Miracle-dz/UniFAR-FTUs huggingface dataset:
PRACTICES AND TRENDS IN GEOSPATIAL CHANGE DETERMINATION

There is a constant effort by the data providers to maintain up-to-date geospatial databases. Multi-temporal coverage of the same geographic area using aerial and satellite images and airborne laser scanning data is the most common approach for directly generating and updating geo-databases from raw source data. Geo-databases can also be updated indirectly from multi-source multiscale up-to-date geo-databases. The patterns of spatial changes in the existing data sets are detected and determined by determining mismatches in the state of a feature over different times. For the determination of spatial changes it is essential that the multitemporal multi-source data sets are co-registered by mapping one data set over the other using appropriate transformation functions. Invariant corresponding features are matched between the two data sets for the determination of the transformation parameters. The methods and quality of data alignment are important in order to reduce registration errors as any difference is interpreted as potential change. In the actual determination of spatial changes factors such as level of change detection, types of data used for change detection, level of processing, types of changes, and turn-around time all influence the method applied. The change detection methods between existing and new features are based on approaches, which depend on the data types, level of pre-processing and on proximity and/or similarity measures. In this paper, using examples, we present methods and common practices applied for change determination in vector databases and identify trends for future approaches. Emphasis is on the use of automated methods due to the increasing data volumes and new types of data.
Propeller: A Scalable Metadata Organization for A Versatile Searchable File System

The exponentially increasing amount of data in file systems has made it increasingly important for file systems to provide fast file-search services. The quality of the file-search services is significantly affected by the file-index overhead, the file-search responsiveness and the accuracy of search results. Unfortunately, the existing file-search solutions either are so poorly scalable that their performance degrades unacceptably when the systems scale up, or incur so much crawling delays that they produce acceptably inaccurate results. We believe that the time is ripe for the re-designing of a searchable file system capable of accurate and scalable system-level file search. The main challenge facing the design and implementation of such a searchable file system is how to update file indices in a real-time and scalable way to obtain accurate file-search results. Thus we propose a lightweight and scalable metadata organization, Propeller, for the envisioned searchable file system. Propeller partitions the namespace according to file-access patterns, which exposes massive parallelism for the emerging manycore architecture to support future searchable file systems. The extensive evaluation results of our Propeller prototype show that it achieves significantly better file-indexing and file-search performance (up to 250×) than a centralized solution (MySQL) and only incurs negligible overhead (< 16%) to the normal file I/O operations and faster direct access performance (16.6×) on a state-ofthe-art file system (Ext4). Furthermore, the 100% recall accuracy ensures Propeller offering a feasible metadata scheme for the system-level file-search services.
Detailed Examination of a Single Conduction Event in a Potassium Channel

Although extensively studied, it has proved difficult to describe in detail how potassium ion channels conduct cations and water. We present a computational study that, by using stratified umbrella sampling, examines nearly an entire conduction event of the Kv1.2/2.1 paddle chimera and thereby identifies the expected stable configurations of ions and waters in the selectivity filter of the channel. We describe in detail the motions of the ions and waters during a conduction event, focusing on how waters and ions enter the filter, the rotation of water molecules inside the filter, and how potassium ions are coordinated as they move from a water to a protein environment. Finally, we analyze the small conformational changes undergone by the protein, showing that the stable configurations are most similar to the experimental crystal structure.
Fast and globally optimal single view reconstruction of curved objects

We propose a novel algorithmic solution for estimating a three-dimensional model of an object observed in a single image. Based on a minimal user input, the algorithm interactively determines the objects' silhouette and subsequently computes a silhouette-consistent 3D model which is precisely the globally minimal surface with user-specified volume. In contrast to a recently published approach to single view reconstruction, the proposed algorithm does not constrain the resolution in the depth-direction, it assures the global optimum and is faster by about an order of magnitude. Experiments demonstrate that plausible high-resolution 3D models can be generated in fractions of a second and compare favorably with other methods.
50 years of hormonal contraception—time to find out, what it does to our brain

Hormonal contraceptives are on the market for more than 50 years and used by 100 million women worldwide. However, while endogenous steroids have been convincingly associated with change in brain structure, function and cognitive performance, the effects of synthetic steroids contained in hormonal contraceptives on brain and cognition have barely been investigated. In this article we summarize the sparse findings, describing brain structural, functional and behavioral findings from the literature and suggest that synthetic steroids may contribute to masculinizing as well as feminizing effects on brain and behavior. We try to identify methodological challenges, explain, how results on endogenous steroids may transfer into research on hormonal contraceptives and point out factors that need to be controlled in the study of hormonal contraceptive dependent effects. We conclude that there is a strong need for more systematic studies, especially on brain structural, functional and cognitive changes due to hormonal contraceptive use. The hormonal contraceptive pill is the major tool for population control. Hence, such behavioral changes could cause a shift in society dynamics and should not stay unattended.
TSimNet: An Industrial Time Sensitive Networking Simulation Framework Based on OMNeT++

The upcoming IEEE Time Sensitive Networking standard will offer a set of new functionality for Ethernet like frame preemption and frame replication that need careful evaluation. The IETF DetNet working group also works on deterministic layer 3 segments and leverages therefore works from the IEEE group. We present here a simulation framework based on OMNeT++ that implements all non time-based features present in TSN in a modular and easily extendable way. The framework gives other researches a stable base to start evaluating existing and future scenarios. An evaluation of frame preemption as well as per-stream policing based on the framework is presented. It was shown, that frame preemption does not always bring latency advantages and highly depends on configuration of the system. The paper concludes with an overview of the computational cost for the use of this framework.
Global statistics of liquid water content and effective number concentration of water clouds over ocean derived from combined CALIPSO and MODIS measurements

This study presents an empirical relation that links the volume extinction coefficients of water clouds, the layer integrated depolarization ratios measured by lidar, and the effective radii of water clouds derived from collocated passive sensor observations. Based on Monte Carlo simulations of CALIPSO lidar observations, this method combines the cloud effective radius reported by MODIS with the lidar depolarization ratios measured by CALIPSO to estimate both the liquid water content and the effective number concentration of water clouds. The method is applied to collocated CALIPSO and MODIS measurements obtained during July and October of 2006, and January 2007. Global statistics of the cloud liquid water content and effective number concentration are presented.
Multiple Cartesian K-Medoids for a Fine Quantization

K-means is a widely used method for the process of vector quantization in image retrieval, and its results will directly affect the subsequent retrieval quality. Although k-means is popular in image retrieval, it has some obvious disadvantages, such as randomness and sensitivity to outliers. This paper presents a new model, namely Multiple Cartesian K-medoids, to replace k-means for quantization and retrieval. The proposed model proceeds in two steps. The first step is to establish multiple K-medoids model to finely quantize feature vectors to codewords. Then, the second step establishes local linear search: adopt an inverted file for efficiently searching candidate nearest neighbors of a given query, and finally obtains accurate neighbors of the query by re-ranking these candidate neighbors with Euclidean distances of the original feature vectors. Experimental results show that the proposed method is effective, and substantially improves the search accuracy of the returned nearest neighbors.
Decreased serum brain-derived neurotrophic factor (BDNF) is associated with post-stroke depression but not with BDNF gene Val66Met polymorphism

Abstract Background: Decreased brain-derived neurotrophic factor (BDNF) has been demonstrated in animal models and patients with depression. However, little is known about changes in BDNF in post-stroke depression (PSD). This study investigated the changes in serum BDNF in patients with PSD, and evaluated whether serum concentrations of BDNF were associated with BDNF gene Val66Met polymorphism. Methods: PSD patients were diagnosed in accordance with DSM-IV criteria, and the severity of depression was evaluated with the Hamilton Rating Scale for depression. Serum BDNF was measured twice, first at 7 days after the onset of stroke and then at 3–6 months after stroke. Val66Met polymorphisms of the BDNF gene were determined using the polymerase chain reaction-restriction fragment length polymorphism method. BDNF concentrations and Val66Met polymorphisms were also measured in 30 healthly controls. Results: A total of 93 patients admitted as a result of first time acute ischemic stroke were included. During the 6-month follow-up, 35 patients (37.6%) were diagnosed with PSD. Serum BDNF concentrations were decreased in PSD patients at 3–6 months after stroke (p<0.05). The serum BDNF concentrations were not associated with BDNF gene Val66Met polymorphisms in either patients or healthy controls. Conclusions: Serum concentrations of BDNF decrease in PSD patients and BDNF may play an important role in the pathogenesis of PSD. However, Val66Met polymorphisms are not associated with serum concentrations of BDNF. The mechanism of decreased serum BDNF requires further study.
Global Stabilization of Nonlinear Systems Based on Vector Control Lyapunov Functions

This paper studies the use of vector Lyapunov functions for the design of globally stabilizing feedback laws for nonlinear systems. Recent results on vector Lyapunov functions are utilized. The main result of the paper shows that the existence of a vector control Lyapunov function is a necessary and sufficient condition for the existence of a smooth globally stabilizing feedback. Applications to nonlinear systems are provided: practically checkable sufficient conditions are proposed to guarantee the existence of a smooth globally stabilizing feedback law. The obtained results are applied to the problem of the stabilization of an equilibrium point of a reaction network taking place in a continuous stirred tank reactor.
Kinship Verification

Kinship verification from facial images is a challenging problem in computer vision and research is going on in this area. In this system, we have used neighborhood repulsed metric learning (NRML) method for kinship verification. Motivated by the fact that interclass samples (without kinship relations) with higher similarity usually lie in a neighbourhood and are more easily misclassified than those with lower similarity. The proposed system uses this distance metric and classifies the test pair of images as kinship or nonkinship relation.
Oily Fish Consumption Modifies the Association between CD36 rs6969989 Polymorphism and Lipid Profiles in Korean Women

The aim of this study was to investigate the association of CD36, a class B scavenger receptor, rs6969989 polymorphism with the serum lipid profiles in Korean women, together with their modulation by oily fish consumption. Subjects were participants from the Korean Genome Epidemiology Study (KoGES), which was initiated in 2001 as a large-scale. A total of 4,210 women aged 39 to 70 were included in this study. Data were collected using self-administered questionnaires, anthropometric measurements, and blood chemical analysis. Dietary intake was analyzed using a semi-quantitative food frequency questionnaire. The minor allele frequency for rs6969989 was found in 12% of this population. Homozygotes minor G allele at the rs6868989 exhibited significantly higher high density lipoprotein cholesterol (HDL-C) concentrations (P-trend=0.043) and lower fasting glucose (P-trend=0.013) than major allele A carriers. The risk of low HDL-C was significantly lower in homozygotes for the G allele than the A allele carriers (P-trend=0.032). Gene-diet interaction effects between rs6969989 and oily fish intake were significantly associated with the risk of dyslipidemia (P-interaction= 0.004). Subjects with homozygotes minor G allele and high oily fish intake generally had a lower risk of dyslipidemia than did those with major allele homozygotes and low oily fish intake. These findings supported that oily fish consumption may modulate the contributions of CD36 rs6969989 on genetic predisposition to the risk of dyslipidemia.
VALIDAÇÃO DE INSTRUMENTO DE AVALIAÇÃO DA ALFABETIZAÇÃO CIENTÍFICA PARA EGRESSOS DO ENSINO MÉDIO NO CONTEXTO DA FÍSICA DO TRÂNSITO

RESUMO: Apresentamos o procedimento de validação de um instrumento para verificação de aspectos da Alfabetização Científica para egressos do Ensino Médio. O questionário dividiu-se em questões sobre conceitos da física aplicada em situações do trânsito e sobre características do perfil das aulas de Física assistidas pelos egressos durante o Ensino Médio. Contando inicialmente com 64 itens, os mesmos foram avaliados quanto ao seu conteúdo por professores da área e posteriormente, através de testes estatísticos, estimou-se os quantitativos de validação e confiabilidade. Ao final, 19 itens foram removidos e obteve-se um instrumento considerado válido e fidedigno com 25 itens sobre física no trânsito e 20 itens sobre o perfil do Ensino de Física, com fins de utilização para avaliação da alfabetização científica.
Clustering fusion with automatic cluster number

Most of the real world applications use data clustering techniques for effective data analysis. All clustering techniques have some assumptions on the underlying dataset. We can get accurate clusters if the assumptions hold good. But it is difficult to satisfy all assumptions. Currently, not a single clustering algorithm is available to find all types of cluster shapes and structures. Therefore, an ensemble clustering algorithm is proposed in this paper in order to produce accurate clusters. Moreover, the existing clustering ensemble methods require more number of clusters in advance to produce final clusters. In this paper, we propose a novel method which groups a set of clusters into accurate final clusters to enhance the decision accuracy. This method does not need the number of clusters as input but produces the clusters automatically assuming the no of clusters.
Adaptation Perspective in Implementing Physical Education in Schools

Education curriculum is a program that constantly changes and develops in line the advancement of society and nation. Development and curriculum change does not happen by itself but is caused by factors that will lead to positive effects (Fullan, 2001). Curriculum development and change is indeed necessary because the community, students, resources and innovation inn teaching are changing from time to time (Marsh & Willis, 2007). The subject curriculum is formulated based on a philosophy and formation of appropriate curriculum whether in the aspect of idealism, realism, naturalism, pragmatism and existentialism (Annarino, Cowell, & Hazelton, 1980; Kelly & Melograno, 2004), aimed at tapping the potential of students from three domains of learning.
Potential Role of Notch Signalling in CD34+ Chronic Myeloid Leukaemia Cells: Cross-Talk between Notch and BCR-ABL

Notch signalling is critical for haemopoietic stem cell (HSC) self-renewal and survival. The role of Notch signalling has been reported recently in chronic myeloid leukaemia (CML) – a stem cell disease characterized by BCR-ABL tyrosine kinase activation. Therefore, we studied the relationship between BCR-ABL and Notch signalling and assessed the expression patterns of Notch and its downstream target Hes1 in CD34+ stem and progenitor cells from chronic-phase CML patients and bone marrow (BM) from normal subjects (NBM). We found significant upregulation (p<0.05) of Notch1, Notch2 and Hes1 on the most primitive CD34+Thy+ subset of CML CD34+ cells suggesting that active Notch signalling in CML primitive progenitors. In addition, Notch1 was also expressed in distinct lymphoid and myeloid progenitors within the CD34+ population of primary CML cells. To further delineate the possible role and interactions of Notch with BCR-ABL in CD34+ primary cells from chronic-phase CML, we used P-crkl detection as a surrogate assay of BCR-ABL tyrosine kinase activity. Our data revealed that Imatinib (IM) induced BCR-ABL inhibition results in significant (p<0.05) upregulation of Notch activity, assessed by Hes1 expression. Similarly, inhibition of Notch leads to hyperactivation of BCR-ABL. This antagonistic relationship between Notch and BCR-ABL signalling was confirmed in K562 and ALL-SIL cell lines. In K562, we further validated this antagonistic relationship by inhibiting histone deacetylase (HDAC) - an effector pathway of Hes1, using valproic acid (VPA) - a HDAC inhibitor. Finally, we also confirmed the potential antagonism between Notch and BCR/ABL in In Vivo, using publically available GSE-database, by analysing gene expression profile of paired samples from chronic-phase CML patients pre- and post-Imatinib therapy. Thus, we have demonstrated an antagonistic relationship between Notch and BCR-ABL in CML. A combined inhibition of Notch and BCR-ABL may therefore provide superior clinical response over tyrosine-kinase inhibitor monotherapy by targeting both quiescent leukaemic stem cells and differentiated leukaemic cells and hence must be explored.
Pedunculopontine Tegmental Nucleus Controls Conditioned Responses of Midbrain Dopamine Neurons in Behaving Rats

Midbrain dopamine (DA) neurons respond to sensory cues that predict reward. We tested the hypothesis that projections from the pedunculopontine tegmental nucleus (PPTg) are involved in driving this DA cell activity. First, the activity of PPTg and DA neurons was compared in a cued-reward associative learning paradigm. The majority of PPTg neurons showed phasic responses to the onset of sensory cues, at significantly shorter latency than DA cells, consistent with a PPTg-to-DA transmission of information. However, unlike DA cells, PPTg responses were almost entirely independent of whether signals were associated with rewards. Second, DA neuron responses to the cues were recorded in free-moving rats during reversible inactivation of the PPTg by microinfusion of local anesthetic. The results showed clear suppression of conditioned sensory responses of DA neurons after PPTg inactivation that was not seen after saline infusion or in non-DA cells. We propose that the PPTg relays information about the precise timing of attended sensory events, which is integrated with information about reward context by DA neurons.
3D Face recognition using Tensor Orthogonal Locality Sensitive Discriminant Analysis

In this paper, a novel appearance-based method that called Tensor Orthogonal Locality Sensitive Discriminât Analysis (Tensor OLSDA) is presented for 3D face recognition. Our algorithm is motivated by the Locality Sensitive Discriminant Analysis (LSDA) algorithm, which aims at finding a projection by maximizing the margin between data points from different classes at each local area. However, LSDA is expressed in the form of 1-D vectors and this makes it difficult to estimate the intrinsic dimensionality and to reconstruct the face data. Furthermore, the object reconstruction criterion of LSDA is non-orthogonality which distorts the local geometrical structure of the data submanifold. In this paper, Tensor OLSDA as a new object reconstruction criterion is proposed to efficiently preserve the neighborhood geometrical structure according to the Locality Sensitive Discriminant Analysis (LSDA), and the locality preserving ability is enforced by computing the mutually orthogonal basis functions iteratively with tensor data representation. Experiments on CASIA 3D face database also show the impressive performance of the proposed method.
Performance Bounds for Remote Estimation under Energy Harvesting Constraints

Remote estimation with an energy harvesting sensor with a limited data and energy buffer is considered. The sensor node observes an unknown Gaussian field and communicates its observations to a remote fusion center using the energy it harvested. The fusion center employs minimum mean-square error (MMSE) estimation to reconstruct the unknown field. The distortion minimization problem under the online scheme, where the sensor has access to only the statistical information for the future energy packets is considered. We provide performance bounds on the achievable distortion under a slotted block transmission scheme, where at each transmission time slot, the data and the energy buffer are completely emptied. Our bounds provide insights to the trade-offs between the buffer sizes, the statistical properties of the energy harvesting process and the achievable distortion. In particular, these trade-offs illustrate the insensitivity of the performance to the buffer sizes for signals with low degree of freedom and suggest performance improvements with increasing buffer size for signals with relatively higher degree of freedom. Depending only on the mean, variance and finite support of the energy arrival process, these results provide practical insights for the battery and buffer sizes for deployment in future energy harvesting wireless sensing systems.