Phase Sensitivity Research Articles

Can instability variations warn developers when open-source projects boost?

Although architecture instability has been studied and measured using a variety of metrics, a deeper analysis of which project parts are less stable and how such instability varies over time is still needed. While having more information on architecture instability is, in general, useful for any software development project, it is especially important in Open Source Software (OSS) projects where the supervision of the development process is more difficult to achieve. In particular, we are interested when OSS projects grow from a small controlled environment (i.e., the cathedral phase) to a community-driven project (i.e., the bazaar phase). In such a transition, the project often explodes in terms of software size and number of contributing developers. Hence, the complexity of the newly added features, and the frequency of the commits and files modified may cause significant variations of the instability of the structure of the classes and packages. Consequently, in this article we analyze the instability in OSS projects, especially during that sensitive phase where they become community-driven. Our results show that instability metrics can be easily obtained in such type of transitions. We also observed from our case studies that instability metrics can help finding out the balance between adding new functionality and performing refactoring. As a conclusions we state that instability metrics offer relevant information in the transition phase from the cathedral to the bazaar.

Pillar[5]arene and Azine Derivative Assembly Improved Dual‐Channel Detection of CN–

Comprehensive SummaryThe cyanide anion (CN–) is known to be one of the most toxic anions. Therefore, there is an urgent need to develop a reliable, sensitive, selective, rapid and effective method for the detection of CN–. Here, a self‐assembly strategy based on pillar[5]arene P5 and azine derivative AZ was used to construct supramolecular sensors, and it was found that the detection effect of CN– was significantly improved by the assembly strategy. The sensitivity of the assembled sensor P5‐AZ to CN– is more than 10 times higher than that of AZ. The detect mechanism was further investigated by theoretical calculations and 1H NMR. The results showed that AZ detects CN– by a deprotonation process with fluorescence enhancement, while P5‐AZ improves the sensitivity of CN– recognition through hydrogen bonding, anion‐π and anion‐dipole interactions, as well as the strong bonding ability of the assembly. Supramolecular assembly P5‐AZ has the advantages of low toxicity, high sensitivity, and more importantly, it provides a method to detect CN– sensitivity in the aqueous phase and organisms by host‐guest assembly.

Phase autoencoder for limit-cycle oscillators.

We present a phase autoencoder that encodes the asymptotic phase of a limit-cycle oscillator, a fundamental quantity characterizing its synchronization dynamics. This autoencoder is trained in such a way that its latent variables directly represent the asymptotic phase of the oscillator. The trained autoencoder can perform two functions without relying on the mathematical model of the oscillator: first, it can evaluate the asymptotic phase and the phase sensitivity function of the oscillator; second, it can reconstruct the oscillator state on the limit cycle in the original space from the phase value as an input. Using several examples of limit-cycle oscillators, we demonstrate that the asymptotic phase and the phase sensitivity function can be estimated only from time-series data by the trained autoencoder. We also present a simple method for globally synchronizing two oscillators as an application of the trained autoencoder.

Beating the Standard Quantum Limit Electronic Field Sensing by Simultaneously Using Quantum Entanglement and Squeezing.

Quantum entanglement and quantum squeezing are two typical approaches to beat the standard quantum limit (SQL) for the sensitive phase estimations in quantum metrology. Each of them has already been utilized individually and sequentially to improve the sensitivity of electric field sensing with the trapped ion platform. However, the upper bound of the demonstrated sensitivity gain is still limited, i.e., the theoretical 6dB and experimental 3dB over the corresponding SQL, for electric field sensing. By simultaneously using the internal (spin)-external (oscillator) state entanglement and the oscillator squeezing to effectively amplify the accumulation phase, we show here that such a theoretical sensitivity gain upper bound can be significantly surpassed. The proposal provides a novel approach to implement the stronger beat of the SQL and even approach the Heisenberg limit, for the sensitive sensings of the desired electric field and also the other metrologies.

Mechanistic screening of reproductive toxicity in a novel 3D testicular co-culture model shows significant impairments following exposure to low-dibutyl phthalate concentrations

To improve the mechanistic screening of reproductive toxicants in chemical-risk assessment and drug development, we have developed a three-dimensional (3D) heterogenous testicular co-culture model from neonatal mice. Di-n-butyl phthalate (DBP), an environmental contaminant that can affect reproductive health negatively, was used as a model compound to illustrate the utility of the in vitro model. The cells were treated with DBP (1 nM to 100 µM) for 7 days. Automated high-content imaging confirmed the presence of cell-specific markers of Leydig cells (CYP11A1 +), Sertoli cells (SOX9 +), and germ cells (DAZL +). Steroidogenic activity of Leydig cells was demonstrated by analyzing testosterone levels in the culture medium. DBP induced a concentration-dependent reduction in testosterone levels and decreased the number of Leydig cells compared to vehicle control. The levels of steroidogenic regulator StAR and the steroidogenic enzyme CYP11A1 were decreased already at the lowest DBP concentration (1 nM), demonstrating upstream effects in the testosterone biosynthesis pathway. Furthermore, exposure to 10 nM DBP decreased the levels of the germ cell-specific RNA binding protein DAZL, central for the spermatogenesis. The 3D model also captured the development of the Sertoli cell junction proteins, N-cadherin and Zonula occludens protein 1 (ZO-1), critical for the blood–testis barrier. However, DBP exposure did not significantly alter the cadherin and ZO-1 levels. Altogether, this 3D in vitro system models testicular cellular signaling and function, making it a powerful tool for mechanistic screening of developmental testicular toxicity. This can open a new avenue for high throughput screening of chemically-induced reproductive toxicity during sensitive developmental phases.

Super-resolution and super-sensitivity of quantum LiDAR with a multi-photonic state and binary outcome photon counting measurement

Here, we are investigating the enhancement in resolution and phase sensitivity of a Mach-Zehnder interferometer (MZI) based quantum LiDAR. We are using a multi-photonic state (MPS), superposition of four coherent states [Int. J. Quantum Inf. 19, 2150013 (2021)0219-749910.1142/S0219749921500131], as the input state and binary outcome parity photon counting measurement and binary outcome zero non-zero photon counting measurement as the measurement schemes. We have thoroughly investigated the results in lossless as well as lossy cases. We found enhancement in resolution and phase sensitivity in comparison to the coherent state and even coherent superposition state (ECSS) based quantum LiDAR. Our analysis shows that MPS may be an alternative nonclassical resource in the field of quantum imaging and quantum sensing technologies, like in quantum LiDAR.

DFUSNN: zero-shot dual-domain fusion unsupervised neural network for parallel MRI reconstruction

Objective. Recently, deep learning models have been used to reconstruct parallel magnetic resonance (MR) images from undersampled k-space data. However, most existing approaches depend on large databases of fully sampled MR data for training, which can be challenging or sometimes infeasible to acquire in certain scenarios. The goal is to develop an effective alternative for improved reconstruction quality that does not rely on external training datasets. Approach. We introduce a novel zero-shot dual-domain fusion unsupervised neural network (DFUSNN) for parallel MR imaging reconstruction without any external training datasets. We employ the Noise2Noise (N2N) network for the reconstruction in the k-space domain, integrate phase and coil sensitivity smoothness priors into the k-space N2N network, and use an early stopping criterion to prevent overfitting. Additionally, we propose a dual-domain fusion method based on Bayesian optimization to enhance reconstruction quality efficiently. Results. Simulation experiments conducted on three datasets with different undersampling patterns showed that the DFUSNN outperforms all other competing unsupervised methods and the one-shot Hankel-k-space generative model (HKGM). The DFUSNN also achieves comparable results to the supervised Deep-SLR method. Significance. The novel DFUSNN model offers a viable solution for reconstructing high-quality MR images without the need for external training datasets, thereby overcoming a major hurdle in scenarios where acquiring fully sampled MR data is difficult.

A mobile edge computing-focused transferable sensitive data identification method based on product quantization

Sensitive data identification represents the initial and crucial step in safeguarding sensitive information. With the ongoing evolution of the industrial internet, including its interconnectivity across various sectors like the electric power industry, the potential for sensitive data to traverse different domains increases, thereby altering the composition of sensitive data. Consequently, traditional approaches reliant on sensitive vocabularies struggle to adequately address the challenges posed by identifying sensitive data in the era of information abundance. Drawing inspiration from advancements in natural language processing within the realm of deep learning, we propose a transferable Sensitive Data Identification method based on Product Quantization, named PQ-SDI. This innovative approach harnesses both the composition and contextual cues within textual data to accurately pinpoint sensitive information within the context of Mobile Edge Computing (MEC). Notably, PQ-SDI exhibits proficiency not only within a singular domain but also demonstrates adaptability to new domains following training on heterogeneous datasets. Moreover, the method autonomously identifies sensitive data throughout the entire process, eliminating the necessity for human upkeep of sensitive vocabularies. Extensive experimentation with the PQ-SDI model across four real-world datasets, resulting in performance improvements ranging from 2% to 5% over the baseline model and achieves an accuracy of up to 94.41%. In cross-domain trials, PQ-SDI achieved comparable accuracy to training and identification within the same domain. Furthermore, our experiments showcased the product quantization technique significantly reduces the parameter size by tens of times for the subsequent sensitive data identification phase, particularly beneficial for resource-constrained environments characteristic of MEC scenarios. This inherent advantage not only bolsters sensitive data protection but also mitigates the risk of data leakage during transmission, thus enhancing overall security measures in MEC environments.

The expression of mantle seismic anisotropy in the global seismic wavefield

SUMMARY The dependence of seismic wave speeds on propagation or polarization direction, called seismic anisotropy, is a relatively direct indicator of mantle deformation and flow. Mantle seismic anisotropy is often inferred from measurements of shear-wave splitting. A number of standard techniques to measure shear-wave splitting have been applied globally; for example, *KS splitting is often used to measure upper mantle anisotropy. In order to obtain robust constraints on anisotropic geometry, it is necessary to sample seismic anisotropy from different directions, ideally using different seismic phases with different incidence angles. However, many standard analysis techniques can only be applied for certain epicentral distances and source–receiver geometries. To search for new ways to detect mantle anisotropy, instead of focusing on the sensitivity of individual phases, we investigate the wavefield as a whole: we apply a ‘wavefield differencing’ approach to (systematically) understand what parts of the seismic wavefield are most affected by splitting due to seismic anisotropy in the mantle. We analyze differences between synthetic global wavefields calculated for isotropic and anisotropic input models, incorporating seismic anisotropy at different depths. Our results confirm that the seismic phases that are commonly used in splitting techniques are indeed strongly influenced by mantle anisotropy. However, we also identify less commonly used phases whose waveforms reflect the effects of anisotropy. For example, PS is strongly affected by splitting due to seismic anisotropy in the upper mantle. We show that PS can be used to fill in gaps in global coverage in shear-wave splitting data sets (for example, beneath ocean basins). We find that PcS is also a promising phase, and present a proof-of-concept example of PcS splitting analysis across the contiguous United States using an array processing approach. Because PcS is recorded at much shorter distances than *KS phases, PcS splitting can therefore fill in gaps in backazimuthal coverage. Our wavefield differencing results further hint at additional potential novel methods to detect and characterize splitting due to mantle seismic anisotropy.

What are the characteristics and results of Tilt Tests in the elderly?

What are the characteristics and results of Tilt Tests in the elderly?

Qualitative analysis and modulation instability for the extended (3+1)-dimensional nonlinear Schrödinger equation with conformable derivative

The focus of the article studies the qualitative analysis and modulation instability for the extended (3+1)-dimensional nonlinear Schrödinger equation with conformable derivative. Firstly, the extended (3+1)-dimensional nonlinear Schrödinger equation with conformable derivative is transformed into two-dimensional planar dynamic system through complex exponential wave transformation. Secondly, phase portrait and its orbit of the system are analyzed through the theory of dynamical system. By using Maple software the phase portrait, Poincaré section and sensitivity analysis are compared and displayed. Finally, parameter conditions for stable systems are provided through modulation instability.

Metabolic-Associated Fatty Liver Disease is Characterized by a Post-Oral Glucose Load Hyperinsulinemia in Individuals with Mild Metabolic Alterations.

Metabolic-associated fatty liver disease (MAFLD) has been identified as risk factor of incident type 2 diabetes (T2D), but the underlying postprandial mechanisms remains unclear. We compared the glucose metabolism, insulin resistance, insulin secretion and insulin clearance post-oral glucose tolerance test (OGTT) between individuals with and without MAFLD. We included 50 individuals with a BMI between 25-40 kg/m2 and ≥1 metabolic alteration: increased fasting triglycerides or insulin, plasma glucose 5.5-6.9 mmol/L, or glycated hemoglobin 5.7-5.9%. Participants were grouped according to MAFLD status, defined as hepatic fat fraction (HFF) ≥5% on MRI. We used oral minimal model on a frequently sampled 3h 75g-OGTT to estimate insulin sensitivity, insulin secretion, and pancreatic ß-cell function. Fifty percents of participants had MAFLD. Median age (IQR) (57 (45-65) vs 57 (44-63) years) and gender (60% vs 56% female) were comparable between groups. Post-OGTT glucose concentrations did not differ between groups, whereas post-OGTT insulin concentrations were higher in the MAFLD group (p <0.03). Individuals with MAFLD exhibited lower insulin clearance, insulin sensitivity and first phase pancreatic β cell function. In all individuals, increased insulin incremental area under the curve and decreased insulin clearance were associated with HFF after adjusting for age, sex, and BMI (p <0.02). Amongst individuals with metabolic alterations, the presence of MAFLD was characterized mainly by post-OGTT hyperinsulinemia and reduced insulin clearance, while exhibiting lower first phase β-cell function and insulin sensitivity. This suggests that MAFLD is linked with impaired insulin metabolism that may precede type 2 diabetes.

Design of a Talbot phase-contrast microscopy imaging system with a digital detector for laser-driven X-ray backlighter sources

Laser-driven shock waves in matter propagate with multiple kilometers per second and therefore require sources like a laser-driven backlighter, which emit the X-rays within picoseconds, to be able to capture sharp images. The small spatial extent of shocks in low-density materials pose challenges on the imaging setup. In this work, we present a design process for a single-shot X-ray phase-contrast imaging system geared towards these objects, consisting of a two-grating Talbot interferometer and a digital X-ray detector. This imaging system is optimized with respect to the detectable refraction angle of the X-rays induced by an object, which implies a high phase sensitivity. Therefore, an optimization parameter is defined that considers experimental constraints such as the limited number of photons, the required magnification, the size and spectrum of the X-ray source, and the visibility of the moiré fringes. In this way, a large parameter space is sampled and a suitable imaging system is chosen. During a campaign at the PHELIX high-power laser facility a static test sample was imaged which is used to benchmark the optimization process and the imaging system under real conditions. The results show good agreement with the predicted performance, which demonstrates the reliability of the presented design process. Likewise, the process can be adapted to other types of laser experiments or X-ray sources and is not limited to the application presented here.

Supporting Well-Being: Exploring the Value of a Digital Coach for Older Adults in the Transition from Work to Retirement.

Supporting older adults' health and well-being in the transition from work to retirement requires a holistic perspective and needs to address physical, mental, and social aspects of life. In a field study, applying a mixed-methods approach, we investigated to what extent the prototype of a digital coach can support older adults in this sensitive phase. We aim at answering the central research question: How can a digital coach support older adults in the transition from work to retirement to establish and maintain a healthy lifestyle? Overall, 32 participants from Austria and Belgium took part in an eight-week trial. App-based interventions in different domains (physical, mental, social) were provided and aimed at motivating the target group to become and/or stay active. The study shows that the digital coach has potential to support health and well-being on various levels. In particular, the mental activities proofed valuable and supported older adults' well-being.

Hypotensive drugs mitigate the high-sodium diet-induced pro-inflammatory activation of mouse macrophages in vivo

Nowadays, there is an increasing emphasis on the need to alleviate the chronic inflammatory response to effectively treat hypertension. However, there are still gaps in our understanding on how to achieve this. Therefore, research on interaction of antihypertensive drugs with the immune system is extremely interesting, since their therapeutic effect could partly result from amelioration of hypertension-related inflammation, in which macrophages seem to play a pivotal role. Thus, current comprehensive studies have investigated the impact of repeatedly administered hypotensive drugs (captopril, olmesartan, propranolol, carvedilol, amlodipine, verapamil) on macrophage functions in the innate and adaptive immunity, as well as if drug-induced effects are affected by a high-sodium diet (HSD), one of the key environmental risk factors of hypertension. Although the assayed medications increased the generation of reactive oxygen and nitrogen intermediates by macrophages from standard fed donors, they reversed HSD-induced enhancing effects on macrophage oxidative burst and secretion of pro-inflammatory cytokines. On the other hand, some drugs increased macrophage phagocytic activity and the expression of surface markers involved in antigen presentation, which translated into enhanced macrophage ability to activate B cells for antibody production. Moreover, the assayed medications augmented macrophage function and the effector phase of contact hypersensitivity reaction, but suppressed the sensitization phase of cell-mediated hypersensitivity under HSD conditions. Our current findings contribute to the recognition of mechanisms, by which excessive sodium intake affects macrophage immune activity in hypertensive individuals, and provide evidence that the assayed medications mitigate most of the HSD-induced adverse effects, suggesting their additional protective therapeutic activity.

Noise correction in differential phase contrast for improving phase sensitivity

Differential phase contrast (DPC) imaging relies on computational analysis to extract quantitative phase information from phase gradient images. However, even modest noise level can introduce errors that propagate through the computational process, degrading the quality of the final phase result and further reducing phase sensitivity. Here, we introduce the noise-corrected DPC (ncDPC) to enhance phase sensitivity. This approach is based on a theoretical DPC model that effectively considers most relevant noise sources in the camera and non-uniform illumination in DPC. In particular, the dominating shot noise and readout noise variance can be jointly estimated using frequency analysis and further corrected by block-matching 3D (BM3D) method. Finally, the denoised images are used for phase retrieval based on the common Tikhonov inversion. Our results, based on both simulated and experimental data, demonstrate that ncDPC outperforms the traditional DPC (tDPC), enabling significant improvements in both phase reconstruction quality and phase sensitivity. Besides, we have demonstrated the broad applicability of ncDPC by showing its performance in various experimental datasets.

High space–time bandwidth product imaging in low coherence quantitative phase microscopy

Current low coherence quantitative phase microscopy (LC-QPM) systems suffer from either reduced field of view (FoV) or reduced temporal resolution due to the short temporal coherence (TC) length of the light source. Here, we propose a hybrid, experimental and numerical approach to address this core problem associated with LC-QPM. We demonstrate high spatial resolution and high phase sensitivity in LC-QPM at high temporal resolution. High space–time bandwidth product is achieved by employing incoherent light source for sample illumination in QPM to increase the spatial resolution and single-shot Hilbert spiral transform (HST) based phase recovery algorithm to enhance the temporal resolution without sacrificing spatial resolution during the reconstruction steps. The high spatial phase sensitivity comes by default due to the use of incoherent light source in QPM which has low temporal coherence length and does not generate speckle noise and coherent noise. The spatial resolution achieved by the HST is slightly inferior to the temporal phase-shifting (TPS) method when tested on a specimen but surpasses that of the single-shot Fourier transform (FT) based phase recovery method. Contrary to HST method, FT method requires high density fringes for lossless phase recovery, which is difficult to achieve in LC-QPM over entire FoV. Consequently, integration of HST algorithm with LC-QPM system makes an attractive route. Here, we demonstrate scalable FoV and resolution in single-shot LC-QPM and experimentally corroborate it on a test object and on both live and fixed biological specimen such as MEF, U2OS and human red blood cells (RBCs). LC-QPM system with HST reconstruction offer high-speed single-shot QPM imaging at high phase sensitivity and high spatial resolution enabling us to study sub-cellular dynamic inside U2OS for extended duration (3 h) and observe high-speed (50 fps) dynamics of human RBCs. The experimental results validate the effectiveness of the present approach and will open new avenues in the domain of biomedical imaging in the future.

Rapid, iterative application of the co-create, build, engage (CBE) framework: development of Blurred Minds Vaping and the Environment module

Purpose The number of young people using e-cigarettes (commonly referred to as vaping) has grown at an alarming rate, creating the need for urgent action. This paper demonstrates rapid step-by-step iterative application of the Co-create, Build and Engage (CBE) framework to showcase how marketing was applied in response to emerging trends that have negative health and environmental consequences. This paper aims to demonstrate how CBE is applied iteratively, ensuring student feedback leads module development. Design/methodology/approach In Study 1, a pure seven-step co-design implementation, 19 high school students were invited to co-design a vaping prevention approach that would work for them and other people like them. During the sensitisation phase of co-design, students completed one Blurred Minds Vaping module. Feedback grids were provided, with students identifying likes, dislikes and ideas. This likeability data was used, together with input from technical experts and pedagogical best practice, in a 12-week research and development project that aimed to develop a new online learning module focused on vaping and their environmental impacts for the Blurred Minds Academy. The new module was tested with 20 high school students. Feedback grids were provided once again, allowing a comparison of results. Findings Examination of feedback grid data demonstrates that the newly developed Vaping and the Environment module was improved. Considerations taken on board in the new module design (e.g. increased variability within the module) overcame criticisms expressed previously (e.g. it was boring and too long). Other criticisms remained evident, albeit at a much lower proportion suggesting the new Vaping and the Environment module, and future Blurred Minds module development, would benefit from iterative CBE application. Originality/value Conduit et al. (2022) note that marketing academia has been criticised for having an increasingly less relevant managerial agenda. This paper outlines a rapid step-by-step application of marketing in response to one of society’s most pressing health challenges – vaping. The iterative application of CBE is outlined, demonstrating that the student experience can be enhanced when marketing’s continual improvement mindset is used. This is the first vaping prevention programme that has included substantive information around the negative impacts of vaping on the environment.

Dicke State Generation and Extreme Spin Squeezing via Rapid Adiabatic Passage.

Considering the unique energy level structure of the one-axis twisting Hamiltonian in combination with standard rotations, we propose the implementation of a rapid adiabatic passage scheme on the Dicke state basis. The method permits to drive Dicke states of the many-atom system into entangled states with maximum quantum Fisher information. The designed states allow us to overcome the classical limit of phase sensitivity in quantum metrology and sensing. We show how to generate superpositions of Dicke states, which maximize metrological gain for a Ramsey interferometric measurement. The proposed scheme is remarkably robust to variations of the driving field and has favorable time scaling, especially for a small to moderate (∼1000) number of atoms, where the total time does not depend on the number of atoms.

Azimuthal Scanning Excitation Surface Plasmon Resonance Holographic Microscopy

AbstractSurface plasmon resonance (SPR) holographic microscopy exploits surface plasmon wave as illumination and acquires both SPR intensity and phase images. It detects extremely tiny variations of weakly interacting objects owing to high sensitivity and has been applied in cell biology, material science, surface chemistry, etc. However, it is very challenging to solve the problem of poor spatial resolution due to the transverse propagation of surface plasmon wave. In this paper, an azimuthal scanning excitation method is proposed in SPR holographic microscopy to improve the spatial resolution by engineering the Fourier spectra of SPR images from dual‐arc to circular shape. The study modulates the light field with spatial position, wavevector, and polarization to realize azimuthal scanning excitation of SPR. Systematic experiments of dielectric spheres, nanowires, two‐dimension materials, and complex nanostructure are conducted to show the resolution improvement with one order of magnitude, the higher detection sensitivity of SPR phase than that of SPR intensity, and the necessities of both of high‐resolution SPR intensity and phase images to retrieve sample information in certain scenarios. Benefiting from the high detection sensitivity and spatial resolution, the proposed microscopy will find wide applications in nanoparticle analysis, low‐dimensional material characterization, and imaging extremely thin or transparent samples.