Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of Cr 3+ Ion on the Dielectric Properties of Nano Crystalline Mg-Ferrites Synthesized by Citrate-Gel Method

Mixed Mg-Cr Nano ferrites having the compositional formula MgCrxFe2-xO4 (where x = 0.0, 0.1, 0.3, 0.5, 0.7, 0.9 and 1.0) were synthesized using Citrate-Gel auto combustion method. Structural characterization was carried out by XRD Analysis which confirmed the formation of single phase cubic spinel structure without any impurity peak. The dielectric properties such as Dielectric constant (e'), Dielectric Loss tangent (tan δ) and AC conductivity (σAC) of Mg-Cr nano ferrites were studied at room temperature in the frequency range of 2 Hz - 2 MHz using Agilent E4980A Precision LCR meter. The dielectric constant, loss tangent and AC conductivity shows a normal behavior with frequency. A qulitative explanation is given for composition and frequency dependance of the dielectric constant, dielectric loss tangent and AC conductivity of the nano ferrite. The loss tangent for the synthesized samples was found to be decreased from 0.09 to 0.054 in higher frequency region showing the potential applications of these materials in high frequency micro wave devices. On the basis of these results the explanation of dielectric mechanism in Mg-Cr ferrites is suggested.
A Fast Method for Measuring Kinematic Parameters of Experimental Vehicle Based on Machine Vision

The vehicle kinematic parameter is important evaluation index of vehicle performance. But the measurement technique for vehicle kinematics parameters is still immature. Practical and efficient measuring system is now in badly demand. With the development of machine vision technique, more and more measurement problems can be solved better by combining the measuring task with optical system. And on this basis the accuracy and efficiency of kinematic parameter measurement can be improved. A measuring plan is presented in this paper. In order to simplify the measuring algorithm, a simple and practical marker is as the substitute of vehicle. The complex measurement system is simplified and transformed to detection and trajectory tracking of the marker. In order to reduce the amount of computation and improve the speed of detection, a motion prediction local detection theory is presented to replace the traditional background subtraction detection method. Several experiments through MATLAB are conducted to verify the feasibility and accuracy of this measuring method. Keywords-kinematic parameters; machine vision; background subtraction; motion prediction
A Good Chance for the Cat’s Life: Erwin Schroedinger’s New Statistics and a Second Quantization Theory of Quantum

In his paper on the Cat’s uncertain situation between life and death, S. intended to criticize the Copenhagen interpretation of Quantum Mechanics and, conversely, to assert the consistency of his own wavelike view of the theory. His ideas contrasted with Heisenberg and Bohr’s positions, but also with Einstein’s attempt at a classically statistical interpretation of a quantum theory. His criticism therefore did not intend to discredit the whole Quantum Mechanics. In the fifties, he proposed a second quantization approach to a many particles state of the theory, which included his New Statistics. He asserted that the new approach modified some aspects of his famous 1926 equations. In my paper, I argue that S. ’s new ideas in the fifties are related to his 1920 and 1926 contributions on rarified gas theory.
An Efficient Genetic Algorithm Orienting to the Protein Fold Prediction

Proteins are amino acid chains that acquire their biological and biochemical properties by folding into unique 3-dimensional structures. The biological function of a protein is dependent on the protein folding into the correct, or "native", state. At present, there are so many ideas to predict the structure of the protein folding. This paper first present the concept of protein folding and how is significant to study protein fold prediction. In this paper we join the simulated annealing factor into Parallel Genetic Algorithm and use this hybrid Parallel GA to predict the structure of protein fold. The revised algorithm is more efficient than traditional Genetic Algorithm and simulated annealing algorithm.
Impact of Sleep Duration on Emotional Status in Adolescents.

Background: Chronic sleep deficiency adversely affects emotional and physical health. This study was to identify the current nocturnal sleep duration in South Korean adolescents and to analyze the association of emotional status such as subjective happiness, depression and suicidal attempts with the nocturnal sleep duration. Methods: We calculated sleep duration in a representative sample of South Korean middle- and high-school students according to grade, sex, and survey year using raw data from the Korea Youth Risk Behavior Web-Based Survey from 2007-2011. Students were then categorized by nocturnal sleep duration into sleep groups with 1 hour interval. Emotional status was assessed according to sleep duration. Total sample size was 291,813 which represent 15 million students. Results: Mean sleep duration for 2007-2011 was 6.32 ± 0.01 hours. Over the 90% of adolescents slept less than 8 hours. Sleep duration was dramatically decreased as students became senior grade. The longer sleep duration adolescents had, the more feeling of happiness they had regardless of grade. Vice versa, the lesser sleep duration students had, the more feeling of stress, depression, suicidal ideation and attempts they had. For example, less than 5 hours sleepers chose very unhappy 2.19 (95%CI 1.87-2.57) times more, extremely stressed 5.10 (4.33-6.02), depressions 1.94 (1.86-2.03), suicidal ideation 1.95 (1.85-2.06) and suicidal attempt 1.39 (1.24-1.55) than adolescents with 8-9 hour sleep duration. Conclusions: Sleep deficiency is associated with increasing stress, depression, suicidal ideation and attempts. Appropriate nocturnal sleep duration is critical for emotional health in adolescents.
Interest Rate Models

In this paper, we review recent developments in modeling term structures of market yields on default-free bonds. Our discussion is restricted to continuous-time dynamic term structure models (DTSMs). We derive joint conditional moment generating functions (CMGFs) of state variables for DTSMs in which state variables follow multivariate affine diffusions and jump-diffusion processes with random intensity. As an illustration of the pricing methods, we provide special cases of the general formulations as examples. The examples span a wide cross-section of models from early one-factor models of Vasicek to more recent interest rate models with stochastic volatility, random intensity jump-diffusions and quadratic-Gaussian DTSMs. We also derive the European call option price on a zero-coupon bond for linear quadratic term structure models.
Vitamin B 12 , Folate and Folate- Binding Proteins in Dairy Products Analysis, process retention and bioavailability

Arkbage, K. 2003. Vitamin B12, folate and folate-binding proteins in dairy products – analysis, process retention and bioavailability. Doctoral dissertation. ISSN 1401-6249, ISBN 91-5766470-6 Vitamin B12 and folate are two important B vitamins for maintaining good health, being involved in amino acid metabolism and DNA synthesis. Milk and dairy products are good sources of vitamin B12 and folate. Moreover, they are of interest due to their content of folate-binding proteins (FBP), since it was hypothesised that these promote folate bioavailability. Furthermore, fermentation of milk is a way to increase the content of both vitamins. Vitamin analysis in fermented dairy products is complicated due to the complex matrix. To gain reliable data on vitamin content, retention and bioavailability, emphasis throughout the project was put on optimisation and evaluation of methods for quantification. A commercial radio protein-binding assay (RPBA), produced for clinical samples, was evaluated regarding, e.g. assay pH, buffer molarity and food matrix effects. The optimised RPBA was demonstrated to be suitable for quantification of vitamin B12 in milk and fermented dairy products, and of folate quantification in dairy samples containing mainly 5-methyltetrahydrofolate. One aim of this project was to map the retention of vitamin B12 and folate during manufacture of six fermented dairy products. Results showed, e.g. that fermentation of milk followed by storage at 4 °C for 14 days decreased vitamin B12 concentrations in fermented milk by 40-60% compared with concentration in the milk. However, vitamin B12 was 4-7fold concentrated during hard cheese making. Regarding folate, the concentrations of folate increased both during fermentation of milk to yoghurt and during manufacture of cheese. Another aim was to study folate bioavailability from milk and fermented milks using both an in vitro gastrointestinal and a human model. Focus was on studying the stability and the nutritional role of bovine milk FBP, which are suggested to have a positive impact on folate bioavailability. Both studies showed FBP to partly endure in vitro and in vivo gastrointestinal passage, and further, to decrease in vitro and in vivo folate bioavailability.
Biofeedback: a Player’s Anxiety as Input into a Video Game Environment

This paper introduces a hardware-software solution for biological feedback game development. Currently, game developers do not utilize any dynamic inputs that are based off of player’s biological reactions. The goal of this paper is to research how effectively and efficiently biofeedback can be implemented into a videogame. This process is focused on the hardware and software implementation. On the software side, the game dynamically generates events based on a player’s heart rate. We use a standard heart rate monitor that can be attached to the player’s thumb. Basing the software response the biofeedback yields an intimate player-game experience. Keywordsbiofeedback; video game; game interaction; hardware; software implementation.
The relationship between wheat baking properties, specific high molecular weight glutenin components and characteristics of varieties

The main objective of this study was to compare the aeration level of ring shaped breads, produced from flour made from different winter wheat varieties with different glutenins composition. Analysis of the qualitative and quantitative composition of low molecular weight glutenins (LMW-glutenins), high molecular weight glutenins (HMW-glutenins) and wheat gluten protein fractions α-, γ-, ω-gliadins was performed by electrophoresis in polyacrylamide gel using sodium dodecyl sulphate polyacrylamide gel electrophoresis (SDS-PAGE). For qualitative evaluation of HMW-glutenin subunits, the obtained electrophoregrams were compared with the standard electrophoretic spectrums of the glutenin components presented in the catalogue. In particular, the indirect acoustic echolocation method can be applied in measurements of the structures of ring shaped breads. Correlations between wheat gluten fractions and some quality parameters characterizing the raw grain material show that HMW-glutenins have the strongest influence on the wheat flour baking properties, and the acoustic method allowed us to assess the quality of ring shaped breads according to the amount of water absorbed and the nature of swelling. This made it possible to classify the ring shaped breads into three quality categories: good (the amount of water absorbed from 37.5 to 50.75 relative units), medium (the amount of water absorbed from 2.54 to 6.28 and from 23.45 to 24.91 relative units), and poor (the amount of water absorbed from 3.6 to 14.7 relative units). According to the specific HMW-glutenin components, it is possible to select the best quality wheat varieties for flour production which could be recommended for ring shaped breads production.
Major impact from a minor merger

Context. Minor mergers are important processes contributing significantly to how galaxies evolve across the age of the Universe. Their impact on the growth of supermassive black holes and star formation is profound – about half of the star formation activity in the local Universe is the result of minor mergers. Aims. The detailed study of dense molecular gas in galaxies provides an important test of the validity of the relation between star formation rate and HCN luminosity on different galactic scales – from whole galaxies to giant molecular clouds in their molecular gas-rich centers. Methods. We use observations of HCN and HCO+ 1−0 with NOEMA and of CO3−2 with the SMA to study the properties of the dense molecular gas in the Medusa merger (NGC 4194) at 1′′ resolution. In particular, we compare the distribution of these dense gas tracers with CO2−1 high-resolution maps in the Medusa merger. To characterize gas properties, we calculate the brightness temperature ratios between the three tracers and use them in conjunction with a non-local thermodynamic equilibrium (non-LTE) radiative line transfer model. Results. The gas represented by HCN and HCO+ 1−0, and CO3−2 does not occupy the same structures as the less dense gas associated with the lower-J CO emission. Interestingly, the only emission from dense gas is detected in a 200 pc region within the “Eye of the Medusa”, an asymmetric 500 pc off-nuclear concentration of molecular gas. Surprisingly, no HCN or HCO+ is detected for the extended starburst of the Medusa merger. Additionally, there are only small amounts of HCN or HCO+ associated with the active galactic nucleus. The CO3−2/2−1 brightness temperature ratio inside “the Eye” is ~2.5 – the highest ratio found so far – implying optically thin CO emission. The CO2−1/HCN 1−0 (~9.8) and CO2−1/HCO+ 1−0 (~7.9) ratios show that the dense gas filling factor must be relatively high in the central region, consistent with the elevated CO3−1/2−1 ratio. Conclusions. The line ratios reveal an extreme, fragmented molecular cloud population inside the Eye with large bulk temperatures (T > 300 K) and high gas densities (n(H2) > 104 cm-3). This is very different from the cool, self-gravitating structures of giant molecular clouds normally found in the disks of galaxies. The Eye of the Medusa is found at an interface between a large-scale minor axis inflow and the central region of the Medusa. Hence, the extreme conditions inside the Eye may be the result of the radiative and mechanical feedback from a deeply embedded, young and massive super star cluster formed due to the gas pile-up at the intersection. Alternatively, shocks from the inflowing gas entering the central region of the Medusa may be strong enough to shock and fragment the gas. For both scenarios, however, it appears that the HCN and HCO+ dense gas tracers are not probing star formation, but instead a post-starburst and/or shocked ISM that is too hot and fragmented to form newstars. Thus, caution is advised in taking the detection of emission from dense gas tracers as evidence of ongoing or imminent star formation.
IMPROVING THE CLUSTER PERFORMANCE BY COMBINING PSO AND K-MEANS ALGORITHM

Clustering is a technique that can divide data objects into groups based on information found in the data that describes the objects and their relationships. In this paper describe to improving the clustering performance by combine Particle Swarm Optimization (PSO) and K-means algorithm. The PSO algorithm successfully converges during the initial stages of a global search, but around global optimum, the search process will become very slow. On the contrary, K-means algorithm can achieve faster convergence to optimum solution. Unlike K-means method, new algorithm does not require a specific number of clusters given before performing the clustering process and it is able to find the local optimal number of clusters during the clustering process. In each iteration process, the inertia weight was changed based on the current iteration and best fitness. The experimental result shows that better performance of new algorithm by using different data sets.
Sexual dimorphism within the stem-group arthropod Isoxys volucris from the Sirius Passet Lagerstätte, North Greenland.

Morphometric analyses carried out on 126 specimens of the early Cambrian (Cambrian Series 2, Stage 3) stem-group arthropod Isoxys volucris from North Greenland reveal a bimodal distribution, where Morphogroup A is characterised by a significantly wider doublure than Morphogroup B. The dimorphism is interpreted as intraspecific variation related to gender (sexual dimorphism), where the relative numbers of individuals within the two morphogroups are equal (ratio 1:1). The discovery of established sexual dimorphism in Isoxys may have implications for the taxonomic discrimination of other stemgroup arthropods within the morphologically diverse and disparate animals of the early Cambrian.
Machine learning vortices at the Kosterlitz-Thouless transition

Efficient and automated classification of phases from minimally processed data is one goal of machine learning in condensed matter and statistical physics. Supervised algorithms trained on raw samples of microstates can successfully detect conventional phase transitions via learning a bulk feature such as an order parameter. In this paper, we investigate whether neural networks can learn to classify phases based on topological defects. We address this question on the two-dimensional classical XY model which exhibits a Kosterlitz-Thouless transition. We find significant feature engineering of the raw spin states is required to convincingly claim that features of the vortex configurations are responsible for learning the transition temperature. We further show a single-layer network does not correctly classify the phases of the XY model, while a convolutional network easily performs classification by learning the global magnetization. Finally, we design a deep network capable of learning vortices without feature engineering. We demonstrate the detection of vortices does not necessarily result in the best classification accuracy, especially for lattices of less than approximately 1000 spins. For larger systems, it remains a difficult task to learn vortices.
TARGET2 imbalances and the need for a lender of last resort

This paper analyses the issue of the dynamics of the TARGET2 system balances during the sovereign debt crisis. The development of these balances reflects the change in the distribution of the monetary base among the EMU Member States. During the sovereign debt crisis, while some countries, among which Germany, registered a decisive inflow of monetary base, some others, as Italy, shown an outflow. The main conclusion of the paper is that the dynamics in TARGET2 is rather due to a fall in the level of confidence in the capacity of the EMU to survive than to disparities in the level of competitiveness among countries of the Eurozone as a part of the literature maintained. In turn, this crisis of confidence has to be considered as the consequence of the implicit refusal of the European institutions of creating a mechanism working as “lender of last resort” for the Eurozone Member States. Two elements, in particular, support this thesis. On the one hand, most of the monetary base outflow occurred in coincidence with those political decisions which determined deterioration in the expectation about the degree of solvency of the periphery countries. On the other hand, the fiscal consolidation that the periphery countries implemented destabilized the economy as a result of a negative conjuncture and a monetary policy ineffective in reducing the interest rate.
TECHNOLOGY SERVICE AND FACTOR INTENSITY: THE EXPORT IMPACT FROM MULTINATIONALS

We develop an industry-level model to examine the impact of multinational firms (MNFs) on revealed comparative advantages (RCA), predicting that it stems from firms’ technology service and factor-intensity. Based on Brazilian manufacturing industries during the importsubstitution period, compared to a set of developed countries, the panel data estimates show that FORGN (multinationals’ share in industries) negatively affected RCA, due to location advantages in industries intensive in skilled labor; or else to horizontally integrated MNFs, shown by the estimates of firms’ location model. In order to control the errors stemming from unobserved variables, we estimate a structural RCA model, where the latent distribution of FORGN is given from the production regime model, which shifts its coefficient to positive.
Community Discovery in Twitter Based on User Interests

Twitter has recently emerged as a popular social microblogging service. There are over 100 million users in Twitter nowadays, little is known yet about Twitter at user level. In this paper, we investigate the problem of identifying communities in Twitter based on users’ interests. To address this problem, we first compute user similarity leveraging both textual contents and social structure, according with Twitter’s role, not only a news media but also a social network. These features include tweet text, URLs, hashtags, following relationship and retweeting relationship, and all of them are closely correlated with users’ interests. Then we use user similarity as well as classical clustering algorithms to discover communities. To assess effectiveness of our method, we propose the metrics in Twitter “average number of mutual following links per user in per community”. Experimental results show that our method can successfully discover communities in Twitter, and gives a much better performance than random selection. From a side view, our experiment also shows that users in our dataset of Twitter can be approximately categorized into 400 communities.
The competitiveness situation of the EU meat processing and beverage manufacturing sectors

Abstract The status of competitiveness for the two most important food and beverage manufacturing sectors (meat processing and beverage manufacturing) in 13 EU countries is analysed empirically, using 1995–2002 Eurostat data. After a review of earlier agribusiness competitiveness studies, an industrial competitiveness index is proposed as a composite measure for multidimensional economic performance, covering profitability, productivity and output growth. The index approach enables relative competitiveness comparisons across industries, countries and over time. The results show that during 1999–2002, as compared to 1995–1998, for both sectors overall competitiveness in real terms slightly increased. At the same time, overall competitiveness also seems to have converged slightly across countries, implying that sector performance has become more similar. However, the two country rankings differ considerably, as do the change patterns during the analysed period.