Full Chain Research Articles

A Silicon-Photo-Multiplier-Based Camera for the Terzina Telescope on Board the Neutrinos and Seismic Electromagnetic Signals Space Mission

NUSES is a pathfinder satellite project hosting two detectors: Ziré and Terzina. Ziré focuses on the study of protons and electrons below 250 MeV and MeV gamma rays. Terzina is dedicated to the detection of Cherenkov light produced by ultra-high-energy cosmic rays above 100 PeV and ultra-high-energy Earth-skimming neutrinos in the atmosphere, ensuring a large exposure. This work mainly concerns the description of the Cherenkov camera, composed of SiPMs, for the Terzina telescope. To increase the data-taking period, the NUSES orbit will be Sun-synchronous (with a height of about 550 km), thus allowing Terzina to always point toward the dark side of the Earth’s limb. The Sun-synchronous orbit requires small distances to the poles, and as a consequence, we expect an elevated dose to be received by the SiPMs. Background rates due to the dose accumulated by the SiPM would become a dominant contribution during the last two years of the NUSES mission. In this paper, we illustrate the measured effect of irradiance on SiPM photosensors with a variable-intensity beam of 50 MeV protons up to a 30 Gy total integrated dose. We also show the results of an initial study conducted without considering the contribution of solar wind protons and with an initial geometry with Geant4. The considered geometry included an entrance lens as one of the options in the initial design of the telescope. We characterize the SiPM output signal shape with different μ-cell sizes. We describe the developed parametric SiPM simulation, which is a part of the full Terzina simulation chain.

The application and modification of WRF-Hydro/Glacier to a cold-based Antarctic glacier

Abstract. The McMurdo Dry Valleys (MDV) are home to a unique microbial ecosystem that is dependent on the availability of freshwater. This is a polar desert and freshwater originates almost entirely from surface and near-surface melt of the cold-based glaciers. Understanding the future evolution of these environments requires the simulation of the full chain of physical processes from net radiative forcing, surface energy balance, melt, runoff and transport of meltwater in stream channels from the glaciers to the terminal lakes where the microbial community resides. To establish a new framework to do this, we present the first application of WRF-Hydro/Glacier in the MDV, which as a fully distributed hydrological model has the capability to resolve the streams from the glaciers to the bare land that surround them. Given that meltwater generation in the MDV is almost entirely dependent on small changes in the energy balance of the glaciers, the aim of this study is to optimize the multi-layer snowpack scheme that is embedded in WRF-Hydro/Glacier to ensure that the feedbacks between albedo, snowfall and melt are fully resolved. To achieve this, WRF-Hydro/Glacier is implemented at a point scale using automatic weather station data on Commonwealth Glacier to physically model the onset, duration and end of melt over a 7-month period (1 August 2021 to 28 February 2022). To resolve the limited energetics controlling melt, it was necessary to (1) limit the percolation of meltwater through the ice layers in the multi-layer snowpack scheme and (2) optimize the parameters controlling the albedo of both snow and ice over the melt season based on observed spectral signatures of albedo. These modifications enabled the variability of broadband albedo over the melt season to be accurately simulated and ensured that modelled surface and near-surface temperatures, surface height change and runoff were fully resolved. By establishing a new framework that couples a detailed snowpack model to a fully distributed hydrological model, this work provides a stepping stone to model the spatial and temporal variability of melt and streamflow in the future, which will enable some of the unknown questions about the hydrological connectivity of the MDV to be answered.

CMS HGCAL electronics vertical integration system tests

In preparation for the High-Luminosity phase of the CERN Large Hadron Collider, the Compact Muon Solenoid collaboration will replace the existing endcap calorimeters with the High Granularity Calorimeter. Considering both endcaps, this novel sub-detector will have around six million readout channels, pushing approximately 108 Tbit s-1 of usable data between the detector front-end (on-detector) electronics and the back-end (off-detector) electronics. Given the scale and complexity of the endcap calorimeter upgrade project, the electronics testing must be carefully planned. The strategy has been to split the efforts between vertical (start-to-end) and horizontal (parallelisation) test systems wherever possible. An important milestone was the development and operation of a test system that prototypes a complete vertical slice of the future endcap electronics system. For the first time, a version of a test system consisting of the full vertical electronics readout chain was successfully operated in a beam test, where it was used to acquire real physics data.

Highly-conductive proton exchange membrane of sulfonated poly(biphenyl alkylene) copolymers for H2/O2 fuel cell with 2.62 W cm-2 power density

Ether-free proton exchange membranes (PEMs) based on aromatic polymers are considered as potential alternatives to perfluorosulfonic acid (PFSA) PEMs due to their low cost, less reactant crossing, exceptional chemical stability and outstanding thermal stability. Herein, a series of high-performance sulfonated poly(biphenyl alkylene) (BPSA-PT-x) membranes with full carbon chain backbones were synthesized to investigate the effect of different ratios of hydrophobic components on membrane properties. Among the prepared membranes, the BPSA-PT-10 % PEM with the highest proton conductivity (311 mS cm-1 at 80 °C water) possessed excellent dimensional stability (in-plane swelling rate ≤19.7 %, through-plane swelling rate ≤24.9 %), mechanical properties (elongation at break: 89.8 % in wet state), thermal stability (glass transition temperature >450 °C) and low H2 crossover (1.80 mA cm-2). Further, the assembled H2/O2 fuel cell based on BPSA-PT-10 % PEM exhibited competitive performance with a peak power density of 2.62 W cm-2. The developed poly(biphenyl alkylene)-based PEMs should have potential applications in hydrogen energy field.

Development of a framework to assess the greenhouse gas mitigation potential from the adoption of low-carbon road vehicles in a hydrocarbon-rich region

This study developed a novel assessment framework to analyze long-term energy transition in the road transport sector in which various technology options, market shares, policy measures, costs, and greenhouse gas emissions are considered in a single framework analysis. A data-intensive model was developed with the Low Emissions Analysis Platform (LEAP) and used to analyze policy scenarios up to 2050 for Alberta, Canada, a hydrocarbon-rich province with an emission-intensive energy sector. Three key policy measures – carbon pricing, zero-emission vehicle sales mandate, and incentivization – were analyzed in nine individual and combined policy scenarios. The transition to both hydrogen fuel cell electric vehicles and battery electric vehicles was assessed for all vehicle categories. Each fuel's full energy supply chain was modelled, including resource extraction, conversion, transmission and distribution, and fuelling, allowing for final and primary energy analysis. The findings show that carbon price and zero-emission vehicle incentives do not effectively lower greenhouse gas emissions on their own; zero-emission vehicle mandates are needed to transition the sector to a low-carbon energy system. The system-wide greenhouse gas emission footprints of hydrogen and battery electric vehicles are significantly below conventional vehicles in all cases. Scenarios biased towards battery electric vehicles had the most favorable results. The greenhouse gas emission footprint of hydrogen vehicles supplied by auto-thermal reforming with 91% carbon capture was lower than for battery electric vehicles powered by a primarily natural gas-based power grid. The findings on the effectiveness of carbon prices, incentives, and vehicle mandates should be considered by government policymakers aiming to reduce greenhouse gas emissions, infrastructure planners, and other energy stakeholders.

Fully Composable and Adequate Verified Compilation with Direct Refinements between Open Modules

Verified compilation of open modules (i.e., modules whose functionality depends on other modules) provides a foundation for end-to-end verification of modular programs ubiquitous in contemporary software. However, despite intensive investigation in this topic for decades,the proposed approaches are still difficult to use in practice as they rely on assumptions about the internal working of compilers which make it difficult for external users to apply the verification results. We propose an approach to verified compositional compilation without such assumptions in the setting of verifying compilation of heterogeneous modules written in first-order languages supporting global memory and pointers. Our approach is based on the memory model of CompCert and a new discovery that a Kripke relation with a notion of memory protection can serve as a uniform and composable semantic interface for the compiler passes. By absorbing the rely-guarantee conditions on memory evolution for all compiler passes into this Kripke Memory Relation and by piggybacking requirements on compiler optimizations onto it, we get compositional correctness theorems for realistic optimizing compilers as refinements that directly relate native semantics of open modules and that are ignorant of intermediate compilation processes. Such direct refinements support all the compositionality and adequacy properties essential for verified compilation of open modules. We have applied this approach to the full compilation chain of CompCert with its Clight source language and demonstrated that our compiler correctness theorem is open to composition and intuitive to use with reduced verification complexity through end-to-end verification of non-trivial heterogeneous modules that may freely invoke each other (e.g.,mutually recursively).

Overview of Cooperative Fault-Tolerant Control Driven by the Full Information Chain of Intelligent Connected Vehicle Platoons Under the Zero-Trust Framework: Opportunities and Challenges

Overview of Cooperative Fault-Tolerant Control Driven by the Full Information Chain of Intelligent Connected Vehicle Platoons Under the Zero-Trust Framework: Opportunities and Challenges

RESTORE VISION: Novel advanced and repurposed therapeutics for vision restoration in a group of severe rare ocular diseases – Short introductory talk

Rare Eye Diseases (REDs) collectively represent a major cause of visual impairment and blindness for children and young adults in Europe. But importantly, REDs also affect adults and the aging population. Defective wound healing at the cornea and ocular surface, excessive inflammation, nerve degeneration, stem cell dysfunction, and aberrant vessel ingrowth are the common denominators in many REDs, representing a critical medical problem and an area of unmet medical need. The onset and progression of many REDs are characterized by common pathophysiologic mechanisms. The goal of many research groups is to disrupt these aberrant mechanisms with the aim of making therapy more effective. Current management is often prohibitively expensive, has low efficacy and leads to debilitating side effects, pointing to a critical medical problem and area of unmet medical need.Here, we will briefly introduce the RESTORE VISION project, which has been recently funded by the European Commission and brings together actors from across the full value chain: 6 leading research institutions, 3 SMEs and a European patient organization. The project will take a ground‐breaking approach to improve eye health by verifying disease pathomechanisms, using cutting‐edge models for each rare disease to test novel and repurposed compounds and determine drug mechanisms of action, formulating compounds as safe eye drop suspensions or subconjunctival drugs, and performing several first‐in‐human trials of novel therapies.

Effects of Full Chain Processes on the Performance of 316L Stainless Steel Composite by Fused Deposition Modeling and Sintering

Fused deposition modeling and sintering (FDMS) is a novel 3D printing technique that combines fused deposition modeling with catalytic debinding and sintering processes to enable the rapid production of metal parts with low energy consumption and costs. Firstly, a 316L/POM composite filament is prepared. Subsequently, test specimens are printed using a fused deposition modeling (FDM) printer, followed by catalytic debinding and sintering processes to create dense metal parts. The process parameters show an influence on the part structure and, subsequently, the properties, and this study examines the microstructural characteristics of the 316L/POM composite filament at each process stage. Using tensile strength as the indicator, an orthogonal experiment is designed to identify suitable combinations of process parameters. Experimental results demonstrate that the FDMS process can manufacture 316L stainless steel parts; moreover, they influence the structure and, consequently, the mechanical behavior, as these are strongly related. By appropriately adjusting the process parameters, this method can be suitable for applications requiring functional parts with less stringent strength requirements.

Pretreatment as a Microplastics Generator during Household Biogenic Waste Treatment

Mechanical pretreatment is an indispensable process in biological treatment plants that remove plastics and other impurities from household biogenic waste (HBW). However, the imperfect separation of plastics in these pretreatment methods has raised concerns that they pose a secondary formation risk for microplastics (MPs). To validate this presumption, herein, quantities and properties of plastic debris and MPs larger than 50 μm were examined in the full chain of three different pretreatment methods in six plants. These facilities received HBW with or without prior depackaging at the source. The key points in the secondary formation of MPs were identified. Moreover, flux estimates of MPs were released, and an analysis of MPs sources was provided to develop an overview of their fate in HBW pretreatment. Pretreated output can contain a maximum of (1673 ± 279) to (3198 ± 263) MP particles per kilogram of wet weight (particles·kg−1 ww) for those undepackaged at source, and secondary MPs formation is primarily attributed to biomass crushers, biohydrolysis reactors, and rough shredders. Comparatively, HBW depackaged at the source can greatly reduce MPs by 8%–72%, regardless of pretreatment processes. Before pretreatment, 4.6–205.6 million MP particles were present in 100 tonnes of HBW. MPs are produced at a rate of 741.11–33 124.22 billion MP particles annually in anaerobic digester feedstock (ADF). This study demonstrated that HBW pretreatment is a competitive source of MPs and emphasized the importance of implementing municipal solid waste segregation at the source. Furthermore, depackaging biogenic waste at the source is recommended to substantially alleviate the negative effect of pretreatment on MPs formation.

Acoustic prediction and testing for "Basajaun" EU Project demo building using neural network, prediction for innovative wooden partition wall with composites and bio-based insulation

"Basajaun" is a major European innovation action about sustainable building with wood. The main objective is to demonstrate how wood construction chains can be optimized to foster both rural development and urban transformation whilst being connected with sustainable forest management in Europe. The project scrolls the full value chain of wood construction in Europe, and it include a demo project in south of France demonstrating implementation of various innovations, among which the studied innovative facade made of pultruded composites, structural insulated panels (SIP) plywood, wooden cladding and bio-based insulation. In building projects, partition walls are commonly designed for mechanical stability, thermal insulation and fire safety, in this article authors focus on acoustic aspects starting from design, optimization, lab testing, implementation specifications and in situ validation. For the design and optimization phase, authors developed prediction tool based on Artificial Intelligence. Programming and data feeding of the tool is described, and predictions are compared to laboratory measurements.

Hybrid Bond Interconnect and Advanced Packaging Solutions

Hybrid bond interconnect is a scalable technology that offers significant improvements over the incumbent Cu mbump technology. The notable advantages include, enhanced reliability of elemental metal interconnect, improved thermal performance of an inorganic bond interface and the high-speed performance with a low capacitance and inductance pad structure. Currently, the industry is adopting this technology for high-performance compute applications; however, we anticipate a broader adoption once the technology is readily available within the full supply chain. In this paper, we present the performance of our hybrid bond interconnect on multiple test vehicles including single 1 to 8-die stacks with various pad-pitch sizes, die sizes and configurations. We share die to wafer assembly yield results using our manufacturing worthy process where die are prepared on tape frame using standard pick and place equipment. The test vehicles cover a range of pad sizes (2-15 um), with pitches (4-40 um) and have different x,y dimensions from 1mmx1mm to 9mmx12mm. Reliability tests include MSL-3 precondition, high temperature storage and thermal cycling and on the various test structures

Research on Digital Transformation of New Retail Enterprises Based on AI+RPA

Faced with the breakthrough of digital technology and upgrading of consumer structure, the traditional retail industry has achieved the basic transformation and efficiency of a full value chain relying on digital technology. Among them, AI+RPA has become a new direction in developing the new retail industry with artificial intelligence empowerment machine automation. This article takes the new retail industry as the target market and the application of AI+RPA technology as the research content, using the theoretical and multiple case analysis methods to study. Choose three companies: Freshippo, Yonghui superstores, and Suning.com, for external horizontal contrast and internal vertical contrast. Relying on the theory of value chain, the division is divided into four aspects: the supply side, the demand side, financial management, and logistics. To a certain extent, this article has made up for the research gap of the omni -channel ecological construction of the new retail industry and the application of the AI+RPA technology industry, expecting to broaden the future development channels and directions of the new retail industry.

Extracellular Vesicles as Possible Plasma Markers and Mediators in Patients with Sepsis-Associated Delirium—A Pilot Study

Patients with sepsis-associated delirium (SAD) show severe neurological impairment, often require an intensive care unit (ICU) stay and have a high risk of mortality. Hence, useful biomarkers for early detection of SAD are urgently needed. Extracellular vesicles (EVs) and their cargo are known to maintain normal physiology but also have been linked to numerous disease states. Here, we sought to identify differentially expressed proteins in plasma EVs from SAD patients as potential biomarkers for SAD. Plasma EVs from 11 SAD patients and 11 age-matched septic patients without delirium (non-SAD) were isolated by differential centrifugation, characterized by nanoparticle tracking analysis, transmission electron microscopy and Western blot analysis. Differential EV protein expression was determined by mass spectrometry and the resulting proteomes were characterized by Gene Ontology term and between-group statistics. As preliminary results because of the small group size, five distinct proteins showed significantly different expression pattern between SAD and non-SAD patients (p ≤ 0.05). In SAD patients, upregulated proteins included paraoxonase-1 (PON1), thrombospondin 1 (THBS1), and full fibrinogen gamma chain (FGG), whereas downregulated proteins comprised immunoglobulin (IgHV3) and complement subcomponent (C1QC). Thus, plasma EVs of SAD patients show significant changes in the expression of distinct proteins involved in immune system regulation and blood coagulation as well as in lipid metabolism in this pilot study. They might be a potential indicator for to the pathogenesis of SAD and thus warrant further examination as potential biomarkers, but further research is needed to expand on these findings in longitudinal study designs with larger samples and comprehensive polymodal data collection.

The CCS greensand project: CO2 pilot injection and monitoring

The CCS greensand project: CO2 pilot injection and monitoring

B-129 Uncertainty Calculations for Reference Measurement Procedures

Abstract Background Quantitative results based on reference measurement procedures (RMP) require the calculation of the uncertainty of the result. In order to take the uncertainty of the full traceability chain into account a modularisation of the different execution steps is needed, starting from the primary reference material until the final concentration value. Different strategies have to be applied and combined to obtain the final uncertainty.We combine different ways for calculating the uncertainty of an isotope dilution -liquid chromatography-tandem mass spectrometry (ID-LC-MS/MS) based reference measurement procedure for Cortisol, and explain the differences between Type A and Type B uncertainties and best strategies to choose from them. In addition, combinations of results from subsequent steps to a final overall uncertainty are presented. Methods An ID-LC-MS/MS based reference measurement procedure requires as a starting point a primary reference material with known purity of the analyte under consideration. Nowadays this purity assessment is often done with quantitative nuclear magnetic resonance (qNMR) spectroscopy. The qNMR uncertainty calculation is a Type A approach, based on replicate sample preparations and measurements. With this primary material a first set of primary calibrators is produced, often through multiple steps of weighings, preparation of stock solutions and dilutions. For these steps balances, volumetric flasks, or pipettes are used, all of them coming with an error budget which has to enter the uncertainty budget of the primary calibrator preparation. We will show how this can be done through Type B uncertainty calculation. Based on the primary calibrators the LC/MS instrument is calibrated and measurements of individual samples are carried out. We will introduce a hierarchical variability experiment, which takes into account the most important error sources and results in a Type A uncertainty for the LC/MS measurements.Finally, the errors of the LC/MS measurements have to be combined with those of the primary calibrator preparation to obtain the overall uncertainty of an LC/MS reference measurement procedure. Results We show the approaches and calculation strategies based on the Cortisol candidate reference measurement procedure, developed within the Roche LC/MS Reference Measurement Procedure project. The purity assessment by qNMR carries an uncertainty of 0.18%. This is incorporated into the uncertainty calculations of the primary calibrators, where in addition uncertainties from weighing and dilutions are incorporated resulting in uncertainties of the primary calibrator values between 0.6% and 1.1%. Combining these uncertainties with the variabilities of the LC/MS measurement procedure results in final uncertainties between 1.6% and 2.8%. Conclusion We have developed a sound framework for uncertainty calculation of reference measurement procedures, taking into account the different procedure steps, and included this into a process for the management of the different input variables up to comprehensive reports of the calculations.

Remote monitoring of a concrete bridge using PSInSAR

AbstractStructural health monitoring (SHM) can support decision makers in structural integrity management by providing information about occurrence of damage and its evolution in time. Recently, due to new Synthetic Aperture Radar (SAR) missions, remote sensing through active satellites provides a promising methodology capable of monitoring infrastructure assets. This paper investigates the use of Multi‐Temporal Synthetic Aperture Radar Interferometry (MT‐InSAR) processing to monitor the structural health of bridges. The full interferometry processing chain is applied using Sentinel‐1 synthetic aperture radar data and a combination of open‐source routines from the Sentinel Application Platform (SNAP) and Stanford Method for Persistent Scatterers (StaMPS). Displacement time‐histories are derived from single look complex products by employing the Persistent Scatterer Interferometry (PSInSAR) technique. The PS‐InSAR technique is applied to study the behavior of a concrete bridge located over the Oglio river in Isola Dovarese, Italy, on which also GNSS receivers are installed. The GNSS data are then used to validate the PS‐InSAR measurements. The effects on PS‐InSAR results of the number of SAR images used as well of the target structure are investigated.

A multiphysics model for fluid-structure-electrophysiology interaction in rowing propulsion

Jellyfish are one of the earliest example of animal that actively regulate swimming, but the mechanisms governing the locomotion are still a matter of research. Jellyfish obtain locomotion by activating the subumbrellar muscle layer. Sensory inputs trigger the contraction of the bell and the fluid-structure interaction effects driving locomotion. These have been extensively studied, whereas a representation of the full neuro-mechanical locomotion chain, with focus on the actuation-locomotion dynamics, has not been proposed yet. A model of such a complex multi-physical phenomenon would be informative for several purposes, ranging from the comprehension of behavioral aspects to the design of soft actuators and bio-inspired devices. In this regard, we propose a computational framework to address the coupled electrophysiological, elastic, and fluid aspects of the locomotion of the Scyphozoan group. This relies on the sequential coupling of segregated solvers, such that each sub-problem can be addressed with the most computationally effective technique. The spatial discretization is addressed by isogeometric analysis for the electrophysiological and elastic sub-problems, and by finite differences for the fluid sub-problem. The active strain approach allows to distribute the active contraction of radial and coronal muscle fibers following the biological architecture.The inherent multi-scale nature of the model is addressed by means of a nested grid approach and multiple time-advancement lines. In view of a reasonable computational effort, we enforce the hypothesis of axial symmetry limiting the number of degrees of freedom used in the simulations. The effectiveness of the scheme employed for each sub-problem is verified against different test-cases of engineering and biologic inspiration. Finally, we carry out an extensive comparison between the simulation output and the in-vivo measurements on a 3-cm specimen of Aurelia Aurita.

Languages in China link climate, voice quality, and tone in a causal chain

Are the sound systems of languages ecologically adaptive like other aspects of human behavior? In previous substantive explorations of the climate–language nexus, the hypothesis that desiccation affects the tone systems of languages was not well supported. The lack of analysis of voice quality data from natural speech undermines the credibility of the following two key premises: the compromised voice quality caused by desiccated ambient air and constrained use of phonemic tone due to a desiccated larynx. Here, the full chain of causation, humidity → voice quality → number of tones, is for the first time strongly supported by direct experimental tests based on a large speech database (China’s Language Resources Protection Project). Voice quality data is sampled from a recording set that includes 997 language varieties in China. Each language is represented by about 1200 sound files, amounting to a total of 1,174,686 recordings. Tonally rich languages are distributed throughout China and vary in their number of tones and in the climatic conditions of their speakers. The results show that, first, the effect of humidity is large enough to influence the voice quality of common speakers in a naturalistic environment; secondly, poorer voice quality is more likely to be observed in speakers of non-tonal languages and languages with fewer tones. Objective measures of phonatory capabilities help to disentangle the humidity effect from the contribution of phylogenetic and areal relatedness to the tone system. The prediction of ecological adaptation of speech is first verified through voice quality analysis. Humidity is observed to be related to synchronic variation in tonality. Concurrently, the findings offer a potential trigger for diachronic changes in tone systems.

Direct Mass Spectrometry-Based Detection and Antibody Sequencing of Monoclonal Gammopathy of Undetermined Significance from Patient Serum: A Case Study.

Monoclonal gammopathy of undetermined significance (MGUS) is a plasma cell disorder characterized by the presence of a predominant monoclonal antibody (i.e., M-protein) in serum, without clinical symptoms. Here we present a case study in which we detect MGUS by liquid-chromatography coupled with mass spectrometry (LC-MS) profiling of IgG1 in human serum. We detected a Fab-glycosylated M-protein and determined the full heavy and light chain sequences by bottom-up proteomics techniques using multiple proteases, further validated by top-down LC-MS. Moreover, the composition and location of the Fab-glycan could be determined in CDR1 of the heavy chain. The outlined approach adds to an expanding mass spectrometry-based toolkit to characterize monoclonal gammopathies such as MGUS and multiple myeloma, with fine molecular detail. The ability to detect monoclonal gammopathies and determine M-protein sequences straight from blood samples by mass spectrometry provides new opportunities to understand the molecular mechanisms of such diseases.