Miracle-dz/UniFAR-FTUs huggingface dataset:
Genetic Deep Learning for Lung Cancer Screening

Convolutional neural networks (CNNs) have shown great promise in improving computer aided detection (CADe). From classifying tumors found via mammography as benign or malignant to automated detection of colorectal polyps in CT colonography, these advances have helped reduce the need for further evaluation with invasive testing and prevent errors from missed diagnoses by acting as a second observer in today's fast paced and high volume clinical environment. CADe methods have become faster and more precise thanks to innovations in deep learning over the past several years. With advancements such as the inception module and utilization of residual connections, the approach to designing CNN architectures has become an art. It is customary to use proven models and fine tune them for particular tasks given a dataset, often requiring tedious work. We investigated using a genetic algorithm (GA) to conduct a neural architectural search (NAS) to generate a novel CNN architecture to find early stage lung cancer in chest x-rays (CXR). Using a dataset of over twelve thousand biopsy proven cases of lung cancer, the trained classification model achieved an accuracy of 97.15% with a PPV of 99.88% and a NPV of 94.81%, beating models such as Inception-V3 and ResNet-152 while simultaneously reducing the number of parameters a factor of 4 and 14, respectively.
Derivation of parameters of Y-Z power-law relation from raindrop size distribution measurements and its application in the calculation of rain attenuation from radar reflectivity factor measurements

The work reported herein empirically derived the coefficients of the power-law relation between the specific attenuation Y and each of two other quantities: the radar reflectivity factor Z and the rainfall rate R. The derivation was accomplished using raindrop size distributions (DSDs) measured in Montreal and Toronto using the precipitation occurrence sensor system (POSS) and a Joss-Waldvogel disdrometer (JWD). The specific attenuation was calculated for both spherical and oblate spheroidal raindrops. Prior to doing so, the effects of inaccuracies in small drop detection by the two systems on the resulting Y-Z and Y-R relations were examined. In computing the relations, the influence of grouping the DSDs according to the corresponding values of Z was assessed. The results from the two sites were then combined in a regression analysis to determine the coefficients of the power-law expressions. The final expressions were used to calculate the probability distribution of rain attenuation over several path lengths at 30 GHz. Conclusions that can be drawn from this work include that (i) the uncertainties in the measurements of small drops do not appear to be critical to the derived relations for some frequencies considered in this work, (ii) in computing rain attenuation estimates from radar reflectivity factors, different criteria for grouping the reflectivity factor measurements can be adopted without changing the statistics of the corresponding attenuation estimates, (iii) differences, which are the smallest for frequencies around 20-30 GHz, are observed in the coefficients derived from the measured DSDs compared with those recommended by the ITU-R, and (iv) the attenuation statistics at 30 GHz computed by applying the Y-Z power-law expression are resistant to spatial averaging.
non-newsworthy posts in building a learning-based credibility assessment lead to poorer quality of a prediction

Social media has received overwhelming interest globally from their functions to post users contents, some of which has not been validated and may contain false or misleading content. There have been several studies to assess the credibility of social media posts to tackle such problem. Most existing online assessment systems evaluated the credibility of every post. This practice may be suboptimal. Many contents are not newsworthy (e.g., selfies and personal opinions, which are irrelevant to credibility notion). Assigning credibility score to a non-newsworthy post may confuse users. In addition, a recent study has shown that the inclusion of such irrelevant non-newsworthy data deteriorates the quality of credibility assessment. Therefore, identification and exclusion of non-newsworthy posts are crucial to reliable credibility assessment. This article investigates how different types of post features are effective for automatic non-newsworthiness removal. Three post features, i.e., text, topic, and social features, were evaluated with two classification methods which were machine learning and cosine similarity. Our findings reveal the essence of social features and its combination for non-newsworthiness identification.
The effect of light acclimation of single leaves on whole tree growth and competition - an application of the tree growth model ALMIS

L'Aulne noir (Alnus glutinosa L. (Gaertn.)) est une espece a croissance rapide exigeante en lumiere. Elle est repandue, mais toujours localisee aux habitats humides. Comme il n'est pas possible de differencier dans la canopee les feuilles d'ombre de celles de lumiere, la question se pose de savoir si ses caracteristiques photosynthetiques peuvent contribuer a la faible competitivite de l'Aulne. Un modele de croissance a fonction structurelle (ALMIS), base sur l'approche orientee objet, a ete developpe et parametrise a partir des donnees resultant d'une investigation extensive dans une foret d'aulne dans le Nord de l'Allemagne. La structure du modele de base est decrite, specialement pour la partie dynamique du carbone. ALMIS a ete utilise pour etudier les effets de l'adaptation des feuilles a la lumiere sur la croissance globale et la competition. Differentes conditions photosynthetiques ont ete simulees pour la croissance, soit en condition isolee, soit en condition de competition entre elles. Dans le cas de la croissance en condition isolee pour une longue periode, le modele d'arbre avec uniquement des feuilles d'ombre accumule moins de biomasse totale que ceux avec uniquement des feuilles de lumiere. Mais un arbre qui aurait la capacite d'adaptation de ses feuilles aux conditions de lumiere au sein de sa canopee aurait une meilleure croissance. La competition entre arbre ameliore les avantages de l'adaptation des feuilles vis-a-vis de la croissance globale de la plante.
Cooperative Coevolutionary Models for the Multi-Depot Vehicle Routing Problem

The Multi-Depot Vehicle Routing Problem (MDVRP) is an important variant of the classical Vehicle Routing Problem (VRP), where the customers can be served from a number of depots. This work introduces a cooperative coevolutionary algorithm to minimize the total route cost of the MDVRP. Coevolutionary algorithms are inspired by the simultaneous evolution process involving two or more species. In this approach, problems can be decomposed into smaller subproblems and each part is evolved separately. After that, those parts are combined to create a complete solution to the original problem. This work presents a problem decomposition approach for the MDVRP in which each subproblem becomes a single depot VRP and evolves independently in its domain space. Customers are distributed among the depots based on their distance from the depots and their distance from their closest neighbor. A population is associated with each depot where the individuals represent partial solutions to the problem, that is, sets of routes over customers assigned to the corresponding depot. The fitness of a partial solution depends on its ability to cooperate with partial solutions from other populations to form a complete solution to the MDVRP. As the problem is decomposed and each part evolves separately, this approach is strongly suitable to parallel environments. Therefore, a parallel and asynchronous evolution strategy environment with a variable length genotype coupled with local search operators is proposed. A large number of experiments have been conducted to assess the performance of these approaches and our model is compared with the best heuristics proposed for the MDVRP. Two versions of our method are presented. The first version is developed considering a CPU multithreading environment. The results suggest our coevolutionary algorithm produces competitive solutions when compared with the best known solutions, even improving some of them. Besides, it is faster than the best method reported in the literature. The benefit of our approach comes from its ability to decompose complex problems into simpler subproblems and evolve solutions to the subproblems in parallel. The second version of our method is developed using GPU computing. It is able to produce competitive solutions in less time when compared to the CPU version only. The average speedup is equal to 8 times over all benchmark instances. Finally, the results of both environments suggest the proposed coevolutionary algorithms in a parallel environment are able to produce high-quality solutions to the MDVRP in low computational time. Key-words: Multi-depot vehicle routing problem. Vehicle routing. Cooperative coevolutionary algorithm. Evolution strategies. GPU computing. GPGPU.
The Environmental cost of Skiing in the Desert? Evidence from Cointegration with unknown Structural breaks in UAE

The present study explores the relationship between economic growth, electricity consumption, urbanization and environmental degradation in case of United Arab Emirates. The study covers the quarter frequency data over the period of 1975-2011. We have applied the ARDL bounds testing approach to examine the long run relationship between the variables in the presence of structural breaks. The VECM Granger causality is applied to investigate the direction of causal relationship between the variables. Our empirical exercise reported the existence of cointegration among the series in case of United Arab Emirates. Further, we found an inverted U-shaped relationship between economic growth and CO2 emissions i.e. economic growth raises energy emissions initially and declines it after a threshold point of income per capita (EKC exists). Electricity consumption declines CO2 emissions. The relationship between urbanization and CO2 emissions is positive. Exports seem to improve the environmental quality by lowering CO2 emissions in case of UAE. The causality analysis validates the feedback effect between CO2 emissions and electricity consumption. Economic growth and urbanization Granger cause CO2 emissions.
Importance of Early Life Stage Limitations on Recovering Populations of Leptosyne gigantea, San Miguel Island, California

Abstract. Plant communities dominated by Leptosyne gigantea (tickseed, formerly giant coreopsis) are distributed widely across the California Islands and provide critical habitat for understory plants and vertebrates, especially in landscapes where trees are absent. Leptosyne gigantea populations were severely impacted by nonnative herbivores and by grazing and ranching practices during the last century. Although these impacts have been absent from most of the islands for over 2 decades, extensive spatial heterogeneity exists both within and across the islands in relation to population growth. Many sites support very dense stands of L. gigantea that established postgrazing; whereas others, particularly on Santa Barbara Island, have experienced relatively minimal increases in L. gigantea abundance and are still dominated by alien annual grasses. To determine the factors that most affect L. gigantea establishment and survival, I conducted seed amendment experiments across populations of variable density and age structure on San Miguel Island. These experiments tested the relative effects of seed predation, seed density, microhabitat conditions, stand density, and competition on germination and seedling survival. Postdispersal seed predation by deer mice reduced germination rates only in the highest density stands. Reduced soil moisture and interspecific competition with alien annual grasses had the strongest negative effects on both germination and seedling survival. The results suggest extreme spatial variability in regulating factors for L. gigantea that include rainfall, the abundance of annual grasses, consumer abundance, and intraspecific density dependence. The presence or absence of these influences on existing site conditions will determine succession following loss of the oldest-aged stands, which will likely occur soon.
Randomization: Techniques and Software-aided Implementation in Medical Studies

In this methodology review we have briefly discussed both the theory and practice of randomization in clinical trials. Necessity, principals, definitions and classifications along with the current contraversies are presented. Practical notes on the methods and procedures of randomization in clinical research with with particular focus on sfotware+aided randomixation is provided and the review is ended by a section on reporting the randomization in clinical trials.
The Results of the KSTAR Superconducting Coil Test

The KSTAR (Korea Superconducting Tokamak Advanced Research) device is under construction using superconducting (SC) coils for long pulse operation. The KSTAR superconducting magnet system consists of 16 D-shaped toroidal field (TF) coils, 3 pairs of poloidal field (PF) coils, and 4 pairs of central solenoid (CS) coils. Two kinds of SC coils have been fabricated and tested in the coil test facility in the Korea Basic Science Institute (KBSI). One of the coils was a prototype TF coil, TF00 coil, which has been fabricated in the same size as the real coils using Nb3Sn SC cable-in-conduit conductor (CICC). The other was a pair of CS model coils, which were fabricated as a part of a background field system to test the superconductor in a pulsed field environment. The major objectives of the SC coil tests were (i) to verify the coil design and fabrication process in the KSTAR coil development, (ii) to measure the coil performances during cool-down, current excitation, and discharge scenarios, and (iii) to achieve the operational experience of the SC coil test facility and the SC magnet system in the KSTAR device. The prototype TF coil was cooled down to the operating temperature of 4.5 K in 10 days. The coil was charged in steps and this was followed by slow or fast discharges. The transient hydraulic parameters were measured according to the different scenarios. The results of the coil test showed that no noticeable defects of the coil were found, such as helium leaks at cryogenic temperature, and helium circulation through the coil was sufficient to keep the coil at the operating temperature. The CS model coil was also cooled down in 9 days and basic current excitation and discharge tests of the coil have been done. To assess the ac performance of the coil, current charging experiments of the coil will be continued until the end of 2004. In this paper, the experimental results of the prototype TF coil and the CS model coil are described as well as the general coil test facility.
An application of answer set programming: Superoptimisation (A preliminary report)

Answer set programming (ASP) is a declarative problem-solving technique that uses the computation of answer set semantics to provide solutions. Despite comprehensive implementations and a strong theoretical basis, ASP has yet to be used for more than a handful of large-scale applications. This paper describes such a large-scale application and presents some preliminary results. The TOAST (Total Optimisation using Answer Set Technology) project seeks to generate optimal machine code for simple, acyclic functions using a technique known as superoptimisation. ASP is used as a scalable computational engine for conducting searches over complex, non-regular domains. The experimental results suggest this is a viable approach to the optimisation problem and demonstrates the value of using parallel answer set solvers. This paper was presented at and accepted for publication in the informal proceedings of the 11th International Workshop on Non-Monotonic Reasoning (NMR’06), Lake District, UK. Brain, Crick, De Vos and Fitch / An Application of Answer Set Programming: Superoptimisation
Revision 1 1 2 Ti resetting in quartz during dynamic recrystallization : Mechanisms and 3 significance

17 The ubiquity of quartz in continental crust, and the involvement of SiO2 in multiple 18 metamorphic processes such as reactions, fluid flux, and solution-transfer processes, makes 19 quartz an obvious choice for reconstructing prograde metamorphic conditions in a variety of rock 20 types. Recent studies have shown the usefulness of analyzing Ti distribution in quartz to 21 constrain pressure temperature (relative) time deformation (P-T-t-D) in metamorphosed 22 tectonites. New high-precision single crystal X-ray diffraction volume constraints on Ti-doped 23 and chemically pure quartz provide further evidence for substitution of Ti for Si in the 24 tetrahedral site in quartz, with resultant lattice strain on the structure. 25 Recent applications of the Ti-in-quartz thermobarometer to dynamically recrystallized 26 quartz have identified recrystallized subgrains that contain lower Ti concentrations ([Ti]) than 27 their host porphyroclasts. In addition, [Ti] are lower than expected for the temperatures of 28 recrystallization. Atomistic simulations that estimate energetic perturbations resulting from Ti 29 incorporation into the quartz lattice indicate that significant increases in strain energy occur only 30 at very high [Ti]; the strain-energy increase is negligible for [Ti] typical of quartz grown under 31 mid-crustal conditions. This suggests that lattice strain rarely provides an appreciable driving 32 force for Ti loss from quartz; instead, it appears that subgrain boundaries and dislocation arrays 33 migrating through recrystallizing quartz crystals can promote localized re-equilibration, 34 thermodynamically regulated by the composition of the intergranular medium (typically 35 undersaturated in Ti). It therefore appears that analyses from dynamically recrystallized quartz 36 cannot be meaningfully interpreted until methods are developed that can account quantitatively 37 for the reduction of Ti resulting from crystal plastic flow. 38 39
Carbon and land footprint time series of the Netherlands-integrating data from the GTAP and WIOD databases

This paper presents the results of an analysis of the carbon and land footprints of the Netherlands from 1995 to 2011. A multi-region input-output (MRIO) model was used for the calculation of these footprints. In recent years, several MRIO databases have become available all with their specific characteristics, advantages and drawbacks. In the MRIO model used, data from two of these databases, WIOD and GTAP, were integrated. The WIOD database enables the calculation of a consistent year-to-year time series. The GTAP database has more detail in regions and sectors than the WIOD database. Therefore, GTAP data were integrated into the WIOD data for a more detailed allocation of greenhouse gas (GHG) emissions and land use in agriculture. Furthermore, the regional detail in the GTAP database was used for allocating land use and greenhouse gas emissions in the WIOD rest-of-the-world region to continents. Greenhouse gas emissions related to Dutch consumption rose slightly with an annual increase of 0.3% in the period 1995-2011 with the rise in CO2 emissions as the main driver. Where the domestic emissions decreased the emissions related to imports for Dutch consumption rose. All WIOD countries outside the EU-27 showed an increase in greenhouse gas emissions for Dutch consumption. The land footprint increased with 0.4% a year as a result of a higher demand for crop and pasture land. The forest land footprint decreased in the period considered. By integrating GTAP data into the WIOD tables, a breakdown of the Dutch footprints into continents became visible. Europe, Central and South America and Asia showed the largest contributions in the Dutch land footprint.
Characterization of T-DNA insertion lines for FLA 1 , FLA 4 and FLA 8 during Arabidopsis thaliana sexual reproduction

This project focuses on understanding the role of fasciclin-like arabinogalactan proteins (FLAs) in the processes required for reproduction in Arabidopsis thaliana. FLAs are a sub-family of chimeric arabinogalactan proteins (AGPs) that possess variable numbers of 1 to 2 fasciclin (FAS) domains. These domains have been previously linked to cell adhesion properties and appear in animals, yeast, bacteria, algae, lichens, and higher plants. FLA1, FLA4 and FLA8 were revealed by a bioinformatics analysis to be present in reproductive tissues. Previously published results indicate that FLA4 was shown to be important in seed development. The roles of FLA1 and FLA8 remain mostly unknown, especially in regard to reproduction. FLA1, FLA4 and FLA8 were studied using a multistep approach: their promoter region was analysed to uncover the types of transcription factors that can potentially bind to them (using bioinformatic tools); the seed set of single mutant lines for each gene was evaluated; the germination rate and seed morphology were also compared to those of wild-type Col-0 plants and marker lines were created for each gene. The results obtained showed that FLA8 may have an important role in silique formation and seed maturation. The fla1 plants revealed defects in the progression of seed maturation, suggesting that FLA1 may be important during these processes. The knockout of FLA4 expression did not reveal defects in the seed set of fla4 siliques. None of the mutants showed significant disturbances in the germination rate and mature seed morphology. As a conclusion to this study, we would like to propose a possible role for these genes on the network controlling plant reproduction and their relation to transcription factors related to plant reproduction.
From Classification to Regression: Model Transfer for Visual Aesthetic Quality Assessment

Visual aesthetic quality assessment has played an important role in increasing number of computer vision applications. Particularly, estimating the quality score precisely is a main task of aesthetic quality assessment, but the training samples labeled with score are usually expensive to obtain. In this paper, we propose a transfer learning method which can improve the performance of aesthetic score prediction by using the coarse labeled samples, which are much easier to obtain. The proposed method incorporates the coarse information from source domain into the target domain by a novel multi-task framework, which can revise the model in target task. The effectiveness of our method is proven by experimental results that the error is reduced obviously with the help of source domain.
Half-Metallic Ferromagnetism in Chalcopyrite (AlGaMn)P2 Alloys

We studied the electronic and magnetic properties of (Al1−yMny)GaP2 (Ga-rich) and Al(Ga1−yMny)P2 (Al-rich) with y = 0.03125, 0.0625, 0.09375, and 0.125 by using the first-principles calculations. The ferromagnetic Mn-doped AlGaP2 chalcopyrite is the most energetically favorable one. The spin polarized Al(GaMn)P2 state (Al-rich system) is more stable than spin polarized (AlMn)GaP2 state (Ga-rich) with the magnetic moment of 3.8 /Mn. The Mn-doped AlGaP2 yields strong half-metallic ground states. The states of host Al, Ga, or P atoms at the Fermi level are mainly a P-3p character, which mediates a strong interaction between the Mn-3d and P-3p states.