Miracle-dz/UniFAR-FTUs huggingface dataset:
Systematic mapping of functional enhancer–promoter connections with CRISPR interference

CRISPR screens illuminate enhancer function The noncoding regions around a gene that control the transcription of the protein-coding region are difficult to identify. Leveraging a CRISPR interference system (CRISPRi), Fulco et al. identified enhancer-promoter connections to map specific noncoding regions affecting gene regulation for the GATA1 and MYC loci (see the Perspective by Einstein and Yeo). Going forward, such CRISPRi-mapping can be used to evaluate promoter-enhancer screens functionally in an unbiased way. Science, this issue p. 769; see also p. 705 Functional mapping of noncoding elements with CRISPR interference may predict enhancer function. Gene expression in mammals is regulated by noncoding elements that can affect physiology and disease, yet the functions and target genes of most noncoding elements remain unknown. We present a high-throughput approach that uses clustered regularly interspaced short palindromic repeats (CRISPR) interference (CRISPRi) to discover regulatory elements and identify their target genes. We assess >1 megabase of sequence in the vicinity of two essential transcription factors, MYC and GATA1, and identify nine distal enhancers that control gene expression and cellular proliferation. Quantitative features of chromatin state and chromosome conformation distinguish the seven enhancers that regulate MYC from other elements that do not, suggesting a strategy for predicting enhancer–promoter connectivity. This CRISPRi-based approach can be applied to dissect transcriptional networks and interpret the contributions of noncoding genetic variation to human disease.
Clock Tree synthesis for TSV-based 3D IC designs

For the cost-effective implementation of clock trees in through-silicon via (TSV)-based 3D IC designs, we propose core algorithms for 3D clock tree synthesis. For a given abstract tree topology, we propose DLE-3D (&dlowbar;eferred &llowbar;ayer &elowbar;mbedding for &3Dlowbar; ICs), which optimally finds the embedding layers of tree nodes, so that the TSV cost required for a tree topology is minimized, and DME-3D (&dlowbar;eferred &mlowbar;erge &elowbar;mbedding for &3Dlowbar; ICs), which is an extended algorithm of the 2D merging segment, to minimize the total wirelength in 3D design space, with the consideration of the TSV effect on delay. In addition, when an abstract tree topology is not given, we propose NN-3D (&nlowbar;earest &nlowbar;eighbor selection for &3Dlowbar; ICs), which constructs a (TSV and wirelength) cost-effective abstract tree topology for 3D ICs. Through experimentation, we have confirmed that the clock tree synthesis flow using the proposed algorithms is very effective, outperforming the existing 3D clock tree synthesis in terms of the number of TSVs, total wirelength, and clock power consumption.
Selecting Among Heuristics by Solving Thresholded k -Armed Bandit Problems

Suppose we are given k randomized heuristics to use in solving a combinatorial problem. Each heuristic, when run, produces a solution with an associated quality or value. Given a budget of n runs, our goal is to allocate runs to the heuristics so as to maximize the number of sampled solutions whose value exceeds a speciﬁed threshold. For this special case of the classical k -armed bandit problem, we present a strategy with O ( √ np ∗ k ln n ) additive regret, where p ∗ is the probability of sampling an above-threshold solution us-ing the best single heuristic. We demonstrate the usefulness of our algorithm by using it to select among priority dispatching rules for the resource-constrained project scheduling problem with maximal time lags (RCPSP/max).
Multiradio Resource Management: Parallel Transmission for Higher Throughput?

Mobile communication systems beyond the third generation will see the interconnection of heterogeneous radio access networks (UMTS, WiMax, wireless local area networks, etc.) in order to always provide the best quality of service (QoS) to users with multimode terminals. This scenario poses a number of critical issues, which have to be faced in order to get the best from the integrated access network. In this paper, we will investigate the issue of parallel transmission over multiple radio access technologies (RATs), focusing the attention on the QoS perceived by final users. We will show that the achievement of a real benefit from parallel transmission over multiple RATs is conditioned to the fulfilment of some requirements related to the kind of RATs, the multiradio resource management (MRRM) strategy, and the transport-level protocol behaviour. All these aspects will be carefully considered in our investigation, which will be carried out partly adopting an analytical approach and partly by means of simulations. In this paper, in particular, we will propose a simple but effective MRRM algorithm, whose performance will be investigated in IEEE802.11a-UMTS and IEEE802.11a-IEEE802.16e heterogeneous networks (adopted as case studies).
Exploiting Language Resources for Semantic Web Annotations

A large portion of the useful information on the web is in the form of unstructured natural language documents. Currently such documents are understandable to humans but not to software agents. One of the goals of the Semantic Web activity is to enrich a considerable number of web documents with annotations, which will then allow new generation search engines and novel web services to access those documents in a more intelligent fashion than currently possible. Currently the most reliable method of providing such semantic markup is via manual annotation, possibly based on predefined ontologies and with the support of specialized editors. In this paper we propose an approach for the automatic processing of textual documents to be published on the web, which can be used to automatically generate (some of) the semantic annotations. In particular, we focus on detecting the entities mentioned in the documents, their roles and relationships to other entities.
Unsupervised learning of face detection models from unlabeled image streams

Modern artificial face detection shows impressive performance in a variety of application areas. This success comes at the cost of supervised training, using large-scale databases provided by human experts. In this paper, we propose a face detection system based on Organic Computing [vdM08] paradigms that acquires necessary domain knowledge autonomously and learns a conceptual model of the human face/head region. Performance of the novel approach is experimentally compared to state-of-the-art face detection, yielding competitive results in scenarios of moderate complexity.
Sixth International Workshop on Tropical Cyclones 0.2.2 Recent Understanding of Tc Structural Change Due to Land-sea Contrasts

Forecasting of wind distribution of a landfalling Tropical Cyclone (TC) is definitely an operational challenge. It is of great importance since the circulation of a TC making landfall would inflict huge losses and widespread damage on the coastal areas. As outlined in Willoughby et al. (2005a), one of the priorities of US Weather Research Program on TC is to make skillful forecasts of gale-and hurricane-force wind radii out to 48 hours with 95% confidence. While there has been much improvement over the years in the forecasting of TC tracks, relatively slow progress was seen during the same period on the problem in question, primarily due to the complexities in the physical processes involved, and the inability of Numerical Weather Prediction (NWP) models to be run at a resolution high enough to adequately resolve the TC structure in an operational manner. Only a limited number of objective guidance tools have been specifically designed for the task and statistical methodologies remain to be the mainstay in tackling the problem. In this report, new developments since IWTC-V are reviewed. The recent researches on TC structural and wind distribution evolution arising from land-sea contrasts, in particular the influence of land-induced asymmetric friction on the boundary layer winds, and the effects of the moist processes in introducing asymmetries in TC structure at landfall, is covered in Sections 0.2. 2a and 0.2. 2b. Damaging fine-scale surface wind features such as boundary-layer rolls, small-scale spiral bands, terrain-induced wind accelerations are frequently observed. A brief account of these features is given in Section 0.2. 3a. Observational issues including a review of the wind-pressure relationship, deployment of surface wind observation network and the emergence of new wind speed averaging standards are discussed in Sections 0.2. 3b, 0.2. 3c and 0.2. 3d. On the forecasting aspects, the development and operational deployment of various empirical and parametric wind models are reviewed in Sections 0.2. 4a and 0.2. 4b. Latest progress in the modeling of the boundary layer processes in NWP is summarized in Section 0.2. 4c. The wind structure of a mature TC is basically axisymmetric. However, when a TC makes landfall, part of the TC circulation is affected by increased surface friction over land. In addition, the surface sensible and latent heat fluxes, and moisture supply over land are different from those over ocean. The major goals of recent researches on TC landfall have been to understand how the contrasts between
Detecting skewed symmetries

Many surfaces of objects are bounded by planar bilaterally symmetric figures. When these figures are imaged under orthographic projection a skewed symmetric contour results. In this paper a new, fast local method to recover skewed symmetries from curve segments is proposed. It can be applied to complete as well as to occluded contours. Furthermore, the skewed symmetry property is employed to overcome fragmentation of a contour during segmentation. <<ETX>>
Dynamical Integration of Language and Behavior in a Recurrent Neural Network for Human–Robot Interaction

To work cooperatively with humans by using language, robots must not only acquire a mapping between language and their behavior but also autonomously utilize the mapping in appropriate contexts of interactive tasks online. To this end, we propose a novel learning method linking language to robot behavior by means of a recurrent neural network. In this method, the network learns from correct examples of the imposed task that are given not as explicitly separated sets of language and behavior but as sequential data constructed from the actual temporal flow of the task. By doing this, the internal dynamics of the network models both language–behavior relationships and the temporal patterns of interaction. Here, “internal dynamics” refers to the time development of the system defined on the fixed-dimensional space of the internal states of the context layer. Thus, in the execution phase, by constantly representing where in the interaction context it is as its current state, the network autonomously switches between recognition and generation phases without any explicit signs and utilizes the acquired mapping in appropriate contexts. To evaluate our method, we conducted an experiment in which a robot generates appropriate behavior responding to a human’s linguistic instruction. After learning, the network actually formed the attractor structure representing both language–behavior relationships and the task’s temporal pattern in its internal dynamics. In the dynamics, language–behavior mapping was achieved by the branching structure. Repetition of human’s instruction and robot’s behavioral response was represented as the cyclic structure, and besides, waiting to a subsequent instruction was represented as the fixed-point attractor. Thanks to this structure, the robot was able to interact online with a human concerning the given task by autonomously switching phases.
Microsatellite Plots in SOD-1 gene with Mutations and Predicted Domains reveals a possible role of Mutagenesis

Approximately 10% of Amyotrophic lateral sclerosis/ Motor Neuron Disease (ALS/MND) is inherited of which up to 20% is caused by mutations, (changes) in the superoxide dismutase 1 (SOD1) gene. Detailed bioinformatics study of all the known mutations in the SOD1 gene revealed interesting information. The information about all the experimentally proven mutations in the SOD1 gene was collected and analyzed using bioinformatics tools and software programs. We computationally tried to find out whether the presence of microsatellite plot in the SOD1 gene has any significance in the generation of these mutations. Our analysis revealed that we found 13 microsatellites out of which 7 microsatellites regions have found to be mutated and have fallen inside domain region. The mutation falling in the domain region seems to be inducting a change in the secondary structure and resulting in change or absence of protein function. Thus indicating a positive role of microsatellites in mutagenesis.
Control of Bipedal Walking Robot through Direct Regulation of the Zero Moment Point

By controlling the zero moment point (ZMP) The unexpected rotation of the supporting foot can be avoided. This paper analyze a control strategy for simultaneously regulating the position of the ZMP and the joints of the robot, the proposed controller is based on a path-following control strategy. The objective of the control law is not to track a (time based), but only the associated path in joint space.
Magnetic Resonance Imaging Analysis of Right Ventricular Pressure-Volume Loops: In Vivo Validation and Clinical Application in Patients With Pulmonary Hypertension

Background—The aims of this study were to validate MRI-derived right ventricular (RV) pressure-volume loops for assessment of RV myocardial contractility and then to apply this technique in patients with chronic RV pressure overload for assessment of myocardial contractility, ventricular pump function, and VA coupling. Methods and Results—Flow-directed catheters were guided under MR fluoroscopy (1.5 T) into the RV for invasive pressure measurements. Simultaneously, ventricular volumes and myocardial mass were assessed from cine MRI. From sampled data, RV pressure-volume loops were constructed, and maximal ventricular elastance indexed to myocardial mass (Emax_i) was derived by use of a single-beat estimation method. This MRI method was first validated in vivo (6 swine), with conductance techniques used as reference. Bland-Altman test showed good agreement between methods (Emax_i=5.1±0.5 versus 5.8±0.7 mm Hg · mL−1 · 100 g−1, respectively; P=0.08). Subsequently, the MRI method was applied in 12 subjects: 6 control subjects and 6 patients with chronic RV pressure overload from pulmonary hypertension. In these patients, indexes of RV pump function (cardiac index), Emax_i, and VA coupling (Emax/Ea) were assessed. In patients with pulmonary hypertension, RV pump function was decreased (cardiac index, 2.2±0.5 versus 2.9±0.4 L · min−1 · m−2; P<0.01), myocardial contractility was enhanced (Emax_I, 9.2±1.1 versus 5.0±0.9 mm Hg · mL−1 · 100 g−1; P<0.01), and VA coupling was inefficient (Emax/Ea, 1.1±0.3 versus 1.9±0.4; P<0.01) compared with control subjects. Conclusions—RV myocardial contractility can be determined from MRI-derived pressure-volume loops. Chronic RV pressure overload was associated with reduced RV pump function despite enhanced RV myocardial contractility. The proposed MRI approach is a promising tool to assess RV contractility in the clinical setting.
Phenopedia and Genopedia: disease-centered and gene-centered views of the evolving knowledge of human genetic associations

Summary: We developed web-based applications that encourage the exploration of the literature on human genetic associations by using a database that is continuously updated from PubMed. These applications provide user-friendly interfaces for searching summarized information on human genetic associations, using either genes or diseases as the starting point. Availability: Phenopedia and Genopedia can be freely accessed at http://www.hugenavigator. net/HuGENavigator/startPagePhenoPedia.do and http://www.hugenavigator. net/HuGENavigator/startPagePedia.do, respectively. Contact: wby0@cdc.gov Supplementary information: Supplementary data are available at Bioinformatics online.
In Hippocampal Oriens Interneurons Anti-Hebbian Long-Term Potentiation Requires Cholinergic Signaling via α7 Nicotinic Acetylcholine Receptors

In the hippocampus, at excitatory synapses between principal cell and oriens/alveus (O/A) interneurons, a particular form of NMDA-independent long-term synaptic plasticity (LTP) has been described (Lamsa et al., 2007). This type of LTP occurs when presynaptic activation coincides with postsynaptic hyperpolarization. For this reason it has been named “anti-Hebbian” to distinguish from the classical Hebbian type of associative learning where presynaptic glutamate release coincides with postsynaptic depolarization. The different voltage dependency of LTP induction is thought to be mediated by calcium-permeable (CP) AMPA receptors that, due to polyamine-mediated rectification, favor calcium entry at hyperpolarized potentials. Here, we report that the induction of this form of LTP needs CP-α7 nicotinic acetylcholine receptors (nAChRs) that, like CP-AMPARs, exhibit a strong inward rectification because of polyamine block at depolarizing potentials. We found that high-frequency stimulation of afferent fibers elicits synaptic currents mediated by α7 nAChRs. Hence, LTP was prevented by α7 nAChR antagonists dihydro-β-erythroidine and methyllycaconitine (MLA) and was absent in α7−/− mice. In addition, in agreement with previous observations (Le Duigou and Kullmann, 2011), in a minority of O/A interneurons in MLA-treated hippocampal slices from WT animals and α7−/− mice, a form of LTP probably dependent on the activation of group I metabotropic glutamate receptors was observed. These data indicate that, in O/A interneurons, anti-Hebbian LTP critically depends on cholinergic signaling via α7 nAChR. This may influence network oscillations and information processing.
Two-Feature Voiced/Unvoiced Classifier Using Wavelet Transform

This paper proposes a new wavelet-based algorithm for voice/unvoiced classification of speech segments. The classification process is based on: 1) statistical analysis of the energy-frequency distribution of the speech signal using wavelet transform, and 2) estimation of the short-time zero-crossing rate of the signal. First, the ratio of the average energy in the low-frequency wavelet subbands to that of highest-frequency wavelet subband is computed for each time segment of the pre-emphasised speech using a 4-level dyadic wavelet transform, and compared to a pre-determined threshold. This is followed by measuring the zero- crossing rate of the segment and comparing it to a threshold determined by a continually up-dated value of the median of the zero-crossing rates of the speech signal. An experimentally verified criterion based on the re- sults of the above two comparison processes is then applied to obtain the classification decision. The perform- ance of the algorithm has been evaluated on speech data taken from the TIMIT database, and is shown to yield high classification accuracy and robustness to additive noise. technique for V/UV speech classification using two features of the speech signal: (a) the frequency distribution of the average energy and (b) zero-crossing rate, for each speech segment. The performance of the proposed technique has been evaluated using a large database of both clean speech and speech degraded with additive noise. Following this introduction, the second Section gives an overview of the discrete wavelet transform (DWT). The de- tailed description of the proposed V/UV classification algo- rithm is given next. In the forth Section, the various experi- mental results of the performance evaluation of the algorithm are illustrated and discussed. The article concludes by giving a summary of the proposed algorithm and findings of the evaluation process.
Friedlander's eigenvalue inequalities and the Dirichlet-to-Neumann semigroup

If $\Omega$ is any compact Lipschitz domain, possibly in a Riemannian manifold, with boundary $\Gamma = \partial \Omega$, the Dirichlet-to-Neumann operator $\mathcal{D}_\lambda$ is defined on $L^2(\Gamma)$ for any real $\lambda$. We prove a close relationship between the eigenvalues of $\mathcal{D}_\lambda$ and those of the Robin Laplacian $\Delta_\mu$, i.e. the Laplacian with Robin boundary conditions $\partial_\nu u =\mu u$. This is used to give another proof of the Friedlander inequalities between Neumann and Dirichlet eigenvalues, $\lambda^N_{k+1} \leq \lambda^D_k$, $k \in N$, and to sharpen the inequality to be strict, whenever $\Omega$ is a Lipschitz domain in $R^d$. We give new counterexamples to these inequalities in the general Riemannian setting. Finally, we prove that the semigroup generated by $-\mathcal{D}_\lambda$, for $\lambda$ sufficiently small or negative, is irreducible.
Classical Conditioning Analog Enhanced Acetylcholine Responses But Reduced Excitability of an Identified Neuron

Although classical and operant conditioning are operationally distinct, it is unclear whether these two forms of learning are mechanistically distinct or similar. Feeding behavior of Aplysia provides a useful model system for addressing this issue. Both classical and operant appetitive behavioral training enhance feeding, and neuronal correlates have been identified. Behavioral training was replicated by in vitro analogs that use isolated ganglia. Moreover, a single-cell analog of operant conditioning was developed using neuron B51, a cell important for the expression of the conditioned behavior. Here, a single-cell analog of classical conditioning was developed. Acetylcholine (ACh) mediated the conditioned stimulus (CS)-elicited excitation of B51 in ganglia and mimicked the CS in the single-cell analog of classical conditioning. Pairing ACh with dopamine, which mediates the unconditioned stimulus in ganglia, decreased the excitability of B51, and increased the CS-elicited excitation of B51, similar to results following both in vivo and in vitro classical training. Finally, a D1 dopamine receptor (D1R) agonist failed to support classical conditioning in the cellular analog, whereas D1R mediates reinforcement in operant conditioning.
Modeling Bidirectional Texture Functions with Multivariate Spherical Radial Basis Functions

This paper presents a novel parametric representation for bidirectional texture functions. Our method mainly relies on two original techniques, namely, multivariate spherical radial basis functions (SRBFs) and optimized parameterization. First, since the surface appearance of a real-world object is frequently a mixed effect of different physical factors, the proposed sum-of-products model based on multivariate SRBFs especially provides an intrinsic and efficient representation for heterogenous materials. Second, optimized parameterization particularly aims at overcoming the major disadvantage of traditional fixed parameterization. By using a parametric model to account for variable transformations, the parameterization process can be tightly integrated with multivariate SRBFs into a unified framework. Finally, a hierarchical fitting algorithm for bidirectional texture functions is developed to exploit spatial coherence and reduce computational cost. Our experimental results further reveal that the proposed representation can easily achieve high-quality approximation and real-time rendering performance.