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Effect of opioid-free general anesthesia versus opioid-based general anesthesia on postoperative pain and immune response in patients undergoing breast cancer surgery: A randomized controlled trial
No full textPerioperative opioids are associated with several adverse effects including nausea, vomiting, and long-term addiction. Opioid-free anesthesia may reduce postoperative morbidity, enable daycare surgery, and decrease cancer recurrence. In our study, we aimed to assess the efficacy of opioid-free anesthesia versus opioid-based anesthesia in patients undergoing breast cancer surgery in terms of postoperative opioid use, pain scores, expression of immune cells, and side effects. Hundred patients undergoing breast cancer surgery were randomized into two groups (1:1 ratio). Group O received opioid-based anesthesia and Group N did not receive any opioid intraoperatively. Our primary outcome was total postoperative morphine consumption in 24 h managed with a patient-controlled analgesia (PCA) pump containing morphine in both groups. Secondary outcomes were numerical rating scale (NRS) at rest and movement at immediate postoperative period, 30 min, 1 h, 2 h, 6 h, and 24 h postoperatively was measured. Blood samples were also taken at different time points to measure inflammatory markers. There was no statistical difference in the total 24 h postoperative morphine consumption in between the two groups (p = 0.13). The patient satisfaction scores and NRS at rest and on movement at various time points postoperatively were similar (p < 0.05). There was a significant difference in neutrophil lymphocyte ratio (NLR) between the two groups in the samples taken at 24 h postoperative period (p = 0.03). No complications were reported in any group. While our study did not show opioid-free anesthesia’s superiority in postoperative morphine consumption, it established the feasibility and safety of a non-opioid technique for breast cancer surgery. The approach may offer advantages, including potential immunosuppression relief, making it a viable option for patients prone to opioid-related side effects
Atmospheric and Land Drivers of Streamflow Flash Droughts in India
No full textStreamflow flash droughts (SFDs), characterized by a rapid decline in streamflow over a relatively short period, affect water availability, hydropower generation, and the ecosystem. However, atmospheric and land processes that drive SFDs in the monsoonal climate of India remain unexplored. Using observations, reanalysis data sets, and model simulations, we examined the critical drivers of SFDs in 64 catchments in India during the 1971–2018 period. We identified meteorological flash droughts (MFDs) using precipitation and SFDs using in situ observations and model simulations of streamflow. We show that precipitation deficit and anomalous high temperature, driven mainly by the summer monsoon breaks, lead to the development of MFDs. Antecedent baseflow conditions play a major role in the propagation of MFDs to SFDs. Favorable atmospheric conditions (driven by the monsoon breaks) cause MFDs, which translate to SFDs. High and low baseflow conditions limit the rapid decline in streamflow, which controls the occurrence of streamflow flash drought. On the other hand, favorable atmospheric conditions combined with moderate baseflow can trigger SFDs in India during the summer monsoon season. Moreover, humid catchments are more prone to propagation from MFDs to SFDs during the monsoon season in India. Understanding the crucial role of atmospheric and land drivers can assist in examining the occurrence of streamflow flash drought with implications for water resources planning and management
Collective intelligent strategy for improved segmentation of COVID-19 from CT
No full textWe propose a novel non-invasive tool, using deep learning and imaging, for delineating COVID-19 infection in lungs. The Ensembling of selective Focus-based Multi-resolution Convolution network (EFMC), employing Leave-One-Patient-Out (LOPO) training, exhibits high sensitivity and precision in outlining infected regions along with assessment of severity. The selective focus mechanism combines contextual with local information, at multiple resolutions, for accurate segmentation. Ensemble learning integrates heterogeneity of decision through different base classifiers. The superiority of EFMC, even with severe class imbalance, is established through comparison with existing state-of-the-art learning models over four publicly-available COVID-19 datasets. The results are suggestive of the relevance of deep learning in providing assistive intelligence to medical practitioners, when they are overburdened with patients as in pandemics
Dot-product proofs and their applications
No full textA dot-product proof (DPP) is a simple probabilistic proof system in which the input statement x and the proof π are vectors over a finite field F, and the proof is verified by making a single dot-product query ⟨q,(x∥π)⟩ jointly to x and π. A DPP can be viewed as a 1-query fully linear PCP. We study the feasibility and efficiency of D PPs, obtaining the following results: •Small-field DPP. For any finite field F and Boolean circuit C of size S, there is a D PP for proving that there exists w such that C(x, w)=1 with a proof ρ of length S⋅poly(|F|) and soundness error ε=O(1/√|F|). We show this error to be asymptotically optimal. In particular, and in contrast to the best known PCPs, there exist strictly linear-length DPPs over constant-size fields. •Large-field DPP. If |F|≥ poly (S/ε), there is a similar DPP with soundness error ε and proof length O(S) (in field elements). The above results do not rely on the PCP theorem and their proofs are considerably simpler. We apply our DPP constructions toward two kinds of applications. •Hardness of approximation. We obtain a simple proof for the NP-hardness of approximating MAXLIN (with dense instances) over any finite field F up to some constant factor c>1, independent of F. Unlike previous PCP-based proofs, our proof yields exponential-time hardness under the exponential time hypothesis (ETH). •Succinct arguments. We improve the concrete efficiency of succinct interactive arguments in the generic group model using input-independent preprocessing. In particular, the communication is comparable to sending two group elements and the verifier's computation is dominated by a single group exponentiation. We also show how to use DPPs together with linear-only encryption to construct succinct commit-and-prove arguments
An Evaluation of Antarctic Ice Core Nitrate Records as a Proxy for Solar Activity
No full textNitrate (NO3-) deposition in polar ice sheets archives valuable information on past solar activity. However, interpretation of Antarctic ice core NO3- records as a proxy for past solar activity remains challenging due to multiple sources and processes controlling NO3- variability in ice core records. Here, we present a new high-resolution ice core NO3- record (1905–2005 CE) from coastal Dronning Maud Land, East Antarctica, to investigate the solar signal and other forcing factors/processes in controlling ice core NO3- variability. Our record exhibits significant periodicity in the range of 8–12 years frequency band during 1940–2005 CE, apparently identified as the signal of ∼11 year sunspot cycle; however, such signal was not detected in the previous interval during 1905–1940 CE. To address the discontinuous and/or obscured signals in the present ice core record and inconsistency among various Antarctica ice core records, we extended our investigations to 10 ice core NO3- records from various regions of Antarctica. Analysis of seven records for the common interval from 1738 to 1990 CE reveals dominant periodicities of 8–12 years, indicating solar forcing as a primary driver, followed by precipitation modulated by El Niño-Southern Oscillation and Pacific Decadal Oscillation. Further, our investigation reveals that the solar signal extracted from multiple records becomes undetectable when mean annual hemispheric sunspot numbers larger than 140, suggesting this is a threshold limit for detecting the solar signal. These findings will improve our present understanding of ice core NO3- records as a proxy for past solar activity
Invariant subspaces of analytic perturbations
No full textAnalytic perturbations are understood here as shifts of the form M2+F, where M2 is the unilateral shift and F is a finite rank operator on the Hardy space over the open unit disk. Here the term “a shift” refers to the multiplication operator M2 on some analytic reproducing kernel Hilbert space. In this paper, first, a natural class of finite rank operators is isolated for which the corresponding perturbations are analytic, and then a complete classification of invariant subspaces of those analytic perturbations is presented. Some instructive examples and several distinctive properties (like cyclicity, essential normality, hyponormality, etc.) of analytic perturbations are also described
Impact of higher harmonics of gravitational radiation on the population inference of binary black holes
No full textTemplates modeling just the dominant mode of gravitational radiation are generally sufficient for the unbiased parameter inference of near-equal-mass compact binary mergers. However, neglecting the subdominant modes can bias the inference if the binary is significantly asymmetric, very massive, or has misaligned spins. In this work, we explore if neglecting these subdominant modes in the parameter estimation of nonspinning binary black hole mergers can bias the inference of their population-level properties such as mass and merger redshift distributions. Assuming the design sensitivity of the advanced LIGO-Virgo detector network, we find that neglecting subdominant modes will not cause a significant bias in the population inference, although including them will provide more precise estimates. This is primarily because asymmetric binaries are expected to be rarer in our detected sample, due to their intrinsic rareness and the observational selection effects. The increased precision in the measurement of the maximum black hole mass can help in better constraining the upper mass gap in the mass spectrum
Search for gravitational-lensing signatures in the full third observing run of the LIGO–Virgo network
No full textGravitational lensing by massive objects along the line of sight to the source causes distortions to gravitational wave (GW) signals; such distortions may reveal information about fundamental physics, cosmology, and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO-Virgo network. We search for repeated signals from strong lensing by (1) performing targeted searches for subthreshold signals, (2) calculating the degree of overlap among the intrinsic parameters and sky location of pairs of signals, (3) comparing the similarities of the spectrograms among pairs of signals, and (4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by (1) frequency-independent phase shifts in strongly lensed images, and (2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the nondetection of GW lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects
Reactive scattering of H<sub>2</sub> on Cu(111) at 925 K: Effective Hartree potential vs sudden approximation
No full textWe present new quantum dynamical results for the reactive scattering of hydrogen molecules from a Cu(111) surface at a surface temperature of 925 K. Reaction, scattering, and diffraction probabilities are compared for results obtained using both an effective Hartree potential (EfHP) and a sudden approximation approach, implemented through the static corrugation model (SCM), to include surface temperature effects. Toward this goal, we show how the SRP48 DFT-functional and an embedded atom potential perform when used to calculate copper lattice constants and thermal expansion coefficients based on lattice dynamics calculations within the quasi-harmonic approximation. The so-calculated phonons are then used in the EfHP approach to replace the normal modes of a fictitious copper cluster used in earlier work. We find that both the EfHP and SCM approaches correctly predict the reaction probability curve broadening effect when the surface temperature is increased. Similarly, results for rovibrationally elastic scattering appear to be improved, predominantly for the SCM model. The behavior of the EfHP results appears to remain much closer to that of a Born–Oppenheimer static surface approach, which excludes any surface temperature effects. Finally, for the diffraction, we show very clear attenuation effects for the SCM approach, significantly decreasing specular diffraction probabilities at 925 K surface temperature. These results demonstrate that state-of-the-art theoretical models are able to reproduce strictly quantum mechanical scattering effects with a sudden approximation model and open up interesting opportunities for further comparisons to experimental diffraction results
Mechanistic insights into the antibacterial property of MIL-100 (Fe) metal-organic framework
No full textMetal organic frameworks (MOFs) have gained immense importance regarding water treatment in the last decade. In this work, an iron (Fe) based highly porous MOF (MIL-100 (Fe)) has been explored for its antibacterial property. The synthesis of the said MOF was carried out in a facile green route without using hydrofluoric acid. MIL-100 (Fe) was characterized in terms of its surface area (1704 m2/g) and surface zeta potential (pHZPC = 7.6, 21.6 mV at pH 2). The stuctural integrity of the prepared MOF was verified by XRD analysis. The prepared MOF was subjected to antibacterial study in simulated as well as real life sample. In the simulated study, effect of MIL-100 (Fe) on both gram positive (Staphylococcus aureus) and gram negative (Pseudomonas aeruginosa) bacteria was observed. It can be inferred from the study that the bactericidal effect of MIL-100 (Fe) can be attributed to the generation of reactive oxygen species and the MOF was more effective towards the gram negative strain