal projects. Because safety conscious foreigners escape any risk by running also in some good states, cheap foreign funding leads to larger and more frequent runs. Beyond some scale, foreign runs also induce domestic runs in order to avoid dilution. When excess liquidation causes social losses, a domestic planner may limit the scale of foreign inflows or credit volume.
A DEEP LEARNING FRAMEWORK FOR ROADS NETWORK DAMAGE ASSESSMENT USING POST-EARTHQUAKE LIDAR DATA

Abstract. Roads network are the most important parts of urban infrastructures, which can cause difficulty to the city whenever they undergo a problem. This paper aims to provide and implement a deep learning-based method to determine the status of the streets network after an earthquake using LiDAR point cloud. The proposed framework composes of three main phases: (1) Deep features of LiDAR data are extracted using a Convolutional Neural Network (CNN). (2) The extracted features are used in a multilayer perceptron (MLP) neural network in which debris areas inside the road network are detected. (3) The amount of debris in each road is applied to damage index for classifying the road segments into blocked or un-blocked. To evaluate the efficiency of the proposed framework, LiDAR point cloud of the Port-au-Prince, Haiti after the 2010 Haiti earthquake was used. The overall accuracy of more than 97% proved the high performance of this framework for debris detection. Moreover, analyzing damage assessment of 37 road segments based on the detected debris and comparing to a visually generated damaged map, 31 of the road segments were correctly labelled as either blocked or un-blocked.
Using Involvement Theory to Examine the Relationship between Undergraduate Participation in Extracurricular Activities and Leadership Development

This study examined the relationship between extracurricular involvement and leadership outcomes among traditional-age college seniors in the College of Agriculture and Life Sciences at Iowa State University. We collected data related to quantitative (i.e., how much time a student spends on an activity) and qualitative (i.e., how focused the student is on the activity) aspects of involvement in extracurricular organizations. We measured leadership, as an outcome, using the individual values scale of the Socially Responsible Leadership Scale (SRLS-R2). The number of clubs in which a student participated and served as an officer was associated with higher leadership scores. We identified a threshold of involvement that suggests the optimum number of clubs or organizations to be actively involved in is three to four.
Occupational identity and culture: the case of Michelin-starred chefs

Purpose The purpose of this study is to conceptualise how the occupational identity and culture of chefs is constructed and maintained through both work and social interaction. Design/methodology/approach The study follows a qualitative interpretivist approach; in total, 54 unstructured, in-depth, face-to-face interviews were conducted with Michelin-starred chefs in Great Britain and Ireland. Findings Drawing upon the fieldwork, fresh insights into the social structures and processes which underpin the creation and maintenance of the occupational identity and culture of chefs are revealed in the chefs’ own words. Research limitations/implications This study generates empirical data that inform contemporary debates about the role of work in identity formation with particular emphasis on the induction–socialisation process. In addition, the findings of this study suggest that identity and culture are interrelated in the sense that the cultural components of an occupational culture operate to reinforce a sense of identity among its occupational members. Practical implications The findings suggest that Michelin-starred chefs have a strong occupational identity and culture. Strict rules and discipline are often used in kitchen brigades as a means of monitoring quality and maintaining the high standards of performance. The occupational socialisation of new members is a long and painful process that very often exceeds the limits of banter, and it is analogous to the military induction. The phenomenon of bullying and violence in commercial kitchens is identified as an unacceptable behaviour that needs to be eliminated. This can be achieved with changes in the education and training of the young chefs and the strict enforcement of the anti-bullying policies. Originality/value The understanding of chefs’ occupational identity and culture is critical for successful hospitality operations; nevertheless, this is an under-researched area. This study is unique in terms of scale and depth; it is expected to provide useful insights in both theoretical and practical perspective, regarding the formation of chefs’ identity and culture in organisational settings.
Probing the origin of quasi-periodic oscillations: the short-time-scale evolution of phase lags in GRS 1915+105

We present a model-independent analysis of the short-time-scale energy dependence of low-frequency quasi-periodic oscillations (QPOs) in the X-ray flux of GRS 1915+105. The QPO frequency in this source has previously been observed to depend on photon energy, with the frequency increasing with energy for observations with a high (≳2 Hz) QPO frequency, and decreasing with energy for observations with a low (≲2 Hz) QPO frequency. As this observed energy dependence is currently unexplained, we investigate if it is intrinsic to the QPO mechanism by tracking phase lags on (sub)second time-scales. We find that the phase lag between two broad energy bands systematically increases for 5–10 QPO cycles, after which the QPO becomes decoherent, the phase lag resets and the pattern repeats. This shows that the band with the higher QPO frequency is running away from the other band on short time-scales, providing strong evidence that the energy dependence of the QPO frequency is intrinsic. We also find that the faster the QPO decoheres, the faster the phase lag increases, suggesting that the intrinsic frequency difference contributes to the decoherence of the QPO. We interpret our results within a simple geometric QPO model, where different radii in the inner accretion flow experience Lense–Thirring precession at different frequencies, causing the decoherence of the oscillation. By varying the spectral shape of the inner accretion flow as a function of radius, we are able to qualitatively explain the energy-dependent behaviour of both QPO frequency and phase lag.
Young athletes' perceptions of a psychological preparation intervention

This article reports a study concerning a psychological preparation intervention in sport environment. The method implemented included performance profiling and goal setting. The purpose of this study is to evaluate the intervention from the young athletes’ point of view. The research task was to analyze how the athletes perceived the intervention, its benefits and weaknesses. The questionnaire data were obtained alongside the intervention case study among 61 young athletes from a sport academy in northern Finland. Their answers were analyzed with the qualitative content analysis. For some of the athletes, the intervention worked as planned increasing their self-knowledge, motivation, concentration, and personal training, while others did not perceive the intervention very meaningful of beneficial. Based on the young athletes’ experiences, suggestions for future psychological preparation interventions are presented.
Estimation of Random Accuracy and its Use in Validation of Predictive Quality of Classification Models within Predictive Challenges

Shortcomings of the correlation coefficient (Pearson's) as a measure for estimating and calculating the accuracy of predictive model properties are analysed. Here we discuss two such cases that can often occur in the application of the model in predicting properties of a new external set of compounds. The first problem in using the correlation coefficient is its insensitivity to the systemic error that must be expected in predicting properties of a novel external set of compounds, which is not a random sample selected from the training set. The second problem is that an external set can be arbitrarily large or small and have an arbitrary and uneven distribution of the measured value of the target variable, whose values are not known in advance. In these conditions, the correlation coefficient can be an overoptimistic measure of agreement of predicted values with the corresponding experimental values and can lead to a highly optimistic conclusion about the predictive ability of the model. Due to these shortcomings of the correlation coefficient, the use of standard error (root-mean-square-error) of prediction is suggested as a better quality measure of predictive capabilities of a model. In the case of classification models, the use of the difference between the real accuracy and the most probable random accuracy of the model shows very good characteristics in ranking different models according to predictive quality, having at the same time an obvious interpretation.
Measurements of nitric oxide and ammonia soil fluxes from a wet savanna ecosystem site in West Africa during the DACCIWA field campaign

Abstract. Biogenic fluxes from soil at a local and regional scale are crucial to study air pollution and climate. Here we present field measurements of soil fluxes of nitric oxide (NO) and ammonia (NH3) observed over four different land cover types, i.e. bare soil, grassland, maize field, and forest, at an inland rural site in Benin, West Africa, during the DACCIWA field campaign in June and July 2016. At the regional scale, urbanization and a massive growth in population in West Africa have been causing a strong increase in anthropogenic emissions. Anthropogenic pollutants are transported inland and northward from the megacities located on the coast, where the reaction with biogenic emissions may lead to enhanced ozone production outside urban areas, as well as secondary organic aerosol formation, with detrimental effects on humans, animals, natural vegetation, and crops. We observe NO fluxes up to 48.05 ngN m−2 s−1. NO fluxes averaged over all land cover types are 4.79±5.59 ngN m−2 s−1, and maximum soil emissions of NO are recorded over bare soil. NH3 is dominated by deposition for all land cover types. NH3 fluxes range between −6.59 and 4.96 ngN m−2 s−1. NH3 fluxes averaged over all land cover types are -0.91±1.27 ngN m−2 s−1, and maximum NH3 deposition is measured over bare soil. The observations show high spatial variability even for the same soil type, same day, and same meteorological conditions. We compare point daytime average measurements of NO emissions recorded during the field campaign with those simulated by GEOS-Chem (Goddard Earth Observing System Chemistry Model) for the same site and find good agreement. In an attempt to quantify NO emissions at the regional and national scale, we also provide a tentative estimate of total NO emissions for the entire country of Benin for the month of July using two distinct methods: upscaling point measurements and using the GEOS-Chem model. The two methods give similar results: 1.17±0.6 and 1.44 GgN month−1, respectively. Total NH3 deposition estimated by upscaling point measurements for the month of July is 0.21 GgN month−1.
Quasi-Particles, Thermodynamic Consistency, and the Gap Equation

The thermodynamic potentials of superconducting electrons are derived by means of the Bogoliubov-Valatin formalism. The thermodynamic potentials can be obtained by computing the free energy of a gas of quasi-particles, whose energy spectrum is conditional on the gap function. However, the nontrivial dependence of the gap on the temperature jeopardises the validity of the standard thermodynamic relations. In this article, it is shown how the thermodynamic consistency (i.e., the validity of the Maxwell relations) is recovered, and the correction terms to the quasi-particles potentials are computed. It is shown that the Bogoliubov-Valatin transformation avoids the problem of the thermodynamic consistency of the quasi-particle approach; in fact, the correct identification of the variables, which are associated with the quasi-particles, leads to a precise calculation of the quasi-particles vacuum energy and of the dependence of the chemical potential on the electron density. The stationarity condition for the grand potential coincides with the gap equation, which guarantees the thermodynamic consistency. The expressions of various thermodynamic potentials, as functions of the variables, are produced in the low temperature limit; as a final check, a rederivation of the condensation energy is presented.
Does directors' and officers' liability insurance affect firms' investment decisions?

The author examines directors’ and officers’ (D&O) insurance coverage affects a firm’s investment decisions. Once managers mitigate their personal legal liability through D&O insurance coverage, their behaviors will be more opportunistic. The author finds that managers are more likely to over-invest when their personal legal liability is covered by abnormally high level of D&O insurance coverage. The author also finds that over-investing firms with excess D&O insurance coverage appear to have poor investment decisions that result in inferior subsequent performance. The author further finds that managers with excess D&O insurance coverage tend to over-invest in R&D. The authors’ results are consistent with the argument that the agency conflicts are aggravated by excess D&O insurance coverage which provides the managements with more room to pursuit private personal benefits via inefficient investments decisions.
Bioactivity of ethanol extracts from Eucalyptus bosistoana F. Muell. heartwood

Abstract: Variability in bioactivity and chemical composition of Eucalyptus bosistoana F. Muell. heartwood extracts between individual trees from two different sites were investigated. Combining the results of fungal assays and quantitative gas chromatography (GC) of the extracts allowed the investigation of bioactive compounds. The bioactivity of extracts was assessed against white rot (Trametes versicolor [L.] Lloyd) and brown rot (Coniophora cerebella Pers.). Ethanol extracts from E. bosistoana heartwood were less effective on the white rot than against the brown rot. Variability in the bioactivity of extracts against the two fungi was observed between the trees. A site effect in the bioactivity was found for the white rot but not the brown rot. Bioactivity of the extracts against the white rot was not correlated to that against the brown rot. The absence of a relationship between of effects of the extracts on the relative growth rates of the white rot and the brown rot indicated that the two fungi were affected by different compounds. Thirty two compounds were quantified in E. bosistoana ethanol extracts by GC, of which six (benzoic acid, hexadecanoic acid, 1,5-dihdroxy-12-methoxy-3,3-dimethyl-3,4-dihydro-1H-anthra[2,3-c]pyran-6,11-dione, octadecanoic acid, polyphenol and beta-sitosterol) were identified. Significant variability in eight compounds was found between the two sites. Multivariate (PLSR) analysis identified compounds at the retention times 10.2 and 11.5 min (hexadecanoic acid) to be most related to the bioactivity of the E. bosistoana heartwood extracts against white rot and brown rot.
Effect of Spillovers on Foreign Versus Domestic Industry Leadership in a Developing Economy

An often contentious issue is how spillovers affect foreign versus domestic industry leadership in a developing economy, for instance, whether policies favour domestic firms. To address such issues it is important to understand the baseline effect of spillovers on industry leadership, which I focus on. I develop a formal model that compares the effect of different types of spillovers on industry leadership. I find that spillovers driven by absorptive capacity, versus by demonstration effects, are more likely contentious as: domestic leadership is higher; outcomes are more sensitive to host country policies; and the firm dynamics, such as entry and exit, due to the spillovers are harder to observe. Thus baseline expectations of which firms lead an industry depend on the types of spillovers.