Miracle-dz/UniFAR-FTUs huggingface dataset:
Protostellar Evolution in Serpens Main: Possible Origin of Disk-size Diversity

We have observed the submillimeter continuum condensations SMM2, SMM4, SMM9, and SMM11 in the star-forming cluster Serpens Main using the Atacama Large Millimeter/submillimeter Array during Cycle 3 in the 1.3 mm continuum, 12CO J = 2 − 1, SO JN = 65 − 54, and C18O J = 2 − 1 lines at an angular resolution of ∼0. ″55 (240 au). Sixteen sources have been detected in the 1.3 mm continuum, which can be classified into three groups. Group 1 consists of six sources showing extended continuum emission and bipolar/monopolar 12CO outflows. Although all the Group 1 members are classified as Class 0 protostars, our observations suggest evolutionary trends among them in terms of 12CO outflow dynamical time, SO emission distribution, C18O fractional abundance, and continuum morphology. Group 2 consists of four sources associated with a continuum filamentary structure and no 12CO outflows. Central densities estimated from the 1.3 mm continuum intensity suggest that they are prestellar sources in a marginally Jeans unstable state. Group 3 consists of six Spitzer sources showing point-like 1.3 mm continuum emission and clumpy 12CO outflows. These features of Group 3 suggest envelope dissipation, preventing disk growth from the present size, r ≲ 60 au. The Group 3 members are protostars that may be precursors to the T Tauri stars associated with small disks at radii, of tens of astronomical units, identified in recent surveys.
Let’s FACE it. Finnish Poetry Generation with Aesthetics and Framing

We present a creative poem generator for the morphologically rich Finnish language. Our method falls into the master-apprentice paradigm, where a computationally creative genetic algorithm teaches a BRNN model to generate poetry. We model several parts of poetic aesthetics in the fitness function of the genetic algorithm, such as sonic features, semantic coherence, imagery and metaphor. Furthermore, we justify the creativity of our method based on the FACE theory on computational creativity and take additional care in evaluating our system by automatic metrics for concepts together with human evaluation for aesthetics, framing and expressions.
Facial Image Deformation Based on Landmark Detection

In this work, we use facial landmarks to make the deformation for facial images more authentic and verisimilar. The deformation includes the expansion for eyes and the shrinking for noses, mouths, and cheeks. An advanced 106-point facial landmark detector is utilized to provide control points for deformation. Bilinear interpolation is used in the expansion part and Moving Least Squares methods (MLS) including Affine Deformation, Similarity Deformation and Rigid Deformation are used in the shrinking part. We then compare the running time as well as the quality of deformed images using different MLS methods. The experimental results show that the Rigid Deformation which can keep other parts of the images unchanged performs best even if it takes the longest time.
THEENIVERSITY OF YORK

In this paper we critically examine the concept of the environmental Kuznets curve (EKC). This concept, most prominently promoted in the World Development Report 1992, proposes that there is an inverted U-shape relation between environmental degradation and income per capita. The concept is dependent on a model of the economy in which there is no feedback from the quality of the environment to economic growth and in which trade has a neutral effect on environmental degradation. There are also some econometric problems with previous estimates of the EKC. The inference from the EKC estimates that further development will reduce environmental degradation is dependent on the assumption that World income is normally distributed when in fact median income is far below mean income. To illustrate the latter point we carry out a simulation under the assumption that one could actually analyze the economy-environment relationship in the way suggested by the EKC. We combine published estimates of the EKC with World Bank forecasts for long-run economic growth. The analysis shows that within the horizon of the Bank's forecast (2025) global emissions of SO2 will continue to increase. Forest loss stabilizes before the end of the period but tropical deforestation continues to proceed at a constant rate throughout the period. This is despite a near doubling in mean world income per capita.
Climate bifurcation during the last deglaciation?

There were two abrupt warming events during the last deglaciation, at the start of the Bølling-Allerød and at the end of the Younger Dryas, but their underlying dynamics are unclear. Some abrupt climate changes may involve gradual forcing past a bifurcation point, in which a prevailing climate state loses its stability and the climate tips into an alternative state, providing an early warning signal in the form of slowing responses to perturbations, which may be accompanied by increasing variability. Alternatively, short-term stochastic variability in the climate system can trigger abrupt climate changes, without early warning. Previous work has found signals consistent with slowing down during the last deglaciation as a whole, and during the Younger Dryas, but with conflicting results in the run-up to the Bølling-Allerød. Based on this, we hypothesise that a bifurcation point was approached at the end of the Younger Dryas, in which the cold climate state, with weak Atlantic overturning circulation, lost its stability, and the climate tipped irreversibly into a warm interglacial state. To test the bifurcation hypothesis, we analysed two different climate proxies in three Greenland ice cores, from the Last Glacial Maximum to the end of the Younger Dryas. Prior to the Bølling warming, there was a robust increase in climate variability but no consistent slowing down signal, suggesting this abrupt change was probably triggered by a stochastic fluctuation. The transition to the warm Bølling-Allerød state was accompanied by a slowing down in climate dynamics and an increase in climate variability. We suggest that the Bølling warming excited an internal mode of variability in Atlantic meridional overturning circulation strength, causing multi-centennial climate fluctuations. However, the return to the Younger Dryas cold state increased climate stability. We find no consistent evidence for slowing down during the Younger Dryas, or in a longer spliced record of the cold climate state before and after the Bølling-Allerød. Therefore, the end of the Younger Dryas may also have been triggered by a stochastic perturbation.
Use of High-Frequency Seismic Waves for the Detection of Buried Land Mines

Over the past three years a system has been under development at Georgia Tech that utilizes a seismic interrogation signal in combination with a non-surface-contacting, radar-based displacement sensor for the detection of buried landmines. Initial work on this system investigated the workability of the system concept. Pragmatic issues regarding the re nement of the current experimental laboratory system into a system which is suitable for eld testing and, in turn, one which would be suited to eld operations have been largely ignored until recently. Both eld operations and realistic eld testing require a system that is di erent from the original laboratory system in two crucial ways. One of these is that a eld system needs a sensor stando from the ground surface larger than the original 1 to 2 cm. This is necessary in order to account for small-scale topography, to avoid ground cover such as grass, and to minimize the risk to the operator. A second di erence is that the scanning speed of a eld system must be substantially greater than that of the original laboratory system, which takes several hours to image 1 m of ground surface. From an operational standpoint, the reason for this is obvious. From an experimental standpoint, it is also important because ambient conditions are diÆcult to control on long time scales outdoors. Both of these new requirements must be met within the design parameters that were established empirically during the development of the laboratory system. One of these is that the system must be capable of measuring peak displacements as small as 1 nm with a 1 Hz resolution band in the low audio frequency range (30 Hz to 2 KHz). This is necessary because of limits placed by the medium on the amplitude of seismic signals that can be generated. Another parameter is that the measurement must be integrated over a region with a diameter of about 2 cm to 5 cm on the ground surface. This is necessary in order to preserve spatial structure of interest for the imaging of small mines. An array of radar-based displacement sensors con gured with focused antennas meets all these requirements. A sensor was designed to test this concept. The new sensor was equipped with an antenna consisting of a conical corrugated horn and a bifocal dielectric lens that permitted a 20-cm surface-stando distance. The sensor was tested in a laboratory experimental model in scenarios similar to those used to evaluate the original system sensor and was found to satisfy all of the new system requirements.
econstor Make Your Publications Visible . A Service of zbw

Purchasing life insurance is for the welfare of young children, particularly preteens, who are liquidity constrained. In this paper, we present a life cycle model of life insurance that takes into account the ages of these young beneciaries. We show that, as the child ages, the need for protection is reduced and, consequently, the size of contingent bequest may shrink. The demand for life insurance is positively related to the number, age differentials, living standards, and the time needed to reach adulthood. Also, the breadwinner's lifetime uncertainty and the unfairness of the insurance market encourage precautionary saving JEL Classification: G22, D91
M ay 2 01 5 OCHA-PP-333 , FU-PCG-1 Cosmological Issues in F ( T ) Gravity Theory

We review recent developments on cosmology in extended teleparallel gravity, called “F (T ) gravity” with T the torsion scalar in teleparallelism. We explore various cosmological aspects of F (T ) gravity including the evolution of the equation of state for the universe, finite-time future singularities, thermodynamics, and four-dimensional effective F (T ) gravity theories coming from the higher-dimensional Kaluza-Klein (KK) and Randall-Sundrum (RS) theories.
Modeling the impact of land use and climate change scenarios of on the hydrology of the upper Mara River, Kenya

With the flow of the Mara River becoming increasingly erratic especially in the upper reaches, attention has been directed to land use change and climate variability as the major cause of this problem. The semi-distributed hydrological model Soil and Water Assessment Tool (SWAT) and Landsat imagery were utilized in the upper Mara River basin in order to 1) map existing field scale land use practices, 2) determine the impacts of land use change on water flux using plausible land use change scenarios; and 3) determine the impacts of rainfall and air temperature variations based on the Intergovernmental Panel on Climate Change projections on the water flux of the upper Mara River This study found that the different scenarios impacted the water budget components differently. Land use changes resulted in a slightly more erratic discharge while rainfall and air temperature changes had a more predictable impact on the discharge and water balance components. These findings demonstrate that the model results show the flow was more sensitive to the rainfall changes than land use changes. It was also shown that land use changes can reduce dry season flow which is the most important problem in the basin. The
Evaluation of Binarization Algorithms

Twenty-one algorithms from five algorithmic families were evaluated for their accuracy at binarizing line drawings. The data set contains binary line drawings (templates) that are converted to gray scale with backgrounds added from scanned elevation drawings. Using normalized cross-correlation to measure similarity between the binarized images and binary templates, clustering and histogram shape based algorithms were found to provide the most accurate results, while histogram shape based algorithms were significantly faster than all other algorithmic families. No single algorithm was observed to produce significantly more accurate results across the entire data set than all other algorithms.
Effect of platelet turnover on whole blood platelet aggregation in patients with coronary artery disease: reply to a rebuttal

See also Grove EL, Hvas AM, Mortensen SB, Larsen SB, Kristensen SD. Effect of platelet turnover on whole blood platelet aggregation in patients with coronary artery disease. J Thromb Haemost 2011; 9: 185–91; Ege MR, Zorlu A. Effect of platelet turnover on whole blood platelet aggregation in patients with coronary artery disease: a rebuttal. This issue, pp 888.
GDP Elasticities of Export Demand

Exports are an important source of income for Sweden. They are influenced by macroeconomic factors such as GDP. This paper examines the elasticity of Swedish export to changes in the GDP of Sweden’s 25 most important export partners. The sensitivity to changes in GDP, the elasticity, can be different for different goods. Therefore, we examine export elasticities for five different commodity groups, which include durable as well as non-durable goods. Moreover, special focus is put on the trade relationship between Sweden and Germany in order to see if their long common trade history has any impact on the elasticity of Swedish exports to Germany. The analysis is based on an export demand function that links exports to GDP and geographical distance. We include dummy variables in our regression model to control for EU-membership and common borders. For Swedish exports to Germany, we find that exports of food and live animals are least elastic, whereas exports of machinery and transport equipment are most elastic. This is coherent with previous empirical findings about demand elasticities of non-durable and durable goods. We find that exports in two out of five commodity groups are unit elastic. This means that when German GDP increases by one percent, Sweden’s export to Germany in these commodity groups also grows by approximately one percent. Thus, Sweden is not able to capture additional profit through over proportional increases in exports to Germany. For Swedish exports to its 25 most important trading partners, on average, we find that exports of manufactured goods as well as machinery and transport equipment are the least elastic exports. This gives them the lowest growth potential.
GERMLINE COPY NUMBER VARIATION OF CANCER SUSCEPTIBILITY 8 GENE IN BREAST CANCER RISK AND PROGNOSIS

Breast cancer is the most common cancer and cause of cancer mortality in women worldwide, showing substantial variation in its biological and clinical behavior. Germline variants discovered to date can only explain half of the genetic susceptibility to this disease and they are mostly poor prognosticators. Structural copy number variations (CNVs) in the germline DNA are recently identified as missing heritable determinants for breast cancer risk and prognosis through their mediated cis-regulation and gene-dosage effects. This is the first case-control study to examine the impact of germline CNV in long non-protein-coding cancer susceptibility 8 (CASC8) gene on breast cancer risk and prognosis among genetically homogenous women (615 invasive cases, 52 in situ cases and 146 healthy controls of Northern Savonia/Eastern Finland origin). The number of copies of the CASC8 gene was determined from the duplex real-time quantitative PCR produced cycle threshold data using single plate and multiplate (combined single plates) analyses. The associations of the copy number status to clinico-pathological (Fisher’s exact or Pearson’s chi-squared test) and survival data (Kaplan–Meier and covariate-adjusted Cox methods) were assessed. The CASC8 deletion was significantly associated with breast cancer diagnosis and age of study participants among older women whereas positivity for human epidermal growth factor receptor 2 and involved regional lymph nodes showed the poorest prognosis. A larger cohort of population-representative cases and controls is needed to understand the contribution of this CNV to breast cancer risk. Further investigation of germline CNVs will bring us a step closer to more personalized breast cancer management.
Editorial from the Editor-in-Chief

On behalf of the Editorial board, we welcome you to the twenty first issue of the EAI Endorsed Transactions on Context-Aware Systems and Applications. In this issue, we present four selected papers that span various aspects of context-aware systems and applications. This issue will serve as a reference material for researchers, scientists, professionals and students in computer science and computer engineering as well as developers and practitioners in computing and networking systems design by providing them with state-of-the-art research findings and future opportunities and trends. These papers include some recent advances in context-awareness reflected in this issue. In particular, the issue covers various themes of context-awareness as follows: Paper 1 by M. Leghari, L. D. Dhomeja and S. A. Memon [2] reports that a smart home is a contextaware system that adapts itself autonomously in response to context to satisfy user needs and to improve safety, security, resource use, etc. On the one hand, software autonomy serves the basic purpose of pervasive computing by reducing interaction with the users, easing the use of the system, and reducing the user distraction. On the other hand, it takes control away from the users of the applications, making users feel loss of control over their contextaware applications. The situations including applications may not behave as expected, user preferences may change over time or users may want to add new behaviors, etc, may arise and require smart home users to interact with the applications to control their behavior. This research addresses this issue and proposes an approach, which would provide a wider support of user control by exposing and manipulating (1) application parameters, (2) adaptation logic(s) thus allowing users to add new behaviors. Using this approach a complete system is developed in order to see its effectiveness; furthermore the system is tested on three different context aware
Constructing human-robot interaction with standard cognitive architecture

This paper discusses how to extend cognitive models with an explicit interaction model. The work is based on the Standard Model of Cognitive Architecture which is extended by an explicit model for (spoken) interactions following the Constructive Dialogue Modelling (CDM) approach. The goal is to study how to integrate a cognitively appropriate framework into an architecture which allows smooth communication in human-robot interactions, and the starting point is to model construction of shared understanding of the dialogue context and the partner’s intentions. Implementation of conversational interaction is considered important in the context of social robotics which aim to understand and respond to the user’s needs and affective state. The paper describes integration of the architectures but not experimental work towards this goal.
Getting results in clinical pathology 4. Influence of medications on biochemical parameters

MEDICATIONS are used for their beneficial actions but, in some patients, can cause adverse effects, some of which are more serious than others. One type of adverse reaction that is often overlooked is the interaction between drugs and diagnostic tests. This article reviews the most common drug-induced alterations in biochemical parameters. An article in the next issue will examine the effect of medications on haematological parameters.
APSKAITOS IR FINANSŲ MOKSLAS IR STUDIJOS: PROBLEMOS IR PERSPEKTYVOS SCIENCE AND STUDIES OF ACCOUNTING AND FINANCE: PROBLEMS AND PERSPECTIVES

The aim of this theoretical paper is to discuss the researches implemented in government bond and other financial markets, and to identify the most important global factors, influencing government bond market comovements. Even though, there exist various groups of factors, influencing government bond markets, this research is concentrated in the existence of global factors. If the influence of these factors is significant, investors cannot hedge from this influence by diversifying. The research in this paper is implemented by using the analysis, synthesis and systemization of the researches and other scientific literature. This research uses a novel approach by excluding and the most common global factors, influencing government bond market comovements and discussing the measures to assess the influence of these factors on the comovements. The research resulted in identification of 5 global factors, most commonly disclosed by other researchers as influencing government bond market comovements: global risk aversion, global market portfolio, money market uncertainty, commodity market uncertainty and economic policy uncertainty, with the most important factor being global risk aversion. The existence of these factors reduces the benefits from international diversification: if the markets are strongly influence by the same global factors, the deterioration of these factors will influence the investment portfolio in the same way.
Gene Expression Dataset Classification Using Artificial Neural Network and Clustering-Based Feature Selection

With the progression of bioinformatics, applications of GE profiles on cancer diagnosis along with classification have become an intriguing subject in the bioinformatics field. It holds numerous genes with few samples that make it arduous to examine and process. A novel strategy aimed at the classification of GE dataset as well as clustering-centered feature selection is proposed in the paper. The proposed technique first preprocesses the dataset using normalization, and later, feature selection was accomplished with the assistance of feature clustering support vector machine (FCSVM). It has two phases, gene clustering and gene representation. To make the chose top-positioned features worthy for classification, feature reduction is performed by utilizing SVM-recursive feature elimination (SVM-RFE) algorithm. Finally, the feature-reduced data set was classified using artificial neural network (ANN) classifier. When compared with some recent swarm intelligence feature reduction approach, FCSVM-ANN showed an elegant performance.