Miracle-dz/UniFAR-FTUs huggingface dataset:
Autonomous Localization of an Unknown Number of Targets Without Data Association Using Teams of Mobile Sensors

This paper considers situations in which a team of mobile sensor platforms autonomously explores an environment to detect and localize an unknown number of targets. Individual sensors may be unreliable, failing to detect objects within the field-of-view, returning false positive measurements to clutter objects, and being unable to disambiguate true targets. In this setting, data association is difficult. We utilize the PHD filter for multitarget localization, simultaneously estimating the number of objects and their locations within the environment without the need to explicitly consider data association. Using sets of potential actions generated at multiple length scales for each robot, the team selects the joint action that maximizes the expected information gain over a finite time horizon. This is computed as the mutual information between the set of targets and the binary events of receiving no detections, effectively hedging against uninformative actions in a computationally tractable manner. We frame the controller as a receding-horizon problem. We demonstrate the real-world applicability of the proposed autonomous exploration strategy through hardware experiments, exploring an office environment with a team of ground robots. We also conduct a series of simulated experiments, varying the planning method, target cardinality, environment, and sensor modality. Note to Practitioners-Teams of small robots have the potential to automate many information gathering tasks, relaying data back to a base station or human operator from multiple vantage points within an environment. The information gathering tasks we consider in this work are those in which the number of objects being sought is not known at the onset of exploration. Such tasks are common in security and surveillance, where the number of such objects is often zero; search and rescue, where, for example, the number of people trapped due to a natural disaster can be large; or smart building/smart city applications, where the data collection needs may be on an even larger scale. This paper seeks to address the problem of automating this data collection process, so that a team of mobile sensor platforms are able to autonomously explore a given environment in order to determine the number of objects of interest and their locations, while avoiding any explicit data association, i.e., matching individual measurements to targets.
Nonlinear unmixing of hyperspectral images using a semiparametric model and spatial regularization

Incorporating spatial information into hyperspectral unmixing procedures has been shown to have positive effects, due to the inherent spatial-spectral duality in hyperspectral scenes. Current research works that consider spatial information are mainly focused on the linear mixing model. In this paper, we investigate a variational approach to incorporating spatial correlation into a nonlinear unmixing procedure. A nonlinear algorithm operating in reproducing kernel Hilbert spaces, associated with an ℓ1 local variation norm as the spatial regularizer, is derived. Experimental results, with both synthetic and real data, illustrate the effectiveness of the proposed scheme.
An 8Gb/s 0.75mW/Gb/s injection-locked receiver with constant jitter tracking bandwidth and accurate quadrature clock generation in 40nm CMOS

This paper presents an energy-efficient forwarded-clock receiver in 40nm CMOS process. The receiver adopts injection-locked ring oscillator (ILRO) to implement jitter filtering and phase deskew. The proposed cascaded ILROs enable our receiver to maintain a constant jitter tracking bandwidth (JTB) for good jitter tolerance and generate accurate quadrature clocks for quarter-rate sampling. The first-stage ILRO is used to control the JTB and filter out the high-frequency clock jitter that cannot track the data jitter. The second-stage ILRO is injected by the first one's outputs to generate precise quadrature clocks for phase shifting and deskew. The simulation results show our receiver can work at 8Gb/s and consume only 6mW under a 0.9V power supply voltage. The JTB can be controlled up to 260 MHz with a variation less than 20 MHz and the quadrature phase error is minimized to 1°.
Functional Genomic Analysis of the let-7 Regulatory Network in Caenorhabditis elegans

The let-7 microRNA (miRNA) regulates cellular differentiation across many animal species. Loss of let-7 activity causes abnormal development in Caenorhabditis elegans and unchecked cellular proliferation in human cells, which contributes to tumorigenesis. These defects are due to improper expression of protein-coding genes normally under let-7 regulation. While some direct targets of let-7 have been identified, the genome-wide effect of let-7 insufficiency in a developing animal has not been fully investigated. Here we report the results of molecular and genetic assays aimed at determining the global network of genes regulated by let-7 in C. elegans. By screening for mis-regulated genes that also contribute to let-7 mutant phenotypes, we derived a list of physiologically relevant potential targets of let-7 regulation. Twenty new suppressors of the rupturing vulva or extra seam cell division phenotypes characteristic of let-7 mutants emerged. Three of these genes, opt-2, prmt-1, and T27D12.1, were found to associate with Argonaute in a let-7–dependent manner and are likely novel direct targets of this miRNA. Overall, a complex network of genes with various activities is subject to let-7 regulation to coordinate developmental timing across tissues during worm development.
Single-Dose Anti-CD138 Radioimmunotherapy: Bismuth-213 is More Efficient than Lutetium-177 for Treatment of Multiple Myeloma in a Preclinical Model

Objectives Radioimmunotherapy (RIT) has emerged as a potential treatment option for multiple myeloma (MM). In humans, a dosimetry study recently showed the relevance of RIT using an antibody targeting the CD138 antigen. The therapeutic efficacy of RIT using an anti-CD138 antibody coupled to 213Bi, an α-emitter, was also demonstrated in a preclinical MM model. Since then, RIT with β-emitters has shown efficacy in treating hematologic cancer. In this paper, we investigate the therapeutic efficacy of RIT in the 5T33 murine MM model using a new anti-CD138 monoclonal antibody labeled either with 213Bi for α-RIT or 177Lu for β-RIT. Methods A new monoclonal anti-CD138 antibody, 9E7.4, was generated by immunizing a rat with a murine CD138-derived peptide. Antibody specificity was validated by flow cytometry, biodistribution, and α-RIT studies. Then, a β-RIT dose-escalation assay with the 177Lu-radiolabeled 9E7.4 mAb was performed in KalwRij C57/BL6 mice 10 days after i.v. engraftment with 5T33 MM cells. Animal survival and toxicological parameters were assessed to define the optimal activity. Results α-RIT performed with 3.7 MBq of 213Bi-labeled 9E7.4 anti-CD138 mAb increased median survival to 80 days compared to 37 days for the untreated control and effected cure in 45% of animals. β-RIT performed with 18.5 MBq of 177Lu-labeled 9E7.4 mAb was well tolerated and significantly increased mouse survival (54 vs. 37 days in the control group); however, no mice were cured with this treatment. Conclusion This study revealed the advantages of α-RIT in the treatment of MM in a preclinical model where β-RIT shows almost no efficacy.
Computer Simulation of Radioactive Source Delivery Process in Nasopharyngeal Carcinoma Brachytherapy

Brachytherapy is one of the major means of nasopharyngeal carcinoma treatments. The process of radioactive source delivery and the distribution of radioactive dose are two pivotal factors of brachytherapy planning. A new method for simulation of the two factors was proposed in this paper. Firstly, the CT images of the nasopharyngeal tissues were segmented and the 3D models of nasopharyngeal tissues were reconstructed. Then the process of cylindrical radioactive source delivery was simulated with virtual endoscopy method. A new computing method of 3D radioactive source delivery path planning based on Ta-chih Lee's thinning algorithm was proposed. Finally, the dose distribution of cylindrical radioactive source was simulated by Monte Carlo method. Based on this method, computer simulation of nasopharyngeal carcinoma brachytherapy process can be realized and it will be of great help to the design of nasopharyngeal carcinoma brachytherapy plan.
Different Cortical Dynamics in Face and Body Perception: An MEG study

Evidence from functional neuroimaging indicates that visual perception of human faces and bodies is carried out by distributed networks of face and body-sensitive areas in the occipito-temporal cortex. However, the dynamics of activity in these areas, needed to understand their respective functional roles, are still largely unknown. We monitored brain activity with millisecond time resolution by recording magnetoencephalographic (MEG) responses while participants viewed photographs of faces, bodies, and control stimuli. The cortical activity underlying the evoked responses was estimated with anatomically-constrained noise-normalised minimum-norm estimate and statistically analysed with spatiotemporal cluster analysis. Our findings point to distinct spatiotemporal organization of the neural systems for face and body perception. Face-selective cortical currents were found at early latencies (120–200 ms) in a widespread occipito-temporal network including the ventral temporal cortex (VTC). In contrast, early body-related responses were confined to the lateral occipito-temporal cortex (LOTC). These were followed by strong sustained body-selective responses in the orbitofrontal cortex from 200–700 ms, and in the lateral temporal cortex and VTC after 500 ms latency. Our data suggest that the VTC region has a key role in the early processing of faces, but not of bodies. Instead, the LOTC, which includes the extra-striate body area (EBA), appears the dominant area for early body perception, whereas the VTC contributes to late and post-perceptual processing.
Deletion of the secretory vesicle proteins IA‐2 and IA‐2β disrupts circadian rhythms of cardiovascular and physical activity

Targeted deletion of IA‐2 and IA‐2β, major autoantigens in type 1 diabetes and transmembrane secretory vesicle proteins, results in impaired secretion of hormones and neurotransmitters. In the present study, we evaluated the effect of these deletions on daily rhythms in blood pressure, heart rate, core body temperature, and spontaneous physical and neuronal activity. We found that deletion of both IA‐2 and IA‐2β profoundly disrupts the usual diurnal variation of each of these parameters, whereas the deletion of either IA‐2 or IA‐2β alone did not produce a major change. In situ hybridization revealed that IA‐2 and IA‐2β transcripts are highly but nonrhythmically expressed in the suprachiasmatic nuclei, the site of the brain's master circadian oscillator. Electrophysiological studies on tissue slices from the suprachiasmatic nuclei showed that disruption of both IA‐2 and IA‐2β results in significant alterations in neuronal firing. From these studies, we concluded that deletion of IA‐2 and IA‐2β, structural proteins of secretory vesicles and modulators of neuroendocrine secretion, has a profound effect on the circadian system. —Kim, S. M. , Power, A. , Brown, T. M. , Constance, C. M. , Coon, S. L. , Nishimura, T. , Hirai, H. , Cai, T. , Eisner, C. , Weaver, D. R. , Piggins, H. D. , Klein, D. C. , Schnermann, J., Notkins, A. L. Deletion of the secretory vesicle proteins IA‐2 and IA‐2β disrupts circadian rhythms of cardiovascular and physical activity. FASEBJ. 23, 3226‐3232 (2009). www.fasebj. org
Codebook constrained iterative noise cancellation with applications to speech enhancement

The performance of widely-used adaptive noise canceling (ANC) deteriorates much when the desired signal is leaked into the reference channel or when there are uncorrelated noise present in the reference channel. This paper proposes a dual-microphone scheme, named iterative noise canceling (INC), to overcome the drawbacks mentioned above. The proposed INC system, in which a codebook-based speech quality measure is employed to control a modified iterative Wiener filter (MIWF), can automatically reduce noises in the primary input until convergence occurs. In comparison with the traditional ANC algorithm, the evaluation using real noise and voices recorded in a car shows the noise reduction performance is dramatically improved, even in cases where the reference SNR is close to 0 dB.
A smoothing kernel for spatially related features and its application to speaker verification

Most commonly used kernels are invariant to permutations of the feature vector components. This characteristic may make machine learning methods that use such kernels suboptimal in cases where the feature vector has an underlying structure. In this paper we will consider one such case, where the features are spatially related. We show a way to modify the objective function of the support vector machine (SVM) optimization problem to account for this structure. The new optimization problem can be implemented as a standard SVM using a particular smoothing kernel. Results are shown on a speaker verification task using prosodic features that are transformed using a particular implementation of the Fisher score. The proposed method leads to improvements of as much as 15% in equal error rate (EER).
A self exciting point process model for neural spike sequences, and its rate estimation

Common neuron firing rate estimators have been criticized because of their Poisson assumption, not accounting for the refractory period of action potentials that induces history dependency in spike sequences. Hence rate estimators that can account for such dependency, although seemingly more difficult to formulate, could provide more accurate results. In this paper a Maximum Likelihood (ML) estimator for an inhomogeneous Poisson process is modified to account for an absolute refractory period in the spike sequence. The proposed estimator treats the refractory period as a nuisance parameter and maximizes the profile likelihood of the stimulus. Through computer simulations we show that by exploiting the refractory phenomenon, the estimator can achieve better performance than the Poisson estimator for moderate to high firing rates. Furthermore, we show that the results provided by this estimator yield an improved goodness of fit to real data when compared to the Poisson estimator.
Testing A Theoretical Model of Exercise Behavior for Older Adults

BackgroundAlthough there are many known benefits to exercise, only 10–30% of older adults report regular exercise. Understanding the factors that explain exercise behavior in older adults will help structure interventions that motivate these individuals to initiate and adhere to regular exercise. ObjectiveThe purpose of this study was to test the impact of components from two theoretical perspectives that explain exercise behavior, social cognitive theory, and the transtheoretical model. MethodsThis was a descriptive study using a sample of 179 older adults living independently in an East Coast continuing care retirement community (CCRC). A single one-time interview was completed and included: (a) stage of change for exercise, (b) self-efficacy and outcome expectations, (c) health status, (d) fear of falling, and (e) exercise activity. Model testing used structural equation modeling. ResultsTesting of the hypothesized model showed that 11 of the 22 paths were statistically significant. Health status and social support influenced self-efficacy and outcome expectations which directly influenced stage of change and exercise. Social support likewise directly influenced stage of change. Together the variables in the model explained 64% of exercise behavior in older adults. There was a poor fit of the hypothesized model to the data with a χ2 of 144.7, degrees of freedom (df) of 23 and a ratio of 6.3. The revised model fit the data better χ2 = 80.5, df = 19, p < . 05, χ2/ df = 4.2) and there was improved fit when compared to the hypothesized model (χ2 difference of 64.0, df difference of 4, p ≤ l. DiscussionThe combined testing of the mediating components of the theory of self-efficacy as well as the incorporation of the stage of change to explain exercise behavior in older adults suggests that both of these approaches are useful. Stage of change may be particularly useful to help determine the most appropriate intervention to increase activity and exercise in older adults.
Studies in Solution Sampling

We introduce novel algorithms for generating random solutions from a uniform distribution over the solutions of a boolean satisfiability problem. Our algorithms operate in two phases. In the first phase, we use a recently introduced SampleSearch scheme to generate biased samples while in the second phase we correct the bias by using either Sampling/lmportance Resampling or the Metropolis-Hastings method. Unlike state-of-the-art algorithms, our algorithms guarantee convergence in the limit. Our empirical results demonstrate the superior performance of our new algorithms over several competing schemes.
CTH16-6: Adaptive Coding and Modulation for Hybrid ARQ Systems over Partially Observable Nakagami-m Fading Channels

We study coding and modulation rate adaptation problem for HARQ systems with partially observable state from cross-layer viewpoint. The rate of convolutionally coded M-QAM is adapted jointly with buffer state and channel state. We assume that perfect channel state information is not known at the transmitter, but it can be estimated from previous actions and observations. POMDP-based approach is utilized to formulate the problem, where average throughput is maximized, and average delay, packet error rate and overflows are minimized. To solve the cross-layer adaptation problem approximately, we discuss two heuristic-based methods and compare their applicability with completely observable channel state case by simulation results.
Heme Oxygenase-1 Inhibits Pro-Oxidant Induced Hypertrophy in HL-1 Cardiomyocytes

Aims: Reactive oxygen species (ROS) activate multiple signaling pathways involved in cardiac hypertrophy. Since HO-1 exerts potent antioxidant effects, we hypothesized that this enzyme inhibits ROS-induced cardiomyocyte hypertrophy. Methods: HL-1 cardiomyocytes were transduced with an adenovirus constitutively expressing HO-1 (AdHO-1) to increase basal HO-1 expression and then exposed to 200 μM hydrogen peroxide (H2O2). Hypertrophy was measured using 3H-leucine incorporation, planar morphometry and cell-size by forward-scatter flow-cytometry. The pro-oxidant effect of H2O2 was assessed by redox sensitive fluorophores. Inducing intracellular redox imbalance resulted in cardiomyocyte hypertrophy through transactivation of nuclear factor kappa B (NF-κB). Results: Pre-emptive HO-1 overexpression attenuated the redox imbalance and reduced hypertrophic indices. This is the first time that HO-1 has directly been shown to inhibit oxidant-induced cardiomyocyte hypertrophy by a NF-κB–dependent mechanism. Conclusion: These results demonstrate that HO-1 inhibits pro-oxidant induced cardiomyocyte hypertrophy and suggest that HO-1 may yield therapeutic potential in treatment of
Parallel structurally-symmetric sparse matrix-vector products on multi-core processors

We consider the problem of developing an ecient multi-threaded implementation of the matrix-vector multiplication algorithm for sparse matrices with structural symmetry. Matrices are stored using the compressed sparse row-column format (CSRC), designed for proting from the symmetric non-zero pattern observed in global nite element matrices. Unlike classical compressed storage formats, performing the sparse matrix-vector product using the CSRC requires thread-safe access to the destination vector. To avoid race conditions, we have implemented two partitioning strategies. In the rst one, each thread allocates an array for storing its contributions, which are later combined in an accumulation step. We analyze how to perform this accumulation in four dierent ways. The second strategy employs a coloring algorithm for grouping rows that can be concurrently processed by threads. Our results indicate that, although incurring an increase in the working set size, the former approach leads to the best performance improvements for most matrices.
Bio-degradation of a resorbable collagen membrane (Bio-Gide) applied in a double-layer technique in rats.

OBJECTIVE The aim of this study was to evaluate histologically the bio-degradation of two layers of Bio-Gide((R)) (BG) membrane, as compared with that of a single layer. MATERIAL AND METHODS Two circular calvarial bony defects, 5 mm in diameter, were made in 24 Wistar rats. BG membrane, labeled with biotin, was cut into 5-mm-diameter disks, and placed in defects either as a mono-layer membrane (MLM) or as a double-layer membrane (DLM). Rats were sacrificed after 4 or 9 weeks and histology was performed. Membranes were stained with horseradish peroxidase-conjugated streptavidin and aminoethyl carbazole as a substrate for detection of biotinylated collagen. The area of collagen and thickness of the residual membranes were measured by image analysis software. Statistical analysis was performed using the non-parametric Wilcoxon's signed-ranks test. RESULTS At 4-week collagen area per measurement window within the DLM sites (0.09+/-0.05 mm(2)) was significantly greater (P<0.01) than that in the MLM sites (0.047+/-0.034 mm(2)). At 9 weeks, the collagen area was also greater in the DLM sites (0.037+/-0.026 mm(2)) compared with that of the MLM sites (0.025+/-0.016 mm(2)); however, this difference did not reach statistical significance. The rate of membrane degradation, calculated as percent membrane lost compared with baseline, was similar for the DLM and MLM at both time points ( approximately 60% at 4 weeks and approximately 80% at 9 weeks). In addition, the residual DLM thickness at 4 weeks (475.5+/-73.77 mum) was significantly (P<0.01) greater than that of MLM (262.38+/-48.01 mum). At 9 weeks, membrane thickness was also greater in the DLM sites (318.22+/-70.45 mum) compared with that of the MLM sites (183.32+/-26.72 mum); however, this difference did not reach statistical significance. The reduction in thickness between 4 and 9 weeks was 30% for MLM and 33% for DLM. DISCUSSION The use of a double layer of BG membrane results in a barrier of increased collagen area and thickness, compared with application of a single layer.
Fully DNN-Based Multi-Label Regression for Audio Tagging

Acoustic event detection for content analysis in most cases relies on lots of labeled data. However, manually annotating data is a time-consuming task, which thus makes few annotated resources available so far. Unlike audio event detection, automatic audio tagging, a multi-label acoustic event classification task, only relies on weakly labeled data. This is highly desirable to some practical applications using audio analysis. In this paper we propose to use a fully deep neural network (DNN) framework to handle the multi-label classification task in a regression way. Considering that only chunk-level rather than frame-level labels are available, the whole or almost whole frames of the chunk were fed into the DNN to perform a multi-label regression for the expected tags. The fully DNN, which is regarded as an encoding function, can well map the audio features sequence to a multi-tag vector. A deep pyramid structure was also designed to extract more robust high-level features related to the target tags. Further improved methods were adopted, such as the Dropout and background noise aware training, to enhance its generalization capability for new audio recordings in mismatched environments. Compared with the conventional Gaussian Mixture Model (GMM) and support vector machine (SVM) methods, the proposed fully DNN-based method could well utilize the long-term temporal information with the whole chunk as the input. The results show that our approach obtained a 15% relative improvement compared with the official GMM-based method of DCASE 2016 challenge.