Riesz transform and commutators in the Dunkl setting

In this paper we characterise the optimal pointwise size and regularity estimates for the Dunkl Riesz transform kernel involving both the Euclidean metric and the Dunkl metric, where these two metrics are not equivalent. We further establish a suitable version of the pointwise kernel lower bound of the Dunkl Riesz transform via the Euclidean metric only. Then we show that the lower bound of commutator of the Dunkl Riesz transform is with respect to the BMO space associated with the Euclidean metric, and that the upper bound is respect to the BMO space associated with the Dunkl metric. Moreover, the compactness and the two types of VMO are also addressed

Fundamental‐mode basin oscillations in the Japan/East Sea

We present observational evidence from coastal tide station and bottom pressure data that basin‐mode oscillations are frequently excited in the Japan/East Sea (JES). The fundamental basin‐mode is a Kelvin‐wave‐like oscillation consisting of a single amphidromic system around which the high water propagates counter‐clockwise. Its period is about 6.7 hours and its coastal wavelength is equivalent to the circumference of the JES. The relative amplitudes of the observed oscillations agree with Rikiishi\u27s 1986 model results except for stations near the Korea Strait where the closed boundary in the model produces unrealistically high amplitudes. The basin oscillation amplitude varies on synoptic time scales (2–17 days) and exhibits seasonal variations. The optimal wind direction to generate basin‐mode oscillations is along 60°/240° T

Real-time Network Intrusion Detection via Decision Transformers

Many cybersecurity problems that require real-time decision-making based on temporal observations can be abstracted as a sequence modeling problem, e.g., network intrusion detection from a sequence of arriving packets. Existing approaches like reinforcement learning may not be suitable for such cybersecurity decision problems, since the Markovian property may not necessarily hold and the underlying network states are often not observable. In this paper, we cast the problem of real-time network intrusion detection as casual sequence modeling and draw upon the power of the transformer architecture for real-time decision-making. By conditioning a causal decision transformer on past trajectories, consisting of the rewards, network packets, and detection decisions, our proposed framework will generate future detection decisions to achieve the desired return. It enables decision transformers to be applied to real-time network intrusion detection, as well as a novel tradeoff between the accuracy and timeliness of detection. The proposed solution is evaluated on public network intrusion detection datasets and outperforms several baseline algorithms using reinforcement learning and sequence modeling, in terms of detection accuracy and timeliness

Low temperature ordering and high (001) orientation of [Fe/Pt/Cu]\u3csub\u3e18\u3c/sub\u3e multilayer films

[Fe/Pt/Cu]18 multilayer films with different Cu thicknesses were prepared on thermally oxidized Si (111) substrates at room temperature using dc- and rf-magnetron sputtering. The magnetic proper-ties and microstructure of [Fe/Pt/Cu]18 multilayer films annealed at various temperatures have been investigated. Compared with pure [Fe/Pt]18 multilayer films low-temperature ordering and (001) ori-entation in the annealed films with Cu volume concentration below 20% can be obtained. During annealing process Cu atoms diffused into FePt lattice which enhanced the diffusion of Fe and Pt atoms and the grain growth of the films. The perpendicular anisotropy and hard magnetic properties of the films deteriorated with increasing Cu volume concentration due to the formation of L10 Fe-CuPt2 phase

Low temperature ordering and high (001) orientation of [Fe/Pt/Cu]\u3csub\u3e18\u3c/sub\u3e multilayer films

[Fe/Pt/Cu]18 multilayer films with different Cu thicknesses were prepared on thermally oxidized Si (111) substrates at room temperature using dc- and rf-magnetron sputtering. The magnetic proper-ties and microstructure of [Fe/Pt/Cu]18 multilayer films annealed at various temperatures have been investigated. Compared with pure [Fe/Pt]18 multilayer films low-temperature ordering and (001) ori-entation in the annealed films with Cu volume concentration below 20% can be obtained. During annealing process Cu atoms diffused into FePt lattice which enhanced the diffusion of Fe and Pt atoms and the grain growth of the films. The perpendicular anisotropy and hard magnetic properties of the films deteriorated with increasing Cu volume concentration due to the formation of L10 Fe-CuPt2 phase

Rapid Variability in the Japan/East Sea: Basin Oscillations, Internal Tides, and Near-Inertial Oscillations

Many processes contribute to the variations of currents, sea surface height (SSH), and thermocline depth in marginal seas. Energetic examples range broadly over time scales from slow mesoscale and interannual variations to rapid basin oscillations, internal tides, and near-inertial oscillations. Our measurement array in the Japan/East Sea (JES) offered a special opportunity to study these processes simultaneously, revealing important interconnections among them

Differentiating Axonal from Demyelinating Neuropathies using Multiparametric Quantitative MRI of Peripheral Nerves

Objectives: To develop a multiparametric quantitative MRI (qMRI) method to track pathological changes in the peripheral neuropathies. Background: Irrespective of the causes or types of polyneuropathies, peripheral nerves are mainly afflicted by two kinds of pathologies – axonal loss and demyelination. It is critical to differentiate between the two as treatments are different for the two conditions. While nerve conduction studies (NCS) have been used to differentiate the two pathologies in the distal nerves, there are no tools to probe the pathologies in the proximal peripheral nerves. This is particularly needed when distal nerves become non-responsive in NCS. Methods: We have developed a qMRI method that quantifies the sciatic and tibial nerves with 10 parameters that are sensitive to different aspects of myelin and axonal pathologies: magnetization transfer ratio (MTR), magnetization transfer saturation index (MTsat), longitudinal relaxation time (T1), proton density (PD), effective transverse relaxation time (T2*), fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), radial diffusivity (RD), and nerve fascicular volume (fVol). In this pilot study, we studied 4 patients with Charcot-Marie-Tooth type-1A (CMT1A), 2 patients with CMT type-2S (CMT2S), and 17 healthy controls. Results: Compared with the healthy controls, patients with CMT2S (axonal type) had a comparable MTR, MTsat, T1, PD and fVol, but a reduced T2*. While patients with CMT1A (demyelinating type) had a reduced MTR and MTsat, increased fVol, T1 and PD, and comparable T2*. All 6 patients with CMT shared a change in reduced FA, which was driven by a reduced AD and an increased RD. Conclusions: The data show different qMRI patterns between axonal and demyelinating neuropathies. The differential changes will be further verified in a larger cohort of patients with peripheral neuropathies

Prevalence of Postpartum Depression Based on Diagnostic Interviews:A Systematic Review and Meta-Analysis

Background. Postpartum depression (PPD) is common after childbirth. Previous reviews on the prevalence of PPD have mainly included results that relied on screening instruments or a mixture of such instruments and diagnostic interviews. In this study, we aimed to assess the prevalence of PPD based exclusively on studies using diagnostic interviews, as they provide the most reliable and valid approach for defining “caseness.” Methods. Using PubMed, Web of Science, Cochrane Library, Embase, CNKI, WANFANG DATA, and CBM up to September 18, 2022, we searched for original articles reporting data that could be used to calculate the prevalence of PPD based on diagnostic interviews. A random-effect meta-analysis model was then used to estimate the pooled prevalence. In addition, we assessed quality, heterogeneity, and publication bias across studies. Also, we did subgroup analyses to explore the pooled prevalence at different time points and settings. This study was registered with PROSPERO, CRD42021244539. Results. Of 17,115 articles retrieved, 54 studies were included (total sample size=15,586 women). The pooled prevalence of all depression and major depression within one year postpartum was 12.1% (95% CI 10.3%-14.1%; I2=91.0%) and 7.0% (95% CI 5.7%-8.4%; I2=83.0%), respectively. The peaks of all depression occurred during the first 6 months postpartum, especially 2-3 weeks and 6-8 weeks. Subgroup analyses showed that the prevalence of major depression was associated with the income level of countries (higher in low- and middle-income countries (LMICs) than in high-income countries (HICs)) and diagnostic criteria (higher using ICD than using DSM and RDC). No evidence of publication bias was found. Conclusions. Approximately one in eight postpartum women experiences a depressive condition, with one in fifteen suffering major depression. The pooled prevalence based on diagnostic interviews was lower than the existing consensus, which was largely based on self-reported screening instruments. The higher prevalence in LMICs underlines the importance of strengthening research and service provision among these populations