Miracle-dz/UniFAR-FTUs huggingface dataset:
DancingAnt: Body-empowered Wireless Sensing Utilizing Pervasive Radiations from Powerline

In recent years, wireless sensing has attracted lots of research attention with a large range of applications enabled. However, several critical issues still hinder wireless sensing from being adopted in daily use: (a) requiring dedicated devices and (or) dedicated signals; (b) limited sensing coverage; and (c) affecting the original function of the wireless technology (e.g., communication). In this work, we propose a new sensing modality, i.e., leveraging the pervasive powerline leakage for sensing. The key observation is that human body can capture such leaked signals, and the received signals vary with body gestures. We design a cheap ring antenna to collect the powerline leaked signals at human body and establish a body-empowered model to sense body motions. We prototype the proposed system with designs spanning both hardware and software. Comprehensive experiments show that the proposed sensing modality can realize a large range of applications in a different way from existing sensing methods. We showcase the powerful capability of this sensing modality using three typical sensing applications: body gesture recognition, sleep posture sensing, and fall detection.
A Joint Analysis of Input Resolution and Quantization Precision in Deep Learning

Deep learning models have become increasingly prevalent in various domains, necessitating their deployment on resource-constrained devices. Quantization is a promising way to reduce the model complexity in that it keeps model architecture intact and enables the model to operate on specialized hardwares(e.g., NPU, DSP). Input resolution is also essential in making a trade-off between accuracy and computation. In this paper, we conduct a joint analysis of input resolution and quantization precision on their influence on accuracy for three popular models: ResNet-18, ResNet-50, and MobileNet-V2. By exploring the combined configuration space, we found that better accuracy can be achieved by jointly optimizing the input resolution and quantization bit-width while maintaining the computational complexity.
A Preliminary Laboratory Investigation of PCB Flux from Dredge Resuspensions and Residuals

A preliminary laboratory investigation was conducted to understand the relative contributions of major dredge resuspension and residual processes on the releases of polychlorinated biphenyl (PCB) contaminants from sediments to water column. Sediments from New Bedford Harbor were used as test samples. Six sets of experiments were run for simulated resuspension and residual scenarios. During the experiments, water above the sediments was recirculated by peristaltic pumping or orbital shaking and the levels of two PCBs, Aroclor 1248 (PCB-1248) and Aroclor 1254 (PCB-1254), were monitored for 15 days. Analysis of the model predicted data indicated that resulting water column PCB concentrations differed with sediment surface, residual, and resuspension type. Highest PCB water column concentrations were observed for a condition which used a settled fluff from thin sediment slurry as a residual source and the column water was recirculated by orbital shaking. Lowest water column PCB levels were observed for a thick sediment deposit placed over clean sand. The PCB levels in the water column for all six simulated conditions were several orders higher than the USEPA ambient water quality criteria concentrations for aquatic environment and human consumption.
TinyRIC: Supercharging O-RAN Base Stations with Real-time Control

The emergence of latency-critical use cases for cellular networks has necessitated the need for real-time (RT) network performance optimization. While solutions such as the O-RAN architecture provide primitives for non-RT and near-RT control, the notion of RT control is still missing. To that end, in this paper, we introduce TinyRIC, a first-of-its-kind RT control platform for O-RAN base stations. Key highlights include a comprehensive system architecture design, a systems-level implementation in support of flexible user scheduling, and a preliminary over-the-air experimental evaluation to demonstrate the system's performance and feasibility.
Mixed Multi-Level Visual, Reward, and Motor Signals in Dorsomedial Frontal Cortex Area F7 during Active Naturalistic Video Exploration

In the primate brain the frontal lobes support complex functions, including social cognition. Understanding the functional organization of these regions requires an approach for rich functional characterization. Here we used a novel paradigm, the visual exploration of dynamic social and non-social video scenes, to characterize diverse functions in area F7 of dorsomedial premotor cortex in the macaque monkey (Macaca mulatta) previously suggested to be involved in the representation of social interactions. We found that neural populations within this area carry information about both visual events in the videos, like head turning, and higher-level social categories, like grooming. In addition to signaling visual events, the population also encoded the delivery of juice reward. Our novel free viewing paradigm and naturalistic stimuli elicited active visual exploration, and we found that a large fraction of F7 neurons responded to the subject’s own saccadic eye movements. Information from these three different domains were not separated across distinct neural sub-populations, but distributed, such that many neurons carried sensory, reward, and motor information in a mixed format. Thus we uncover a hitherto unappreciated diversity of functions in region F7 within dorsomedial frontal cortex.
DISTINCT METABOLIC STATES DIRECT RETINAL PIGMENT EPITHELIUM CELL FATE DECISIONS

During tissue regeneration, proliferation, dedifferentiation, and reprogramming are necessary to restore lost structures. However, it is not fully understood how metabolism intersects with these processes. Chicken embryos can regenerate their retina through retinal pigment epithelium (RPE) reprogramming when treated with fibroblast factor 2 (FGF2). Using transcriptome profiling, we uncovered extensive regulation of gene sets pertaining to proliferation, neurogenesis, and glycolysis throughout RPE-to-neural retina reprogramming. By manipulating cell media composition, we determined that glucose, glutamine, or pyruvate are sufficient to support RPE reprogramming identifying glycolysis as a requisite. Conversely, the induction of oxidative metabolism by activation of pyruvate dehydrogenase induces Epithelial-to-mesenchymal transition (EMT), while simultaneously blocking the activation of neural retina fate. We also identify that EMT is partially driven by an oxidative environment. Our findings provide evidence that metabolism controls RPE cell fate decisions and provide insights into the metabolic state of RPE cells, which are prone to fate changes in regeneration and pathologies, such as proliferative vitreoretinopathy.
A green-fluorescent siderophore protects bacterial communities from UV damage

Sunlight enables virtually all life on earth, but also entails harmful ultraviolet (UV) radiation inducing DNA damage. In response to UV stress, natural selection has favored both curative and preventive measures such as DNA repair mechanisms and UV-absorbing pigments. While UV protection by pigments is well documented in plants, animals and fungi, little is known about their protective role in bacteria. Here, we combine batch-culture and microscopy experiments to show that the siderophore pyoverdine, a fluorescent pigment produced by the opportunistic pathogen Pseudomonas aeruginosa offers high-level protection against UV radiation. Our results reveal that bacteria up-regulate pyoverdine production following UV exposure, seemingly as part of a general stress response. We further found that pyoverdine cannot curatively alleviate UV-damage but protects cells preventively and collectively from oncoming UV exposures through its accumulation in the environment. Altogether, our results reveal a new and non-canonical function of this iron-scavenging molecule, demonstrating that pyoverdine acts as a public sunscreen protecting bacterial populations from UV damage. Given that many bacteria produce pigments, such protection might be widespread in species colonizing habitats exposed to UV radiation.
Regulation of Chromatin Architecture by Transcription Factor Binding

Transcription factors (TF) bind to chromatin and regulate the expression of genes. The pair Myc:Max binds to E-box regulatory DNA elements throughout the genome, controlling transcription of a large group of specific genes. We introduce an implicit modeling protocol for Myc:Max binding to mesoscale chromatin fibers to determine TF effect on chromatin architecture and shed light on its mechanism of gene regulation. We first bind Myc:Max to different chromatin locations and show how it can direct fiber folding and formation of microdomains, and how this depends on the linker DNA length. Second, by simulating increasing concentrations of Myc:Max binding to fibers that differ in the DNA linker length, linker histone density, and acetylation levels, we assess the interplay between Myc:Max and other chromatin internal parameters. Third, we study the mechanism of gene silencing by Myc:Max binding to the Eed gene loci. Overall, our results show how chromatin architecture can be regulated by TF binding. The position of TF binding dictates the formation of microdomains that appear visible only at the ensemble level. On the other hand, the presence of linker histone, acetylations, or different linker DNA lengths regulates the concentration-dependent effect of TF binding. Furthermore, we show how TF binding can repress gene expression by increasing fiber folding motifs that help compact and occlude the promoter region. Importantly, this effect can be reversed by increasing linker histone density. Overall, these results shed light on the epigenetic control of the genome dictated by TF binding.
Ionospheric flow shear associated with the preexisting auroral arc: A statistical study from the FAST spacecraft data

An auroral substorm is a disturbance in the magnetosphere that releases energy stored in the magnetotail into the high‐latitude ionosphere. By definition, an auroral substorm commences when a discrete auroral arc brightens and subsequently expands poleward and azimuthally. The arc that brightens is usually the most equatorward of several auroral arcs that remain quiescent for ~5 to ~60 min before the breakup commences. This arc is often referred to as the “preexisting auroral arc (PAA)” or the “growth‐phase arc. ” In this study, we use FAST measurements to establish the statistics of flow patterns near PAAs in the ionosphere. We find that flow shear is present in the vicinity of a preexisting arc. When a PAA appears in the evening sector, enhanced westward flow develops equatorward of the arc, whereas when a PAA appears in the morning sector, enhanced eastward flow develops poleward of the arc. We benchmark locations of the PAAs relative to large‐scale field‐aligned currents (FACs) and convective flows in the ionosphere, finding that the arc forms in the upward current region within ~1° of the Region 1/Region 2 boundary in all local time sectors from 20 MLT to 03 MLT. We also find that near midnight in the Harang region, most of the PAAs lie within 0.5° poleward of the low‐latitude Region 1/Region 2 currents boundary and sit between the westward and eastward flow peak but equatorward of the flow reversal point. Finally, we examine arc‐associated electrodynamics and find that the FAC of the PAA is mainly closed by the north‐south Pedersen current in the ionosphere.
Elastic Bandwidth Allocation in Flexible OFDM-Based Optical Networks

Orthogonal Frequency Division Multiplexing (OFDM) has recently been proposed as a modulation technique for optical networks, because of its good spectral efficiency, flexibility, and tolerance to impairments. We consider the planning problem of an OFDM optical network, where we are given a traffic matrix that includes the requested transmission rates of the connections to be served. Connections are provisioned for their requested rate by elastically allocating spectrum using a variable number of OFDM subcarriers and choosing an appropriate modulation level, taking into account the transmission distance. We introduce the Routing, Modulation Level and Spectrum Allocation (RMLSA) problem, as opposed to the typical Routing and Wavelength Assignment (RWA) problem of traditional WDM networks, prove that is also NP-complete and present various algorithms to solve it. We start by presenting an optimal ILP RMLSA algorithm that minimizes the spectrum used to serve the traffic matrix, and also present a decomposition method that breaks RMLSA into its two substituent subproblems, namely 1) routing and modulation level and 2) spectrum allocation (RML+SA), and solves them sequentially. We also propose a heuristic algorithm that serves connections one-by-one and use it to solve the planning problem by sequentially serving all the connections in the traffic matrix. In the sequential algorithm, we investigate two policies for defining the order in which connections are considered. We also use a simulated annealing meta-heuristic to obtain even better orderings. We examine the performance of the proposed algorithms through simulation experiments and evaluate the spectrum utilization benefits that can be obtained by utilizing OFDM elastic bandwidth allocation, when compared to a traditional WDM network.
The transition from the Last Glacial Period in inland and near‐coastal Antarctica

Recent studies suggested that, during the transition out of the last glacial period, one near‐coastal site in Antarctica showed a response similar to that of Greenland, and unlike that of central Antarctica. Here, we present a new high‐resolution record of calcium from Dome C, Antarctica. Changes in flux of calcium, an indicator of dust input from other continents, should be synchronous across the region and probably the continent. Using Ca to synchronise records, we find that the main warming at the near‐coastal site of Taylor Dome was slower than suggested previously, and similar to that of central Antarctica. Until there is further evidence, it is still a reasonable hypothesis that Antarctic climate behaved more or less as a single unit during the transition.
USE OF THE CROSS-POWER-SPECTRUM PHASE IN ACOUSTIC EVENT LOCATION

LOCATION M. Omologo P. Svaizer ITC-IRST I-38050 Povo di Trento (Italy) ABSTRACT This orresponden e reports on the use of CrosspowerSpe trum Phase (CSP) analysis as an a urate Time Delay Estimation (TDE) te hnique. It is used in a mi rophone array system for the lo ation of a ousti events in noisy and reverberant environments. A orresponding Coheren e Measure and its graphi al representation are introdu ed to show TDE a ura y. Using a two mi rophone pair array, real experiments show less than 10 m average lo ation error in a 6m x 6m area.
Interpretable whole-brain prediction analysis with GraphNet

15 16 17 18 Article history: Accepted 26 December 2012 Available online xxxx 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 R R E C T E D P R Multivariate machine learning methods are increasingly used to analyze neuroimaging data, often replacing more traditional “mass univariate” techniques that fit data one voxel at a time. In the functional magnetic resonance imaging (fMRI) literature, this has led to broad application of “off-the-shelf” classification and regression methods. These generic approaches allow investigators to use ready-made algorithms to accurately decode perceptual, cognitive, or behavioral states from distributed patterns of neural activity. However, when applied to correlated whole-brain fMRI data these methods suffer from coefficient instability, are sensitive to outliers, and yield dense solutions that are hard to interpret without arbitrary thresholding. Here, we develop variants of the Graph-constrained Elastic Net (GraphNet), a fast, whole-brain regression and classification method developed for spatially and temporally correlated data that automatically yields interpretable coefficient maps (Grosenick et al., 2009b). GraphNet methods yield sparse but structured solutions by combining structured graph constraints (based on knowledge about coefficient smoothness or connectivity) with a global sparsity-inducing prior that automatically selects important variables. Because GraphNet methods can efficiently fit regression or classification models to whole-brain, multiple time-point data sets and enhance classification accuracy relative to volume-of-interest (VOI) approaches, they eliminate the need for inherently biased VOI analyses and allow whole-brain fitting without the multiple comparison problems that plague mass univariate and roaming VOI (“searchlight”) methods. As fMRI data are unlikely to be normally distributed, we (1) extend GraphNet to include robust loss functions that confer insensitivity to outliers, (2) equip them with “adaptive” penalties that asymptotically guarantee correct variable selection, and (3) develop a novel sparse structured Support Vector GraphNet classifier (SVGN). When applied to previously published data (Knutson et al., 2007), these efficient whole-brain methods significantly improved classification accuracy over previously reported VOI-based analyses on the same data (Grosenick et al., 2008; Knutson et al., 2007) while discovering task-related regions not documented in the original VOI approach. Critically, GraphNet estimates fit to the Knutson et al. (2007) data generalize well to out-of-sample data collected more than three years later on the same task but with different subjects and stimuli (Karmarkar et al., submitted for publication). By enabling robust and efficient selection of important voxels from whole-brain data taken over multiple time points (>100,000 “features”), these methods enable data-driven selection of brain areas that accurately predict single-trial behavior within and across individuals. © 2012 Published by Elsevier Inc.
Note — Providing a Window of Opportunity for Converting eStore Visitors

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A Performance Study of General Purpose Applications on Graphics Processors

Graphic processors (GPUs), with many light-weight data-parallel cores, can provide substantial parallel computational power to accelerate general purpose applications. To best utilize the GPU’s parallel computing resources, it is crucial to understand how GPU architectures and programming models can be applied to different categories of traditionally CPU applications. In this paper we examine several common, computationally demanding applications—Traffic Simulation, Thermal Simulation, and K-Means—whose performance may benefit from graphics hardware’s parallel computing capabilities. We show that all of our applications can be accelerated using the GPU, demonstrating as high as 40× speedup when compared with a CPU implementation. We also examine the performance characteristics of our applications, presenting advantages and inefficiencies of the programming model and desirable features to more easily and completely support a larger body of applications.
An evaluation of the SWATRER and, CERES-Millet models for southwest Niger

The SWATKER (Dierckx el aL, 1986) soil water and CERES-Millet (Godwin el ol. 1984; Jones el al. 1984) growth models wcre evaluated for millet (PennisNwn arnuicmun) during the 1989 growing season at Tara, Niger (300 km, south of Niamey). The required minimum data sets for the plant and soil components of each modcl were either f~ld determined or obtained from the literature. A field experiment was carried out in order to validate the soil water balance and plant growth subroutine6 Soil water content. leaf area and dry matter (DM) were measured weekly. Good agreement between simulated and measured soil water content was obtained with SWATRER. The CERES-Millet modcl overestimated leaf area index (LAI). DM and yield by 46%, 40% and 101% respectively. The CERES-Millet modcl consistently overestimated soil water content by 5% throughout the growing season. The SWATRER model showed good promise for evaluating waterilertilizcr management strategies. Once the CERES-Millet modcl is calibrated. it can be utilized to evaluate new production zonq new cultivara and numerous cultural practices.
Design of Cognitive Radio Systems Under Temperature-Interference Constraints: A Variational Inequality Approach

The concept of cognitive radio (CR) has recently received great attention from the research community as a promising paradigm to achieve efficient use of the frequency resource by allowing the coexistence of licensed (primary) and unlicensed (secondary) users in the same bandwidth. In this paper, we propose a novel Nash equilibrium (NE) problem to model concurrent communications of cognitive secondary users who compete against each other to maximize their information rate. The formulation contains constraints on the transmit power (and possibly spectral masks) as well as aggregate interference tolerable at the primary users' receivers. The coupling among the strategies of the players due to the interference constraints presents a new challenge for the analysis of this class of Nash games that cannot be addressed using the game theoretical models proposed in the literature. For this purpose, we need the framework given by the more advanced theory of finite-dimensional variational inequalities (VI). This provides us with all the mathematical tools necessary to analyze the proposed NE problem (e.g., existence and uniqueness of the solution) and to devise alternative distributed algorithms along with their convergence properties.
Glacial structures in northern Germany revealed by a high-resolution reflection seismic survey

In recent years, the sediments filling Pleistocene glacial structures have become of increasing importance to paleoclimate research. Climatic changes are documented by the deposition cycles in small, closed, trough or bowl-like structures. A 2-D, high-resolution, shallow reflection seismic survey was conducted in 1996 over such a structure near Tostedt in northern Germany. The objective was to obtain a more accurate picture of the structure and the underlying geology. Designed especially for shallow surveys, a newly developed impulse source provided sufficient energy to observe reflectors as deep as 400 m. Signals are characterized by a high-frequency content with maximum energy between 80 and 180 Hz. The migrated section shows a distinct reflection pattern revealing local glacial dynamics. Reflectors at depths of 30, 40, and 45 m from inside the Tostedt structure correlate well with three interstadials of the Weichselian period. Weak reflections define the bottom of the structure, with a maximum depth of 70 m. The structure is imbedded in a much larger, previously unexpected depression of similar shape. The fill of this larger depression is seismically nearly transparent. High-amplitude reflections delineate its lower boundary with a maximum depth of 130 m. Two major reflectors at depths of 170 and 270 m correlate with lower Miocene and middle Oligocene units. They indicate that subrosion, which might have been expected from the presence of a nearby salt diapir, is absent. This confirms the purely glacial origin of the two bowl-like structures.