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While Spin Waves (SW) interaction provides natural support for low power Majority (MAJ) gate implementations many hurdles still exists on the road towards the realization of practically relevant SW circuits. In this paper we leave the SW interaction avenue and propose Threshold Logic (TL) inspired SW computing, which relies on successive phase rotations applied to one single SW instead of on the interference of an odd number of SWs. After providing a short TL inside we introduce the SW TL gate concept and discuss the way to mirror TL gate weight and threshold values into physical phase-shifter parameters. Subsequently, we design and demonstrate proper operation of a SW TL based Full Adder (FA) by means of micro-magnetic simulations. We conclude the paper by providing inside on the potential advantages of our proposal by means of a conceptual comparison of MAJ and TL based FA implementations., Comment: This work has received funding from the Horizon Europe research and innovation program within the project "Spider" (grant agreement no. 101070417)

While magnetic solid-state memory has found commercial applications to date, magnetic logic has rather remained on a conceptual level so far. Here, we discuss open challenges of different spintronic logic approaches, which use magnetic excitations for computation. While different logic gate designs have been proposed and proof of concept experiments have been reported, no nontrivial operational spintronic circuit has been demonstrated due to many open challenges in spintronic circuit and system design. Furthermore, the integration of spintronic circuits in CMOS systems will require the usage of transducers between the electric (CMOS) and magnetic domains. We show that these transducers can limit the performance as well as the energy consumption of hybrid CMOS-spintronic systems. Hence, the optimization of transducer efficiency will be a major step towards competitive spintronic logic system., Comment: This work has received funding from the European Union's Horizon 2020 research and innovation program within the project CHIRON (grant agreement no. 801055) as well as from the Horizon Europe research and innovation program within the project SPIDER (grant agreement no. 101070417)

Vico et al. (2016) suggest a fast algorithm for computing volume potentials, beneficial to fields with problems requiring the solution of Poisson's equation with free-space boundary conditions, such as the beam and plasma physics communities. Currently, the standard method for solving the free-space Poisson equation is the algorithm of Hockney and Eastwood (1988), which is second order in convergence at best. The algorithm proposed by Vico et al. converges spectrally for sufficiently smooth functions i.e. faster than any fixed order in the number of grid points. In this paper, we implement a performance portable version of the traditional Hockney-Eastwood and the novel Vico-Greengard Poisson solver as part of the IPPL (Independent Parallel Particle Layer) library. For sufficiently smooth source functions, the Vico-Greengard algorithm achieves higher accuracy than the Hockney-Eastwood method with the same grid size, reducing the computational demands of high resolution simulations since one could use coarser grids to achieve them. More concretely, to get a relative error of $10^{-4}$ between the numerical and analytical solution, one requires only $16^3$ grid points in the former, but $128^3$ in the latter, more than a 99% memory footprint reduction. Additionally, we propose an algorithmic improvement to the Vico-Greengard method which further reduces its memory footprint. This is particularly important for GPUs which have limited memory resources, and should be taken into account when selecting numerical algorithms for performance portable codes. Finally, we showcase performance through GPU and CPU scaling studies on the Perlmutter (NERSC) supercomputer, with efficiencies staying above 50% in the strong scaling case., Comment: 18 pages, 11 figures

The computational cost for high energy physics detector simulation in future experimental facilities is going to exceed the current available resources. To overcome this challenge, new ideas on surrogate models using machine learning methods are being explored to replace computationally expensive components. Additionally, differentiable programming has been proposed as a complementary approach, providing controllable and scalable simulation routines. In this document, new and ongoing efforts for surrogate models and differential programming applied to detector simulation are discussed in the context of the 2021 Particle Physics Community Planning Exercise (`Snowmass').

Introduction: In 2013, a new liver transplant allocation policy (Share 35) aimed to reduce waitlist-mortality was introduced in the United States. Regional organ sharing for recipients with a MELD score of ≥35 was prioritized over local allocation to those with lower MELD scores. Our aim was to assess the changes in perioperative mortality following the introduction of Share 35 as well as changes in patients’ short-term 7-day survival, patients discharged alive and 1-year survival. Analyses were also carried out for the subgroups of patients with MELD scores ≥ and < 35. Methods: We used data from the Scientific Registry of Transplant Recipients and included liver transplants between March 2002 and December 2018 in this retrospective cohort study. Perioperative mortality was defined as death during and within two days of liver transplant. We used robust interrupted time series analyses to evaluate the impact of Share 35 on mortality. Results: We included 90 002 liver transplants in our analysis and observed a decreasing trend in perioperative mortality over time (−.061 deaths per 1000 cases per month, 95% CI −.084 to −.037, p <.001). Share 35 was not associated with a change in perioperative mortality (p =.33), short-term 7-day survival (p =.48), survival to discharge (p =.56), or 1-year survival (p =.27). Conclusions: Prioritizing sicker recipients with a MELD score ≥35 for liver transplantation was not associated with a change in postoperative mortality.

BACKGROUND: The impact of albumin use during major surgery is unknown, and a dearth of evidence governing its use in major noncardiac surgery has long precluded its standardization in clinical guidelines. OBJECTIVE: In this study, we investigate institutional variation in albumin use among medical centers in the United States during major noncardiac surgery and explore the association of intraoperative albumin administration with important postoperative outcomes. METHODS: The study is an observational retrospective cohort analysis performed among 54 U.S. hospitals in the Multicenter Perioperative Outcomes Group and includes adult patients who underwent major noncardiac surgery under general anesthesia between January 2014 and June 2020. The primary endpoint was the incidence of albumin administration. Secondary endpoints are acute kidney injury (AKI), net-positive fluid balance, pulmonary complications, and 30-day mortality. Albumin-exposed and albumin-unexposed cases were compared within a propensity score-matched cohort to evaluate associations of albumin use with outcomes. RESULTS: Among 614,215 major surgeries, predominantly iso-oncotic albumin was administered in 15.3% of cases and featured significant inter-institutional variability in use patterns. Cases receiving intraoperative albumin involved patients of higher American Society of Anesthesiologists physical status and featured larger infused crystalloid volumes, greater blood loss, and vasopressor use. Overall, albumin was most often administered at high-volume surgery centers with academic affiliation, and within a propensity score-matched cohort (n=153,218), the use of albumin was associated with AKI (aOR 1.24, 95% CI 1.20-1.28, P <0.001), severe AKI (aOR 1.45, 95% CI 1.34-1.56, P <0.001), net-positive fluid balance (aOR 1.18, 95% CI 1.16-1.20, P <0.001), pulmonary complications (aOR 1.56, 95% CI 1.30-1.86, P <0.001), and 30-day all-cause mortality (aOR 1.37, 95% CI 1.26-1.49, P <0.001). C

The wait times for patients with hepatocellular carcinoma (HCC) listed for liver transplant are longer than ever, which has led to an increased reliance on the use of pre-operative LRTs. The impact that multiple rounds of LRTs have on peri-operative outcomes following transplant is unknown. This was a retrospective single center analysis of 298 consecutive patients with HCC who underwent liver transplant (January 2017 to May 2021). The data was obtained from two institution-specific databases and the TransQIP database. Of the 298 patients, 27 (9.1%) underwent no LRTs, 156 (52.4%) underwent 1-2 LRTs, and 115 (38.6%) underwent ≥3 LRTs prior to LT. The patients with ≥3 LRTs had a significantly higher rate of bile leak compared to patients who received 1-2 LRTs (7.0 vs. 1.3%, p = 0.014). Unadjusted and adjusted regression analyses demonstrated a significant association between the total number of LRTs administered and bile leak, but not rates of overall biliary complications. The total number of LRTs was not significantly associated with any other peri-operative or post-operative outcome measure. These findings support the aggressive use of LRTs to control HCC in patients awaiting liver transplant, with further evaluation needed to confirm the biliary leak findings.

INTRODUCTION: Catecholamine vasopressors such as norepinephrine are the standard drugs used to maintain mean arterial pressure during liver transplantation. At high doses, catecholamines may impair organ perfusion. Angiotensin II is a peptide vasoconstrictor that may improve renal perfusion pressure and glomerular filtration rate, a haemodynamic profile that could reduce acute kidney injury. Angiotensin II is approved for vasodilatory shock but has not been rigorously evaluated for treatment of hypotension during liver transplantation. The objective is to assess the efficacy of angiotensin II as a second-line vasopressor infusion during liver transplantation. This trial will establish the efficacy of angiotensin II in decreasing the dose of norepinephrine to maintain adequate blood pressure. Completion of this study will allow design of a follow-up, multicentre trial powered to detect a reduction of organ injury in liver transplantation. METHODS AND ANALYSIS: This is a double-blind, randomised clinical trial. Eligible subjects are adults with a Model for End-Stage Liver Disease Sodium Score ≥25 undergoing deceased donor liver transplantation. Subjects are randomised 1:1 to receive angiotensin II or saline placebo as the second-line vasopressor infusion. The study drug infusion is initiated on reaching a norepinephrine dose of 0.05 µg kg ETHICS AND DISSEMINATION: The trial protocol was approved by the local Institutional Review Board (#20-30948). Results will be posted on ClinicalTrials.gov and published in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: ClinicalTrials.govNCT04901169.

Conventional electronics use the flow of electric charges and are based on standard semiconductors. Spintronic devices exploit the electrons’ spin to generate and control currents and to combine electric and magnetic signals. Today there is a strong effort worldwide to integrate spintronic devices with standard CMOS technology towards hybrid spin-CMOS chips, offering advantages in terms of power consumption, compactness, and speed. Recent results (from SAMSUNG [1], TSMC [2], etc.) confirm the merit of this approach.

Unforeseen particle accelerator interruptions, also known as interlocks, lead to abrupt operational changes despite being necessary safety measures. These may result in substantial loss of beam time and perhaps even equipment damage. We propose a simple yet powerful binary classification model aiming to forecast such interruptions, in the case of the High Intensity Proton Accelerator complex at the Paul Scherrer Institut. The model is formulated as logistic regression penalized by least absolute shrinkage and selection operator, based on a statistical two sample test to distinguish between unstable and stable states of the accelerator. The primary objective for receiving alarms prior to interlocks is to allow for countermeasures and reduce beam time loss. Hence, a continuous evaluation metric is developed to measure the saved beam time in any period, given the assumption that interlocks could be circumvented by reducing the beam current. The best-performing interlock-to-stable classifier can potentially increase the beam time by around 5 min in a day. Possible instrumentation for fast adjustment of the beam current is also listed and discussed., Comment: 12 pages, 13 figures

To accelerate the translation of cancer nanomedicine, we used an integrated genomic approach to improve our understanding of the cellular processes that govern nanoparticle trafficking. We developed a massively parallel screen that leverages barcoded, pooled cancer cell lines annotated with multiomic data to investigate cell association patterns across a nanoparticle library spanning a range of formulations with clinical potential. We identified both materials properties and cell-intrinsic features that mediate nanoparticle-cell association. Using machine learning algorithms, we constructed genomic nanoparticle trafficking networks and identified nanoparticle-specific biomarkers. We validated one such biomarker: gene expression of SLC46A3 , which inversely predicts lipid-based nanoparticle uptake in vitro and in vivo. Our work establishes the power of integrated screens for nanoparticle delivery and enables the identification and utilization of biomarkers to rationally design nanoformulations.

BACKGROUND Previous research studies have demonstrated that medical content image retrieval can play an important role by assisting dermatologists in skin lesion diagnosis. However, current state-of-the-art approaches have not been adopted in routine consultation, partly due to the lack of interpretability limiting trust by clinical users. OBJECTIVE This study developed a new image retrieval architecture for polarized or dermoscopic imaging guided by interpretable saliency maps. This approach provides better feature extraction, leading to better quantitative retrieval performance as well as providing interpretability for an eventual real-world implementation. METHODS Content-based image retrieval (CBIR) algorithms rely on the comparison of image features embedded by convolutional neural network (CNN) against a labeled data set. Saliency maps are computer vision-interpretable methods that highlight the most relevant regions for the prediction made by a neural network. By introducing a fine-tuning stage that includes saliency maps to guide feature extraction, the accuracy of image retrieval is optimized. We refer to this approach as saliency-enhanced CBIR (SE-CBIR). A reader study was designed at the University Hospital Zurich Dermatology Clinic to evaluate SE-CBIR's retrieval accuracy as well as the impact of the participant's confidence on the diagnosis. RESULTS SE-CBIR improved the retrieval accuracy by 7% (77% vs 84%) when doing single-lesion retrieval against traditional CBIR. The reader study showed an overall increase in classification accuracy of 22% (62% vs 84%) when the participant is provided with SE-CBIR retrieved images. In addition, the overall confidence in the lesion's diagnosis increased by 24%. Finally, the use of SE-CBIR as a support tool helped the participants reduce the number of nonmelanoma lesions previously diagnosed as melanoma (overdiagnosis) by 53%. CONCLUSIONS SE-CBIR presents better retrieval accuracy compared to traditional CBIR CNN-base

The accurate calculation and uncertainty quantification of the characteristics of spent nuclear fuel (SNF) play a crucial role in ensuring the safety, efficiency, and sustainability of nuclear energy production, waste management, and nuclear safeguards. State of the art physics-based models, while reliable, are computationally intensive and time-consuming. This paper presents a surrogate modeling approach using neural networks (NN) to predict a number of SNF characteristics with reduced computational costs compared to physics-based models. An NN is trained using data generated from CASMO5 lattice calculations. The trained NN accurately predicts decay heat and nuclide concentrations of SNF, as a function of key input parameters, such as enrichment, burnup, cooling time between cycles, mean boron concentration and fuel temperature. The model is validated against physics-based decay heat simulations and measurements of different uranium oxide fuel assemblies from two different pressurized water reactors. In addition, the NN is used to perform sensitivity analysis and uncertainty quantification. The results are in very good alignment to CASMO5, while the computational costs (taking into account the costs of generating training samples) are reduced by a factor of 10 or more. Our findings demonstrate the feasibility of using NNs as surrogate models for fast characterization of SNF, providing a promising avenue for improving computational efficiency in assessing nuclear fuel behavior and associated risks.

In the early stages of a novel technology development, it is difficult to provide a comprehensive assessment of its potential capabilities and impact. Nevertheless, some preliminary estimates can be drawn and are certainly of great interest and in this paper we follow this line of reasoning within the framework of the Spin Wave (SW) based computing paradigm. In particular, we are interested in assessing the technological development horizon that needs to be reached in order to unleash the full SW paradigm potential such that SW circuits can outperform CMOS counterparts in terms of energy consumption. In view of the zero power SWs propagation through ferromagnetic waveguides, the overall SW circuit power consumption is determined by the one associated to SWs generation and sensing by means of transducers. While current antenna based transducers are clearly power hungry recent developments indicate that magneto-electric (ME) cells have a great potential for ultra-low power SW generation and sensing. Given that MEs have been only proposed at the conceptual level and no actual experimental demonstration has been reported we cannot evaluate the impact of their utilization on the SW circuit energy consumption. However, we can perform a reverse engineering alike analysis to determine ME delay and power consumption upper bounds that can place SW circuits in the leading position. To this end, we utilize a 32-bit Brent-Kung Adder (BKA) as discussion vehicle and compute the maximum ME delay and power consumption that could potentially enable a SW implementation able to outperform its 7nm CMOS counterpart. We evaluate different BKA SW implementations that rely on conversion- or normalization-based gate cascading and consider continuous or pulsed SW generation scenarios. Our evaluations indicate that 31nW is the maximum transducer power consumption for which a 32-bit Brent-Kung SW implementation can outperform its 7nm CMOS counterpart in terms of energy consumption., Computer Engineering, Quantum & Computer Engineering

The presence of a permanent electric dipole moment in an elementary particle implies Charge-Parity symmetry violation and thus could help explain the matter-antimatter asymmetry observed in our universe. Within the context of the Standard Model, the electric dipole moment of elementary particles is extremely small. However, many Standard Model extensions such as supersymmetry predict large electric dipole moments. Recently, the muon electric dipole moment has become a topic of particular interest due to the tensions in the magnetic anomaly of the muon and the electron, and hints of lepton-flavor universality violation in B-meson decays. In this article, we discuss a dedicated effort at the Paul Scherrer Institute in Switzerland to search for the muon electric dipole moment using a 3-T compact solenoid storage ring and the frozen-spin technique. This technique could reach a sensitivity of $6\times10^{-23}$ $e\cdot$cm after a year of data taking with the $p=125$ MeV/$c$ muon beam at the Paul Scherrer Institute. This allows us to probe various Standard Model extensions not reachable by traditional searches using muon $g-2$ storage rings., Comment: 5 pages, 4 figures, prepared for the conference proceedings of the 22nd International Workshop on Neutrinos from Accelerators (NuFact 2021) in Cagliari, Italy

BackgroundMost patients are listed for liver transplant (LT) following extensive workup as outpatients ("conventional evaluation"). Some patients undergo urgent evaluation as inpatients after being transferred to a transplant center ("expedited evaluation"). We hypothesized that expedited patients would have inferior survival due to disease severity at the time of transplant and shorter workup time.MethodsPatients who underwent evaluation for LT at our institution between 2012 and 2016 were retrospectively reviewed. The expedited and conventional cohorts were defined as above. Living donor LT recipients, combined liver-kidney recipients, acute liver failure patients, and re-transplant patients were excluded. We compared patient characteristics and overall survival between patients who received a transplant following expedited evaluation and those who did not, and between LT recipients based on expedited or conventional evaluation.ResultsFive-hundred and nine patients were included (110 expedited, 399 conventional). There was no difference in graft or patient survival at 1 year for expedited versus conventional LT recipients. In multivariable analysis of overall survival, only Donor Risk Index (HR 1.97, CI 1.04-3.73, P = .037, per unit increase) was associated with increased risk of death.ConclusionsPatients who underwent expedited evaluation for LT had significant demographic and clinical differences from patients who underwent conventional evaluation, but comparable post-transplant survival.

In this article, we propose an energy-efficient spin wave (SW)-based approximate 4:2 compressor including three- and five-input majority gates. We validate our proposal by means of micromagnetic simulations and assess and compare its performance with state-of-the-art SW 45-nm CMOS and spin-CMOS counterparts. The evaluation results indicate that the proposed compressor consumes 31.5% less energy than its accurate SW-design version. Furthermore, it has the same energy consumption and error rate as a directional coupler (DC)-based approximate compressor, but it exhibits a 3× shorter delay. In addition, it consumes 14% less energy while having a 17% lower average error rate than its approximate 45-nm CMOS counterpart. When compared with other emerging technologies, the proposed compressor outperforms the approximate spin-CMOS-based compressor by three orders of magnitude in terms of energy consumption while providing the same error rate. Finally, the proposed compressor requires the smallest chip real estate measured in terms of devices., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Computer Engineering, Quantum & Computer Engineering

By their very nature Spin Waves (SWs) enable the realization of energy efficient circuits, as they propagate and interfere within waveguides without consuming noticeable energy. However, SW computing can be even more energy efficient by taking advantage of the approximate computing paradigm as many applications, e.g., multimedia and social media, are error-tolerant. In this paper, we propose an ultra-low energy Approximate Full Adder (AFA) and an Approximate 2-bit inputs Multiplier (AMUL). AFA consists of one Majority gate whereas AMUL is built by means of 3 AND gates. We validate the correct functionality of our proposal by means of micromagnetic simulations and evaluate AFA's figures of merit against state-of-the-art accurate SW, 7nm CMOS, Spin Hall Effect (SHE), Domain Wall Motion (DWM), accurate and approximate 45nm CMOS, Magnetic Tunnel Junction (MTJ), and Spin-CMOS FA implementations. Our results indicate that AFA consumes 38% and 6% less energy than state-of-the-art accurate SW and 7nm CMOS FA implementations, respectively. Moreover, it saves 56% and 20% energy when compared with accurate and approximate 45nm CMOS counterparts, respectively. Furthermore, it provides 2 orders of magnitude energy reduction when compared with accurate SHE, accurate and approximate DWM, MTJ, and Spin-CMOS, counterparts. In addition, it achieves the same error rate as approximate 45nm CMOS and Spin-CMOS FAs whereas it exhibits 50% less error rate than the approximate DWM FA. Last but not least, it outperforms its contenders in terms of area by saving at least 29% chip real-estate. AMUL is evaluated and compared with state-of-the-art SW and 16nm CMOS accurate and approximate designs. The evaluation results indicate that AMUL energy consumption is at least 2.8x and 2.6x smaller than the one of state-of-the-art SW and 16nm CMOS accurate and approximate designs, respectively. AMUL has an error rate of 25%, whereas the approximate CMOS multiplier has an error rate of 38%, and requir, Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Computer Engineering, Quantum & Computer Engineering

By their very nature, Spin Waves (SWs) excited at the same frequency but different amplitudes, propagate through waveguides and interfere with each other at the expense of ultra-low energy consumption. In addition, all (part) of the SW energy can be moved from one waveguide to another by means of coupling effects. In this paper we make use of these SW features and introduce a novel non Boolean algebra based paradigm, which enables domain conversion free ultra-low energy consumption SW based computing. Subsequently, we leverage this computing paradigm by designing a non-binary spin wave adder, which we validate by means of micro-magnetic simulation. To get more inside on the proposed adder potential we assume a 2-bit adder implementation as discussion vehicle, evaluate its area, delay, and energy consumption, and compare it with conventional SW and 7 nm CMOS counterparts. The results indicate that our proposal diminishes the energy consumption by a factor of 3.14 × and 6 ×, when compared with the conventional SW and 7 nm CMOS functionally equivalent designs, respectively. Furthermore, the proposed non-binary adder implementation requires the least number of devices, which indicates its potential for small chip real-estate realizations., Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Computer Engineering, Quantum & Computer Engineering

Particle accelerators are complex facilities that produce large amounts of structured data and have clear optimization goals as well as precisely defined control requirements. As such they are naturally amenable to data-driven research methodologies. The data from sensors and monitors inside the accelerator form multivariate time series. With fast pre-emptive approaches being highly preferred in accelerator control and diagnostics, the application of data-driven time series forecasting methods is particularly promising. This review formulates the time series forecasting problem and summarizes existing models with applications in various scientific areas. Several current and future attempts in the field of particle accelerators are introduced. The application of time series forecasting to particle accelerators has shown encouraging results and the promise for broader use, and existing problems such as data consistency and compatibility have started to be addressed., Comment: 13 pages, 11 figures

This paper addresses the question: Can spintronic circuits based on Magnetic Tunnel Junction (MTJ) transducers outperform their state-of-the-art CMOS counterparts? To this end, we use the EPFL combinational benchmark sets, synthesize them in 7 nm CMOS and in MTJ-based spintronic technologies, and compare the two implementation methods in terms of Energy-Delay-Product (EDP). To fully utilize the technologies potential, CMOS and spintronic implementations are built upon standard Boolean and Majority Gates, respectively. For the spintronic circuits, we assumed that domain conversion (electric/magnetic to magnetic/electric) is performed by means of MTJs and the computation is accomplished by domain wall based majority gates, and considered two EDP estimation scenarios: (i) Uniform Benchmarking, which ignores the circuit's internal structure and only includes domain transducers power and delay contributions into the calculations, and (ii) Majority-Inverter-Graph Benchmarking, which also embeds the circuit structure, the associated critical path delay and energy consumption by DW propagation. Our results indicate that for the uniform case, the spintronic route is better suited for the implementation of complex circuits with few inputs and outputs. On the other hand, when the circuit structure is also considered via majority and inverter synthesis, our analysis clearly indicates that in order to match and eventually outperform CMOS performance, MTJ efficiency has to be improved by 3-4 orders of magnitude. While it is clear that for the time being the MTJ-based-spintronic way cannot compete with CMOS, further transducer developments may tip the balance, which, when combined with information non-volatility, may make spintronic implementation for certain applications that require a large number of calculations and have a rather limited amount of interaction with the environment., Comment: This work was supported by imec Industrial Affiliation Program on Exploratory Logic Devices. It has also received funding from the European Union Horizon Europe research and innovation programme within the project SPIDER under grant agreement No 101070417

We perform a scaling and performance portability study of the particle-in-cell scheme for plasma physics applications through a set of mini-apps we name "Alpine", which can make use of exascale computing capabilities. The mini-apps are based on Independent Parallel Particle Layer, a framework that is designed around performance portable and dimension independent particles and fields. We benchmark the simulations with varying parameters such as grid resolutions ($512^3$ to $2048^3$) and number of simulation particles ($10^9$ to $10^{11}$) with the following mini-apps: weak and strong Landau damping, bump-on-tail and two-stream instabilities, and the dynamics of an electron bunch in a charge-neutral Penning trap. We show strong and weak scaling and analyze the performance of different components on several pre-exascale architectures such as Piz-Daint, Cori, Summit and Perlmutter. While the scaling and portability study helps identify the performance critical components of the particle-in-cell scheme in the current state-of-the-art computing architectures, the mini-apps by themselves can be used to develop new algorithms and optimize their high performance implementations targeting exascale architectures.

We derive an analytical model for the power transfer in a magnetoelectric film bulk acoustic resonator consisting of a piezoelectric--magnetostrictive bilayer. The model describes the dynamic magnetostrictive influence on the elastodynamics via an effective frequency-dependent stiffness constant. This allows for the calculation of both the magnetic and elastic power absorption in the resonator as well as of its energy efficiency when such a resonator is considered as a magnetic transducer. The model is then applied to example systems consisting of piezoelectric ScAlN and magnetostrictive CoFeB, Ni, or Terfenol-D layers., Comment: 39 pages, 9 figures. This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 801055 "Spin Wave Computing for Ultimately-Scaled Hybrid Low-Power Electronics" - CHIRON

© 2021 National Academy of Sciences. All rights reserved. In mammalian cells, nutrients and growth factors signal through an array of upstream proteins to regulate the mTORC1 growth control pathway. Because the full complement of these proteins has not been systematically identified, we developed a FACS-based CRISPR-Cas9 genetic screening strategy to pinpoint genes that regulate mTORC1 activity. Along with almost all known positive components of the mTORC1 pathway, we identified many genes that impact mTORC1 activity, including DCAF7, CSNK2B, SRSF2, IRS4, CCDC43, and HSD17B10. Using the genome-wide screening data, we generated a focused sublibrary containing single guide RNAs (sgRNAs) targeting hundreds of genes and carried out epistasis screens in cells lacking nutrient- and stress-responsive mTORC1 modulators, including GATOR1, AMPK, GCN2, and ATF4. From these data, we pinpointed mitochondrial function as a particularly important input into mTORC1 signaling. While it is well appreciated that mitochondria signal to mTORC1, the mechanisms are not completely clear. We find that the kinases AMPK and HRI signal, with varying kinetics, mitochondrial distress to mTORC1, and that HRI acts through the ATF4-dependent up-regulation of both Sestrin2 and Redd1. Loss of both AMPK and HRI is sufficient to render mTORC1 signaling largely resistant to mitochondrial dysfunction induced by the ATP synthase inhibitor oligomycin as well as the electron transport chain inhibitors piericidin and antimycin. Taken together, our data reveal a catalog of genes that impact the mTORC1 pathway and clarify the multifaceted ways in which mTORC1 senses mitochondrial dysfunction.

Abstract There is great need for high intensity proton beams from compact particle accelerators in particle physics, medical isotope production, and materials- and energy-research. To address this need, we present, for the first time, a design for a compact isochronous cyclotron that will be able to deliver 10 mA of 60 MeV protons—an order of magnitude higher than on-market compact cyclotrons and a factor four higher than research machines. A key breakthrough is that vortex motion is incorporated in the design of a cyclotron, leading to clean extraction. Beam losses on the septa of the electrostatic extraction channels stay below 120 W (40% below the required safety limit), while maintaining good beam quality. We present a set of highly accurate particle-in-cell simulations, and an uncertainty quantification of select beam input parameters using machine learning, showing the robustness of the design. This design can be utilized for beams for experiments in particle and nuclear physics, materials science and medical physics as well as for industrial applications.

We present a novel machine learning-based approach to generate fast-executing virtual radiofrequency quadrupole (RFQ) particle accelerators using surrogate modelling. These could potentially be used as on-line feedback tools during beam commissioning and operation, and to optimize the RFQ beam dynamics design prior to construction. Since surrogate models execute orders of magnitude faster than corresponding physics beam dynamics simulations using standard tools like PARMTEQM and RFQGen, the computational complexity of the multi-objective optimization problem reduces significantly. Ultimately, this presents a computationally inexpensive and time efficient method to perform sensitivity studies and an optimization of the crucial RFQ beam output parameters like transmission and emittances. Two different methods of surrogate model creation (polynomial chaos expansion and neural networks) are discussed and the achieved model accuracy is evaluated for different study cases with gradually increasing complexity, ranging from a simple FODO cell example to the full RFQ optimization. We find that variations of the beam input Twiss parameters can be reproduced well. The prediction of the beam with respect to hardware changes, e.g., the electrode modulation, are challenging on the other hand. We discuss possible reasons for that and elucidate nevertheless existing benefits of the applied method to RFQ beam dynamics design.

IsoDAR@Yemilab is a novel isotope-decay-at-rest experiment that has preliminary approval to run at the Yemi underground laboratory (Yemilab) in Jeongseon-gun, South Korea. In this technical report, we describe in detail the considerations for installing this compact particle accelerator and neutrino target system at the Yemilab underground facility. Specifically, we describe the caverns being prepared for IsoDAR, and address installation, hielding, and utilities requirements. To give context and for completeness, we also briefly describe the physics opportunities of the IsoDAR neutrino source when paired with the Liquid Scintillator Counter (LSC) at Yemilab, and review the technical design of the neutrino source., Comment: Under review at JINST. Condensed article version of full Conceptual Design Report (arXiv:2110.10635)

The search for a permanent electric dipole moment (EDM) of the muon is an excellent probe for physics beyond the Standard Model of particle physics. We propose the first dedicated muon EDM search employing the frozen-spin technique at the Paul Scherrer Institute (PSI), Switzerland, with a sensitivity of $6 \times 10^{-23}~e\!\cdot\!\mathrm{cm}$, improving the current best limit set by the E821 experiment at Brookhaven National Laboratory by more than three orders of magnitude. In preparation for a high precision experiment to measure the muon EDM, several R&D studies have been performed at PSI: the characterisation of a possible beamline to host the experiment for the muon beam injection study and the measurement of the multiple Coulomb scattering of positrons in potential detector materials at low momenta for the positron tracking scheme development. This paper discusses experimental concepts and the current status of the muEDM experiment at PSI., Comment: 5 pages, 3 figures, prepared for the conference proceedings of the 24th International Spin Symposium (SPIN2021) in Matsue, Japan. Minor modifications to match accepted version

Discusses a research project on the Tuskegee Airmen conducted by at-risk students at the Central Alternative High School (Dubuque, Iowa). These students interacted and corresponded with World War II veterans and composed a book on these men and women. Includes information about the Tuskegee Airmen's response to a questionnaire. (CMK)

Early prediction of whether a liver allograft will be utilized for transplantation may allow better resource deployment during donor management and improve organ allocation. The national donor management goals (DMG) registry contains critical care data collected during donor management. We developed a machine learning model to predict transplantation of a liver graft based on data from the DMG registry.MethodsSeveral machine learning classifiers were trained to predict transplantation of a liver graft. We utilized 127 variables available in the DMG dataset. We included data from potential deceased organ donors between April 2012 and January 2019. The outcome was defined as liver recovery for transplantation in the operating room. The prediction was made based on data available 12-18 h after the time of authorization for transplantation. The data were randomly separated into training (60%), validation (20%), and test sets (20%). We compared the performance of our models to the Liver Discard Risk Index.ResultsOf 13 629 donors in the dataset, 9255 (68%) livers were recovered and transplanted, 1519 recovered but used for research or discarded, 2855 were not recovered. The optimized gradient boosting machine classifier achieved an area under the curve of the receiver operator characteristic of 0.84 on the test set, outperforming all other classifiers.ConclusionsThis model predicts successful liver recovery for transplantation in the operating room, using data available early during donor management. It performs favorably when compared to existing models. It may provide real-time decision support during organ donor management and transplant logistics.

Electrical four-terminal sensing at (sub-)micrometer scales enables the characterization of key electromagnetic properties within the semiconductor industry, including materials' resistivity, Hall mobility/carrier density, and magnetoresistance. However, as devices' critical dimensions continue to shrink, significant over/underestimation of properties due to a by-product Joule heating of the probed volume becomes increasingly common. Here, we demonstrate how self-heating effects can be quantified and compensated for via 3ω signals to yield zero-current transfer resistance. Under further assumptions, these signals can be used to characterize selected thermal properties of the probed volume, such as the temperature coefficient of resistance and/or the Seebeck coefficient.

Background: Scoring systems have been proposed to select donation after circulatory death (DCD) donors and recipients for liver transplantation (LT). We hypothesized that complex scoring systems derived in large datasets might not predict outcomes locally. Methods: Based on 1-year DCD-LT graft survival predictors in multivariate logistic regression models, we designed, validated, and compared a simple index using the University of California, San Francisco (UCSF) cohort (n = 136) and a universal-comprehensive (UC)-DCD score using the United Network for Organ Sharing (UNOS) cohort (n = 5,792) to previously published DCD scoring systems. Results: The total warm ischemia time (WIT)-index included donor WIT (dWIT) and hepatectomy time (dHep). The UC-DCD score included dWIT, dHep, recipient on mechanical ventilation, transjugular-intrahepatic-portosystemic-shunt, cause of liver disease, model for end-stage liver disease, body mass index, donor/recipient age, and cold ischemia time. In the UNOS cohort, the UC-score outperformed all previously published scores in predicting DCD-LT graft survival (AUC: 0.635 vs. ≤0.562). In the UCSF cohort, the total WIT index successfully stratified survival and biliary complications, whereas other scores did not. Conclusion: DCD risk scores generated in large cohorts provide general guidance for safe recipient/donor selection, but they must be tailored based on non-/partially-modifiable local circumstances to expand DCD utilization.

Magnonics is a budding research field in nanomagnetism and nanoscience that addresses the use of spin waves (magnons) to transmit, store, and process information. The rapid advancements of this field during last one decade in terms of upsurge in research papers, review articles, citations, proposals of devices as well as introduction of new sub-topics prompted us to present the first roadmap on magnonics. This is a collection of 22 sections written by leading experts in this field who review and discuss the current status besides presenting their vision of future perspectives. Today, the principal challenges in applied magnonics are the excitation of sub-100 nm wavelength magnons, their manipulation on the nanoscale and the creation of sub-micrometre devices using low-Gilbert damping magnetic materials and its interconnections to standard electronics. To this end, magnonics offers lower energy consumption, easier integrability and compatibility with CMOS structure, reprogrammability, shorter wavelength, smaller device features, anisotropic properties, negative group velocity, non-reciprocity and efficient tunability by various external stimuli to name a few. Hence, despite being a young research field, magnonics has come a long way since its early inception. This roadmap asserts a milestone for future emerging research directions in magnonics, and hopefully, it will inspire a series of exciting new articles on the same topic in the coming years., Computer Engineering

By their very nature, Spin Waves (SWs) consume ultra-low amounts of energy, which makes them suitable for ultra-low energy consumption applications. In addition, a compressor can be utilized to further reduce the energy consumption and enhance the speed of a multiplier. Therefore, we propose a novel energy efficient SW based 4-2 compressor consisting of 4 XOR gates and 2 Majority gates. The proposed compressor is validated by means of micromagnetic simulations and compared with the state-of-the-art SW, 22 nm CMOS, Magnetic Tunnel Junction (MTJ), Domain Wall Motion (DWM), and Spin-CMOS technologies. The performance evaluation shows that the proposed compressor consumes 2.5x less and 1.25× less energy than the 22 nm CMOS and the conventional SW compressor, respectively, whereas it consumes at least 3 orders of magnitude less energy than the MTJ, DWM, and Spin-CMOS designs. Furthermore, the compressor achieves the smallest chip real-estate. In summary, the performance evaluation of our proposed compressor shows that the SW technology has the potential to progress the state-of-the-art circuit design in terms of energy consumption and scalability., Accepted author manuscript, Computer Engineering, Quantum & Computer Engineering

Having multi-output logic gates saves much energy because the same structure can be used to feed multiple inputs of next stage gates simultaneously. This paper proposes novel triangle shape fanout of 2 spin wave Majority and XOR gates; the Majority gate is achieved by phase detection, whereas the XOR gate is achieved by threshold detection. The proposed logic gates are validated by means of micromagnetic simulations. Furthermore, the energy and delay are estimated for the proposed structures and compared with the state-of-the-art spin wave, and 16 nm and 7 nm CMOS logic gates. The results demonstrate that the proposed structures provide energy reduction of 25%–50% in comparison to the other 2-output spin-wave devices while having the same delay, and energy reduction of 43x-0.8x when compared to the 16 nm and 7 nm CMOS counterparts while having delay overhead of 11x-40x., Computer Engineering, Quantum & Computer Engineering

Spin Waves (SWs) propagate through magnetic waveguides and interfere with each other without consuming noticeable energy, which opens the road to new ultra-low energy circuit designs. In this paper we build upon SW features and propose a novel energy efficient Full Adder (FA) design consisting of 1 Majority and 2 XOR gates, which outputs Sum and Carry − out are generated by means of threshold and phase detection, respectively. We validate our proposal by means of MuMax3 micromagnetic simulations and we evaluate and compare its performance with state-of-the-art SW, 22 nm CMOS, Magnetic Tunnel Junction (MTJ), Spin Hall Effect (SHE), Domain Wall Motion (DWM), and Spin-CMOS implementations. Our evaluation indicates that the proposed SW FA consumes 22.5% and 43% less energy than the direct SW gate based and 22 nm CMOS counterparts, respectively. Moreover it exhibits a more than 3 orders of magnitude smaller energy consumption when compared with state-of-the-art MTJ, SHE, DWM, and Spin-CMOS based FAs, and outperforms its contenders in terms of area by requiring at least 22% less chip real-estate., Computer Engineering, Quantum & Computer Engineering

By their very nature, spin waves (SWs) with different frequencies can propagate through the same waveguide, while mostly interfering with their own species. Therefore, more SW encoded data sets can coexist, propagate, and interact in parallel, which opens the road toward hardware replication-free parallel data processing. In this article, we take advantage of these features and propose a novel data parallel SW-based computing approach. To explain and validate the proposed concept, byte-wide 2-input XOR and 3-input majority gates are implemented and validated by means of Object-Oriented MicroMagnetic Framework (OOMMF) simulations. Furthermore, we introduce an optimization algorithm meant to minimize the area overhead associated with multifrequency operation and demonstrate that it diminishes the byte-wide gate area by 30% and 41% for XOR and majority implementations, respectively. To get inside on the practical implications of our proposal, we compare the byte-wide gates with conventional functionally equivalent scalar SW gate-based implementations in terms of area, delay, and power consumption. Our results indicate that the area optimized 8-bit 2-input XOR and 3-input majority gates require 4.47x and 4.16x less area, respectively, at the expense of 5% and 7% delay increase, respectively, without inducing any power consumption overhead. Finally, we discuss factors that are limiting the currently achievable parallelism to 8 for phase-based gate output detection and demonstrate by means of OOMMF simulations that this can be increased 16 for threshold-based detection-based gates., Computer Engineering, Quantum & Computer Engineering

By their very nature, voltage/current excited Spin Waves (SWs) propagate through waveguides without consuming noticeable power. If SW excitation is performed by the continuous application of voltages/currents to the input, which is usually the case, the overall energy consumption is determined by the transducer power and the circuit critical path delay, which leads to high energy consumption because of SWs slowness. However, if transducers are operated in pulses the energy becomes circuit delay independent and it is mainly determined by the transducer power and delay, thus pulse operation should be targeted. In this paper, we utilize a 3-input Majority gate (MAJ) to investigate the Continuous Mode Operation (CMO), and Pulse Mode Operation (PMO). Moreover, we validate CMO and PMO 3-input Majority gate by means of micromagnetic simulations. Furthermore, we evaluate and compare the CMO and PMO Majority gate implementations in term of energy. The results indicate that PMO diminishes MAJ gate energy consumption by a factor of 18. In addition, we describe how PMO can open the road towards the utilization of the Wave Pipelining (WP) concept in SW circuits. We validate the WP concept by means of micromagnetic simulations and we evaluate its implications in term of throughput. Our evaluation indicates that for a circuit formed by four cascaded MAJ gates WP increases the throughput by 3.6x., Computer Engineering, Quantum & Computer Engineering

The key enabling factor for Spin Wave (SW) technology utilization for building ultra low power circuits is the ability to energy efficiently cascade SW basic computation blocks. SW Majority gates, which constitute a universal gate set for this paradigm, operating on phase encoded data are not input output coherent in terms of SW amplitude. Thus, their cascading requires information representation conversion from SW to voltage and back, which is by no means energy effective. In this paper, a novel conversion free SW gate cascading scheme is proposed that achieves SW amplitude normalization by means of a directional coupler. After introducing the normalization concept, we utilize it in the implementation of three simple circuits and, to demonstrate its bigger scale potential, of a 2-bit inputs SW multiplier. The proposed structures are validated by means of the Object Oriented Micromagnetic Framework (OOMMF) and GPU-accelerated Micromagnetics (MuMax3). Furthermore, we assess the normalization induced energy overhead and demonstrate that the proposed approach consumes 1.25 times to 1.5 times less energy when compared with the transducers based conventional counterpart. Finally, we introduce a normalization based SW 2-bit inputs multiplier design and compare it with functionally equivalent SW transducer based and 16nm CMOS designs. Our evaluation indicates that the proposed approach provided 1.34 times and 6.25 times energy reductions when compared with the conventional approach and 16nm CMOS counterpart, respectively, which demonstrates that our proposal is energy effective and opens the road towards the full utilization of the SW paradigm potential and the development of SW only circuits., Computer Engineering, Quantum & Computer Engineering

Bestseller, Blockbuster, Top 100 - Listen und Rankings sind zentrale Ordnungs- und Wissensstrukturen der Populärkultur. Auf Internetplattformen und in Sozialen Medien machen sie populärkulturelles Wissen sichtbar, verfügbar und tauschbar. Der Autor geht der flüchtigen und heterogenen Wissenskultur dieser Taxonomien des Populären nach und zeigt: Sie arrangieren und strukturieren als mediale Formen populärkulturelle Produkte und deren Rezeption. Sie bieten ebenso kommunikative und mediale Anschlusspunkte für Subjektivierungen und soziale Formationen., Bestsellers, blockbusters, the Top 100 - lists and rankings arrange and structure pop-cultural knowledge. The author explores this fleeting and heterogenous knowledge culture.

Magnonics is a rather young physics research field in nanomagnetism and nanoscience that addresses the use of spin waves (magnons) to transmit, store, and process information. After several papers and review articles published in the last decade, with a steadily increase in the number of citations, we are presenting the first Roadmap on Magnonics. This a collection of 22 sections written by leading experts in this field who review and discuss the current status but also present their vision of future perspectives. Today, the principal challenges in applied magnonics are the excitation of sub-100 nm wavelength magnons, their manipulation on the nanoscale and the creation of sub-micrometre devices using low-Gilbert damping magnetic materials and the interconnections to standard electronics. In this respect, magnonics offers lower energy consumption, easier integrability and compatibility with CMOS structure, reprogrammability, shorter wavelength, smaller device features, anisotropic properties, negative group velocity, non-reciprocity and efficient tunability by various external stimuli to name a few. Hence, despite being a young research field, magnonics has come a long way since its early inception. This Roadmap represents a milestone for future emerging research directions in magnonics and hopefully it will be followed by a series of articles on the same topic.

We derive a lumped circuit model for inductive antenna spin-wave transducers in the vicinity of a ferromagnetic medium. The model considers the antenna's Ohmic resistance, its inductance, as well as the additional inductance due to the excitation of ferromagnetic resonance or spin waves in the ferromagnetic medium. As an example, the additional inductance is discussed for a wire antenna on top of a ferromagnetic waveguide, a structure that is characteristic for many magnonic devices and experiments. The model is used to assess the scaling properties and the energy efficiency of inductive antennas. Issues related to scaling antenna transducers to the nanoscale and possible solutions are also addressed., Comment: This project has received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 801055 "Spin Wave Computing for Ultimately-Scaled Hybrid Low-Power Electronics" CHIRON

Cancer is a multifactorial disease with increasing incidence. There are more than 100 different cancer types, defined by location, cell of origin, and genomic alterations that influence oncogenesis and therapeutic response. This heterogeneity between tumors of different patients and also the heterogeneity within the same patient’s tumor pose an enormous challenge to cancer treatment. In this review, we explore tumor heterogeneity on the longitudinal and the latitudinal axis, reviewing current and future approaches to study this heterogeneity and their potential to support oncologists in tailoring a patient’s treatment regimen. We highlight how the ideal of precision oncology is reaching far beyond the knowledge of genetic variants to inform clinical practice and discuss the technologies and strategies already available to improve our understanding and management of heterogeneity in cancer treatment. We will focus on integrating multi-omics technologies with suitable in vitro models and their proficiency in mimicking endogenous tumor heterogeneity.

© 2021 National Academy of Sciences. All rights reserved. In mammalian cells, nutrients and growth factors signal through an array of upstream proteins to regulate the mTORC1 growth control pathway. Because the full complement of these proteins has not been systematically identified, we developed a FACS-based CRISPR-Cas9 genetic screening strategy to pinpoint genes that regulate mTORC1 activity. Along with almost all known positive components of the mTORC1 pathway, we identified many genes that impact mTORC1 activity, including DCAF7, CSNK2B, SRSF2, IRS4, CCDC43, and HSD17B10. Using the genome-wide screening data, we generated a focused sublibrary containing single guide RNAs (sgRNAs) targeting hundreds of genes and carried out epistasis screens in cells lacking nutrient- and stress-responsive mTORC1 modulators, including GATOR1, AMPK, GCN2, and ATF4. From these data, we pinpointed mitochondrial function as a particularly important input into mTORC1 signaling. While it is well appreciated that mitochondria signal to mTORC1, the mechanisms are not completely clear. We find that the kinases AMPK and HRI signal, with varying kinetics, mitochondrial distress to mTORC1, and that HRI acts through the ATF4-dependent up-regulation of both Sestrin2 and Redd1. Loss of both AMPK and HRI is sufficient to render mTORC1 signaling largely resistant to mitochondrial dysfunction induced by the ATP synthase inhibitor oligomycin as well as the electron transport chain inhibitors piericidin and antimycin. Taken together, our data reveal a catalog of genes that impact the mTORC1 pathway and clarify the multifaceted ways in which mTORC1 senses mitochondrial dysfunction.

© 2020, The Author(s), under exclusive licence to Springer Nature Limited. Dozens of genes contribute to the wide variation in human pigmentation. Many of these genes encode proteins that localize to the melanosome—the organelle, related to the lysosome, that synthesizes pigment—but have unclear functions1,2. Here we describe MelanoIP, a method for rapidly isolating melanosomes and profiling their labile metabolite contents. We use this method to study MFSD12, a transmembrane protein of unknown molecular function that, when suppressed, causes darker pigmentation in mice and humans3,4. We find that MFSD12 is required to maintain normal levels of cystine—the oxidized dimer of cysteine—in melanosomes, and to produce cysteinyldopas, the precursors of pheomelanin synthesis made in melanosomes via cysteine oxidation5,6. Tracing and biochemical analyses show that MFSD12 is necessary for the import of cysteine into melanosomes and, in non-pigmented cells, lysosomes. Indeed, loss of MFSD12 reduced the accumulation of cystine in lysosomes of fibroblasts from patients with cystinosis, a lysosomal-storage disease caused by inactivation of the lysosomal cystine exporter cystinosin7–9. Thus, MFSD12 is an essential component of the cysteine importer for melanosomes and lysosomes.

Since its formulation in the late 1940s, the Feynman-Kac formula has proven to be an effective tool for both theoretical reformulations and practical simulations of differential equations. The link it establishes between such equations and stochastic processes can be exploited to develop Monte Carlo sampling methods that are effective, especially in high dimensions. There exist many techniques of improving standard Monte Carlo sampling methods, a relatively new development being the so-called Multilevel Monte Carlo method. This paper investigates the applicability of multilevel ideas to the stochastic representation of partial differential equations by the Feynman-Kac formula, using the Walk on Spheres algorithm to generate the required random paths. We focus on the Laplace equation, the simplest elliptic PDE, while mentioning some extension possibilities.

The beam interruptions (interlocks) of particle accelerators, despite being necessary safety measures, lead to abrupt operational changes and a substantial loss of beam time. A novel time series classification approach is applied to decrease beam time loss in the High Intensity Proton Accelerator complex by forecasting interlock events. The forecasting is performed through binary classification of windows of multivariate time series. The time series are transformed into Recurrence Plots which are then classified by a Convolutional Neural Network, which not only captures the inner structure of the time series but also utilizes the advances of image classification techniques. Our best performing interlock-to-stable classifier reaches an Area under the ROC Curve value of $0.71 \pm 0.01$ compared to $0.65 \pm 0.01$ of a Random Forest model, and it can potentially reduce the beam time loss by $0.5 \pm 0.2$ seconds per interlock.