Feasibility study on manganese nodules recovery in the Clarion-Clipperton Zone

The sea occupies three quarters of the area on the earth and provides various kinds of resources to mankind in the form of minerals, food, medicines and even energy. “Seabed exploitation” specifically deals with recovery of the resources that are found on the seabed, in the form of solids, liquids and gasses (methane hydrates, oil and natural gas). The resources are abundant; nevertheless the recovery process from the seabed, poses various challenges to mankind. This study starts with a review on three types of resources: polymetallic manganese nodules, polymetallic manganese crusts and massive sulphides deposits. Each of them are rich in minerals, such as manganese, cobalt, nickel, copper and some rare earth elements. They are found at many locations in the deep seas and are potentially a big source of minerals. No commercial seabed mining activity has been accomplished to date due to the great complexities in recovery. This book describes the various challenges associated with a potential underwater mineral recovery operation, reviews and analyses the existing recovery techniques, and provides an innovative engineering system. It further identifies the associated risks and a suitable business model.Chapter 1 presents a brief background about the past and present industrial trends of seabed mining. A description of the sea, seabed and the three types of seabed mineral resources are also included. A section on motivations for deep sea mining follows which also compares the latter with terrestrial mining.Chapter 2 deals with the decision making process, including a market analysis, for selecting manganese nodules as the resource of interest. This is followed by a case study specific to the location of interest: West COMRA in the Clarion-Clipperton Zone. Specific site location is determined in order to estimate commercial risk, environmental impact assessment and logistic challenge.Chapter 3 lists the existing techniques for nodule recovery operation. The study identifies the main components of a nodules recovery system, and organizes them into: collector, propulsion and vertical transport systems.Chapter 4 discusses various challenges posed by manganese nodules recovery, in terms of the engineering and environment. The geo-political and legal-social issues have also been considered. This chapter plays an important role in defining the proposed engineering system, as addressing the identified challenges will better shape the proposed solution.Chapter 5 proposes an engineering system, by considering the key components in greater details. An innovative component, the black box is introduced, which is intended to be an environmentally-friendly solution for manganese nodules recovery. Other auxiliary components, such as the mother ship and metallurgical processing, are briefly included. A brief power supply analysis is also provided.Chapter 6 assesses the associated risks, which are divided into sections namely commercial viability, logistic challenges, environmental impact assessment and safety assessment. The feasibility of the proposed solution is also dealt with.Chapter 7 provides a business model for the proposed engineering system. Potential customers are identified, value proposition is determined, costumer relation is also suggested. Public awareness is then discussed and finally a SWOT analysis is presented. This business model serves as an important bridge to reach both industry and research institutes.Finally, Chapter 8 provides some conclusions and recommendation for future work

The Homophobic Call-Outs of COVID-19: Spurring and Spreading Angry Attention From Girregi Journalism Online to YouTube in South Korea

South Korea’s gay community received heightened public attention in May 2020 when a news agency reported that a COVID-19 patient had visited several gay clubs in the multicultural district Itaewon, Seoul. Following this announcement, a plethora of news content was published across various online media platforms. Through a case study of how the news on the Itaewon outbreak spread from online news to YouTube, we investigate the modalities of homophobic discourse and its circulation across different online media outlets. By examining the interplay between the Korean online news media (derogatorily called girregi journalism) and YouTube news channels in spreading the Itaewon story, we discuss how the nationwide homophobic call-outs against the gay community were instigated within an attention ecology. We argue that news media and YouTube news channels work together as affective mechanisms that define the dominant feeling rules about nonnormative subjects as a way of engaging with the pandemic crisis, through the accumulation of affect and attention toward gay bodies

The Evolution of Fiscal Decentralization in China and India: A Comparative Study of Design and Performance

In this article, we compare and contrast the design and performance of China and India’s intergovernmental fiscal systems. We find that there are remarkable similarities in the design and performance of China and India’s intergovernmental fiscal systems. More specifically, both countries have highly decentralized expenditures assignments and highly centralized revenue assignments. As a result, sub-national governments in both countries must rely on fiscal transfers to finance their assigned functions. Finally, there is considerable off the books and hidden borrowing by sub-national governments in both countries. We also find that there are considerable and growing disparities in the rate of expenditure decentralization among sub-national governments within each country. Lack fiscal discipline and growing fiscal disparities among sub-national governments create risks to future economic growth and to social cohesion, absent policy reforms to address these issues

Robotics Research with Turtlebot 2016

A Turtlebot robot platform is being used for robotics and computer vision research at Boise State. Turtlebot is an open­source robotics platform controlled by the ROS (Robot Operating System) framework. This semester we are developing capabilities for the robot to participate in the Boise State Easter Egg Hunt, an event for children on the blue turf. The broad steps include: a) retro­fit Turtlebot with a small motor­controlled egg scooper, b) use Turtlebot’s vision hardware to identify and locate eggs and c) navigate to and pick up located egg(s). The team used 3D modelling and printing techniques to retro­fit Turtlebot with a motorized scooper controlled by an Arduino UNO and equipped with sensors. Computer vision capabilities were integrated with ROS through OpenCV Python to analyze the Kinect’s video data. Frames from the Kinect video stream were modified to minimize noise while preserving features. Frames are searched to find circular clusters of white pixels (the eggs). After a target egg is chosen, Turtlebot moves towards the egg and captures it with the scoop. Through SLAM (Simultaneous Localization and Mapping), Turtlebot navigates back to its predetermined “Home” location. We utilize slow speeds and object avoidance to ensure Turtlebot was also kid­friendl

CO(J = 1-0) Imaging of M51 with CARMA and the Nobeyama 45 m Telescope

We report the CO(J = 1-0) observations of the Whirlpool Galaxy M51 using both the Combined Array for Research in Millimeter Astronomy (CARMA) and the Nobeyama 45 m telescope (NRO45). We describe a procedure for the combination of interferometer and single-dish data. In particular, we discuss (1) the joint imaging and deconvolution of heterogeneous data, (2) the weighting scheme based on the root-mean-square (rms) noise in the maps, (3) the sensitivity and uv coverage requirements, and (4) the flux recovery of a combined map. We generate visibilities from the single-dish map and calculate the noise of each visibility based on the rms noise. Our weighting scheme, though it is applied to discrete visibilities in this paper, should be applicable to grids in uv space, and this scheme may advance in future software development. For a realistic amount of observing time, the sensitivities of the NRO45 and CARMA visibility data sets are best matched by using the single-dish baselines only up to 4-6 kλ (about 1/4-1/3 of the dish diameter). The synthesized beam size is determined to conserve the flux between the synthesized beam and convolution beam. The superior uv coverage provided by the combination of CARMA long baseline data with 15 antennas and NRO45 short spacing data results in the high image fidelity, which is evidenced by the excellent overlap between even the faint CO emission and dust lanes in an optical Hubble Space Telescope image and polycyclicaromatichydrocarbon emission in a Spitzer 8 μm image. The total molecular gas masses of NGC 5194 and 5195 (d = 8.2 Mpc) are 4.9 × 10^9 M_⊙ and 7.8 × 10^7 M_⊙, respectively, assuming the CO-to-H_2 conversion factor of X _(CO) = 1.8 × 10^(20) cm-2(K km s^(–1))^(–1). The presented images are an indication of the millimeter-wave images that will become standard in the next decade with CARMA and NRO45, and the Atacama Large Millimeter/Submillimeter Array

Navigating the Ocean of Biases: Political Bias Attribution in Language Models via Causal Structures

The rapid advancement of Large Language Models (LLMs) has sparked intense debate regarding their ability to perceive and interpret complex socio-political landscapes. In this study, we undertake an exploration of decision-making processes and inherent biases within LLMs, exemplified by ChatGPT, specifically contextualizing our analysis within political debates. We aim not to critique or validate LLMs' values, but rather to discern how they interpret and adjudicate "good arguments." By applying Activity Dependency Networks (ADNs), we extract the LLMs' implicit criteria for such assessments and illustrate how normative values influence these perceptions. We discuss the consequences of our findings for human-AI alignment and bias mitigation. Our code and data at https://github.com/david-jenny/LLM-Political-Study

Identification of Technologies for Provision of Future Aeronautical Communications

This report describes the process, findings, and recommendations of the second of three phases of the Future Communications Study (FCS) technology investigation conducted by NASA Glenn Research Center and ITT Advanced Engineering & Sciences Division for the Federal Aviation Administration (FAA). The FCS is a collaborative research effort between the FAA and Eurocontrol to address frequency congestion and spectrum depletion for safety critical airground communications. The goal of the technology investigation is to identify technologies that can support the longterm aeronautical mobile communication operating concept. A derived set of evaluation criteria traceable to the operating concept document is presented. An adaptation of the analytical hierarchy process is described and recommended for selecting candidates for detailed evaluation. Evaluations of a subset of technologies brought forward from the prescreening process are provided. Five of those are identified as candidates with the highest potential for continental airspace solutions in L-band (P-34, W-CDMA, LDL, B-VHF, and E-TDMA). Additional technologies are identified as best performers in the unique environments of remote/oceanic airspace in the satellite bands (Inmarsat SBB and a custom satellite solution) and the airport flight domain in C-band (802.16e). Details of the evaluation criteria, channel models, and the technology evaluations are provided in appendixes

Gold Ion–Angiotensin Peptide Interaction by Mass Spectrometry

Stimulated by the interest in developing gold compounds for treating cancer, gold ion– angiotensin peptide interactions are investigated by mass spectrometry. Under the experimental conditions used, the majority of gold ion–angiotensin peptide complexes contain gold in the oxidation states I and III. Both ESI-MS and MALDI-TOF MS detect singly/multiply charged ions for mononuclear/multinuclear gold-attached peptides, which are represented as [peptide+a Au (I)+b Au(III)+(e - a -3b) H]e+, where a,b≥0 and e is charge. ESI-MS data shows singly/multiply charged ions of Au(I)-peptide and Au(III)-peptide complexes. This study reveals that MALDITOF MS mainly detects singly charged Au(I)-peptide complexes, presumably due to the ionization process. The electrons in the MALDI plume seem to efficiently reduce Au(III) to Au(I). MALDI also tends to enhance the higher polymeric forms of gold-peptide complexes regardless of the laser power used. Collision-induced dissociation experiments of the mononuclear and dinuclear gold-attached peptide ions for angiotensin peptides show that the gold ion (a soft acid) binding sites are in the vicinity of Cys (a soft ligand), His (a major anchor of peptide for metal ion chelation), and the basic residue Arg. Data also suggests that the abundance of gold-attached peptides increases with higher gold concentration until saturation, after which an increase in gold ion concentration leads to the aggregation and/or precipitation of gold-bound peptides

The Stroke Neuro-Imaging Phenotype Repository: An open data science platform for stroke research

Stroke is one of the leading causes of death and disability worldwide. Reducing this disease burden through drug discovery and evaluation of stroke patient outcomes requires broader characterization of stroke pathophysiology, yet the underlying biologic and genetic factors contributing to outcomes are largely unknown. Remedying this critical knowledge gap requires deeper phenotyping, including large-scale integration of demographic, clinical, genomic, and imaging features. Such big data approaches will be facilitated by developing and running processing pipelines to extract stroke-related phenotypes at large scale. Millions of stroke patients undergo routine brain imaging each year, capturing a rich set of data on stroke-related injury and outcomes. The Stroke Neuroimaging Phenotype Repository (SNIPR) was developed as a multi-center centralized imaging repository of clinical computed tomography (CT) and magnetic resonance imaging (MRI) scans from stroke patients worldwide, based on the open source XNAT imaging informatics platform. The aims of this repository are to: (i) store, manage, process, and facilitate sharing of high-value stroke imaging data sets, (ii) implement containerized automated computational methods to extract image characteristics and disease-specific features from contributed images, (iii) facilitate integration of imaging, genomic, and clinical data to perform large-scale analysis of complications after stroke; and (iv) develop SNIPR as a collaborative platform aimed at both data scientists and clinical investigators. Currently, SNIPR hosts research projects encompassing ischemic and hemorrhagic stroke, with data from 2,246 subjects, and 6,149 imaging sessions from Washington University\u27s clinical image archive as well as contributions from collaborators in different countries, including Finland, Poland, and Spain. Moreover, we have extended the XNAT data model to include relevant clinical features, including subject demographics, stroke severity (NIH Stroke Scale), stroke subtype (using TOAST classification), and outcome [modified Rankin Scale (mRS)]. Image processing pipelines are deployed on SNIPR using containerized modules, which facilitate replicability at a large scale. The first such pipeline identifies axial brain CT scans from DICOM header data and image data using a meta deep learning scan classifier, registers serial scans to an atlas, segments tissue compartments, and calculates CSF volume. The resulting volume can be used to quantify the progression of cerebral edema after ischemic stroke. SNIPR thus enables the development and validation of pipelines to automatically extract imaging phenotypes and couple them with clinical data with the overarching aim of enabling a broad understanding of stroke progression and outcomes