Small Time Research Articles

Tisserand-Leveraging Lambert Problem: Formulation, Solution, and Applications

Tisserand-leveraging transfers (TILTs) were proposed as techniques to achieve an endgame tour with small orbit insertion maneuvers and short flight times in low-energy regions of the planar, circular, restricted three-body problem. This paper presents a new formulation of TILTs with a framework similar to the classical Lambert problem. The developed algorithm searches for trajectories of TILTs with constraints on boundary values and time of flight by solving a one-dimensional root-finding problem. Compared to the traditional algorithm for TILTs, the developed algorithm enhances its generality by removing the restriction on the initial and final phases of the transfer. Additionally, the algorithm can achieve trajectory patching that includes TILTs without reoptimization and tour redesign based on the actual position of the spacecraft due to the Lambert-like input–output design. The algorithm uses existing neural network tools for fast and broad search in the solution space. Simulation results indicate that the algorithm can explicitly find TILT solutions and families satisfying boundary value constraints. Furthermore, the algorithm is applied to design a new endgame trajectory from Ganymede to Europa, demonstrating the potential of integrating the new algorithms with other trajectory design tools.

Iterative learning robust security predictive tracking control for small delay batch processes: Deception attacks on unreliable network channel

During the batch process, the need for security control is becoming increasingly urgent with the gradual penetration of network control technology. For small time delay batch processes subject to deception attacks, an iterative learning robust security predictive tracking control approach is developed. Reviewing previous studies for iterative learning control, the issue that the repetitive character of the batch process would mask the characteristics of deception attacks was not considered. Moreover, the gains of iterative learning control law are utilized offline, which makes large deviations for the system state as the operating time increases. This will lead to “excessive-input” conditions for control inputs, which means more consumption of energy and production resources. To address these challenges, we introduce robust security invariant sets to improve the robustness of the system by constraining the system state to be in a safe range. Also, the design of the iterative learning controller incorporates deception attack data for historical batches, which is continuously improved and optimized to withstand deception attacks. Meanwhile, by calculating stability conditions online, the real-time control law gain is obtained, which could make the control inputs adjusted online based on the real-time system’s dynamic characteristics, avoiding excessive inputs and improving the efficiency of energy and resource utilization. Additionally, the stability analysis proves that the system is input to state stability. Ultimately, simulation verifies the effectiveness and feasibility of the developed method.

Relationship between fatigue and quantitative electromyography findings in patients with myasthenia gravis

BackgroundFatigue is a common complaint among patients with myasthenia gravis (MG). In this study, we investigated the alterations in muscle morphology in patients with MG experiencing fatigue using quantitative electromyography (QEMG), and explored the relationship between electrophysiological findings and the severity of both fatigue and disease. MethodsWe performed QEMG of the biceps brachii muscle using the peak ratio method and multi-motor unit potential (MUP) analysis across three groups: 18 MG patients with fatigue, 34 MG patients without fatigue, and 33 healthy subjects. Stimulated single-fiber EMG was performed on the frontalis muscle. The severity of perceived fatigue and disease was subsequently assessed using the quantitative myasthenia gravis (QMG) score, the MG-activities of daily living (MG-ADL) profile, self-reported fatigue questionnaires, and handgrip strength measurements. ResultsThe QEMG study revealed a reduced mean MUP duration and size index (SI), in addition to an increased peak ratio in patients with MG (p < 0.05), which tended to be more pronounced in those experiencing fatigue. Compared to healthy subjects, MG patients with fatigue displayed a myopathic pattern characterised by a high peak ratio, short duration, and small-amplitude MUPs, without any increase in the number of phases or small time intervals. The mean peak ratio was positively correlated with the QMG, MG-ADL, and Fatigue Impact Scale total and physical subscores (p < 0.05). Further, MG patients with fatigue exhibited reduced maximum grip strength, which was positively correlated with the mean MUP duration, amplitude, SI, and thickness, and negatively correlated with the mean peak ratio (p < 0.05). No significant differences were observed in the jitter or block measurements (p > 0.05). ConclusionsThe present study investigated electrophysiological findings that were not considered or theorised in prior studies on patients with MG experiencing fatigue. The results of this study suggest that myopathic changes may be a critical pathophysiological component underlying the fatigue associated with MG.

Experimental setup for comprehensive study of non-stationary heat transfer in complex liquid media.

This paper presents a setup for studying non-stationary heat exchange in liquid media on a scale of small times and sizes at high heat flux densities created using a high-speed precision power controller. A platinum wire with a diameter of 20μm and a length from 0.5 to 1cm is used as a probe. The heating time ranged from 1 to 300ms, and the heat flux densities from 1 to 20 MW/m2 were achieved in the experiments. Strictly specified conditions for heat release in the probe are confirmed by maintaining a constant power in a series of pulses with an accuracy of 0.05%. Acquiring a primary electrical signal of thermograms is synchronized with high-speed video recording, allowing an accurate relationship between the applied thermal load and the mechanics of processes in the studied liquid. The setup capabilities were shown by comparing the boiling patterns of a simple substance, such as ethanol, and a solution with a lower critical solution temperature, a 30 vol.% solution of polypropylene glycol-425 in water, which have similar thermograms. As a result, a qualitative difference between the heating and boiling patterns observed using high-speed video and the presented setup fitting its purpose has been shown.

Gravitational waves from collapse of pressureless matter in the early universe

If an early matter phase of the Universe existed after inflation with the proper power spectrum, enhanced density perturbations can decouple from the Hubble flow, turn around and collapse. In contrast towhat happens in a radiation dominated Universe where pressure nullifies deviations from sphericity in these perturbations, in a matter dominated Universe, the lack of pressure although on the one hand facilitates the gravitational collapse, it allows small deviations from sphericity to grow substantially as the collapse takes place. The subsequent collapse is complicated: initially as non-spherical deviations grow, the collapsing cloud takes the form of a “Zel'dovich pancake”. After that, the more chaotic and nonlinear stage of violent relaxation begins where shells of the cloud cross and the matter is redistributed within a factor of a few of the free fall timescale, reaching a spherical virialized state. During the whole process, strong gravitational waves are emitted due to the anisotropy of the collapse andthe small time interval that the effect takes place. The emission of gravitational waves during the stage of the violent relaxation cannot be easily estimated with an analytical model. We perform an N-body simulation to capture the behaviour of matter during this stage in order to estimate the precise spectrum of gravitational waves produced in this scenario.

Estimates concerning the heat content for the Schrödinger operator related to a subordinate Brownian motion

In this paper, we study the heat content for the Schrödinger operator related to a subordinate Brownian motion and we also establish its small time asymptotic behavior for suitable potentials V. The case V=c1Ω for c>0 and Ω a Borel set of finite measure is investigated in detail.

Synchronization and limit cycles in a simple contagion model with time delays

We examine a system of N=2 coupled non-linear delay-differential equations representing financial market dynamics. In such time delay systems, coupled oscillations have been derived. We linearize the system for small time delays and study its collective dynamics. Using analytical and numerical solutions, we obtain the bifurcation diagrams and analyze the corresponding regions of amplitude death, phase locking, limit cycles and market synchronization in terms of the system frequency-like parameters and time delays. We further numerically explore higher order systems with N>2, and demonstrate that limit cycles can be maintained for coupled N−asset models with appropriate parameterization.

Energy consumption analysis and operating characteristics research on small time scale of variable refrigerant flow air conditioning systems in public buildings

In order to analyze the energy consumption and operation characteristics of the variable refrigerant flow (VRF) air-conditioning system on small time scale and put forward effective energy-saving suggestions, the VRF system operation experiments are carried out under different indoor set temperatures, different indoor unit opening quantities and different indoor set air velocities. This experiment studies the main influencing factors of energy consumption and operation of the VRF system, such as indoor temperature difference, indoor air velocity, outdoor environment temperature and so on. The results show that the rated power of indoor unit is linearly related to the energy consumption of the VRF system. The total active power changes greatly when the VRF starts and stops, and the outdoor ambient temperature changes. The indoor set air velocities have a great influence on the energy consumption and operation of the VRF system. The performance parameters increase first and then decrease with the increase of compressor frequency and load rate. When the load rate is 40 %∼60 %, the performance parameters can reach 3.2 ∼ 4.2.

Gastrointestinal Dysmotility, Autonomic Function and Small Intestinal Bacterial Overgrowth Among People with Well-Controlled HIV.

Gastrointestinal dysfunction, including microbiome changes and increased translocation across a compromised gastrointestinal barrier plays a role in the chronic inflammation experienced by people with HIV (PWH). It is unknown whether autonomic neuropathy (AN) may contribute to these mechanisms by altering gastrointestinal motility. This is a cross-sectional study of 100 PWH and 89 controls. All participants underwent assessment of gastrointestinal transit times using a wireless motility capsule (WMC). All PWH and a subset of controls also underwent: a standardized battery of autonomic function tests summarized as the Modified Composite Autonomic Severity Score (MCASS) and its adrenergic, cardiovagal and sudomotor sub-scores, breath testing for small intestinal bacterial overgrowth (SIBO), and the Patient Assessment of Upper Gastrointestinal Disorders Symptoms (PAGI-SYM) and Composite Autonomic Symptom Score 31 (COMPASS-31) questionnaires. PWH displayed shorter gastric emptying times (GET) and longer small bowel and colonic transit times (SBTT, CTT) compared to controls. Among PWH, GET was associated with PAGI-SYM score. The MCASS and its sudomotor sub-score (reflecting peripheral sympathetic function) were associated with SBTT but not GET or CTT. PWH with prolonged SBTT (>6h) were more likely to have SIBO. Gastrointestinal motility is altered in PWH. This study provides preliminary evidence that changes in autonomic function may influence SBTT in PWH and that prolonged SBTT may contribute to the development of SIBO. Future studies are needed to more fully elucidate the pathophysiologic links between HIV-associated AN, altered gastrointestinal motility, the gastrointestinal microbiome, chronic inflammation, and resulting morbidity and mortality among PWH.

Testing Rate-and-State Predictions of Aftershock Decay with Distance

Abstract We analyze aftershocks of the 2019 M 7.1 Ridgecrest mainshock and isolated M 5–6 mainshocks in southern California to test predictions made by the rate-and-state friction model of Dieterich (1994). Rate-and-state friction predicts that the seismicity rate after a stress step follows Omori decay, where the Omori c-value, which is the saturation in aftershock rate observed at small times, is larger for smaller stress steps. Put in the context of an aftershock sequence, this predicts that the Omori c-value will be systematically larger at greater distances from the mainshock. To our knowledge, this predicted effect has not been observed. In part this may be because the Omori c-value is difficult to measure because it often reflects short-term catalog incompleteness rather than a true saturation in aftershock rate. We explore the dependence of the Omori c-value on the distance to the mainshock by applying the “a-positive” method (van der Elst and Page, 2023). This method is insensitive to short-term aftershock incompleteness and allows resolution of the true aftershock rate deep into the mainshock coda. For aftershocks of the Ridgecrest mainshock and stacked M 5–6 mainshocks, we observe systematic differences in early aftershock rates, relative to mainshock distance, consistent with the predictions of rate-and-state friction. Furthermore, for the larger Ridgecrest dataset, we observe that aftershocks nearer to the mainshock start earlier, and we resolve a flattening of the Omori curve consistent with a larger Omori c-value for the farthest aftershocks, as predicted by Dieterich (1994).

Liraglutide and Colesevelam Changes Serum and Fecal Bile Acid Levels in a Randomized Trial with Patients with Bile Acid Diarrhea.

Both liraglutide and colesevelam improve bile acid diarrhea (BAD) symptoms. Colesevelam binds excess amounts of diarrhea-causing bile acids in the colon whereas the mode of action for liraglutide remains elusive. Here, we examined the impact of colesevelam and liraglutide treatment on the concentrations of bile acids in serum and feces and the fecal microbiota composition to better understand the two drugs' modes of action. Bile acid species were analyzed in serum and fecal samples from a randomized, double-blind, double-dummy trial at baseline and after three and six weeks of orally administered colesevelam (1,875 mg twice daily, n = 26) or subcutaneously administered liraglutide (uptitrated by weekly increments of 0.6 mg from 0.6 to 1.8 mg daily, n = 26) in patients with 75selenium-homotaurocholic acid test-verified, idiopathic, or post-cholecystectomy BAD. Fecal microbiota composition was analyzed by 16S rRNA gene amplicon sequencing at the same time points. Colesevelam increased the fecal concentrations of all bile acid species while it decreased serum concentrations of secondary bile acids. Liraglutide induced a small increase in serum unconjugated bile acid concentrations without affecting fecal bile acid concentrations. No changes in fecal microbiota composition were observed with either treatment. Colesevelam and liraglutide exhibit distinct effects on serum and fecal bile acid concentrations with colesevelam reducing serum concentrations of secondary bile acids and promoting fecal bile acid excretion while liraglutide enhances serum concentrations of unconjugated bile acids, potentially through deceleration of small intestinal transit time allowing more time for passive absorption of bile acids.

Escape of an active ring from an attractive surface: Behaving like a self-propelled Brownian particle.

Escape of active agents from metastable states is of great interest in statistical and biological physics. In this paper, we investigate the escape of a flexible active ring, composed of active Brownian particles, from a flat attractive surface using Brownian dynamics simulations. To systematically explore the effects of activity, persistence time, and the shape of attractive potentials, we calculate escape time τ_{e} and effective temperature T_{eff}. We observe two distinct escape mechanisms: Kramers-like thermal activation at small persistence times, where ln(τ_{e})∼1/(k_{B}T_{eff}), and the maximal force problem at large persistence time, where τ_{e} is determined by persistence time. The escape time explicitly depends on the shape of the potential barrier at high activity and large persistence time. Moreover, when the propulsion force is biased along the ring's contour, escape becomes more difficult and is primarily driven by thermal noise. Our findings highlight that, despite its intricate configuration, the active ring can be effectively modeled as a self-propelled Brownian particle when studying its escape from a smooth surface.

Spherical Logvinenko–Sereda–Kovrijkine type inequality and null-controllability of the heat equation on the sphere

It is shown that the restriction of a polynomial to a sphere satisfies a Logvinenko–Sereda–Kovrijkine type inequality (a specific type of uncertainty relation). This implies a spectral inequality for the Laplace–Beltrami operator, which, in turn, yields observability and null-controllability with explicit estimates on the control costs for the spherical heat equation that are sharp in the large and in the small time regime.

Active Inference and Reinforcement Learning: A Unified Inference on Continuous State and Action Spaces Under Partial Observability.

Reinforcement learning (RL) has garnered significant attention for developing decision-making agents that aim to maximize rewards, specified by an external supervisor, within fully observable environments. However, many real-world problems involve partial or noisy observations, where agents cannot access complete and accurate information about the environment. These problems are commonly formulated as partially observable Markov decision processes (POMDPs). Previous studies have tackled RL in POMDPs by either incorporating the memory of past actions and observations or by inferring the true state of the environment from observed data. Nevertheless, aggregating observations and actions over time becomes impractical in problems with large decision-making time horizons and high-dimensional spaces. Furthermore, inference-based RL approaches often require many environmental samples to perform well, as they focus solely on reward maximization and neglect uncertainty in the inferred state. Active inference (AIF) is a framework naturally formulated in POMDPs and directs agents to select actions by minimizing a function called expected free energy (EFE). This supplies reward-maximizing (or exploitative) behavior, as in RL, with information-seeking (or exploratory) behavior. Despite this exploratory behavior of AIF, its use is limited to problems with small time horizons and discrete spaces due to the computational challenges associated with EFE. In this article, we propose a unified principle that establishes a theoretical connection between AIF and RL, enabling seamless integration of these two approaches and overcoming their limitations in continuous space POMDP settings. We substantiate our findings with rigorous theoretical analysis, providing novel perspectives for using AIF in designing and implementing artificial agents. Experimental results demonstrate the superior learning capabilities of our method compared to other alternative RL approaches in solving partially observable tasks with continuous spaces. Notably, our approach harnesses information-seeking exploration, enabling it to effectively solve reward-free problems and rendering explicit task reward design by an external supervisor optional.

Effective quantum dynamics for magnetic fermions

We show how to derive an effective nonlinear dynamics, described by the Hartree-Fock equations, for fermionic quantum particles confined to a two-dimensional box and in presence of an external, uniform magnetic field. The derivation invokes the Dirac-Frenkel principle. We discuss the validity of this effective description with respect to the many-body Schr\"odinger dynamics for small times and for weak interactions, and also in regards to the number of particles.

The distribution amplitude of the ηc-meson at leading twist from lattice QCD

Distribution amplitudes are functions of non-perturbative matrix elements describing the hadronization of quarks and gluons. Thanks to factorization theorems, they can be used to compute the scattering amplitude of high-energy processes. Recently, new ideas have allowed their computation using lattice QCD, which should provide us with a general, fully relativistic determination. We present the first lattice calculation of the ηc-meson distribution amplitude at leading twist. Starting from the relevant matrix element in discrete Euclidean space on a set of Nf = 2 CLS ensembles, we explain the method to connect to continuum Minkowski spacetime. After addressing several sources of systematic uncertainty, we compare to Dyson-Schwinger and non-relativistic QCD determinations of this quantity. We find significant deviations between the latter and our result even at small Ioffe times.

Efficient BFGS quasi-Newton method for large deformation phase-field modeling of fracture in hyperelastic materials

The prediction of crack propagation in materials is a crucial problem in solid mechanics, with many practical applications ranging from structural integrity assessment to the design of advanced materials. The phase-field method has emerged as a powerful tool for modeling crack propagation in materials, due to its ability to accurately capture the propagation of cracks. However, current phase-field algorithms suffer from the elevated computational cost associated with the so-called staggered solution scheme, which requires extremely small time increments to advance the crack due to its inherent conditional stability. In this paper, we present, for the first time, a quantitative analysis detailing the numerical implementation and comparison of two common solution strategies for the coupled large-deformation solid-mechanics-phase-field problem, namely the quasi-Newton based Broyden–Fletcher–Goldfarb–Shanno algorithm (BFGS) and the full Newton based alternating minimization (or staggered) (AM/staggered) algorithm. We demonstrate that the BFGS algorithm is a more efficient and advantageous alternative to the traditional AM/staggered approach for solving coupled large-deformation solid-mechanics-phase-field problems. Our results highlight the potential of the quasi-Newton BFGS algorithm to significantly reduce the computational cost of predicting crack propagation in hyperelastic materials while maintaining the accuracy and robustness of the phase-field method.

A Space–Time Coding Array Sidelobe Optimization Method Combining Array Element Spatial Coding and Mismatched Filtering

Digital array radar (DAR) can fully realize digitalization at both the transmitting and receiving ends. However, the development of freedom at the transmitting end is far from mature. So, the new concept of multi-dimensional waveform coding array has appeared, which can optimize the transmitting resources in space–time/frequency waveform or another dimension. Space–time coding array (STCA) is a typical kind of multi-dimensional waveform coding array, which can make full use of the high degree of freedom at the transmitting end. It realizes emission diversity by introducing a small time delay between different transmission array elements. In this paper, an optimization method for STCA, which combines the array spatial coding at the transmitting end and mismatched filter design at the receiving end, is proposed. This method aims to solve the sidelobe problems of STCA: the inherent resonance phenomenon and the resolution loss problem. The experimental verification and quantitative comparative analysis prove the effectiveness of the proposed method. The resolution is restored to the ideal level under the premise of maintaining the beam-scanning ability and ultra-low sidelobe, and the resonance phenomenon caused by spectrum discontinuity is eliminated simultaneously.

Treatment of table olive processing wastewater with US/UV processes

Agroindustry factory's such as the table olive industry etc. that gain importance in the economies of Mediterranean countries. Conventional treatment methods are not effective for treating table olive processing wastewater due to its unique composition. Ultrasound/Ultraviolet light (US/UV) oxidation was used to treat wastewater of table olive industry to improve hydroxyl radicals and enhance organic compound removals. A statistical experimental design was used on table olive processing wastewater to examine the effects of the UV/US oxidation process. The highest removal efficiency for chemical oxygen demand, total organic carbon, color, suspended solids and phenol were obtained as 64 %, 52 % 60 %, 87.5 % and 22.3 %, respectively. These results were obtained under optimal conditions of 20 min reaction time for ultrasound process, intensity of 50 W/cm2, and 20 min reaction time for ultraviolet process in the US/UV process. The study also showed that the ultrasound/ultraviolet oxidation process resulted in small reaction time and low chemical requirements. Sludge production and operational cost decreased at best experimental conditions due to small reaction time and low chemical requirement.

The Effect of Spatio‐Temporal Sampling and Biological Replication on the Detection of Kelp Forest Fish Communities Using eDNA Metabarcoding

ABSTRACTEnvironmental DNA (eDNA) metabarcoding surveys can support the acquisition of extensive biodiversity data to support ecosystem monitoring and conservation actions. However, the optimization of eDNA metabarcoding project design is essential to capture spatio‐temporal heterogeneity of eDNA signals and maximize diversity detection. In this study, we developed a system‐specific approach to detect fish communities in kelp forests, by analyzing fine‐scale spatio‐temporal patterns in eDNA signals at two sites along the South African coastline, as well as testing the effect of biological replication and pooling of replicates on species detection. At each site, samples were collected at two stations along the shoreline at two depth zones, and this was repeated at two time points (24 h apart). We detected 113 operational taxonomic units (OTUs) across 32 families, but fewer than 20% of OTUs could be assigned to species, indicating that barcode reference libraries need to be drastically improved. We detected significant differences in communities across small spatial scales (&lt; 600 m) and time points, suggesting that to best capture a site's diversity patterns, samples should be collected at multiple points and times within at least 24 h. To detect ~80% of the fish community, including some low abundance species, a minimum of four samples appear sufficient. In addition, a higher number of OTUs (76 vs. 65) were found in individual replicates than in any of the pools. However, pooling samples prior to sequencing can still detect valuable broad‐scale biodiversity patterns for monitoring and can offset the decrease in data resolution with the benefit of accumulating comprehensive data from increased sampling efforts over time. As a pilot investigation into how best to maximize kelp forest‐associated fish communities, this study provides a basis for optimizing sampling design for coastal eDNA‐based surveys in southern Africa and strengthens the development of long‐term eDNA monitoring programs to better support conservation and management actions.