Submarine Cables: Issues of Maritime Security, Jurisdiction, and Legalities

This paper delves into the complex issues surrounding submarine cables, vital for global communication and data exchange. These issues include maritime security, legal jurisdictions, and broader legalities. Because submarine cables are located deep in the world's oceans, they face numerous security threats such as sabotage, illegal fishing, and deep-sea mining, highlighting the need for comprehensive maritime security measures. Legal Jurisdiction over these cables, especially those outside territorial waters, is equally complicated. Different international norms and regulations contribute to a fragmented legal landscape, creating jurisdictional authority and regulatory compliance ambiguities. Moreover, international laws offer inconsistent solutions to cable damage, repair, and maintenance, adding further complexity. This paper examines these interconnected issues, analyzing the existing regulatory frameworks and their effectiveness in addressing submarine cables' security and legal challenges. We provide a nuanced understanding of this essential infrastructure's vulnerabilities and propose recommendations for enhanced legal frameworks, increased international cooperation, and improved security measures. This comprehensive study is particularly relevant in the current era of digital interconnectedness, where reliable, secure, and uninterrupted international data flows are crucial. We hope this paper will stimulate further discussion and research in this critical yet often underestimated international law and global security area

Cosmology And Astrophysics From Small Scales

Cross-correlations between tracers of large-scale structure (LSS), such as galaxies, weak lensing, and thermodynamics of hot gas, provide powerful tests of the cosmological model. In this Ph.D. thesis, we develop analytical models of these tracers and apply them to compare measurements to theoretical predictions of the standard model of cosmology. The complicated non-linear interactions between various components of the Universe present a significant challenge to constraining cosmological or astrophysical models. We aim to maximize the information gained from current and future cosmological datasets in the presence of astrophysical and observational sources of uncertainty. In the first half of the thesis, we describe and validate a hybrid galaxy biasing model (non-linear mapping between dark matter and galaxies) aimed at analyzing the correlations between galaxy positions and weak lensing. We then apply this model to recent data from the Dark Energy Survey, leading to a significant gain in cosmological constraints. In the second half of the thesis, we carry out high significance measurements of cross-correlations between the pressure of hot gas and weak lensing (shear-$y$) and galaxy positions (galaxy-$y$). We constrain the evolution of the average thermal pressure of the Universe and find evidence for reduced pressure in low mass halos. Our results point to the effects of increased baryonic feedback (the impact of supernovae or active galactic nuclei on LSS). These results will help in understanding how baryonic feedback impacts galaxy formation and using the non-linear regime for cosmological analysis with future survey data

India's Strategic and Economic Perspective in Maritime Affairs: A New Horizon

The research paper “India’s Strategic and Economic Perspective in Maritime Affairs: A New Horizon” delves into India’s evolving role in the maritime domain, both from a strategic and economic viewpoint. Situated at the crossroads of vital sea lanes and with a vast coastline, India is uniquely positioned to influence maritime affairs. The paper explores India’s multi-dimensional approach to maritime challenges, focusing on the blue economy, regional initiatives, and geopolitical significance. It also examines India’s participation in global platforms like the G20 and its efforts to balance economic development with sustainable practices in the maritime sector. Through a comprehensive analysis, the paper argues that India is at a pivotal juncture, with the potential to shape a new horizon in maritime affairs that could have significant implications for regional stability, global trade, and environmental sustainability

The rise in preanalytical errors during COVID-19 pandemic

The COVID-19 pandemic has posed several challenges to clinical laboratories across the globe. Amidst the outbreak, errors occurring in the preanalytical phase of sample collection, transport and processing, can further lead to undesirable clinical consequences. Thus, this study was designed with the following objectives: (i) to determine and compare the blood specimen rejection rate of a clinical laboratory and (ii) to characterise and compare the types of preanalytical errors between the pre-pandemic and the pandemic phases. This retrospective study was carried out in a trauma-care hospital, presently converted to COVID-19 care centre. Data was collected from (i) pre-pandemic phase: 1st October 2019 to 23rd March 2020 and (ii) pandemic phase: 24th March to 31st October 2020. Blood specimen rejection rate was calculated as the proportion of blood collection tubes with preanalytical errors out of the total number received, expressed as percentage. Total of 107,716 blood specimens were screened of which 43,396 (40.3%) were received during the pandemic. The blood specimen rejection rate during the pandemic was significantly higher than the pre-pandemic phase (3.0% versus 1.1%; P < 0.001). Clotted samples were the commonest source of preanalytical errors in both phases. There was a significant increase in the improperly labelled samples (P < 0.001) and samples with insufficient volume (P < 0.001), whereas, a significant decline in samples with inadequate sample-anticoagulant ratio and haemolysed samples (P < 0.001). In the ongoing pandemic, preanalytical errors and resultant blood specimen rejection rate in the clinical laboratory have significantly increased due to changed logistics. The study highlights the need for corrective steps at various levels to reduce preanalytical errors in order to optimise patient care and resource utilisation

Sensitivity Analysis of Simulation-Based Inference for Galaxy Clustering

Simulation-based inference (SBI) is a promising approach to leverage high fidelity cosmological simulations and extract information from the non-Gaussian, non-linear scales that cannot be modeled analytically. However, scaling SBI to the next generation of cosmological surveys faces the computational challenge of requiring a large number of accurate simulations over a wide range of cosmologies, while simultaneously encompassing large cosmological volumes at high resolution. This challenge can potentially be mitigated by balancing the accuracy and computational cost for different components of the the forward model while ensuring robust inference. To guide our steps in this, we perform a sensitivity analysis of SBI for galaxy clustering on various components of the cosmological simulations: gravity model, halo-finder and the galaxy-halo distribution models (halo-occupation distribution, HOD). We infer the $\sigma_8$ and $\Omega_m$ using galaxy power spectrum multipoles and the bispectrum monopole assuming a galaxy number density expected from the luminous red galaxies observed using the Dark Energy Spectroscopy Instrument (DESI). We find that SBI is insensitive to changing gravity model between $N$-body simulations and particle mesh (PM) simulations. However, changing the halo-finder from friends-of-friends (FoF) to Rockstar can lead to biased estimate of $\sigma_8$ based on the bispectrum. For galaxy models, training SBI on more complex HOD leads to consistent inference for less complex HOD models, but SBI trained on simpler HOD models fails when applied to analyze data from a more complex HOD model. Based on our results, we discuss the outlook on cosmological simulations with a focus on applying SBI approaches to future galaxy surveys.Comment: 11 pages, 5 figures. Comments welcom

The correlation of high-redshift galaxies with the thermal Sunyaev-Zel’dovich effect traces reionization

We explore a potential new probe of reionization: the cross-correlation of high-redshift galaxies with maps of the thermal Sunyaev-Zel’dovich (tSZ) effect. We consider two types of high redshift galaxies: Lyman break galaxies (LBGs) and Lyman-α emitters (LAEs). LBGs and LAEs will be detected in large numbers at high redshift (z ≈ 4 – 7) by ongoing and future surveys. We consider a future LBG sample from The Rubin Observatory Legacy Survey of Space and Time (LSST), and a selection of LAEs modelled after the Subaru SILVERRUSH program, but covering a much larger sky fraction. The tSZ effect is sensitive to a line-of-sight integral of the ionized gas pressure, and is measured across large patches of sky using multi-frequency CMB surveys. We consider forecast tSZ maps from CMB Stage 4 and more futuristic observations. Using a suite of hydrodynamical simulations, we show that LBGs and LAEs are correlated with the tSZ signal from reionization. The cross-spectra between LBGs/LAEs with tSZ maps contain information about the reionization history of the Universe, such as the distribution of bubble sizes, and could be used to directly measure the timing of reionization. The amplitude of the signal is small, however, and its detectability is hindered by low-redshift contributions to tSZ maps and by instrumental noise. If the low-redshift contribution to the observed tSZ signal is suppressed by masking of massive halos, a combination of overlapping futuristic CMB and galaxy surveys could probe this signal

The impact of halo concentration on the Sunyaev Zel'dovich effect signal from massive galaxy clusters

The Sunyaev Zel'dovich (SZ) effect is sensitive to the pressure of ionized gas inside galaxy clusters. The gas pressure responds to changes in the gravitational potential of the cluster, which is dominated by the host dark matter halo. Changes in halo concentration therefore impact the SZ signal, with implications for cosmological and other analyses of SZ-selected clusters. We investigate the concentration-SZ relation in theory and simulations. We find that the impact of concentration on the inner SZ profile ($R \lesssim 0.75 R_{200c}$) can be captured with standard polytropic gas models. However, we find that such models do a poor job of reproducing the outer SZ profiles ($R \gtrsim 0.75 R_{200c}$) and the relation between the integrated SZ signal, $Y$, and concentration. This disagreement results from a sharp truncation of the gas pressure profile near the splashback radius, likely caused by virial shocks. We develop a simple description of the truncation that leads to a good match with simulated SZ profiles out to several $R_{200c}$ for clusters of varying mass and concentration, and that also accurately predicts the concentration-$Y$ relationship. Finally, we determine how inference of the linear bias parameter and splashback radius for SZ-selected clusters can be biased by ignoring the concentration dependence of the SZ signal.Comment: 15 pages, 11 figures; comments welcome

Predicting the impact of feedback on matter clustering with machine learning in CAMELS

Extracting information from the total matter power spectrum with the precision needed for upcoming cosmological surveys requires unraveling the complex effects of galaxy formation processes on the distribution of matter. We investigate the impact of baryonic physics on matter clustering at $z=0$ using a library of power spectra from the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project, containing thousands of $(25\,h^{-1}{\rm Mpc})^3$ volume realizations with varying cosmology, initial random field, stellar and AGN feedback strength and sub-grid model implementation methods. We show that baryonic physics affects matter clustering on scales $k \gtrsim 0.4\,h\,\mathrm{Mpc}^{-1}$ and the magnitude of this effect is dependent on the details of the galaxy formation implementation and variations of cosmological and astrophysical parameters. Increasing AGN feedback strength decreases halo baryon fractions and yields stronger suppression of power relative to N-body simulations, while stronger stellar feedback often results in weaker effects by suppressing black hole growth and therefore the impact of AGN feedback. We find a broad correlation between mean baryon fraction of massive halos ($M_{\rm 200c} > 10^{13.5}$\,\Msun) and suppression of matter clustering but with significant scatter compared to previous work owing to wider exploration of feedback parameters and cosmic variance effects. We show that a random forest regressor trained on the baryon content and abundance of halos across the full mass range $10^{10} \leq M_\mathrm{halo}/$\Msun$< 10^{15}$ can predict the effect of galaxy formation on the matter power spectrum on scales $k = 1.0$--20.0\,$h\,\mathrm{Mpc}^{-1}$

The SZ flux-mass (YY-MM) relation at low halo masses: improvements with symbolic regression and strong constraints on baryonic feedback

Feedback from active galactic nuclei (AGN) and supernovae can affect measurements of integrated SZ flux of halos ($Y_\mathrm{SZ}$) from CMB surveys, and cause its relation with the halo mass ($Y_\mathrm{SZ}-M$) to deviate from the self-similar power-law prediction of the virial theorem. We perform a comprehensive study of such deviations using CAMELS, a suite of hydrodynamic simulations with extensive variations in feedback prescriptions. We use a combination of two machine learning tools (random forest and symbolic regression) to search for analogues of the $Y-M$ relation which are more robust to feedback processes for low masses ($M\lesssim 10^{14}\, h^{-1} \, M_\odot$); we find that simply replacing $Y\rightarrow Y(1+M_*/M_\mathrm{gas})$ in the relation makes it remarkably self-similar. This could serve as a robust multiwavelength mass proxy for low-mass clusters and galaxy groups. Our methodology can also be generally useful to improve the domain of validity of other astrophysical scaling relations. We also forecast that measurements of the $Y-M$ relation could provide percent-level constraints on certain combinations of feedback parameters and/or rule out a major part of the parameter space of supernova and AGN feedback models used in current state-of-the-art hydrodynamic simulations. Our results can be useful for using upcoming SZ surveys (e.g., SO, CMB-S4) and galaxy surveys (e.g., DESI and Rubin) to constrain the nature of baryonic feedback. Finally, we find that the an alternative relation, $Y-M_*$, provides complementary information on feedback than $Y-M$Comment: Version appearing in MNRAS. Minor change to Fig.6 and added Fig. A5 compared to the previous version. 7+5 pages. The code and data associated with this paper are available at https://github.com/JayWadekar/ScalingRelations_M

Estimation of Serum Levels of Heavy Metals in Patients with Chronic Invasive Fungal Rhinosinusitis Before the COVID-19 Era: A Pilot Study

Objective:Various metals play role in the survival and pathogenesis of the invasive fungal disease. The objectives of this study were to compare the levels of heavy metals in patients with chronic invasive fungal rhinosinusitis (CIFR) and healthy controls, and to analyze their role in disease outcome.Methods:Twenty-three patients (15 with invasive mucormycosis and 8 with invasive aspergillosis, Group 1), and 14 healthy controls (Group 2) were recruited. Blood samples were collected from each group into ion-free tubes and analyzed for serum levels of Nickel (Ni), Copper (Cu), Zinc (Zn), Gallium (Ga), Arsenic (As), Selenium (Se), Rubidium (Rb), Strontium (Sr), Cadmium (Cd), and Lead (Pb). The final outcome of the patients during their hospital stay was categorized clinico-radiologically as improved or worsened, or death.Results:The levels of all metals were higher in Group 1 except for As and Pb. However, the differences in Cu (p=0.0026), Ga (p=0.002), Cd (p=0.0027), and Pb (p=0.0075) levels were significant. Higher levels of Zn (p=0.009), Se (p=0.020), and Rb (p=0.016) were seen in the invasive aspergillosis subgroup. Although Zn (p=0.035), As (p=0.022), and Sr (p=0.002) levels were higher in patients with improved outcome, subgroup analysis showed no differences.Conclusion:The levels of some heavy metals in CIFR significantly differ from those of the general population and also vary with the type of the disease and its outcome. These levels may not have a direct effect on the outcome of the patient, but they do play a role in the pathogenesis of the invading fungus