Operational Space Research Articles

Protocol for nearly deterministic parity projection on two photonic qubits

Photonic parity projection plays an important role in photonic quantum information processing. Nondestructive parity projections normally require high-fidelity controlled-Z gates between photonic and matter qubits, which can be experimentally demanding. In this paper, we propose a nearly deterministic parity projection protocol on two photonic qubits which only requires stable matter-photon controlled-phase gates. We also demonstrate that our protocol can tolerate moderate Gaussian phase errors in the controlled-phase gates as well as Pauli errors on the matter qubits. The fact that our protocol does not require perfect controlled-Z gates makes it more amenable to experimental implementation. Although we focus on photonic qubits, our protocol can be applied to any physical system or circuit with imperfect controlled-Z gates. Our protocol also provides a new optimization space for parity projection operations on various physical platforms, which is potentially beneficial for achieving high-fidelity parity projection operations. Published by the American Physical Society 2024

Boundedness of Metaplectic Operators Within $$L^p$$ Spaces, Applications to Pseudodifferential Calculus, and Time–Frequency Representations

AbstractHausdorff–Young’s inequality establishes the boundedness of the Fourier transform from $$L^p$$ L p to $$L^q$$ L q spaces for $$1\le p\le 2$$ 1 ≤ p ≤ 2 and $$q=p'$$ q = p ′ , where $$p'$$ p ′ denotes the Lebesgue-conjugate exponent of p. This paper extends this classical result by characterizing the $$L^p-L^q$$ L p - L q boundedness of metaplectic operators, which play a significant role in harmonic analysis. We demonstrate that metaplectic operators are bounded on Lebesgue spaces if and only if their symplectic projection is either free or lower block triangular. As a byproduct, we identify metaplectic operators that serve as homeomorphisms of $$L^p$$ L p spaces. To achieve this, we leverage a parametrization of the symplectic group by Dopico and Johnson. We use our findings to provide boundedness results within $$L^p$$ L p spaces for pseudodifferential operators with symbols in Lebesgue spaces, and quantized by means of metaplectic operators. These quantizations consists of shift-invertible metaplectic Wigner distributions, which are essential to measure local phase-space concentration of signals. Using the factorization by Dopico and Johnson, we infer a decomposition law for metaplectic operators on $$L^2({\mathbb {R}^{2d}})$$ L 2 ( R 2 d ) in terms of shift-invertible metaplectic operators, establish the density of shift-invertible symplectic matrices in $$\mathop {\mathrm {{Sp}}}\limits (2d,\mathbb {R})$$ Sp ( 2 d , R ) , and prove that the lack of shift-invertibility prevents metaplectic Wigner distributions to define the so-called modulation spaces $$M^p(\mathbb {R}^d)$$ M p ( R d ) .

ST40 electromagnetic predictive studies supported by machine learning applied to experimental database

Nuclear fusion is entering the era of power plant-scale devices, which are now undergoing extensive studies to support the design phase. Plasma disruptions pose a high risk to these classes of devices because of the large stored thermal and magnetic energy which might jeopardize machine integrity and availability. Therefore, disruptions within these devices must be virtually eliminated, and any disruptions which do happen must be highly mitigated. However, the characterisation, prediction and technology used to mitigate disruptions is still an area of active development. In this paper, the authors investigate the disruptions within ST40, with particular attention at the identification of causes and effects associated with disruptions, both from a physics basis and an engineering standpoint. This paper aims at presenting preliminary predictive analyses of ST40 plasma scenarios by exploiting Machine Learning techniques applied to an experimental database populated by plasma pulses executed during the ST40 2021–2022 experimental campaign. The database contains both disrupted and non-disrupted pulses. Using Machine Learning, common features within disruptions are automatically classified and identified, mapping the controllable operational space in terms of plasma displacement and variation of specific plasma internal parameters. The classification was validated by benchmarking the numerical reconstruction of the plasma dynamics with experimental data recovered from the plasma diagnostics. Subsequent Machine Learning analyses allowed the extrapolation of new disrupted plasma configurations for preliminary predictive simulations of the plasma column displacement. Thanks to the numerical simulations performed in MAXFEA environment, it is possible to investigate the plasma vertical displacement both during disrupted and regularly terminated plasma scenarios and to provide lessons to be learnt for the next ST40 experimental campaign and for the design of future ST devices.

A Planetary Boundary for Mineral, Metal, and Fossil Resource Extraction Rates: How Much Primary Materials Can a Circular Economy Extract?

Resource consumption is expected to further increase in the next decades. A circular economy could decrease the environmental impact of this resource consumption by minimizing the primary raw materials consumption and minimizing emissions that render materials inaccessible for further use. However, such a circular economy will still have primary raw material inflows, due to population growth, stock expansion, energy transition, and inevitable dissipation. The potential magnitude of such primary raw material inflows in a circular economy remains unclear. To address this uncertainty, the planetary boundary framework, which defines absolute limits on resource and emission flows, could be utilized. Although this framework incorporates aspects of biomass, water, and land use, mineral, metal, and fossil resources are not included. This study provides a principle for a planetary boundary for these three resources, based on the net accessibility rate and an allocated share of the accessible resource stock in the ecosphere. Inter- and intragenerational equality are crucial for determining this allocated share and for quantifying a sustainable rate of resource extraction in (an economy transitioning toward) a circular economy. Next steps to operationalize this principle provide further guidance to determine the safe operating space for mineral, metal, and fossil resource extraction.

Operational Space Balancing Control Based on Integrated CoM Dynamics for Underactuated Triple Pendulum Robot

Operational Space Balancing Control Based on Integrated CoM Dynamics for Underactuated Triple Pendulum Robot

An efficient Protocol for Enhanced Flynet Communication in Presence of Partitioning

This paper presents an adaptive fault-tolerant resource allocation protocol tailored for FlyNet, a dynamic aerial network characterized by its mobility and three-dimensional operational space. Addressing the challenges of network partitioning and resource allocation in aerial networks, the proposed algorithm dynamically adjusts to the network's changing topology, ensuring consistent and efficient resource management. Through robust fault tolerance mechanisms, the protocol enhances FlyNet's reliability, maintaining seamless communication and optimal resource utilization even amid node mobility and disruptions. Simulation results demonstrate the algorithm's effectiveness in adapting to dynamic environments, maximizing resource utilization, and minimizing communication delays.

Quasi-continuous exhaust operational space

Abstract The IPED predictive pedestal code has been used to determine the critical gradients for the onset of 1) separatrix ballooning modes and 2) global peeling-ballooning modes as a function of plasma shaping. This results in a scaling of the onset threshold of separatrix ballooning modes as a function of elongation and triangularity αedge,crit = 0.64κ2.2(1+δ)0.9, while the critical gradient for global peeling-balloonig modes increases as αedge,crit 1.5. This implies that operational space for a ballooning unstable separatrix and stable peeling-ballooning modes exists at sufficiently high shaping. Applying a collisional broadnening based scaling of the separatrix gradients allows the critical separatrix density, required to drive the separatrix ballooning mode, to be derived from global plasma parameters for any operational scenario on any device. Evaluations for ASDEX Upgrade, JET, and the ITER 15 MA baseline plasma predict critical separatrix densities of 0.3-0.4 nGW for QCE access, making the QCE an attractive operational scenario for fusion devices.

Nanoparticle-based Biosensors for Detection of Heavy Metal Ions

Heavy metal pollution is one of the most serious environmental problems in the world. Many efforts have been made to develop biosensors for monitoring heavy metals in the environment. Development of nanoparticle-based biosensors is the most effective way to solve this problem. This review presents the latest technology of nanoparticle-based biosensors for environment monitoring to detect heavy metal ions, which are magnetic chitosan biosensor, colorimetric biosensor, and electrochemical biosensor. Magnetic chitosan biosensor acts as a nanoabsorbent, which can easily detect and extract poisonous heavy metal ions such as lead ions and copper ions. There are several methods to prepare the chitosan based on the nanoparticle, which are cross-linking, co-precipitation, multi-cyanoguanidine, and covalent binding method. In colorimetric biosensor, gold and silver nanoparticles are commonly used to detect the lead and mercury ions. In addition, this biosensor is very sensitive, fast and selective to detect metal ions based on the color change of the solution mixture. Meanwhile, electrochemical biosensor is widely used to detect heavy metal ions due to a simple and rapid process, easy, convenient and inexpensive. This biosensor is focused on the surface area, which leads to significant improvement in the performance of devices in terms of sensitivity. The wide surface area can affect the performance of the biosensor due to a limited space for operation of electrode. Therefore, reduced graphene oxide is a suitable material for making the electrochemical biosensor due to a wide surface area, good conductivity and high mechanical strength. In conclusion, these three technologies have their own advantages in making a very useful biosensor in the detection of heavy metal ions.

Extended Endoscopic Transsphenoidal Surgery with Total Cyst Wall Decollement for Suprasellar Cystic Craniopharyngioma: Case Report and Literature Review.

For most cystic craniopharyngiomas, intracapsular debulking is a good strategy to get a large operation space and protect vital structures. However, this surgical strategy may lead to the residual and recurrence of the tumor capsule wall. Therefore, there is an urgent need for a new surgical strategy without residual capsule walls for the removal of cystic craniopharyngiomas. We reviewed a 45-year-old male with vision loss and visual field defects, whose head MRI revealed a suprasellar cystic lesion. The patient underwent extended endoscopic transsphenoidal surgery. The surgical strategy of total cystic wall decollement was adopted, which was that the lesion surrounded by the capsule was completely separated from the surrounding tissue without destroying the capsule and maintaining the tension of the capsule. The lesion was totally resected and pathological findings confirmed the diagnosis of craniopharyngioma. After the operation, both the visual acuity and pituitary function were significantly improved. In addition, he suffered from transient diabetes insipidus, which was subsequently relieved. During the 33-month follow-up, there was no tumor recurrence. Compared with the traditional surgical strategy of intracapsular debulking, the surgical strategy of total cystic wall decollement has the advantages of less residual tumor capsules, low tumor recurrence rates, etc. Therefore, for specific cystic craniopharyngiomas, the surgical strategy of total cystic wall decollement may be an effective surgical strategy to reduce tumor recurrence.

Boundary Conditions for Organizations in the Anthropocene: A Review of the Planetary Boundaries Framework 10 Years On

AbstractWe systematically review business research concerning the planetary boundaries framework: A natural science framework that identifies nine Earth system boundaries that govern the safe operating space for humanity. Ten years after the introduction of the planetary boundaries in business studies, we pose two critical questions: How has the planetary boundaries concept been integrated into business studies and how has research on each of the nine boundaries advanced? Our review demonstrates growing scholarly interest in both questions. However, the topic remains niche with critical gaps, with most studies published in sustainability‐focused journals and only occasionally in mainstream journals. Theoretical development remains fragmented and of greater concern, a systems perspective is lacking in empirical studies: Most articles focus solely on one issue – climate change – and there is almost no cross‐analysis between boundaries. We contrast this with evidence that the planetary pressures of the Anthropocene are approaching dangerous thresholds and make the provocative assertion that planetary boundaries are not simply the foundation for specialized research on corporate sustainability but rather are the necessary boundary conditions for all business studies in the Anthropocene. We call for a transformation in how business scholars theorize, measure and engage.

Vector geographic data commutative encryption and watermarking algorithm based on prediction differences

Commutative encryption and watermarking (CEW) is a seamless integration of encryption and watermarking technologies, overcoming the limitations of single security protection methods that may fail to provide comprehensive data protection. It is a research hotspot in the field of geographic information security. However, constructing or selecting stable features for vector point data to apply CEW algorithms remains a challenging problem. To address this, this paper utilizes space-filling curves to organize discrete points into line or polygon types and proposes a CEW algorithm for vector data based on prediction differences. Specifically, feature points are used to fit curves, providing independent operational spaces for watermarking and encryption. The segmented fitted curves are arbitrarily flipped to achieve perceptual encryption, while watermarks are embedded in the differences between the fitted curves and the actual data. Experimental results demonstrate that the proposed algorithm effectively addresses the issue of existing algorithms being unsuitable for point data. In simulated real-world scenarios, the extracted watermark information achieved NC values above 0.75, indicating strong robustness. Under conditions using existing lossless algorithms, the watermark capacity of the proposed method is thousands of times higher than that of existing algorithms, and it exhibits excellent encryption security, providing a new perspective for further research on lossless CEW.

LiveWire: Horizontal Geoelectric Field Prediction With 1‐hr Lead‐Time Using Multi‐Fidelity Boosted Neural Networks

AbstractGeomagnetically Induced Currents (GICs) are electrical currents generated by rapid changes in the geomagnetic field during space weather events, posing risks to power grids and pipelines. Traditional approaches predict GICs indirectly by forecasting , the temporal variation of the geomagnetic field, which is proportional to the induced electric field via Faraday's law. However, current physics‐based models driven by in situ solar wind measurements offer only 10–30 min lead times, insufficient for power grid operators to take mitigating actions. Additionally, grid operators prefer direct forecasts of the geoelectric field, which directly influences GICs, rather than relying on intermediate predictions of that require complex and time‐consuming calculations. We present a novel approach that directly forecasts the horizontal geoelectric field with a one‐hour lead time, bypassing predictions. Our method combines magnetometer data, magnetotelluric survey data, and solar wind inputs into a new probabilistic multi‐fidelity machine learning technique, ProBoost, resulting in the LiveWire model. Using data from the Boulder Geomagnetic Observatory (BOU) since 2002, we trained and validated LiveWire on the top 50 geoelectric field events during geomagnetic storms. Our results show that LiveWire outperforms both a persistence forecast and the operational Space Weather Modeling Framework (SWMF) by at least 31% and 23%, respectively. This advancement in geoelectric field forecasting promises more accurate GIC predictions, helping enhance the resilience of critical infrastructure to space weather.

Current Status and Prospects of Robotic Pancreatic Surgery

Introduction Over the past two decades, the application of robotic surgery (RS) in pancreatic surgery has steadily increased. RS offers advantages such as reduced blood loss, less postoperative pain, and shorter hospital stays. However, there is still no consensus on its safety, efficacy, and learning curve in pancreatic diseases. This study aims to summarize the current state of RS in pancreatic surgery and to forecast its prospects. Method A literature search was conducted in PubMed using keywords including “robotic surgery”, “pancreatic surgery”, “minimally invasive surgery”, “open surgery” and “laparoscopic surgery”. Studies on robotic surgery in pancreatic surgery were collected, including research comparing robotic surgery with open or laparoscopic surgery. Results RS has been applied to various pancreatic surgeries, demonstrating good safety and feasibility. Compared to open or laparoscopic surgery, robotic pancreatic surgery (RPS) shows favorable short-term outcomes such as reduced blood loss, shorter hospital stays, and lower conversion rates, especially in surgeries with narrow operative spaces or complex anatomical structures. No significant differences were reported in postoperative complications or short-term mortality rates. RPS achieves comparable R0 resection rates, lymph node harvest numbers, and long-term outcomes. However, RPS also presents limitations, including a long learning curve, high surgical costs, a lack of dedicated instruments, and the absence of natural tactile feedback. Conclusion Robotic pancreatic surgery demonstrates favorable short-term and long-term outcomes, showing promising potential for application. Further multi-center randomized controlled trials are needed to determine its safety and efficacy conclusively.

Validation of prediction capability of operating space for plasma initiation in MAST-U

Abstract DYON is a plasma initiation modelling code that solves the differential equation system of the full circuit equations (plasma current, active coil currents and eddy currents in full passive structures) and 0D global energy and particle balance equations[1]. In order to test the capability of the full electromagnetic plasma initiation model to predict individual discharges in experiments and thus the operating space in the device, a dedicated experimental database was built in MAST-U by scanning the prefilled gas pressure p0 and the induced loop voltage Vloop . In the experimental operating space of p0 and Vloop the lower and the upper limits of p0 are determined by the plasma breakdown failure and the plasma burn-through failure, respectively. The lower limit of Vloop is determined by the plasma burn-through failure. By directly reading the control room data used in each discharge (i.e. currents in the solenoid, poloidal field coils, and toroidal field coils, p0 , and gas puffing rate), the full electromagnetic DYON consistently predicted the failed breakdown, failed burn-through, and successful plasma initiation discharges in the experimental database, demonstrating its capability to predict the operating space for inductive plasma initiation. The Paschen curve calculated with the effective connection length in MAST-U indicates a much higher p0 required for plasma breakdown than the experimental data, indicating that individual field line evaluation is necessary to calculate the quantitative requirements for Townsend breakdown. The demonstration in this paper shows that the full electromagnetic DYON could be a useful simulation tool to assess the feasibility of inductive plasma initiation and to optimise operating scenarios in future devices. [1] Hyun-Tae Kim 2022 Nuclear Fusion 62 126012

Impact of repetitive ELM transients on ITER divertor tungsten monoblock top surfaces

Abstract Owing to the high stored energy of ITER plasmas, the heat pulses due to uncontrolled Type I edge localized modes (ELMs) can be sufficient to melt the top surface of several poloidal rows of tungsten monoblocks in the divertor strike point regions. Coupled with the melt motion associated with tungsten in the strong tokamak magnetic fields, the resulting surface damage after even a comparatively small number of such repetitive transients may have a significant impact on long-term stationary power handling capability. The permissible numbers set important boundaries on operation and on the performance required from the plasma control system. Modelling is carried out with the recently updated MEMENTO melt dynamics code, which is tailored to tackle melt motion problems characterized by a vast spatio-temporal scale separation. The crucial role of coupling between surface deformation and shallow angle heat loading in aggravating melt damage is highlighted. As a consequence, the allowable operational space in terms of ELM-induced transient heat loads is history-dependent and once deformation has occurred, weaker heat loads, incapable of melting a pristine surface, can further extend the damage.

A safe operating space for the major rivers in the Bangladesh Delta

Abstract The contributions of water to all Sustainable Development Goals (SDGs) are critical to achieving SDGs in the context of climate change. This poses a major challenge as nearly 40% of the global population lives under water scarcity, including areas such as Bangladesh, which is one of the largest, most populous and climate-vulnerable deltas (Ganges–Brahmaputra–Meghna: GBM) in the world. Here, we aim (first attempt) to analyse the historical dynamics (spatial and temporal) of river flows in 10 major rivers and provide policy implications using a safe operating space (SOS) concept for the Bangladesh delta. In general, the space just before the unsustainable state is defined as an SOS, within which humanity can safely thrive and beyond which is dangerous to humanity. Time series analysis highlights that all seasonal river flow shows a decreasing trend in the last three decades except in the winter season. The hydrological alteration using range of variability approach confirms that the majority of the river flow has been altered high to severely including three major rivers (Ganges, Jamuna, and Old Brahmaputra) in the Bangladesh delta. Our findings show that four out of ten rivers (Ganges (dry season), Gorai, Halda and Old Brahmaputra) exceeded the SOS, with the rest of the six rivers given cautious status considering the hydrological alteration (moderate to severe) in the Bangladesh delta. Our assessment provides scientific evidence to inform science and policy related to transboundary water disputes and achieving SDGs in Bangladesh and South Asia.

Bi-level task planning strategy for blended-wing-body underwater gliders

ABSTRACT This study focuses on the task planning problem of the blended-wing-body underwater glider (BWBUG), which must autonomously navigate through a sequence of underwater visitation points while ensuring safety and economy. Firstly, the task planning problem of the BWBUG is analysed, with attention given to operational space and task requirements. Subsequently, a bi-level planning framework that incorporates both the bottom-level and top-level planners is proposed. The bottom-level planner optimises the glide path between any two visit points by considering safety and glide angle constraints, with the objective of minimising energy usage. The top-level planner focuses on the task constraints and optimises the global visitation path of the BWBUG to achieve the objective of global energy minimisation. Simulations demonstrate the effectiveness of the bi-level based task planning strategy proposed in this study. The solution algorithms are highly competitive, capable of planning rational global visitation paths for the BWBUG.

Hierarchical decision-making approach for the task planning of the BWBUG cluster with three-dimensional time-varying ocean currents

This study concerns the task planning problem for a Blended-Wing-Body Underwater Glider (BWBUG) cluster with three-dimensional, time-varying ocean currents. The objective is to achieve task allocation and three-dimensional glide path planning for the BWBUG cluster in a manner that ensures safety and cost-effectiveness. First, the task planning problem for the BWBUG cluster is analyzed, detailing the task requirements and operational space. Next, a hierarchical decision-making approach is proposed, which comprises an upstream planner and a downstream planner. The upstream planner aims to determine a feasible task space for the BWBUG cluster while satisfying task constraints. The downstream planner fully considers the impact of ocean currents on BWBUG movement, as well as the safety and kinematic constraints of BWBUGs. It optimizes the three-dimensional movement trajectories of each BWBUG with the objective of minimizing energy consumption. Inspired by the nest-seeking behavior of bees, a novel heuristic algorithm called the Bee Nesting Optimization Algorithm (BNOA) is proposed to solve both upstream and downstream planning problems. The results of the simulations demonstrate the efficacy of the hierarchical decision-making approach developed in this study. Additionally, the proposed BNOA is highly competitive, offering reasonable task allocations and optimal three-dimensional glide paths for the BWBUG cluster.

Study on the tensile properties of a novel modular splicing joint

The interconnection among module elements within a modular structure assumes a pivotal role in upholding structural integrity and stability. To address the challenges posed by existing inter-module connection joints, which necessitate operational space and may compromise the integrity of the module unit while impeding assembly efficiency, an innovative modular steel structure splicing joint is proposed. Through adjustments to the dimensions of the connection box and fastener components, four distinct spliced joints were established for axial tensile analysis. The subsequent evaluation included an examination of axial tensile capacity, strain distribution, and failure modes at critical points across various joints, providing insights into their tensile effectiveness. To comprehensively explore the influence of size parameters on tensile performance, a corresponding numerical model was developed for parametric analysis. Results indicate that tensile failure modes entail the extrication of the lower-end plate from the upper module column connection box and the cylindrical radius of the fastener. Notably, the protrusion radius of the fastener (R2), markedly influences the tensile bearing capacity of the spliced joints, with precedence over the lower end plate thickness (d0), cylinder radius (R1), sliding block thickness (d1), and limiting plate thickness (d2). The joint obviates the need for external operations to interlink module units, thereby augmenting the installation efficiency of the modular structure and mitigating complexities in design and the enigmatic transmission of forces within the self-locking joint.

Operational space robust impedance control of the redundant surgical robot for minimally invasive surgery.

The motion accuracy, compliance, and control smoothness for the surgical robot are of great importance to improve the safety of human-robot interaction. However, the end effector that interacts with soft tissue during surgery affects the dynamics of the robot. The control performance of the controller may be decreased if the changing dynamics are not identified and updated in time. This paper proposes a robust impedance controller for the redundant remote center of motion manipulator influenced by external disturbances, including external torque, uncertainties, and unmodeled terms in the dynamics. To achieve the desired impedance, a continuously switching sliding manifold is proposed. When the sliding manifold is driven to zero, the motion error will converge to a bounded region. This can overcome the adverse effects of external disturbances while guaranteeing motion accuracy and compliance. Chattering of the sliding mode control is alleviated through the formulated continuously switching sliding manifold and integrated nonlinear disturbance observer. Simulations and experiments demonstrate that the proposed controller has excellent motion accuracy, compliance, and control smoothness. This provides potential application prospects for the redundant surgical robot to guarantee safe human-robot interaction.