Miracle-dz/UniFAR-FTUs huggingface dataset:
Hydroclimate Variability in the Equatorial Western Indian Ocean for the Last 250,000 Years

Indian Ocean sea surface temperatures impact precipitation across the basin through coupled ocean‐atmosphere responses to changes in climate. To understand the hydroclimate response over the western Indian Ocean and equatorial east Africa to different forcing mechanisms, we present four new proxy reconstructions from core VM19‐193 (2.98°N, 51.47°E) that span the last 250 ky. Sub‐surface water temperatures (Sub‐T; TEX86) show strong precessional (23 ky) variability that is primarily influenced by maximum incoming solar radiation (insolation) during the Northern Hemisphere spring season, likely indicating that local insolation dominates the upper water column at this tropical location over time. Leaf waxes, on the other hand, reflect two different precipitation signals: δ13Cwax (in phase with boreal fall insolation) is likely reflecting vegetation changes in response to local rainfall over east Africa, whereas δDprecip (primarily driven by boreal summer insolation) represents changes in regional circulation associated with the summer monsoon. Glacial‐interglacial changes in ocean temperatures support glacial shelf exposure over the Maritime Continent in the eastern Indian Ocean and the subsequent weakening of the Indian Walker Circulation as a mechanism driving 100 ky climate variability across the tropical Indo‐Pacific. Additionally, the 100 ky spectral power in δDprecip supports a basin‐wide weakening of summer monsoon circulation in response to glacial climates. Overall, the proxy records from VM19‐193 indicate that both precession and glacial‐interglacial cycles exert control over hydroclimate at this tropical location.
An Analysis of the Effects of Nanofluid-Based Serpentine Tube Cooling Enhancement in Solar Photovoltaic Cells for Green Cities

In this work, the impact of the serpentine copper tube heat exchanger with nanofluids on 100 W solar photovoltaic thermal collectors (PV/T) was analyzed experimentally and numerically. The cooling fluids assessed in this system were distilled water, Al2O3 0.1%, and Al2O3 0.2% based nanofluids. Tests were accomplished at diverse coolant mass flow rate in India’s summer days of 2018. A computational fluid dynamics (CFD) investigation was carried out to perform a parametric study, identify surface and exit T profiles, and examine the cooling effectiveness. The impact of mass flow rate of nanofluid on the outside T and Reynolds number were studied. The Reynolds number obtained in the flow experiments and CFD analysis was in the range of 900–1,300. The maximum irreversibility occurred while using water, whereas minimum irreversibility obtained Al2O3 0.2% nanofluid. Exergy efficiency was found to be increased from 20% to 36% during the day. It was identified that the increase in PV/T scheme led to higher exergy losses. The thermal efficiency of a water-based cooling system resulted in 53.61%. Meanwhile, Al2O3 0.1% and Al2O3 0.2% based coolants provided 69.45% and 71.02%, respectively. A good agreement was obtained between the experimental results and the computer model.
Conductive oxide thin films: Model systems for understanding and controlling surface plasmon resonance

Degeneratively doped conductive oxides represent a unique host for exploring the inter-relationship between the properties of charge carriers and their collective plasmonic response. These materials often lack interband transitions that obfuscate interpretation of spectral response in elemental metals, and unlike metals, the electronic transport properties of conductive oxides are easily tunable. This work explores the process-structure-property relationships that regulate surface plasmon resonance (SPR) in sputter deposited indium tin oxide (ITO) thin films. Film deposition conditions are used to regulate film microstructure and tune the electronic mobility to between 7 and 40 cm2 V−1 s−1. Postdeposition annealing in low oxygen partial pressure atmospheres is used to engineer the ITO defect equilibrium and modulate carrier concentrations to between 1020 and 1021 cm−3. These electronic transport properties are modulated with near independence enabling straightforward interpretation of their influence on t.
Robust Estimation of Dispersion Matrices and Principal Components

Abstract This paper uses Monte Carlo methods to compare the performances of several robust procedures for estimating a correlation matrix and its principal components. The estimators are formed either from separate bivariate analyses or by simultaneous manipulation of all variables by using techniques such as multivariate trimming and M-estimation. The M-estimators stand up exceptionally well. They and the multivariate trimming procedure are especially effective at estimating the principal components, including a near singularity. However, the M-estimators can break down relatively easily when the dimensionality is large and the outliers are asymmetric. With missing data, the element-wise approach becomes more attractive.
Energetic particle acceleration in a three-dimensional magnetic field reconnection model: the role of magnetohydrodynamic turbulence

The role of magnetohydrodynamic (MHD) turbulence in the cosmic ray acceleration process in a volume with a reconnecting magnetic field is studied by means of Monte Carlo simulations. We performed modelling of proton acceleration, with the three-dimensional analytic model of stationary reconnection of Craig et al. providing the unperturbed background conditions. Perturbations of particle trajectories resulting from a turbulent magnetic field component were simulated using small-amplitude pitch-angle momentum scattering, enabling modelling of both small- and large-amplitude turbulence in a wide wavevector range. Within the approach, no second-order Fermi acceleration process is allowed. Comparison of the acceleration process in models involving particle trajectory perturbations with the unperturbed model reveals that the turbulence can substantially increase the acceleration efficiency, enabling much higher final particle energies and flat particle spectra.
Plasma etch transfer of self-assembled polymer patterns

Self-organizing block copolymer thin films hold promise as a photolithography enhancement material for the 22-nm microelectronics technology generation and beyond, primarily because of their ability to form highly uniform patterns at the relevant nanometer-scale dimensions. Importantly, the materials are chemically similar to photoresists and can be implemented in synergy with photolithography. Beyond the challenges of achieving sufficient control of self-assembled pattern defectivity and feature roughness, block copolymer-based patterning requires creation of robust processes for transferring the polymer patterns into underlying electronic materials. Here, we describe research efforts in hardening block copolymer resist patterns using inorganic materials and high aspect ratio plasma etch transfer of self-assembled patterns to silicon using fluorine-based etch chemistries.
Dissipative small-scale actuation of a turbulent shear layer

The effects of small-scale dissipative fluidic actuation on the evolution of large- and small-scale motions in a turbulent shear layer downstream of a backward-facing step are investigated experimentally. Actuation is applied by modulation of the vorticity flux into the shear layer at frequencies that are substantially higher than the frequencies that are typically amplified in the near field, and has a profound effect on the evolution of the vortical structures within the layer. Specifically, there is a strong broadband increase in the energy of the small-scale motions and a nearly uniform decrease in the energy of the large-scale motions which correspond to the most amplified unstable modes of the base flow. The near field of the forced shear layer has three distinct domains. The first domain (x/θ0 < 50) is dominated by significant concomitant increases in the production and dissipation of turbulent kinetic energy and in the shear layer cross-stream width. In the second domain (50 < x/θ0 < 300), the streamwise rates of change of these quantities become similar to the corresponding rates in the unforced flow although their magnitudes are substantially different. Finally, in the third domain (x/θ0 > 350) the inviscid instability of the shear layer re-emerges in what might be described as a ‘new’ baseline flow.
Designing observational biologging studies to assess the causal effect of instrumentation

Biologging has improved ecological knowledge on an increasing number of species for more than 2 decades. Most studies looking at the incidence of tags on behavioural, physiological or demographic parameters rely on ‘control’ individuals chosen randomly within the population, assuming that they will be comparable with equipped individuals. This assumption is usually untestable and untenable since biologging studies are more observational than experimental, and often involve small sample sizes. Notably, background characteristics of wild animals are, most of the time, unknown. Consequently, investigating any causal effect of instrumentation is a difficult task, subjected to hidden biases. We describe the counterfactual model to causal inference which was implicit in early biologging studies. We adopted methods developed in social and political sciences to construct a posteriori an appropriate control group. Using biologging data collected on Scopoli's shearwaters (Calonectris diomedea) from a small Mediterranean island, we used this method to achieve objective causal inference on the effect of instrumentation on breeding performance and divorce. Our method revealed that the sample of instrumented birds was nonrandom. After identification of a relevant control group, we found no carry‐over effects of instrumentation on breeding performance (taking into account imperfect detection probability) or divorce rate in Scopoli's shearwaters. Randomly chosen control groups can be both counterproductive and ethically dubious via unnecessary additional disturbance of populations. The counterfactual approach, which can correct for selection bias, has wide applicability to biologging within long‐term studies.
UrsaX: Integrating Block I/O and Message Transfer for Ultrafast Block Storage on Supercomputers

It is increasingly important for the next-generation exascale supercomputers to extend its applications beyond traditional high-performance computing (HPC) scenarios, so as to achieve high social and economic benefit. Similar to Amazon Web Services (AWS) and Alibaba Cloud, cloud-style virtual HPC service is a promising application scenario on supercomputers, for which remote block storage is the key to provide tenants with supercomputers’ extremely high storage performance. Unfortunately, the state-of-the-art block storage software systems (such as URSA and Ceph) cannot adapt to the advanced hardware features of supercomputers. This article presents UrsaX, an efficient block storage service for our next-generation Tianhe exascale supercomputer that is equipped with the high-performance global express (GLEX) network and nonvolatile memory express (NVMe) SSDs. UrsaX’s virtual disks, which can be mounted like normal physical ones, enable not only traditional HPC applications but also supercomputer-oblivious POSIX applications to enjoy the high performance of supercomputers. At the core of UrsaX is with a novel design of the efficient integration of on-disk block I/O and in-network message transfer on supercomputers. UrsaX utilizes the NVMe Fabrics kernel module to expand the NVMe standard on the supercomputer network, and separates metadata I/O and data I/O of blocks, respectively, being handled over the mini packet (MP) and remote direct memory access (RDMA) protocols. We thoroughly explore the design space for remote block storage on supercomputers, including parallelism, scalability, fault tolerance, and consistency. We conduct an extensive evaluation on a subset of our exascale supercomputer consisting of 44 storage machines (each with four NVMe SSDs). The result shows that UrsaX achieves local-storage-level I/O latency (tens of microseconds) while being able to linearly increase the aggregate performance (IOPS and throughput) as the system scale increases, an order of magnitude higher than the state-of-the-art block storage systems.
Lung Ultrasound Is Useful for Evaluating Lung Damage in COVID-19 Patients Treated with Bamlanivimab and Etesevimab: A Single-Center Pilot Study

Background and Objectives: COVID-19 induces massive systemic inflammation. Researchers have spent much time and effort finding an excellent and rapid image tool to evaluate COVID-19 patients. Since the pandemic’s beginning, lung ultrasound (LUS) has been identified for this purpose. Monoclonal antibodies (mAb) were used to treat mild patients and prevent respiratory disease worsening. Materials and Methods: We evaluated 15 Caucasian patients with mild COVID-19 who did not require home oxygen, treated with Bamlanivimab and Etesevimab (Group 1). A molecular nose–throat swab test confirmed the diagnosis. All were office patients, and nobody was affected by respiratory failure. They were admitted to receive the single-day infusion of mAb treatment in agreement with the Italian Drug Agency (AIFA) rules for approval. LUS was performed before the drug administration (T0) and after three months (T1). We compared LUS at T1 in other outpatients who came for follow-up and were overlapping at the time of diagnosis for admittance criteria to receive mAb (Group 2). Results: Our COVID-19 outpatients reported no hospitalization in a follow-up visit after recovery. All patients became SARS-CoV-2 negative within one month since T0. LUS score at T0 was 8.23 ± 6.46. At T1 we found a significant decrease in Group 1 LUS score (5.18 ± 4.74; p < 0.05). We also found a significant decrease in the LUS score of Group 1 T1 compared to Group2 T1 (5.18 ± 4.74 vs 7.82 ± 5.21; p < 0.05). Conclusion: Early treatment of the SARS-CoV-2 virus effectively achieves a better recovery from disease and reduces lung involvement after three months as evaluated with LUS. Despite extrapolation to the general population may be done with caution, based on our data this ultrasound method is also effective for evaluating and following lung involvement in COVID-19 patients.
Research on the Karhunen–Loève Transform Method and Its Application to Hull Form Optimization

Hull form optimization becomes prone to the curse of dimensionality as the number of design variables increases. The traditional sensitivity analysis method requires massive computational fluid dynamics (CFD) computations and analyzing the effects of all variables on the output; thus, it is extremely time-consuming. Considering this, the development of a rapid and effective dimensionality reduction method is particularly important. The Karhunen–Loève (K–L) transform method projects data from a high-dimensional space onto a low-dimensional space in the direction of the eigenvectors corresponding to large-variance eigenvalues. It extracts the principal components that represent the hull offset information to represent the hull geometric characteristics by analyzing the relationship between the variables in the sample offset matrix. The geometric information matrices of new hull forms can be rapidly reconstructed from the principal components. Compared with direct optimization methods, fewer variables are used to control the deformation of the hull form from the perspective of geometric deformation, avoid a large number of CFD calculations, and improve the efficiency of optimization. This study examined the relevant K–L matrix solution methods and the corresponding hull form reconstruction methods and proposed eigenvalue-based hull form reconstruction equations. The K–L transform method was combined with a previously developed multidisciplinary platform for a comprehensive optimization of ship hydrodynamic performance for hull form optimization, and its effectiveness was verified by using it to optimize DTMB 5415. The results showed that the K–L transform–based dimensionality reduction method significantly reduces the time consumption of optimization while maintaining an acceptable optimization performance.
Development of viscosity sensor with long period fiber grating technology

In this paper, we describe the development of a viscosity sensing system using a simple and low-cost long-period fiber grating (LPFG) sensor. The LPFG sensor was extremely sensitive to the refractive index of the medium surrounding the cladding surface of the sensing grating, thus allowing it to be used as an ambient index sensor or chemical concentration indicator. Viscosity can be simply defined as resistance to flow of a liquid. We have measured asphalt binder, 100-190000 centistokes, in comparison with optical sensing results. The system sensing asphalt binders exhibited increase trend in the resonance wavelength shift when the refractive index of the medium changed. The prototype sensor consisted of a LPFG sensing component and a cone-shaped reservoir where gravitational force can cause asphalt binders flow through the capillary. Thus the measured time for a constant volume of asphalt binders can be converted into either absolute or kinematic viscosity. In addition, a rotational viscometer and a dynamic shear rheometer were also used to evaluate the viscosity of this liquid, the ratio between the applied shear stress and rate of shear, as well as the viscoelastic property including complex shear modulus and phase angle. The measured time could be converted into viscosity of asphalt binder based on calculation. This simple LPFG viscosity sensing system is hopefully expected to benefit the viscosity measurement for the field of civil, mechanical and aerospace engineering.
Asymptotic prediction mean squared error for vector autoregressive models

SUMMARY This paper derives the asymptotic mean squared error of multistep prediction for the general vector autoregressive process. For one-step-ahead prediction the result is a surprisingly simple generalization of the result for the scalar autoregressive process. Results for multistep prediction are also derived for the regression model with autoregressive errors, where the set of exogenous variables follows a vector autoregressive process.
Double clad YAG crystalline fiber waveguides for diode pumped high power lasing

Double-clade crystalline fiber waveguide (CFW) has been produced by using adhesive-free bond (AFB®) technology. The waveguide consists of a 1 at. % Yb:YAG core, un-doped YAG inner cladding and ceramic spinel outer cladding. It is a direct analog of the conventional double-clad glass fiber laser in the crystal domain. Signal gain of 45 or 16.5 dB has been measured in a preliminary master oscillator power amplifier (MOPA) experiment. Due to the high laser gain and the weak Fresnel reflection at the uncoated waveguide ends, the CFW even starts self-lasing above a certain pump power. Laser output power of 4 W in the backward propagation direction has been measured for input pump power of 44 W. After considering the same amount of forward propagated laser power, the laser efficiency to the absorbed pump power is estimated to be about 44%. In principle, CFW can have extremely large single mode area for high efficiency and high power laser applications. So far, Single mode area < 6700 μm2 has been demonstrated in Er:YAG CFWs.
The Impact of AI Technologies on E-Business

The outbreak of COVID-19 has entirely changed how consumers behave, due to an over-reliance on online shopping. With the global pandemic demanding people to stay home, multiple companies had to find innovative strategies to remain competitive and adapt to these rapid changes. However, the pandemic has also propelled the development of technologies, such as artificial intelligence (AI). AI concerns the engineering of machines and programs to make them intelligent, make decisions on their own or provide humans with information that will aid them in the decision-making process. Artificial intelligence software can be programmed according to an organization’s needs and performance goals. Although AI offers e-businesses multiple advantages, in order to differentiate themselves from their competitors, it is still a relatively new technology. A lack of understanding of its implementation will hinder organizations from reaping the full benefits of this technology. Moreover, multiple disputes regarding AI’s ethicality and privacy concerns have led to further research focused on making these systems more reliable and ethical.
Exact Solutions for Out-of-Plane Vibration of Curved Nonuniform Beams

The governing differential equations for the out-of-plane vibrations of curved nonuniform beams of constant radius are derived. Two physical parameters are introduced to simplify the analysis, and the explicit relations between the torsional displacement, its derivative and the flexural displacement are derived. With these explicit relations, the two coupled goveruing characteristic differential equations can be decoupled and reduced to one sixth-order ordinary differential equation with variable coefficients in the out-of-plane flexural displacement. It is shown that if the material and geometric properties of the beam are in arbitrary polynomial forms, then the exact solutions for the out-of-plane vibrations of the beam can be obtained. The derived explicit relations can also be used to reduce the difficulty in experimental measurement. Finally, two limiting cases are considered and the influence of taper ratio, center angle, and are length on the first two natural frequencies of the beams are illustrated.
Identification of Potent Zika Virus NS5 RNA-Dependent RNA Polymerase Inhibitors Combining Virtual Screening and Biological Assays

The Zika virus (ZIKV) epidemic poses a significant threat to human health globally. Thus, there is an urgent need for developing effective anti-ZIKV agents. ZIKV non-structural protein 5 RNA-dependent RNA polymerase (RdRp), a viral enzyme for viral replication, has been considered an attractive drug target. In this work, we screened an anti-infection compound library and a natural product library by virtual screening to identify potential candidates targeting RdRp. Then, five selected candidates were further applied for RdRp enzymatic analysis, cytotoxicity, and binding examination by SPR. Finally, posaconazole (POS) was confirmed to effectively inhibit both RdRp activity with an IC50 of 4.29 μM and the ZIKV replication with an EC50 of 0.59 μM. Moreover, POS was shown to reduce RdRp activity by binding with the key amino acid D666 through molecular docking and site-directed mutation analysis. For the first time, our work found that POS could inhibit ZIKV replication with a stronger inhibitory activity than chloroquine. This work also demonstrated fast anti-ZIKV screening for inhibitors of RdRp and provided POS as a potential anti-ZIKV agent.
Diurnal and annual variations in 10‐kHz radio noise

It is shown that the investigation of lightning activity levels, using very low frequency radio emissions near 10 kHz, needs to take into account the significant influences of subionospheric propagation. Ten‐kilohertz spectral power measurements made at Halley, Antarctica (76°S, 26°W), show at least two significant periodicities. The largest variation (10 dB) is due to the diurnal cycle and is strongly dominated by South American thunderstorm activity levels. The effect of African thunderstorm activity is observable in the diurnal variation plots but is strongly reduced by disadvantageous propagation conditions. The analysis suggests that given two identical tropical source regions, one situated east and one situated west, of a polar receiver site, the region to the west will tend to dominate the diurnal variation. The smaller annual variation at Halley (3 dB) can be explained by the improved subionospheric propagation conditions during the Southern Hemisphere winter counterbalancing the seasonal effects of decreased source activity in South America.