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Abstract We report a new population of outer belt electron acceleration events ranging from hundreds of keV to ∼1.5 MeV that occurred inside the plasmasphere, which we named “Inside Events” (IEs). Based on 6 year observations from Van Allen Probes, we compare the statistical distributions of IEs with electron acceleration events outside the plasmasphere (OEs). We find that most IEs were observed atL < 4.0 at energies below ∼1.5 MeV, with weaker acceleration ratio (<10) and larger event numbers (peaking value reaching >200), compared to stronger but less frequently occurred (peaking event numbers only reaching ∼80) OEs that were mostly observed atL > 4.0. The evolution of electron phase space density of a typical IE shows signature of inward radial diffusion or transport. Our study provides a feasible mechanism for IE, which is the results of the inward radial transport of the electron acceleration in the outer region of outer belt. 

Abstract Previous research has shown that when domain‐general transitional probability (TP) cues to word segmentation are in conflict with language‐specific stress cues, English‐learning 5‐ and 7‐month‐olds rely on TP, whereas 9‐month‐olds rely on stress. In two artificial languages, we evaluated English‐learning infants’ sensitivity to TP cues to word segmentation vis‐a‐vis language‐specific vowel phonotactic (VP) cues—English words do not end in lax vowels. These cues were either consistent or conflicting. When these cues were in conflict, 10‐month‐olds relied on the VP cues, whereas 5‐month‐olds relied on TP. These findings align with statistical bootstrapping accounts, where infants initially use domain‐general distributional information for word segmentation, and subsequently discover language‐specific patterns based on segmented words. Research HighlightsResearch indicates that when transitional probability (TP) conflicts with stress cues for word segmentation, English‐learning 9‐month‐olds rely on stress, whereas younger infants rely on TP.In two artificial languages, we evaluated English‐learning infants’ sensitivity to TP versus vowel phonotactic (VP) cues for word segmentation.When these cues conflicted, 10‐month‐olds relied on VPs, whereas 5‐month‐olds relied on TP.These findings align with statistical bootstrapping accounts, where infants first utilize domain‐general distributional information for word segmentation, and then identify language‐specific patterns from segmented words. 

Abstract We perform a comprehensive investigation of the statistical distribution of outer belt electron acceleration events over energies from 300 keV to ∼10 MeV regardless of storm activity using 6‐years of observations from Van Allen Probes. We find that the statistical properties of acceleration events are consistent with the characteristic energies of combined local acceleration by chorus waves and inward radial diffusion. While electron acceleration events frequently occur both at <2 MeV atL < 4.0 and at multi‐MeV atL > 4.5, significant acceleration events are confined toL > ∼4.0. By performing superposed epoch analysis of acceleration events during storm and non/weak storm events and comparing their geomagnetic conditions, we reveal the strong correlation (>0.8) between accumulated impacts of substorms as measured by time‐integrated AL (Int(AL)) and the upper flux limit of electron acceleration. While intense storms can provide favorable conditions for efficient acceleration, they are not necessarily required to produce large maximum fluxes. 

Abstract Understanding and forecasting outer radiation belt electron flux dropouts is one of the top concerns in space physics. By constructing Support Vector Machine (SVM) models to predict storm‐time dropouts for both relativistic and ultra‐relativistic electrons overL = 4.0–6.0, we investigate the nonlinear correlations between various driving factors (model inputs) and dropouts (model output) and rank their relative importance. Only time series of geomagnetic indices and solar wind parameters are adopted as model inputs. A comparison of the performance of the SVM models that uses only one driving factor at a time enables us to identify the most informative parameter and its optimal length of time history. Its accuracy and the ability to correctly predict dropouts identifies the SYM‐H index as the governing factor atL = 4.0–4.5, while solar wind parameters dominate the dropouts at higher L‐shells (L = 6.0). Our SVM model also gives good prediction of dropouts during completely out‐of‐sample storms. 

The proliferation of low-end low-power internet-of-things (IoT) devices in smart environments necessitates secure identification and authentication of these devices via low-overhead fingerprinting methods. Previous work typically utilizes characteristics of the device's wireless modulation (WiFi, BLE, etc.) in the spectrum, or more recently, electromagnetic emanations from the device's DRAM to perform fingerprinting. The problem is that many devices, especially low-end IoT/embedded systems, may not have transmitter modules, DRAM, or other complex components, therefore making fingerprinting infeasible or challenging. To address this concern, we utilize electromagnetic emanations derived from the processor's clock to fingerprint. We present Digitus, an emanations-based fingerprinting system that can authenticate IoT devices at range. The advantage of Digitus is that we can authenticate low-power IoT devices using features intrinsic to their normal operation without the need for additional transmitters and/or other complex components such as DRAM. Our experiments demonstrate that we achieve ≥ 95% accuracy on average, applicability in a wide range of IoT scenarios (range ≥ 5m, non-line-of-sight, etc.), as well as support for IoT applications such as finding hidden devices. Digitus represents a low-overhead solution for the authentication of low-end IoT devices. 

Abstract Utilizing observations from the Electron Losses and Fields Investigation satellites, we present a statistical study of ∼2,000 events in 2019–2020 characterizing the occurrence in magnetic local time (MLT) and latitude of ≥50 keV electron isotropy boundaries (IBs) and associated electron precipitation. The isotropy boundary of an electron of a given energy is the magnetic latitude poleward of which persistent isotropized pitch angle distributions (J_prec/J_perp∼ 1) are first observed to occur, interpreted as resulting from magnetic field‐line curvature scattering in the equatorial magnetosphere. We find that energetic electron IBs can be well‐recognized on the nightside from dusk until dawn, under all geomagnetic activity conditions, with a peak occurrence rate of almost 90% near ∼22 hr in MLT, remaining above 80% from 21 to 01 MLT. The observed IBs span International Geophysical Reference Field (IGRF) magnetic latitudes of 60°–74° with a maximum occurrence between 66° and 71° (Lof 6–8), trending toward lower latitudes and premidnight local times with activity. The precipitating energy flux of ≥50 keV electrons averaged over the IB‐associated latitudes varies over four orders of magnitude, up to 1 erg/cm²‐s, and often includes wide‐energy electron spectra exceeding 1 MeV. The IB‐associated energies and precipitating fluxes also exhibit peak values near midnight for low activity, shifting toward premidnight for elevated activity. The average total precipitating power deposited over the high‐latitude nightside atmosphere (55°–80°; IGRFL ≥ 3) attributed to IBs is 10%–20%, or 10 MW, but at times can approach 100% of the total ≥50 keV electron energy deposition over the entire subauroral and auroral zone region, exceeding 1 GW. 

Abstract Using 5‐year of measurements from Van Allen Probes, we present a survey of the statistical dependence of the Earth's outer radiation belt electron flux dropouts during geomagnetic storms on electron energy and various driving parameters including interplanetary magnetic field B_z, P_SW, SYM‐H, and AE. By systematically investigating the dropouts over energies of 1 keV–10 MeV at L‐shells spanning 4.0–6.5, we find that the dropouts are naturally divided into three regions. The dropouts show much higher occurrence rates at energies below ∼100 keV and above ∼1 MeV compared to much smaller occurrence rate at intermediate energies around hundreds of keV. The flux decays more dramatically at energies above ∼1 MeV compared to the energies below ∼100 keV. The flux dropouts of electrons below ∼100 keV strongly depend on magnetic local time (MLT), which demonstrate high occurrence rates on the nightside (18–06 MLT), with the highest occurrence rate associated with northward B_z, strong P_SWand SYM‐H, and weak AE conditions. The strongest flux decay of these dropouts is found on the nightside, which strongly depends on P_SWand SYM‐H. However, there is no clear MLT dependence of the occurrence rate of relativistic electron flux dropouts above ∼1 MeV, but the flux decay of these dropouts is more significant on the dayside, with stronger decay associated with southward IMF B_z, strong P_SW, SYM‐H, and AE conditions. Our statistical results are crucial for understanding of the fundamental physical mechanisms that control the outer belt electron dynamics and developing future potential radiation belt forecasting capability. 

Remote memory techniques are gaining traction in datacenters because they can significantly improve memory utilization. A popular approach is to use kernel-level, page-based memory swapping to deliver remote memory as it is transparent, enabling existing applications to benefit without modifications. Unfortunately, current implementations suffer from high software overheads, resulting in significantly worse tail latency and throughput relative to local memory. Hermit is a redesigned swap system that overcomes this limitation through a novel technique called adaptive, feedback-directed asynchrony. It takes non-urgent but time-consuming operations (e.g., swap-out, cgroup charge, I/O deduplication, etc.) off the fault-handling path and executes them asynchronously. Different from prior work such as Fastswap, Hermit collects runtime feedback and uses it to direct how asynchrony should be performed—i.e., whether asynchronous operations should be enabled, the level of asynchrony, and how asynchronous operations should be scheduled. We implemented Hermit in Linux 5.14. An evaluation with a set of latency-critical applications shows that Hermit delivers low-latency remote memory. For example, it reduces the 99th percentile latency of Memcached by 99.7% from 36 ms to 91 µs. Running Hermit over batch applications improves their overall throughput by 1.24× on average. These results are achieved without changing a single line of user code.