Theoretical Limit Research Articles

Comparison of contrast-enhanced ultrasound imaging (CEUS) and super-resolution ultrasound (SRU) for the quantification of ischaemia flow redistribution: A theoretical study.

The study of microcirculation can reveal important information related to pathology. Focusing on alterations that are
represented by an obstruction of blood flow in microcirculatory regions may provide an insight into vascular biomarkers.
The current in silico study assesses the capability of CEUS and SRU flow-quantification to study occlusive actions in a
microvascular bed, particularly the ability to characterise known and model induced flow behaviours. The aim is to in-
vestigate theoretical limits with the use of CEUS and the upcoming particle-tracking in SRU in order to propose realistic
biomarker targets relevant for clinical diagnosis. Results from CEUS flow parameters display limitations congruent with
prior investigations. Conventional resolution limits lead to signals dominated by large vessels, making discrimination
of microvasculature specific signals difficult. Additionally, some occlusions lead to weakened parametric correlation
against flow rate in the remainder of the network. Loss of correlation is dependent on the degree to which flow is redis-
tributed, with comparatively minor redistribution correlating in accordance with ground truth measurements for change
in mean transit time, dM T T (CEUS, R = 0.85; GT, R = 0.82) and change in peak intensity, dIp (CEUS, R = 0.87;
GT, R = 0.96). Major redistributions, however, result in a loss of correlation, demonstrating that TIC-related parame-
ters have efficacy dependent on the location of occlusion. Conversely, results from SRU processing provides accurate
depiction of the anatomy and dynamics present in the vascular bed, that extends to individual microvessels. Correspon-
dence between model vessel structure displayed in SRU maps with the ground truth was > 91% for cases of minor and
major flow redistributions. In conclusion, SRU appears to be a highly promising technology in the quantification of
subtle flow phenomena due ischaemia induced vascular flow redistribution.

Experienced autonomy in the curriculum and Didaktik traditions

ABSTRACT This study investigates Finnish and Californian (US) elementary and secondary school teachers. The main objective of the study is to explore the experienced autonomy in different educational policy regimes. The ideologies and traditions that these two countries represent can be called Didaktik tradition and curriculum tradition. The research question is: How do the teachers’ perceptions of curriculum traditions in the two country contexts differ concerning experienced autonomy, and what might the theoretical and methodological implications of such comparison be? A total of 17 Finnish and 15 US teachers were interviewed using a semi-structured interview guide. The results show that both groups of teachers experienced a lot of autonomy despite of the fact that the US teachers operate in a more restricted accountability policy than the Finnish teachers. This raises some methodological and theoretical implications and limitations of self-reporting comparative studies on teacher autonomy.

The Antecedents and Consequences of Customer Participation in Community Group Buying: A Systematic Literature Review and Future Agenda

Community group buying (CGB) has shown exponential development recently because of the widespread use of social commerce and e-commerce. As a result of its popularity, the field has received increasing attention from academia, leading to a plethora of empirical studies to comprehend CGB and the elements that influence it. Therefore, reviewing the existing literature to identify potential gaps and future research opportunities becomes vital. Our study conducts a systematic literature review of CGB. We followed the PRISMA protocol, which generated 288 articles. Application of inclusion and exclusion criteria selected 41 studies for the detailed analysis. We analyzed the features of CGB from three perspectives: group leader, logistics, and localization, summarized five categories of antecedents (self-related, online-related, quality-related, operations-related, and risk-related), and identified two types of consequences (attitudinal, behavioral) of customers’ participation. Several research gaps are identified, and corresponding research directions in the future are uncovered. Finally, we discuss the theoretical contribution and limitations of the study.

Improving the Efficiency of Semitransparent Perovskite Solar Cell Using Down-Conversion Coating.

Perovskite solar cells (PSCs) have demonstrated exceptional efficiency, yet surpassing theoretical performance limits requires innovative methodologies. Among these, down-conversion techniques are pivotal in reducing optical losses and enhancing energy conversion efficiency. In this study, optical modeling, including a generalized transfer-matrix optical model, was employed to meticulously assess optical losses in semitransparent PSCs illuminated from the front and rear sides of the device. To reduce these losses, two down-conversion layers, made of N,N-diphenyl-4-(1,2,2-triphenylethenyl)-benzenamine and 4-(N,N-diphenylamino)benzaldehyde mixed with polymeric binder, were developed, showcasing initial photoluminescence quantum yields of 60% and 50% as films, respectively. The materials luminescence relies on the effect of aggregation-induced emission, which enhances the fluorescence of the dyes within the binder, providing their films with a unique behavior beneficial for photovoltaic applications. An optimization of these layers was performed, which aimed to reduce UV optical losses by adjusting the film thickness atop the PSCs. The refined down-conversion layers yielded a notable increase in the power conversion efficiency by approximately 0.4% for both the front and rear sides of the PSCs, demonstrating their significant potential in pushing the boundaries of solar cell performance.

Four-level diffractive photon sieves by deep-UV femtosecond laser ablation

A growing demand for complex light manipulation and miniaturization of optics necessitates advanced optical elements, operating on light diffraction phenomena, capable not only of reshaping the intensity distribution but also integrating many optical functions in a compact, durable device. The prevailing fabrication methods for these elements often involve multi-step lithographic processes. In contrast, direct laser ablation offers a single-step, cost-effective, and maskless alternative. However, using solid-state laser systems’ fundamental wavelength (in the IR range) for ablation lacks the precise depth control required for multi-level diffractive optical element fabrication. In this paper, we present the first experimental proof that femtosecond direct laser ablation in the UV spectral range is a reliable method for fabricating diffractive optical elements. We demonstrate the high-quality production of compact photon sieve focusing elements with the shortest focal length ever reported at 9 mm. Furthermore, we report an efficiency of 3.3%, which, to our knowledge, is the highest for elements with such a small focal length and not far from the theoretical efficiency limit of 4.46% (considering perfect cylindrical ablated pits). Moreover, our fabricated elements focus light to a 2.3% smaller focal spot if compared to the refractive lens with the same parameters. This fabrication method shows great promise for advanced applications that require precise depth control in wide band gap materials, such as the fused quartz used in this study.

Estimation of the Chances to Find New Phenomena at the LHC in a Model-Agnostic Combinatorial Analysis

In this paper, we estimate the number of event topologies that have the potential to be produced in pp collisions at the Large Hadron Collider (LHC) without violating kinematic and other constraints. We use numerical calculations and combinatorics, guided by large-scale Monte Carlo simulations of Standard Model (SM) processes. Then, we set the upper limit on the probability that new physics may escape detection, assuming a model-agnostic approach. The calculated probability is unexpectedly large, and the fact that LHC has not found new physics until now is not entirely surprising. Theoretical limitations and experimental challenges in observing new physics within the studied exclusive event classes are examined.

Lateral Flow Assay for Preeclampsia Screening Using DNA Hairpins and Surface-Enhanced Raman-Active Nanoprobes Targeting hsa-miR-17-5p

Preeclampsia (PE) is a serious complication that poses risks to both mothers and their children. This condition is typically asymptomatic until the second or even third trimester, which can lead to poor outcomes and can be costly. Detection is particularly challenging in low- and middle-income countries, where a lack of centralized testing facilities coincides with high rates of PE-related maternal mortality. Variations in the levels of hsa-miR-17-5p have been identified as constituting a potential early indicator for distinguishing between individuals with PE and those without PE during the first trimester. Thus, developing a screening test to measure hsa-miR-17-5p levels would not only facilitate rapid detection in the early stages of pregnancy but also help democratize testing globally. Here, we present a proof-of-principle lateral-flow assay (LFA) designed to measure hsa-miR-17-5p levels using DNA-hairpin recognition elements for enhanced specificity and nanoprobes for sensitive surface-enhanced resonance Raman scattering (SERS) signal transduction. The theoretical limit of detection for hsa-miR-17-5p was 3.84 × 10−4 pg/µL using SERS.

Design and optimization of two-terminal InGaP/Si tandem solar cell through numerical simulation

Abstract The III-V/Si double junction solar cells demonstrate cost-effective performance comparable to III-V/III-V tandems, with an efficiency of 35.9%, below the 43% theoretical limit. Considering monolithic InGaP//Si based tandem solar cell, this work dealt with the optimization of its efficiency as a function of layer thicknesses and dopings. Considering ideal optoelectronic parameters of materials, numerical simulations were performed by using Silvaco/ATLAS TCAD software. They were conducted within the context of a multi-step optimization procedure that was proposed in this work. The obtained optimum tandem InGaP//Si structure reached an unprecedented power conversion efficiency of 40.74% under 1.5G spectrum.

CANCER. Is this Forever? Examining the Relationship Between Event Centrality and Fear of Cancer Recurrence from a Cognitive-Behavioral Standpoint

The purpose of this study was to test a moderated mediation model. We first looked into whether fear of a cancer recurrence mediated the effect of time since diagnosis on trauma centrality, a concept rendering the impact of cancer on one’s self-identity. Secondly, we looked into whether the indirect effect would depend on the stage of diagnosis. We expected a more pronounced indirect effect for early stages as opposed to late stages. We acquired data from 234 cancer survivors (78.02% female; Mage= 35.58), who received a cancer diagnosis, were undergoing cancer treatment or had finished their treatment. Together with demographics and basic medical information, participants completed the Fear of Cancer Recurrence Inventory Short Form (FCRI-SF) and the Centrality of Event Scale – the Short - Form (CED-SF). In line with our expectations, the results confirmed an indirect effect of fear of cancer recurrence which was stronger for survivors in the early stage of diagnosis (i.e., I, II) as compared to those in the late stage (i.e., III, IV). Conclusions and Future Directions. The study emphasizes the significance of taking into account both the disease stage at diagnosis and the length of time since diagnosis when creating interventions to help cancer survivors address their fear of cancer recurrence. Theoretical ramifications and interpretive limitations are presented.

Dual active site pathways in cobalt-based bimetallic catalysts enhance oxygen evolution reaction activity: Density functional theory studies

Co single-atom catalysts show significant potential in enhancing oxygen evolution reaction (OER) efficiency, crucial for advancing renewable energy technologies. However, their performance is constrained by a single active site, making it challenging for traditional OER pathways to surpass theoretical overpotential limits. By focusing on dual active sites, this study systematically investigates the structural evolution and catalytic performance of Co based double atom catalysts using density functional theory. Co as the primary metal (M1), pairs with 15 different transition metals (M2) to create bimetallic catalysts. The formation energies, binding energies, and Gibbs free energy changes along four potential OER reaction pathways are calculated to assess the stability and activity of these catalysts. The results show enhanced catalytic performance along path II (H₂O → *OH → *2OH → *OOH → O₂) for Co-Ni, Co-Cu, Co-Pd, and Co-Pt catalysts. This improvement stems from synergistic interactions between metal atoms, bypassing high-energy barriers in traditional pathways. Notably, the d-band centers of Cu, Pd, and Pt near the Fermi level boost electron transfer. Co provides stable adsorption sites, optimizing the conversion of intermediates. This study advances understanding of the reaction mechanism and guides the development of more efficient catalysts.

Statistical resolution analysis of microwave computational imaging

AbstractThis letter presents a model based on the Cramér–Rao bound theory for calculating the theoretical lower limit of imaging resolution of microwave computational imaging aided by re‐configurable metasurface. The model takes into account two crucial parameters: the signal‐to‐noise ratio and the number of measurements in the imaging process. By simultaneously considering the signal‐to‐noise ratio and the number of measurements, as well as other parameters, the model allows for a comprehensive assessment of the imaging resolution of the imaging system. In addition, both position estimation and intensity estimation are considered, and a new composite statistical resolution concept is proposed, which is more suitable for microwave computational imaging.

Deep Learning for Solving Partial Differential Equations: A Review of Literature

Partial Differential Equations (PDEs) are fundamental in modeling various phenomena in physics, engineering, and finance. Traditional numerical methods for solving PDEs, such as finite element and finite difference methods, often face limitations when applied to high-dimensional and complex systems. In recent years, deep learning has emerged as a promising alternative for approximating solutions to PDEs, offering potential improvements in both efficiency and scalability. This paper provides a comprehensive review of the literature on deep learning-based methods for solving PDEs, focusing on key approaches such as Physics-Informed Neural Networks (PINNs), deep Galerkin methods, and neural operators. These methods leverage the expressiveness of neural networks to capture underlying physics while avoiding the curse of dimensionality associated with classical techniques. We explore the theoretical foundations, advantages, and limitations of these deep learning models, along with their applications in diverse fields like fluid dynamics, quantum mechanics, and financial modeling. Additionally, this review examines recent advancements in hybrid models that combine traditional numerical methods with deep learning approaches to enhance accuracy and stability. Through this review, we highlight key trends and open challenges in the field, paving the way for future research at the intersection of deep learning and computational mathematics.

A 3D-Printed Bionic Membrane with Autonomously Passive Unidirectional Liquid Transfer Capability for Water Condensation, Collection, and Purification.

Interfacial solar vapor generation is a promising technology for alleviating the current global water crisis, and the evaporation rate and efficiency have approached the theoretical limit. In a practical interfacial evaporation water purification system, the collection rate of purified water is typically lower than the evaporation rate. Passive collection devices based on gravity are susceptible to environmental influences and exhibit low collection efficiency, while active collection devices consuming external energy suffer from complex device systems and extra energy consumption. Given that both collection devices are nonselective and unable to distinguish contaminants mixed in the vapor, bionic membranes with autonomously passive and unidirectional water transfer capacity are developed through 3D printing for efficient water collection. More importantly, the bionic membranes are capable of high-speed water transportation without the need for external energy or gravity drive and liquid-selective transportation for separating oily pollutants from the collected products. The directional transport property facilitates the modular assembly of the bionic membrane, extending its application to practical large-scale solar-driven seawater desalination systems.

Research on Multi-Parameter Error Model of Backcalculated Modulus Using Abaqus Finite Element Batch Modeling Based on Python Language

The error in modulus backcalculation is a crucial component in validating the rationality and reliability of results for engineering applications. The objective of this study is to identify the theoretical limitations associated with backcalculated modulus errors under typical parameter uncertainties and to determine the primary factors contributing to these errors. Firstly, using the actual measurements or data from the Long-Term Pavement Performance (LTPP) project, the statistical distributions of errors for typical parameters in the modulus backcalculation model were determined. Subsequently, a factor level table for orthogonal experimental design was developed, leading to the construction of 81 orthogonal design experimental schemes and their corresponding theoretical pavement structure models based on the actual error distributions. The deflection responses of 81 theoretical pavement structure models were then computed using an ABAQUS finite element batch analysis method devised in Python. Furthermore, a multi-parameter error model for modulus was established using multiple linear regression and variance analysis. Finally, the theoretical limitations of modulus errors under actual errors were analyzed. The results show that the errors of thickness, load amplitude and load frequency follow a normal distribution, while the distribution of backcalculated modulus errors follows an approximate mixed Gaussian distribution. When the errors of multiple parameters are combined randomly, the modulus errors range from −100% to 595%, and the probability of the modulus errors being less than 15% is highest in the asphalt surface layer, followed by the subgrade, and then the base and subbase layers. Within the same error range, the modulus error is random. However, with different error ranges, the overall level of modulus error increases in proportion to the size of those ranges. Compared to factors such as thickness, load amplitude, and load frequency, the errors in deflections have a highly contribution rate on the modulus errors exceeding 99%.

Mathematical Modeling Unveils Optimization Strategies for Targeted Radionuclide Therapy of Blood Cancers.

Targeted radionuclide therapy is based on injections of cancer-specific molecules conjugated with radioactive nuclides. Despite the specificity of this treatment, it is not devoid of side-effects limiting its use and is especially harmful for rapidly proliferating organs well perfused by blood, like bone marrow. Optimization of radioconjugates administration accounting for toxicity constraints can increase treatment efficacy. Based on our experiments on disseminated multiple myeloma mouse model treated by 225Ac-DOTA-daratumumab, we developed a mathematical model which investigation highlighted the following principles for optimization of targeted radionuclide therapy. 1) Nuclide to antibody ratio importance. The density of radioconjugates on cancer cells determines the density of radiation energy deposited in them. Low labeling ratio as well as accumulation of unlabeled antibodies and antibodies attached to decay products in the bloodstream can mitigate cancer radiation damage due to excessive occupation of specific receptors by antibodies devoid of radioactive nuclides. 2) Cancer binding capacity-based dosing. The total number of specific receptors on cancer cells is a critical factor for treatment optimization, which estimation may allow increasing treatment efficacy close to its theoretical limit. Injection of doses significantly exceeding cancer binding capacity should be avoided since radioconjugates remaining in the bloodstream have negligible efficacy to toxicity ratio. 3) Particle range-guided multi-dosing. The use of short-range particle emitters and high-affinity antibodies can allow for robust treatment optimization via initial saturation of cancer binding capacity, enabling redistribution of further injected radioconjugates and deposited dose towards still viable cells that continue expressing specific receptors.

Vanadium oxide thin films growth by a chemical solution deposition method and its pH sensor toward bio-sensing devices

Abstract We report on the evaluation of the structure of VOx thin films under different fabrication conditions of the chemical solution deposition method and the pH response of an extended gate field effect transistor (EGFET)-type pH sensor. Polycrystalline V2O5 thin films of 30 and 60 nm thick and amorphous VOx thin films of about 30 nm thick were successfully prepared under different precursor solution conditions. Using polycrystalline V2O5 thin films and amorphous VOx thin films as an extended gate (EG) electrode, protypes of EGFET-type pH sensors were fabricated and investigated their pH response characteristics. The average pH responsibility of 64 mV/pH, which exceeded the theoretical Nernst limit, was observed over a wide pH range from 2.4 to 8.0 in the amorphous VOx extended gate sensor. It was also found that stable pH response measurements could be performed on amorphous VOx film samples.

Study on the deep deoxidation mechanism of titanium powder using Y/YOCl/YCl3 and Y/Y2O3 systems

Low-oxygen high-purity titanium (oxygen concentration ≤ 500 ppm) is a critical material for advanced semiconductor and biomedical applications. Current deoxidation methods limit oxygen concentration in titanium to approximately 1000–2000 ppm, failing to meet the demand for ultra-low oxygen levels in high-performance materials. This study investigated the preparation mechanism and conditions for low-oxygen high-purity titanium utilizing a molten salt thermochemical method, employing Y as the deoxidant with a theoretical deoxidation limit below 10 ppm. We experimentally explored the deoxidation mechanisms of titanium using Y/YOCl/YCl3 and Y/Y2O3 systems, successfully reducing the oxygen concentration in titanium to 200 ppm, and proving that the Y/YOCl/YCl3 system is more efficient than the Y/Y2O3 system. Additionally, the titanium samples were analyzed using SEM-EDS, XRD, XPS, and 3D surface profilometry before and after deoxidation. These analyses examined the impact of the deoxidation process using Y on the crystal structure, oxide film, and surface roughness of titanium specimens, which are useful for understanding the deoxidation mechanism. During the sintering process of titanium powder attached to Y, the deoxidation process will produce YOCl or Y2O3. The formation of these deoxidation products leads to local oxygen diffusion, and the crystals of YOCl or Y2O3 are gathered at grain boundaries, which will resolve during the subsequent acid etching process, thus reducing the oxidation concentration of the titanium. The above results provide further theoretical guidance and technical support for the production of ultra-high-purity titanium powder.

Linearly programmable two-dimensional halide perovskite memristor arrays for neuromorphic computing.

The exotic properties of three-dimensional halide perovskites, such as mixed ionic-electronic conductivity and feasible ion migration, have enabled them to challenge traditional memristive materials. However, the poor moisture stability and difficulty in controlling ion transport due to their polycrystalline nature have hindered their use as a neuromorphic hardware. Recently, two-dimensional (2D) halide perovskites have emerged as promising artificial synapses owing to their phase versatility, microstructural anisotropy in electrical and optoelectronic properties, and excellent moisture resistance. However, their asymmetrical and nonlinear conductance changes still limit the efficiency of training and accuracy of inference. Here we achieve highly linear and symmetrical conductance changes in Dion-Jacobson 2D perovskites. We further build a 7 × 7 crossbar array based on analogue perovskite synapses, achieving a high device yield, low variation with synaptic weight storing capability, multi-level analogue states with long retention, and moisture stability over 7 months. We explore the potential of such devices in large-scale image inference via simulations and show an accuracy within 0.08% of the theoretical limit. The excellent device performance is attributed to the elimination of gaps between inorganic layers, allowing the halide vacancies to migrate homogeneously regardless of grain boundaries. This was confirmed by first-principles calculations and experimental analysis.

The Time of the Stones: A Call for Palimpsest Dissection to Explore Lithic Record Formation Processes

The dissection of archaeological palimpsests has become a crucial process for achieving a diachronic understanding of the history of human groups. However, its widespread application to archaeological deposits has been hampered by both methodological and theoretical limitations, as well as by the inherent characteristics of the deposits. This paper explores whether overcoming these barriers, both methodological and theoretical, truly represents a significant shift in understanding past human behaviour, thereby motivating the pursuit of shorter timescales. To this end, we have analysed the lithic assemblages of Unit Xb from the Neanderthal site of El Salt (Alcoi, Iberian Peninsula) focusing on lithic attributes and raw material analyses, enabling the definition of raw material units and refitting sets. Considering these variables, we have applied archaeostratigraphic and spatial analyses in order to generate units of analysis whose content is compared to that of the entire unit. The defined archaeostratigraphic units display different spatial distributions and lithic composition. Some of them are attached to certain hearths and composed of refitted sets, while other units are related to areas without combustion evidence and integrated with bigger and heavier single products. Through this approach, here, we show that reducing the spatiotemporal scale of the record helps to unravel behavioural variability, reducing interpretative errors implicit in the assemblage-as-a-whole approach. This highlights the role of temporal resolution in reconstructing site formation processes and challenges research perspectives that assert the unnecessary or impossible nature of palimpsest dissection.

Electrolyte‐free solid‐state batteries demonstrated with bifunctional Li2VCl4

All‐solid‐state batteries have attracted much attention because of the expected high energy density and inherent safety stemming from their nonflammable property. While improving the energy density of the cathode poses a significant challenge, here we introduce a novel battery design strategy to enhance energy density by employing bifunctional cathode material, allowing the weight ratio of the active material to be increased without using an electrolyte for the cathode. By employing lithium‐containing vanadium halide Li2VCl4, serving as both active material and electrolyte, the all‐solid‐state battery cell with no electrolyte for the cathode with a capacity approaching the theoretical limit is demonstrated. In addition, we present a guideline for improving capacity retention from the perspective of interfacial stability. Notably, thermodynamic analysis revealed interfacial instability between Li2VCl4 and sulfide material. A double‐layer separator, incorporating halide materials for the cathode side, was implemented to enhance the interfacial stability and mitigate the capacity degradation. Furthermore, it was found that the rate capability depends on the lithium content in synthesized Li2‐xVCl4 and does not change with the state of charge significantly. This study will contribute to designing the bifunctional cathode material for an all‐solid‐state battery and describe its unique properties.