Miracle-dz/UniFAR-FTUs huggingface dataset:
Multiparametric characterization of grade 2 glioma subtypes using magnetic resonance spectroscopic, perfusion, and diffusion imaging.

BACKGROUND AND PURPOSE The purpose of this study was to derive quantitative parameters from magnetic resonance (MR) spectroscopic, perfusion, and diffusion imaging of grade 2 gliomas according to the World Health Organization and to investigate how these multiple imaging modalities can contribute to evaluating their histologic subtypes and spatial characteristics. MATERIALS AND METHODS MR spectroscopic, perfusion, and diffusion images from 56 patients with newly diagnosed grade 2 glioma (24 oligodendrogliomas, 18 astrocytomas, and 14 oligoastrocytomas) were retrospectively studied. Metabolite intensities, relative cerebral blood volume (rCBV), and apparent diffusion coefficient (ADC) were statistically evaluated. RESULTS The 75th percentile rCBV and median ADC were significantly different between oligodendrogliomas and astrocytomas (P < .0001) and between oligodendrogliomas and oligoastrocytomas (P < .001). Logistic regression analysis identified both 75th percentile rCBV and median ADC as significant variables in the differentiation of oligodendrogliomas from astrocytomas and oligoastrocytomas. Group differences in metabolite intensities were not significant, but there was a much larger variation in the volumes and maximum values of metabolic abnormalities for patients with oligodendroglioma compared with the other tumor subtypes. CONCLUSIONS Perfusion and diffusion imaging provide quantitative MR parameters that can help to differentiate grade 2 oligodendrogliomas from grade 2 astrocytomas and oligoastrocytomas. The large variations in the magnitude and spatial extent of the metabolic lesions between patients and the fact that their values are not correlated with the other imaging parameters indicate that MR spectroscopic imaging may provide complementary information that is helpful in targeting therapy, evaluating residual disease, and assessing response to therapy.
X-Ray Emission from the Prototypical LINER Galaxy NGC 1052

We examine the 0.1-10.0 keV X-ray spectrum of the bright nuclear LINER galaxy NGC 1052, one of two elliptical galaxies known to contain a luminous H2O maser. The observed 2.0-10.0 keV spectrum is unusually flat (photon index Γ ~ 0.2) and is best described as intrinsically power-law shaped nuclear flux that is either (1) attenuated by a complex absorber with ~70% of the nuclear flux absorbed by a column density of NH ~ 3 × 1023 cm-2 and ~30% absorbed by a column density of NH ~ 3-5 × 1022 cm-2 or (2) reprocessed, with the nuclear source blocked and the X-rays Compton reflected in our direction by high column density (≥1024 cm-2) gas. The moderate equivalent width of the Fe Kα line favors the dual absorption model as the most likely scenario. The 0.1-2.0 keV spectrum does not resemble the few times 106-107 K thermal emission typically found in other elliptical galaxies, but instead is best described as nuclear X-rays leaking through a patchy absorber or scattered in our direction by low-density, ionized gas plus a 15%-20% contribution from a thermal component, which is most likely due to the galaxy. The absorption-corrected 2-10 keV luminosity of the nuclear source is LX ~ 8 × 1041 ergs s-1 or LX ~ 2 × 1043 ergs s-1 for the dual-absorption and Compton-reflection models, respectively. The absorbing and H2O masing gases appear to be spatially separate in this galaxy.
A comparison of interactions on Facebook brand pages between global brands and publics in individualistic and collectivistic countries

PITCHPATU WAIYACHOTE: A comparison of interactions on Facebook brand pages between global brands and publics in individualistic and collectivistic countries (Under the direction of Lois Boynton) The present study presents a comparative analysis of how Facebook was used to build and maintain relationships between global brands and their publics in individualistic and collectivistic cultures. Mixed methods — a quantitative content analysis and an online survey — were used. A total of 5,753 wall posts on the six global brands' Facebook brand pages available in five selected countries were analyzed. The U.S. represented individualistic cultures, while four Southeast Asian countries represented collectivistic cultures. Overall, the study found that differences in cultures play an important role in the interactions on Facebook between the global brands and their publics. The global brands used Facebook to build and maintain relationships with their publics in the U.S., but used it as an integrated tool to promote products and stay in touch with their publics in Southeast Asian countries. The publics in individualistic and collectivistic cultures alike were likely to use Facebook to maintain relationships with the global brands. The study also found that two dialogic communication features, a communication loop and an incentive, had an impact on the volumes of responding comments, especially in the individualistic country. A greater number of the brand community characteristics were found on Facebook brand pages in the U.S. than those in the Southeast Asian countries. iv! The findings in regards to brand personality suggested that the global brands did not use heavily Facebook to portray brand personality. Acknowledging the limited survey sample size, the study found that the congruency between brand personality portrayal and brand personality perceptions seemed to be associated with the presence of brand community on Facebook brand pages. ACKNOWLEDGEMENT First of all, I would like to express my gratitude to my dissertation committee members: Dr. and Dr. William Ware for their guidance and support throughout the process of my dissertation work. I also want to thank my professors and cohorts at the school of Journalism for making my experience at UNC a memorable one. My gratitude also goes to all of my professors and teachers who have influenced me to want to become a teacher. I also would like to thank my soon-to-be coworkers at UTCC. Thank you all of my friends at Maree, Traim, ISU, and H&K for cheering me on. Thanks so …
Vehicle backward driving control with obstacle avoidance

This paper introduces an autonomous backward driving control method using space information from stereo vision system. For forward driving, numerous autonomous driving control methods are already developed and they work better than inexperienced drivers. However, autonomous backward driving control works in very limited cases, such as for autonomous parking within short distances. In case of backward driving in a long, narrow, and bended corridor, even a human driver may have a difficulty in passing through because of the non-minimum phase nature of a backwardly driven car and a limited lateral space margin. For autonomous backward driving in such case, we design a controller using a Model Predictive Control (MPC) technique that can explicitly handle the constraints and upcoming driving conditions. The near future information can be obtained using a stereo camera. We evaluated the performance of the suggested method using simulations.
A TSK fuzzy model and adaptive sliding-mode controller design for four-Mecanum-wheel omni-directional mobile free-bases

In this paper, we propose a Takagi-Sugeno-Kang (TSK) fuzzy model for a four-Mecanum-wheel omni-directional mobile free-base (4MW-ODMFB) with system uncertainties and external disturbances based on the model given, and then design an adaptive sliding-mode control (ASMC) system for trajectory tracking of 4MW-ODMFB, which combines the techniques of adaptive control and sliding-mode control. By using Lyapunov method we prove that the ASMC system is global asymptotic stable. We also conduct simulation experiments in MATLAB environment to test our TSK fuzzy model and the ASMC method. All the simulation results demonstrate the effectiveness of the proposed TSK fuzzy model and the stability and robustness of ASMC system.
FRT capability of direct power controlled converters connected by an actively damped LCL-filter for wind power applications

A Direct Power Control method for grid connected voltage source converters in wind power applications is investigated and improved. A damping algorithm for the LCL-filter as well as a FRT concept is designed and applied. The proposed control method is analyzed in regard to the fault ride through behavior required by the grid codes and shows good performance. Steady-state and dynamic performance of this control are shown by simulation and measurement results.
A ROBUST FALSE MATCHING POINTS DETECTION METHOD FOR REMOTE SENSING IMAGE REGISTRATION

Abstract. Given the influences of illumination, imaging angle, and geometric distortion, among others, false matching points still occur in all image registration algorithms. Therefore, false matching points detection is an important step in remote sensing image registration. Random Sample Consensus (RANSAC) is typically used to detect false matching points. However, RANSAC method cannot detect all false matching points in some remote sensing images. Therefore, a robust false matching points detection method based on Knearest- neighbour (K-NN) graph (KGD) is proposed in this method to obtain robust and high accuracy result. The KGD method starts with the construction of the K-NN graph in one image. K-NN graph can be first generated for each matching points and its K nearest matching points. Local transformation model for each matching point is then obtained by using its K nearest matching points. The error of each matching point is computed by using its transformation model. Last, L matching points with largest error are identified false matching points and removed. This process is iterative until all errors are smaller than the given threshold. In addition, KGD method can be used in combination with other methods, such as RANSAC. Several remote sensing images with different resolutions and terrains are used in the experiment. We evaluate the performance of KGD method, RANSAC + KGD method, RANSAC, and Graph Transformation Matching (GTM). The experimental results demonstrate the superior performance of the KGD and RANSAC + KGD methods.
A new LSTM model by introducing biological cell state

Long Short Term Memory (LSTM) has been a very successful augmented recurrent neural network model employed to learn sequential information with long term dependencies where LSTM can store and compute information for a long period of time. In this study, a biologically inspired variation has been incorporated in LSTM by introducing additive cell state into the functionally computational system. The novel biological variant of LSTM model has been employed to conduct sentiment analysis of textual data. As the learning dataset, fifty thousand movie reviews have been used from IMDB where equal number of review data has been used for training and testing purposes. The comparative performance of the new variant is found to be promisingly better and show more stability than that of the traditional LSTM.
Moving in small steps towards verb second: A case study

This paper examines rule-based learning and item-based learning in relation to a Swedish child's acquisition of verb second in main clauses. While rule-based accounts assert that young children have access to syntactic structure and acquire a rule of generalized verb second, item-based accounts claim that young children are reproducing frequent word combinations in the input. The paper provides new and important data from one Swedish child, concluding that the acquisition of verb second is the result of rule-based learning.
PRESCHOOL CHILDREN

Current research on spatial orientation indicates that, so far, we do not fully understand how spatial orientation develops in ontogenesis. Similarly, one encounters difficulties when searching for norms concerning orientation, e.g. the body scheme in adults. Another unsettled issue is the claim that a given child has disturbed spatial orientation. Certainly it is impossible to diagnose a disorder when there is no norm established. The aim of our research was to explore the level of spatial orientation skills in kindergarten children. 1055 children were assessed: 523 girls and 523 boys from various regions of Poland. We applied an experimental method based on diagnostic experiments used to assess children’s com petence in spatial orientation. We observed a certain order of spatial orientation competen ces: knowledge of body scheme; directions in space from one’s body; projecting one’s own body scheme onto another person and establishing directions in space from the body, while simultaneously speaking about the action being taken; and finally spatial orientation on paper. Simultaneously, the research shows that a majority of 6and 7-year-olds manage the first two skills well, while orientation on a flat piece of paper is a demanding task even for 7-year-olds. The exercises in notebooks or books so often used by therapists should definitely be preceded by exercises in natural conditions, i.e. in three-dimensional reality. Should we ignore these indications, based on the ontogenetic development, we cannot expect a child to improve her functioning.
PEMILIHAN MODEL PENENTUAN KELAYAKAN PINJAMAN ANGGOTA KOPERASI BERDASARKAN ALGORITMA SUPPORT VECTOR MACHINE, GENETIC ALGORITHMS, DAN NEURAL NETWORK

Saat ini kredit/pinjaman merupakan salah satu sumber keuntungan bisnis yang dengan resiko tinggi. Banyak metode klasifikasi telah diusulkan dalam literatur untuk mengatasi masalah ini. Tapi kebanyakan tidak diterima oleh para ahli karena berbagai alasan. Kebutuhan untuk mengetahui dan membedakan antara anggota baik dan yang buruk perlu dibangun sehingga pihak yang berkepentingan dapat mengambil salah satu tindakan pencegahan terjadinya masalah kredit macet. Dalam penelitian ini dilakukan Support vector macine, Genetic Algorithms, dan Neural Network terhadap data Anggota yang mendapat pembiayaan kredit/pinjaman koperasi baik yang bermasalah dalam pembayaran angsurannya maupun tidak. Dari hasil pengujian dengan mengukur kinerja ketiga algoritma tersebut menggunakan metode pengujian Cross Validation, Confusion Matrix dan Kurva ROC, diketahui bahwa algoritma GA memiliki nilai accuracy paling tinggi, yaitu 85.25%, diikuti oleh metode SVM dengan accuracy sebesar 83.50% dan yang terendah adalah metode NN dengan nilai accuracy 74.75%. Nilai AUC untuk metode GA juga menunjukkan nilai tertinggi, yaitu 0.776 disusul metode SVM dengan nilai AUC sebesar 0.760, dan yang terendah adalah nilai AUC NN, yaitu 0.714. Melihat nilai AUC dari ketiga metode tersebut maka ketiganya termasuk kelompok klasifikasi cukup karena nilai AUC-nya antara 0.70-0.80. Kata kunci: Support vector machine, Genetixc Algorithms, Neural Network, Receiver Operating Charactheristic, Confusion Matrix
Multilocus Sequence Analysis for Assessment of the Biogeography and Evolutionary Genetics of Four Bradyrhizobium Species That Nodulate Soybeans on the Asiatic Continent

ABSTRACT A highly supported maximum-likelihood species phylogeny for the genus Bradyrhizobium was inferred from a supermatrix obtained from the concatenation of partial atpD, recA, glnII, and rpoB sequences corresponding to 33 reference strains and 76 bradyrhizobia isolated from the nodules of Glycine max (soybean) trap plants inoculated with soil samples from Myanmar, India, Nepal, and Vietnam. The power of the multigene approach using multiple strains per species was evaluated in terms of overall tree resolution and phylogenetic congruence, representing a practical and portable option for bacterial molecular systematics. Potential pitfalls of the approach are highlighted. Seventy-five of the isolates could be classified as B. japonicum type Ia (USDA110/USDA122-like), B. liaoningense, B. yuanmingense, or B. elkanii, whereas one represented a novel Bradyrhizobium lineage. Most Nepalese B. japonicum Ia isolates belong to a highly epidemic clone closely related to strain USDA110. Significant phylogenetic evidence against the monophyly of the of B. japonicum I and Ia lineages was found. Analysis of their DNA polymorphisms revealed high population distances, significant genetic differentiation, and contrasting population genetic structures, suggesting that the strains in the Ia lineage are misclassified as B. japonicum. The DNA polymorphism patterns of all species conformed to the expectations of the neutral mutation and population equilibrium models and, excluding the B. japonicum Ia lineage, were consistent with intermediate recombination levels. All species displayed epidemic clones and had broad geographic and environmental distribution ranges, as revealed by mapping climate types and geographic origins of the isolates on the species tree.
Short —term electricity load forecasting based on SAPSO-ANN algorithm

Accurate forecasting of short-term electricity load has been one of the most important issues in the electricity industry. And the forecasting accuracy is influenced by many unpredicted factors. Artificial neural network is a novel type of learning method, which has been successfully employed to solve nonlinear regression and time series problems. In this paper, it is proposed a new optimal model to train ANN. The model that calls simulated annealing particle swarm optimization algorithm (SAPSO) combines the advantages of PSO algorithm and SA algorithm. The new model is proved to be able to enhance the accuracy and improve the convergence ability and reduce operation time by numerical experiment. Subsequently, examples of electricity load data from a city in China are used to illustrate the proposed SAPSO-ANN. Results show that forecasters trained by this method consistently produce lower prediction error than other methods.
Modelling spread with context-based dispersal strategies

Dispersal is a context-dependent adaptive trait. Different dispersal strategies arise as species need to optimize their fitness in the ever changing quality of habitats further imposed by abiotic and biotic factors. This work reviews the spread of populations under different dispersal strategies. Namely, we address the spread of a population when dispersal is driven by habitat fragmentations, density-dependent predation and mixed propagules. The context-based dispersal can explain a variety of range dynamics. It is of common accord however that the cause and effect of dispersal could have a wider effect on population dynamics that goes beyond purely ecological nature.
Generating an urban domain ontology through the merging of cross-domain lexical ontologies

In order to classify resources, digital libraries have traditionally used different types of lexical ontologies, which describe the terminology used in an area of knowledge. This paper analyzes how lexical ontologies covering different areas of knowledge can be merged to generate an enriched urban terminology. This work proposes a method to combine these different perspectives into a single network of urban related concepts. The objective of this network is to facilitate a draft for a more formal (non lexical) urban domain ontology.
The TTC 2014 Movie Database Case

Social networks and other web 2.0 platforms use huge amounts of data to offer new services to customers. Often this data can be expressed as huge graphs and thus could be seen as a potential new application field for model transformations. However, this application area requires that model transformation tools scale to models with millions of objects. This transformation case targets this application area by using the IMDb movie database as a model. The transformation deals with identifying all actor couples which perform together in a set of at least three movies.
CI and CO in the center of M 51

Received ? ; accepted ? Abstract. We present J=2-1, J=3-2, J=4-3 12 CO maps as well as J=2-1, J=3-2 13 CO and 492 GHz (CI) measurements of the central region in M 51. The distribution of CO is strongly concentrated towards the spiral arms. The center itself is poor in, though not devoid of, CO emission. The observed line intensities require modelling with a multi-component molecular gas. A dense component must be present (n(H2) � 10 3 ) with kinetic temperature Tkin � 100 K, combined with either a less dense (� 10 2 cm −3 ) component of the same temperature, or a more dense (n(H2) � 3 × 10 3 cm −3 ) and much cooler (Tkin = 10-30 K) component. Atomic carbon amounts are between 5 and 10 times those of CO. Much of the molecular gas mass is associated with the hot PDR phase. The center of M 51 has a face-on gas mass density of about 40 ± 20M⊙ pc −2 , and a well-established CO-to-H2
The Battle of the Screens: Unraveling Attention Allocation and Memory Effects When Multiscreening

Multiscreening, the simultaneous usage of multiple screens, is a relatively understudied phenomenon that may have a large impact on media effects. First, we explored people's viewing behavior while multiscreening by means of an eye-tracker. Second, we examined people's reporting of attention, by comparing eye-tracker and self-reported attention measures. Third, we assessed the effects of multiscreening on people's memory, by comparing people's memory for editorial and advertising content when multiscreening (television–tablet) versus single screening. The results of the experiment (N = 177) show that (a) people switched between screens 2.5 times per minute, (b) people were capable of reporting their own attention, and (c) multiscreeners remembered content just as well as single screeners, when they devoted sufficient attention to the content.
Exact and Approximate Algorithms for Unordered ' H E Matching

We consider the problem of comparison between unordered trees, i.e., trees for which the order among siblings is unimportant. The criterion for comparison is the distance as measured by a weighted sum of the costs of deletion, insertion and relabel operations on tree nodes. Such comparisons may contribute to pattern recognition efforts in any field (e.g., genetics) where data can naturally be characterized by unordered trees. In companion work, we have shown this problem to be NP-complete. This paper presents an efflcient enumerative algorithm and several heuristics leading to approximate solutions. The algorithms are based on probabilistic hill climbing and bipartite matching techniques. The paper evaluates the accuracy and time efficiency of the heuristics by applying them to a set of trees transformed from industrial parts based on a previously proposed morphological model.
Enhanced Stimulus Encoding Capabilities with Spectral Selectivity in Inhibitory Circuits by STDP

The ability to encode and transmit a signal is an essential property that must demonstrate many neuronal circuits in sensory areas in addition to any processing they may provide. It is known that an appropriate level of lateral inhibition, as observed in these areas, can significantly improve the encoding ability of a population of neurons. We show here a homeostatic mechanism by which a spike-timing-dependent plasticity (STDP) rule with a symmetric timing window (swSTDP) spontaneously drives the inhibitory coupling to a level that ensures accurate encoding in response to input signals within a certain frequency range. Interpreting these results mathematically, we find that this coupling level depends on the overlap of spectral information between stimulus and STDP window function. Generalization to arbitrary swSTDP and arbitrary stimuli reveals that the signals for which this improvement of encoding takes place can be finely selected on spectral criteria. We finally show that this spectral overlap principle holds for a variety of neuron types and network characteristics. The highly tunable frequency-power domain of efficiency of this mechanism, together with its ability to operate in very various neuronal contexts, suggest that it may be at work in most sensory areas.