Fermi Research Alliance

The Donan Creek is a coastal ecosystem in Central Java that is strongly affected by industrial activities. This study represents the first attempt to use the polychaete worms Diopatra claparedii Grube, 1878 (Onuphidae) as a bioindicator of heavy metal contaminations. The work was conducted between July and September 2023 at four sampling sites, designated from the farthest to the closest to the Indian Ocean. Samples of D. claparedii, sediment and water were collected at each site during low tide. The samples were analyzed for Cd, Cr and Pb concentration using Atomic Absorption Spectrophotometry. In addition, several other environmental parameters were also measured to examine the water quality of the creek. Our study highlights the capability of D. claparedii to accumulate all the three heavy metals. The concentrations of Cd, Cr and Pb in the body tissues of the worms ranged from 29.743 ± 0.011 mg.kg-1 to 50.036 ± 0.028 mg.kg-1, from 21.718 ± 0.024 mg.kg-1 to 40.032 ± 0.052 mg.kg-1, and from 20.068 ± 0.008 mg.kg-1 to 44.030 ± 0.000 mg.kg-1, respectively. These amounts were so far the highest among all other aquatic animals (i.e. bivalves, crustaceans and fishes) used as bioindicators in the Donan Creek. The heavy metal concentrations in D. claparedii were significantly correlated with those in the sediment (p < 0.05). In general, the levels of the metals were considerably higher in the more industrial area than those of the less industrial area (P<0.05). We further found that the concentrations of Cd, Cr and Pb as well as several other environmental parameters including BOD, COD, the total nitrate and phosphate in the water column of the creek did not meet the water quality standards stipulated by the Indonesian Government. These findings indicate that the ecosystem has been polluted by both heavy metals and organic matters. While environmental remediation is urgently required, a comprehensive review and improvement of industrial and domestic waste management practices in the region are equally essential to prevent further degradation.

Abstract Cold-air outbreaks over high-latitude oceans typically include mixed-phase clouds and precipitation, in particular supercooled liquid clouds that support snow and graupel through ice growth processes. The partitioning of the total water into the liquid and ice phases impacts both weather and climate prediction, but accurate measurements on the phase partitioning remain difficult to acquire, especially near–real time. Here, we present a machine learning approach to retrieve liquid water path (LWP) using passive microwave measurements combined with vertically integrated radar reflectivities. The approach is an extension of Cadeddu et al. (2009), with the novel addition of radar reflectivity. The machine learning models are trained using the Passive and Active Microwave Radiative Transfer (PAMTRA) code applied to output from numerical simulations of three independent cold-air outbreaks sampled during the Cold-Air Outbreaks in the Marine Boundary Layer Experiment (COMBLE) campaign. Brightness temperatures corresponding to the four sidebands of an upward-looking G-band (183 GHz) vapor radiometer, along with the vertically integrated reflectivity from a zenith-pointing 95-GHz Wyoming Cloud Radar, are simulated from the perspective of a near-surface aircraft track. The radar reflectivity helps discriminate the snow contribution to the brightness temperatures. The machine learning models are thereafter tested on a simulation of an independent cold-air outbreak during COMBLE and against measurements from the U.S. Department of Energy Atmospheric Radiation Measurement North Slope of Alaska observatory. This machine learning approach is shown to provide robust, computationally efficient, near-real-time measurements of LWP and water vapor path during the Cold-Air Outbreak Experiment in the Sub-Arctic Region (CAESAR) campaign in February–April 2024. Significance Statement Precipitation from mixed-phase clouds over the high-latitude open waters impacts shipping, fishing, and coastal communities. Mixed-phase clouds are also a modeling challenge, inhibiting weather and climate prediction skill. More comprehensive measurements of the cloud liquid and ice water path occupying the same vertical column improve our understanding and ability to represent this challenging cloud type. Here, we propose a new retrieval to determine the liquid water path within air columns that also contain ice.

The US Magnet Development Program is leading an effort to design and manufacture a 20 T accelerator dipole magnet. Various designs are under development featuring cos-theta, block-coil, or common-coil geometries. To achieve the target field while maintaining cost-effectiveness the magnet cross-section includes high-temperature superconductor (HTS) inner coils and Nb<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$_{3}$</tex-math></inline-formula>Sn outer coils, which are all powered in series. The quench protection of this class of high-field accelerator magnets is extremely challenging due to the high energy density, high current density, slow quench propagation, in particular in the HTS coils, and highly inhomogeneous thermal properties of HTS and Nb<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$_{3}$</tex-math></inline-formula>Sn coils. The magnet quench discharge is simulated with the STEAM-LEDET program as coupled electro-magnetic and thermal transients. The peak temperature and voltage to ground in the magnet coils during the transient are presented. The performance of a CLIQ-based quench protection system applied to 1 m long model magnets in terms of peak temperature and voltage to ground is investigated. Furthermore, the scalability of the proposed solution to full-scale, 15 m long magnets is discussed.

The SPARC Toroidal Field Model Coil (TFMC) Program was a three-year effort between 2018 and 2021 that developed novel Rare Earth Barium Copper Oxide (REBCO) superconductor technologies and then successfully utilized these technologies to design, build, and test a first-in-class, high-field (∼20 T), representative-scale (∼3 m) superconducting toroidal field (TF) coil. The program was executed jointly by the MIT Plasma Science and Fusion Center (PSFC) and Commonwealth Fusion Systems (CFS) as a technology enabler of the superconducting high-field pathway to fusion energy, and, in particular, as a risk retirement program for the no insulation (NI) TF magnet in the SPARC net-energy fusion tokamak. The TFMC achieved its programmatic goal of experimentally demonstrating a large-scale high-field REBCO magnet, achieving 20.1 T peak field-on-conductor with 40.5 kA of terminal current, 815 kN/m of Lorentz loading on the REBCO stacks, and almost 1 GPa of mechanical stress accommodated by the structural case. Fifteen internal demountable pancake-to-pancake joints operated in the 0.5 to 2.0 nΩ range at 20 K and in magnetic fields up to 12 T. The DC and AC electromagnetic performance of the magnet predicted by new advances in high-fidelity computational models was confirmed in two test campaigns while the parallel, single-pass, pressure-vessel style coolant scheme capable of large heat removal was validated. In the test facility, a feeder system composed of REBCO current leads and cables was experimentally qualified up to 50 kA, and a liquid-free cryocooler-based helium cryogenic system provided 600 W of cooling power at 20 K with mass flow rates up to 70 g/s at a maximum design pressure of 2 MPa for the test campaigns. Finally, the feasibility of using passive, self-protection against a quench in a fusion-scale NI TF coil was experimentally assessed. While the TFMC was intentionally not optimized for quench resiliency – and suffered localized thermal damage in response to an intentional open-circuit quench at 31.5 kA terminal current – the extensive data and validated models that it produced represent a critical step towards this important objective.

In this section we present the magnet technology for the High Luminosity LHC. After a short review of the project targets and constraints, we discuss the main guidelines used to determine the technology, the field/gradients, the operational margins, and the choice of the current density for each type of magnet. Then we discuss the peculiar aspects of the design of each class of magnet, with special emphasis on the triplet.

A prototype cryomodule containing eight Single Spoke Resonators type-1 (SSR1) operating at 325 MHz and four superconducting focusing lenses was successfully assembled, cold tested, and accelerated beam in the framework of the PIP-II project at Fermilab. The impact of induced residual magnetic fields from the solenoids on performance of cavities is presented in this contribution. In addition, design optimizations for the production cryomodules as a result of this impact are highlighted.

The Reflections series takes a look back on historical articles from The Journal of the Acoustical Society of America that have had a significant impact on the science and practice of acoustics.

Abimanyu son of Arjuna, father of Parikesit, killed in action [19] Abiyasa son of Palasara, father of Pandhudwanata [19] Adam Prophet [1]

This paper outlines the arguments and counterarguments within the scientific communities on the issue of common genetic factors discovered in mental disorders. The main objective of the research is to analyse the relationship between genetics and mental health. The relevance of this study by FAAVM Canada, (North America), is to help recognize that major mental health disorders share certain genetic defects. These findings may also point to apply better multidisciplinary scientific research methodologies to diagnose and treat these conditions. However, genetic factors can increase the risks of mental health issues, or make us more vulnerable to developing them, by reducing the brain’s ability to deal with or compensate for traumas and other cognitive disruptions. This research empirically confirms and theoretically proves that the results can be useful for vaccine and pharmaceutical drug development. Across the European Union (EU) region, approximately 165 million people are affected annually by mental illnesses, for the most part, anxiety, mood, and substance abuse disorders. On average, over 50% of the general population in middle-income and high-income countries will experience at least one mental illness at some point in their lives. That being said, mental illnesses are by no means limited to a minority group of predisposed persons but are a major public health challenge. These scientific attributes are in fact mandatory diagnostic criteria that exert considerable socio-economic repercussions not only for those affected but also for their families, communities, social, and employment related environments. In the first year of the Coronavirus (COVID-19) global pandemic, global frequency of anxiety and depression increased by an immense 25%, according to a scientific summary released by the World Health Organization (WHO). Mental illnesses and substance abuse disorders account for over 10.4% of the global burden of mental health diseases, owing to demographic changes and prolonged life expectancy, and were the leading cause of years lived with disability among all disease groups.