Miracle-dz/UniFAR-FTUs huggingface dataset:
THE ESTIMATION OF BIRDSONG CONTROL PARAMETERS USING MAXIMUM LIKELIHOOD AND MINIMUM ACTION

In this research, a method is presented for extracting the control parameters of an avian syrinx synthesis model from recorded birdsong. A look-up table pairs combinations of pressure and tension parameters with the model’s corresponding output power spectra. At each time frame, a generalized likelihood ratio fills a pressuretension matrix indicating similarity between the birdsong power spectrum and the tabulated spectra. Successive pressure-tension matrices are stacked and points exhibiting a good fit to the data align to form trajectories corresponding to changes in pressure and tension over time which can then be used to control the model. In the event a range of trajectories matches the data well, the selected trajectory is that of least action. A physical model of the bird’s vocal tract was developed using waveguide synthesis techniques for the bronchi and trachea tubes and finite difference methods for the nonlinear vibrating syringeal membranes [1, 2]. In order to judge the model’s ability to produce realistic birdsong, and also to improve playability of the model by limiting the parameter space, we have devised a method for extracting the two primary control parameters of the model, pressure and tension, from recorded birdsong. We employ a maximum likelihood approach illustrated in Fig. 3 to extract pressure and tension trajectories. Recorded birdsong is segmented and the power spectra frames are compared to tabulated model power spectra using a likelihood function to indicate goodness of fit. Those control parameter sets having large likelihood at each frame are then aligned to form trajectories over time. Finally, the trajectories are adjusted to account for the ability of the bird to generate and change pressure and tension. We begin by briefly outlining aspects of the avian syrinx model to give context to the discussion that follows. The maximum likelihood approach is described and the likelihood function detailed. The method is then applied to a field recording of a zebra finch.
Domain Swapping and Different Oligomeric States for the Complex Between Calmodulin and the Calmodulin-Binding Domain of Calcineurin A

Background Calmodulin (CaM) is a ubiquitously expressed calcium sensor that engages in regulatory interactions with a large number of cellular proteins. Previously, a unique mode of CaM target recognition has been observed in the crystal structure of a complex between CaM and the CaM-binding domain of calcineurin A. Methodology/Principal Findings We have solved a high-resolution crystal structure of a complex between CaM and the CaM-binding domain of calcineurin A in a novel crystal form, which shows a dimeric assembly of calmodulin, as observed before in the crystal state. We note that the conformation of CaM in this complex is very similar to that of unliganded CaM, and a detailed analysis revels that the CaM-binding motif in calcineurin A is of a novel ‘1-11’ type. However, using small-angle X-ray scattering (SAXS), we show that the complex is fully monomeric in solution, and a structure of a canonically collapsed CaM-peptide complex can easily be fitted into the SAXS data. This result is also supported by size exclusion chromatography, where the addition of the ligand peptide decreases the apparent size of CaM. In addition, we studied the energetics of binding by isothermal titration calorimetry and found them to closely resemble those observed previously for ligand peptides from CaM-dependent kinases. Conclusions/Significance Our results implicate that CaM can also form a complex with the CaM-binding domain of calcineurin in a 1∶1 stoichiometry, in addition to the previously observed 2∶2 arrangement in the crystal state. At the structural level, going from 2∶2 association to two 1∶1 complexes will require domain swapping in CaM, accompanied by the characteristic bending of the central linker helix between the two lobes of CaM.
Prediction of time series using Yule-Walker equations with kernels

The autoregressive (AR) model is a well-known technique to analyze time series. The Yule-Walker equations provide a straightforward connection between the AR model parameters and the covariance function of the process. In this paper, we propose a nonlinear extension of the AR model using kernel machines. To this end, we explore the Yule-Walker equations in the feature space, and show that the model parameters can be estimated using the concept of expected kernels. Finally, in order to predict once the model identified, we solve a pre-image problem by getting back from the feature space to the input space. We also give new insights into the convexity of the pre-image problem. The relevance of the proposed method is evaluated on several time series.
Gene expression analysis of aberrant signaling pathways in meningiomas

Examining aberrant pathway alterations is one method for understanding the abnormal signals that are involved in tumorigenesis and tumor progression. In the present study, expression arrays were performed on tumor-related genes in meningiomas. The GE Array Q Series HS-006 was used to determine the expression levels of 96 genes that corresponded to six primary biological regulatory pathways in a series of 42 meningiomas, including 32 grade I, four recurrent grade I and six grade II tumors, in addition to three normal tissue controls. Results showed that 25 genes that were primarily associated with apoptosis and angiogenesis functions were downregulated and 13 genes frequently involving DNA damage repair functions were upregulated. In addition to the inactivation of the neurofibromin gene, NF2, which is considered to be an early step in tumorigenesis, variations of other biological regulatory pathways may play a significant role in the development of meningioma.
EpCAM Aptamer-mediated Survivin Silencing Sensitized Cancer Stem Cells to Doxorubicin in a Breast Cancer Model

Understanding the molecular basis of drug resistance and utilising this information to overcome chemoresistance remains a key challenge in oncology. Here we report that survivin, a key protein implicated in drug resistance, is overexpressed in cancer stem cell pool of doxorubicin-resistant breast cancer cells. Moreover, by utilising an active targeting system consisting of an RNA aptamer targeted against the epithelial cell adhesion molecule and a Dicer substrate survivin siRNA, we could deliver a high dose of the siRNA to cancer stem cells in xenograft tumours. Importantly, silencing of survivin with this aptamer-siRNA chimera in cancer stem cell population led to the reversal of chemoresistance, such that combined treatment with low dose of doxorubicin inhibited stemness, eliminated cancer stem cells via apoptosis, suppressed tumour growth, and prolonged survival in mice bearing chemoresistant tumours. This strategy for in vivo cancer stem cell targeting has wide application for future effective silencing of anti-death genes and in fact any dysregulated genes involved in chemoresistance and tumour relapse.
Towards Service Discovery and Subscription based on Community-of-Interest

Current service discovery and subscription are "provider-centric " indeed, which costs the consumers too many efforts and makes the wide spectrum of QoS hard to use. In this position paper, we propose a "consumer-centric" service discovery and subscription approach. The core idea is derived from the "community-of-interest (CoI)" concept, which means the services with same or similar functionalities can form a community of the consumer's interest. This approach facilitates the consumers in three ways. Firstly, it simplifies the service discovery for the consumers who can "purely" care about the functionality and qualities instead of the providers. Secondly, it optimizes the service subscription for the consumers who just subscribe the CoI instead of a single and monolithic service provider while the COI takes charge of matching and scheduling the "best-of-breed" service automatically. Thirdly, it incarnates the wide spectrum of QoS to the consumers who will face with all possible QoS supported by the services in the CoI. The supporting framework is discussed and some key technical issues are demonstrated
Slip detection by array-type pressure sensor for a grasp task

This paper proposes a useful method to detect the incipient slip by using array-type pressure sensors planted into the soft skin of the fingertip based on the vibration power of the pressure center. In order to use the same threshold value to judge the incipient slip in different grasping forces, a weight coefficient is identified by experiments and it is used in the proposed slip-judge function. Experimental results show that the incipient slip can be detected by using the same threshold value under conditions of different material objects, different slipping speeds and different grasping forces. In addition, the slip detection method was proved to be repeatable by many experiments in the same conditions.
Expression of Angiopoietin-1 in Human Glioblastomas Regulates Tumor-Induced Angiogenesis: In Vivo and In Vitro Studies

Abstract— To define a role for the angiopoietin/Tie2 system in astrocytoma angiogenesis, we examined the expression of angiopoietin-1 (Ang1) and angiopoietin-2 (Ang2) in these tumors by immunohistochemistry and in situ hybridization. Furthermore, we studied in vitro the effects elicited by glioblastoma cell-secreted Ang1 or by recombinant Ang1 on functions of endothelial cells (ECs). Our observations of astrocytomas show that a stage-specific induction of angiopoietins occurs and is correlated with angiogenic phases of different intensity. Ang1 expression was found in a few astrocytes scattered in the tumor at all stages of astrocytoma progression. In blood vessels, Ang1 mRNA increased progressively in high-grade glioblastomas, in which the number of vessels was higher than in low-grade tumors. Ang2 was detected in tumor cells and in ECs in high-grade astrocytomas, whereas its expression was negligible in low-grade tumors. Coculture of glioblastoma cell lines producing Ang1 with endothelium demonstrated a key role of this ligand in the control of EC network organization. We found that recombinant Ang1 in vitro induces EC spreading and reorganization of the cell monolayer into cordlike structures. These results suggest that Ang1 directly acts on ECs by modulating cell-cell and cell-matrix associations and promoting the differentiation phase of angiogenesis.
Flexible microphone array based on multichannel nonnegative matrix factorization and statistical signal estimation

In this paper, we propose a novel source separation method for the hose-shaped rescue robot based on multichannel nonnegative matrix factorization (MNMF) and statistical speech enhancement. The rescue robot is aimed to detect victims’ speech in a disaster area, wearing multiple microphones around the body. Different from the common microphone array, the positions of microphones are unknown, and the conventional beamformer cannot be utilized. In addition, the vibration noise (ego-noise) is generated when the robot moves, yielding the serious contamination in the observed signals. Therefore, it is important to eliminate the ego-noise in this system. Blind source separation is a technique taken to separately estimate the sources without knowing the sensors’ positions. Several methods, e.g., independent component analysis, independent vector analysis, and spatially rank-1 MNMF (Rank-1 MNMF) have been proposed so far, but their separation performance is not sufficient. To address this problem, in this study, first, supervised Rank-1 MNMF is proposed, thanks to the stationary properties of the ego-noise, where we train spectral bases of the ego-noise in advance. Secondly, to reduce the mismatch problem between the trained bases and the spectrogram in observed data, we propose an algorithm that an all-pole model is estimated to deform the bases using the reliable spectral components sampled by the statistical signal enhancement method. Thirdly, we propose to initialize Rank-1 MNMF by using the low-rank representation of the estimated speech spectrogram, and improve the convergence. Finally, we reveal that the proposed method outperforms the conventional methods in the source separation accuracy via experiments with actual sounds observed in the rescue robot.
Automatically repairing test cases for evolving method declarations

When software systems evolve, for example due to fault fixes, modification of functionalities or refactoring activities, test cases may become obsolete thus generating wrong results or even not being executable or compilable. Maintaining test cases is expensive and time consuming, and often test cases are discarded by software developers due to high maintenance costs. This paper presents TestCareAssistant, a technique that combines data-flow analysis with program diffing for automatically repairing test cases that become obsolete because of changes in method declarations (addition, removal, or type modification of parameters or return values). The paper illustrates the efficacy of TestCareAssistant by analyzing the impact of method declarations changes on the executability of test cases, and by presenting the preliminary results of applying TestCareAssistant to repair 22 test cases.
The role of the centriolar region in animal cell mitosis. A laser microbeam study

An argon ion laser microbeam (488 and 514 nm) was used to selectively irradiate one of the two centriolar regions of rat kangaroo Potorous tridactylis (PtK2) prophase cells in vitro. The cells were sensitized to the laser radiation by treatment with acridine orange (0.1-0.2 mug/ml). Ultrastructural examination of the irradiated centriolar regions demonstrated that the primary site of damage was the pericentriolar material. This result suggests that nucleic acid is present in the pericentriolar material. Behavioral and ultrastructural analysis demonstrated that cells with one damaged pericentriolar zone could undergo (a) nuclear membrane breakdown, (b) chromosome condensation, (c) metaphase plate formation, and (d) cytokinesis. However, the chromosomes neither separated nor exhibited any anaphase movements. Detailed ultrastructural analysis revealed the presence of kinetochore microtubules on both sides of chromosome mass and a lack of microtubules in the cytokinesis constriction. These results indicate that the pericentriolar material is important in spindle orgainization and essential for the formation of the interpolar microtubules.
Asymptotic Error Expansions for the Finite Element Method for Second Order Elliptic Problems in RN, N>=2. I: Local Interior Expansions

Our aim here is to give sufficient conditions on the finite element spaces near a point so that the error in the finite element method for the function and its derivatives at the point have exact asymptotic expansions in terms of the mesh parameter $h$, valid for $h$ sufficiently small. Such expansions are obtained from the so-called asymptotic expansion inequalities valid in $\mathbf{R}^N$ for $N\geq2$, studies by Schatz in [Math. Comp., 67 (1998), pp. 877-899] and [SIAM J. Numer. Anal. , 38 (2000), pp. 1269-1293].
Solutions to Detect and Analyze Online Radicalization : A Survey

Online Radicalization (also called Cyber-Terrorism or Extremism or Cyber-Racism or Cyber- Hate) is widespread and has become a major and growing concern to the society, governments and law enforcement agencies around the world. Research shows that various platforms on the Internet (low barrier to publish content, allows anonymity, provides exposure to millions of users and a potential of a very quick and widespread diffusion of message) such as YouTube (a popular video sharing website), Twitter (an online micro-blogging service), Facebook (a popular social networking website), online discussion forums and blogosphere are being misused for malicious intent. Such platforms are being used to form hate groups, racist communities, spread extremist agenda, incite anger or violence, promote radicalization, recruit members and create virtual organi- zations and communities. Automatic detection of online radicalization is a technically challenging problem because of the vast amount of the data, unstructured and noisy user-generated content, dynamically changing content and adversary behavior. There are several solutions proposed in the literature aiming to combat and counter cyber-hate and cyber-extremism. In this survey, we review solutions to detect and analyze online radicalization. We review 40 papers published at 12 venues from June 2003 to November 2011. We present a novel classification scheme to classify these papers. We analyze these techniques, perform trend analysis, discuss limitations of existing techniques and find out research gaps.
How can preclinical mouse models be used to gain insight into prefrontal cortex dysfunction in obsessive-compulsive disorder?

Obsessive-compulsive disorder is a debilitating psychiatric disorder that is characterised by perseverative thoughts and behaviours. Cognitive and affective disturbances play a central role in this illness, and it is therefore not surprising that clinical neuroimaging studies have demonstrated widespread alterations in prefrontal cortex functioning in patients. Preclinical mouse experimental systems provide the opportunity to gain mechanistic insight into the neurobiological changes underlying prefrontal cortex dysfunction through new technologies that allow measurement and manipulation of activity in discrete neural populations in awake, behaving mice. However, recent preclinical research has focused on striatal dysfunction, and has therefore provided relatively little insight regarding the role of the prefrontal cortex in obsessive-compulsive disorder–relevant behaviours. Here, we will discuss a number of translational prefrontal cortex–dependent paradigms, including obsessive-compulsive disorder–relevant tasks that produce compulsive responding, and how they can be leveraged in this context. Drawing on recent examples that have led to mechanistic insight about specific genes, cell types and circuits that mediate prefrontal cortex contributions to distinct aspects of cognition, we will provide a framework for applying similar strategies to identify neural mechanisms underlying obsessive-compulsive disorder–relevant behavioural domains. We propose that research using clinically relevant paradigms will accelerate translation of findings from preclinical mouse models, thus supporting the development of novel therapeutics targeted to specific pathophysiological mechanisms.
The improvement of caching strategies about unstructured P2P system

Improving cache replacement strategies is an important way to enhance the performance of network. As the lack of cache replacement strategies about P2P systems, the author proposes the corresponding improvement measures and designs a new cache replacement strategy - MFU (Most Frequently Used). This algorithm aims to achieve high-degree peers to delete popular contents and low-degree ones hold popular contents by setting threshold properly, thus reducing the maximum load of peers. And then, using Gnutella system as network model, the author compares MFU with LRU, LFU and ARP through simulation experiment to prove the advantage of hit rate and load balancing about MFU.
Phylogenetic Bootstrapping under Resource Constraints: Higher Model Accuracy or more Replicates?

some cases even lead to the shutdown of relatively new and powerful facilities. This recent development has lead to a new research area in high performance computing called power-aware computing. Following this trend, the so-called green500 list (http://www.green500.org/) that covers the 500 most energy efficient supercomputers in the world was introduced. This list only partially overlaps with the “classic” top500 list (http://www.top500.org/) that comprises the most powerful supercomputers worldwide. Thus, taking into account this trend in computer architectures and energy prices, combined with the current molecular data explosion and rapidly growing alignment sizes we address the following question: Given a certain amount of time- or cost-constrained computational resources (CPU hours), how can those limited resources best be used for accurate phylogeny reconstruction? We intend to determine the trade-off, by means of the relative topological accuracy, between investing resources into optimization of per-bootstrap (bootstrapping: see below) replicate ML model parameters at the expense of computing less replicates versus superficial model parameter optimization for the sake of computing more replicates. The general Bootstrapping procedure is a well-established computer-based statistical method to obtain nonparametric error estimates (Efron, 1979), by inferring the variability in an unknown distribution from which the data (bootstrap replicates) was drawn by re-sampling from the original data. The seminal paper by Joe Felsenstein (Felsenstein, 1985), introduced the application of the
de Travail du Centre d ’ Economie de la Sorbonne How to Improve Pupils ’ Literacy ? A Cost-Effectiveness Analysis of a French Educational Project

The Action Lecture program is an innovative teaching method run in some nursery and primary schools in Paris and designed to improve pupils’ literacy. We report the results of an evaluation of this program. We describe the experimental protocol that was built to estimate the program’s impact on several types of indicators. Data were processed following a Differences-in-Differences (DID) method. Then we use the estimation of the impact on academic achievement to conduct a costeffectiveness analysis and take a reduction of the class size program as a benchmark. The results are positive for the Action Lecture program.
Relationship between academic achievement and healthy school transformations in urban elementary schools in the United States

ABSTRACT Purpose: Given the recent push to increase children’s physical activity levels through whole-of-school approaches, the relationship between physical activity and academic achievement has received much attention. Therefore, this study sought to understand the relationship between academic achievement and healthy school transformations in urban elementary school children (4th grade; ∼10 years old). Method: A total of 378 urban elementary students participated in an 8-month healthy school transformation that included both physical activity and nutrition programming. The Building Healthy Communities (BHC) program is a nutrition and physical activity program that has six main components: (1) principal engagement, (2) classroom physical activity and nutrition education, (3) active recess, (4) physical education, (5) healthy kids club, and (6) student leadership team. A path analysis was conducted to determine the relationship between the BHC healthy school transformation and student academic achievement. Results: The final model in the path analysis had a good model fit ( = 28.43, p = .10; CFI = .991; TLI = .965; RMSEA = .03, 90% CI [.00–.06]; SRMR = .03). In the final model, program fidelity was a significant predictor of students’ reading comprehension rates of improvement, while students’ aerobic fitness level and time two physical activity levels were all significant contributors to rates of improvement in math. Conclusions: Given recent suggestions to increase physical activity throughout the school day, understanding the relationship that comprehensive programming has on the academic achievement of children is needed. This study demonstrated a clear link between academic achievement and healthy school transformations and sets the stage for more research in this area, as well as implications for pedagogy around health and wellness in the school setting.