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\"A clear understanding of the Earth's past evolution can provide the key to its possible future development. The Earth: Its Birth and Growth explores the evolution of the Earth over 4.6 billion years using basic reasoning and simple illustrations to help explain the underlying physical and chemical principles and major processes involved. Fully updated and revised, this rigorous but accessible second edition includes three completely new chapters. It incorporates exciting developments in isotope geology, placing results within a wider framework of Earth evolution and plate tectonics. Some background in physics and chemistry is assumed, but basic theories and processes are explained concisely in self-contained sections. Key research papers and review articles are fully referenced. This book is ideal as supplementary reading for undergraduate and graduate students in isotope geochemistry, geodynamics, plate tectonics and planetary science. It also provides an enjoyable overview of Earth's evolution for professional scientists and general readers\"-- Provided by publisher.

Acbstract Background Inhibition of proprotein convertase subtilisin/kexin type 9 (PCSK9) has been intensively studied to lower low-density lipoprotein cholesterol (LDL-C) levels. The purpose of this meta-analysis was to evaluate the safety and efficacy of anti-PCSK9 antibodies in randomized, controlled trials (RCTs). Methods PubMed, EMBASE, CENTRAL databases, and recent conferences were searched. Safety outcomes were rates of common adverse events. Efficacy outcomes included percentages of LDL-C lowering and other lipid changes compared with placebo and ezetimibe, respectively. Results Twenty-five RCTs encompassing 12,200 patients were included. The rates of common adverse events were firstly reported in our study by pooling together all evidence in RCTs, showing largely no significant difference between anti-PCSK9 antibodies and placebo (or ezetimibe), except that alirocumab was associated with reduced rates of death (relative risk (RR): 0.43, 95 % confidence interval (CI): 0.19 to 0.96, P = 0.04) and an increased rate of injection-site reactions (RR: 1.48, 95 % CI: 1.05 to 2.09, P = 0.02); evolocumab reduced the rate of abnormal liver function (RR: 0.43, 95 % CI: 0.20 to 0.93, P = 0.03), both compared with placebo. No significant difference in safety outcomes was detected between monthly 420 mg and biweekly 140 mg evolocumab treatments. Monthly 420 mg evolocumab treatment significantly reduced LDL-C by −54.6 % (95 % CI: −58.7 to −50.5 %) and by absolute −78.9 mg/dl (95 % CI: −88.9 to −68.9 mg/dl) versus placebo, and by −36.3 % (95 % CI: −38.8 to −33.9 %) versus ezetimibe, and increased high-density lipoprotein cholesterol (HDL-C) by 7.6 % (95 % CI: 5.7 to 9.5 %) versus placebo and 6.4 % (95 % CI: 4.3 to 8.4 %) versus ezetimibe. An equal or even greater change was observed following biweekly 140 mg administration. Significant and favorable changes were also detected in other lipids following evolocumab treatment. Biweekly 50 to 150 mg alirocumab lowered LDL-C by −52.6 % (95 % CI: −58.2 to −47.0 %) versus placebo, by −29.9 % (95 % CI: −32.9 to −26.9 %) versus ezetimibe, and increased HDL-C by 8.0 % (95 % CI: 4.2 to 11.7 %) versus placebo. Conclusions Evolocumab and alirocumab were safe and well-tolerated from our most-powered analyses. Both antibodies substantially reduced the LDL-C level by over 50 %, increased the HDL-C level, and resulted in favorable changes in other lipids.

Recent pulsar timing array collaborations have reported evidence of the stochastic gravitational wave background. The gravitational waves induced by primordial curvature perturbations, referred to as scalar-induced gravitational waves (SIGWs), could potentially be the physical origins of the gravitational wave background. Due to nonlinearity of Einstein’s gravity, there is non-Gaussianity of SIGWs even when the sourced primordial curvature perturbation is Gaussian. This paper investigates the intrinsic non-Gaussianity of SIGWs influenced by formation of primordial black holes. Specifically, we examine whether spectral width of Gaussian primordial curvature perturbations can affect non-Gaussianity of SIGWs. In order to ensure us to correctly quantify the degree of non-Gaussianity, we introduce an oscillation average scheme that can conserve the exact results of skewness of SIGWs. In this framework, the oscillation of SIGWs not only suppresses the bispectrum amplitude but also leads to a flattened-type bispectrum. Based on our results of skewness, it is found that the primordial curvature power spectrum with a narrower width can enhance the intrinsic non-Gaussianity.

Arc magmas are important building blocks of the continental crust. Because many arc lavas are oxidized, continent formation is thought to be associated with oxidizing conditions. On the basis of copper's (Cu's) affinity for reduced sulfur phases, we tracked the redox state of arc magmas from mantle source to emplacement in the crust. Primary arc and mid-ocean ridge basalts have identical Cu contents, indicating that the redox states of primitive arc magmas are indistinguishable from that of mid-ocean ridge basalts. During magmatic differentiation, the Cu content of most arc magmas decreases markedly because of sulfide segregation. Because a similar depletion in Cu characterizes global continental crust, the formation of sulfide-bearing cumulates under reducing conditions may be a critical step in continent formation.

The rapid growth of electric vehicles (EVs) presents significant challenges for power grids, particularly in managing fluctuating demand and optimizing the placement of charging infrastructure. This study proposes an integrated framework combining deep learning, reinforcement learning, path optimization, and power trading strategies to address these challenges. A Long Short-Term Memory (LSTM) model was employed to predict regional EV charging demand, improving forecasting accuracy by 12.3%. A Deep Q-Network (DQN) optimized charging station placement, reducing supply-demand imbalances by 8.9%. Path optimization, using the Dijkstra algorithm, minimized travel times for EV users by 11.4%. Additionally, regional power trading was optimized to balance electricity supply and demand, reducing locational marginal price (LMP) disparities by 10%. The combined system resulted in reduced grid congestion, lower operational costs, and improved user satisfaction. These findings demonstrate the potential of integrating advanced machine learning techniques with power grid management to support the growing demand for EVs.

Since it was confirmed two decades ago that the expansion of the Universe is accelerating, it would be of theoretical interests to figure out what is the influence from cosmological constant on detection of stochastic gravitational wave background. This paper studies the overlap reduction functions in de-Sitter space-time for a pair of one-way tracking gravitational wave detectors. It is shown to be non-trivial in an expanding Universe, because the propagation of light along line of sight also has effect on the response of GW detectors. It is found that the expansion of the Universe can enhance the value of magnitude of the overlap reduction functions, when the detector pairs are close to each other. For nanohertz gravitational waves, this effect can dominate the values of overlap reduction functions when the galactic pulsar pairs are separated by milliarcsecond.

AbstractObjectiveTo examine the protective effects of appropriate personal protective equipment for frontline healthcare professionals who provided care for patients with coronavirus disease 2019 (covid-19).DesignCross sectional study.SettingFour hospitals in Wuhan, China.Participants420 healthcare professionals (116 doctors and 304 nurses) who were deployed to Wuhan by two affiliated hospitals of Sun Yat-sen University and Nanfang Hospital of Southern Medical University for 6-8 weeks from 24 January to 7 April 2020. These study participants were provided with appropriate personal protective equipment to deliver healthcare to patients admitted to hospital with covid-19 and were involved in aerosol generating procedures. 77 healthcare professionals with no exposure history to covid-19 and 80 patients who had recovered from covid-19 were recruited to verify the accuracy of antibody testing.Main outcome measuresCovid-19 related symptoms (fever, cough, and dyspnoea) and evidence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, defined as a positive test for virus specific nucleic acids in nasopharyngeal swabs, or a positive test for IgM or IgG antibodies in the serum samples.ResultsThe average age of study participants was 35.8 years and 68.1% (286/420) were women. These study participants worked 4-6 hour shifts for an average of 5.4 days a week; they worked an average of 16.2 hours each week in intensive care units. All 420 study participants had direct contact with patients with covid-19 and performed at least one aerosol generating procedure. During the deployment period in Wuhan, none of the study participants reported covid-19 related symptoms. When the participants returned home, they all tested negative for SARS-CoV-2 specific nucleic acids and IgM or IgG antibodies (95% confidence interval 0.0 to 0.7%).ConclusionBefore a safe and effective vaccine becomes available, healthcare professionals remain susceptible to covid-19. Despite being at high risk of exposure, study participants were appropriately protected and did not contract infection or develop protective immunity against SARS-CoV-2. Healthcare systems must give priority to the procurement and distribution of personal protective equipment, and provide adequate training to healthcare professionals in its use.

The importance of highly siderophile elements (HSEs; namely, gold, iridium, osmium, palladium, platinum, rhenium, rhodium and ruthenium) in tracking the late accretion stages of planetary formation has long been recognized. However, the precise nature of the Moon’s accretional history remains enigmatic. There is a substantial mismatch in the HSE budgets of the Earth and the Moon, with the Earth seeming to have accreted disproportionally more HSEs than the Moon 1 . Several scenarios have been proposed to explain this conundrum, including the delivery of HSEs to the Earth by a few big impactors 1 , the accretion of pebble-sized objects on dynamically cold orbits that enhanced the Earth’s gravitational focusing factor 2 , and the ‘sawtooth’ impact model, with its much reduced impact flux before about 4.10 billion years ago 3 . However, most of these models assume a high impactor-retention ratio (the fraction of impactor mass retained on the target) for the Moon. Here we perform a series of impact simulations to quantify the impactor-retention ratio, followed by a Monte Carlo procedure considering a monotonically decaying impact flux 4 , to compute the impactor mass accreted into the lunar crust and mantle over their histories. We find that the average impactor-retention ratio for the Moon’s entire impact history is about three times lower than previously estimated 1 , 3 . Our results indicate that, to match the HSE budgets of the lunar crust and mantle 5 , 6 , the retention of HSEs should have started 4.35 billion years ago, when most of the lunar magma ocean was solidified 7 , 8 . Mass accreted before this time must have lost its HSEs to the lunar core, presumably during lunar mantle crystallization 9 . The combination of a low impactor-retention ratio and a late retention of HSEs in the lunar mantle provides a realistic explanation for the apparent deficit of the Moon’s late-accreted mass relative to that of the Earth. Lunar impact simulations find an impactor-retention ratio three times lower than previously thought and indicate that highly siderophile element retention began 4.35 billion years ago, resolving accretion mass discrepancies between Earth and the Moon.

With the spread of the novel coronavirus disease 2019 (COVID-19) around the world, the estimation of the incubation period of COVID-19 has become a hot issue. Based on the doubly interval-censored data model, we assume that the incubation period follows lognormal and Gamma distribution, and estimate the parameters of the incubation period of COVID-19 by adopting the maximum likelihood estimation, expectation maximization algorithm and a newly proposed algorithm (expectation mostly conditional maximization algorithm, referred as ECIMM). The main innovation of this paper lies in two aspects: Firstly, we regard the sample data of the incubation period as the doubly interval-censored data without unnecessary data simplification to improve the accuracy and credibility of the results; secondly, our new ECIMM algorithm enjoys better convergence and universality compared with others. With the framework of this paper, we conclude that 14-day quarantine period can largely interrupt the transmission of COVID-19, however, people who need specially monitoring should be isolated for about 20 days for the sake of safety. The results provide some suggestions for the prevention and control of COVID-19. The newly proposed ECIMM algorithm can also be used to deal with the doubly interval-censored data model appearing in various fields.