bluuebunny/crossref_metadata_2025_split huggingface dataset:
Passive communication for low power distributed sensors using MEMS optical cavities
Authors: Schopp Jacob , McNamara Shamus 
Published: February 2024

Abstract
Distributed sensing has been of great interest in recent research. Distributed sensors are in part defined by the methods they use to communicate. We demonstrate a new low power method of optical communication. Instead of communicating optically by generating new light to communicate using a light emitting diode or laser, our method uses optical interference to vary the reflectivity of a micro-electromechanical systems (MEMS) optical cavity. A thin air gap between an adjustable MEMS mirror made on a silicon on insulator die and glass encapsulation generates optical interference. By moving the mirror electrostatically, the reflected light intensity is modulated, and signals are transmitted passively. The transmitted signal is measured by observing the reflected light intensity with a photodiode. We demonstrate the use of fiber optic cables to deliver illumination and collect reflected light with modulated intensity. We propose that these devices may also be used in series arrays where reflected light from one optical cavity can be used as illumination for another.
Controlling the charge of dust particles in an afterglow by modulating the plasma power
Authors: Chaubey Neeraj , Goree J 
Published: February 2024

Abstract
A dust particle immersed in a glow-discharge plasma has long been known to have a charge that is negative, while the plasma is powered. However, in the afterglow, following the stopping of the plasma power, a large positive charge can collect on the particle, as was shown recently for particles in a cathodic sheath. While that outcome of positive charging in the afterglow may be common, an experimental discovery reported here reveals that the opposite outcome is also possible: a particle can develop a negative charge in the afterglow, if the plasma had previously been operated with a modulated power. Before stopping the plasma power off altogether, in a run with power modulated at a low duty cycle of 4.5

%

, the particle’s residual charge was negative, but it was positive in a control run without modulation. This result points to a way of controlling the charge of dust particles in a decaying plasma, which can be useful for mitigating defects in semiconductor manufacturing.
A meta-learning method for few-shot bearing fault diagnosis under variable working conditions
Authors: Zeng Liang , Jian Junjie , Chang Xinyu , Wang Shanshan 
Published: February 2024

Abstract
Intelligent fault diagnosis in various industrial applications has rapidly evolved due to the recent advancements in data-driven techniques. However, the scarcity of fault data and a wide range of working conditions pose significant challenges for existing diagnostic algorithms. This study introduces a meta-learning method tailored for the classification of motor rolling bearing faults, addressing the challenges of limited data and diverse conditions. In this approach, a deep residual shrinkage network is employed to extract salient features from bearing vibration signals. These features are then analyzed in terms of their proximity to established fault prototypes, enabling precise fault categorization. Moreover, the model’s generalization in few-shot scenarios is enhanced through the incorporation of a meta-learning paradigm during training. The approach is evaluated using two well-known public bearing datasets, focusing on varying speeds, loads, and high noise environments. The experimental results indicate the superior diagnostic accuracy and robustness of our method compared with those of existing studies.
Modeling the interplay of oscillatory synchronization and aggregation via cell–cell adhesion
Authors: Glimm Tilmann , Gruszka Daniel 
Published: February 2024

Abstract
We present a model of systems of cells with intracellular oscillators (‘clocks’). This is motivated by examples from developmental biology and from the behavior of organisms on the threshold to multicellularity. Cells undergo random motion and adhere to each other. The adhesion strength between neighbors depends on their clock phases in addition to a constant baseline strength. The oscillators are linked via Kuramoto-type local interactions. The model is an advection-diffusion partial differential equation with nonlocal advection terms. We demonstrate that synchronized states correspond to Dirac-delta measure solutions of a weak version of the equation. To analyze the complex interplay of aggregation and synchronization, we then perform a linear stability analysis of the incoherent, spatially uniform state. This lets us classify possibly emerging patterns depending on model parameters. Combining these results with numerical simulations, we determine a range of possible far-from equilibrium patterns when baseline adhesion strength is zero: There is aggregation into separate synchronized clusters with or without global synchrony; global synchronization without aggregation; or unexpectedly a ‘phase wave’ pattern characterized by spatial gradients of clock phases. A 2D Lattice-Gas Cellular Automaton model confirms and illustrates these results.
Unsupervised ensembling of multiple software sensors with phase synchronization: a robust approach for electrocardiogram-derived respiration
Authors: McErlean Jacob , Malik John , Lin Yu-Ting , Talmon Ronen , Wu Hau-Tieng 
Published: February 2024

Abstract

Objective. We aimed to fuse the outputs of different electrocardiogram-derived respiration (EDR) algorithms to create one higher quality EDR signal. Methods. We viewed each EDR algorithm as a software sensor that recorded breathing activity from a different vantage point, identified high-quality software sensors based on the respiratory signal quality index, aligned the highest-quality EDRs with a phase synchronization technique based on the graph connection Laplacian, and finally fused those aligned, high-quality EDRs. We refer to the output as the sync-ensembled EDR signal. The proposed algorithm was evaluated on two large-scale databases of whole-night polysomnograms. We evaluated the performance of the proposed algorithm using three respiratory signals recorded from different hardware sensors, and compared it with other existing EDR algorithms. A sensitivity analysis was carried out for a total of five cases: fusion by taking the mean of EDR signals, and the four cases of EDR signal alignment without and with synchronization and without and with signal quality selection. Results. The sync-ensembled EDR algorithm outperforms existing EDR algorithms when evaluated by the synchronized correlation (

γ

-score), optimal transport (OT) distance, and estimated average respiratory rate score, all with statistical significance. The sensitivity analysis shows that the signal quality selection and EDR signal alignment are both critical for the performance, both with statistical significance. Conclusion. The sync-ensembled EDR provides robust respiratory information from electrocardiogram. Significance. Phase synchronization is not only theoretically rigorous but also practical to design a robust EDR.
First measurements with a Coherence Imaging Charge Exchange Recombination Spectroscopy (CICERS) diagnostic at Wendelstein 7-X
Authors: Lopez-Cansino R , Perseo V , Viezzer E , Kriete D M , Ford O P , Romba T , Poloskei P Zs ,   the W7-X Team
Published: February 2024

Abstract
In this work, the Coherence Imaging Spectroscopy technique is exploited for active charge exchange radiation measurements to infer high spatial resolution 2D ion temperature (

T

i

) maps in the core region of Wendelstein 7-X plasmas. A synthetic model of the diagnostic is developed and used for the optimization of the hardware components for the expected ion temperatures (

T

i

∼
2

keV) prioritizing

T

i

measurements while also considering the ion velocity flow resolution. The experimental set-up is shown and the diagnostic calibration procedure for

T

i

measurements is introduced. A combination of both simulations and experimental calibrations enable high fidelity system group delay (

∂
ϕ

∂
λ

) characterization in the whole visible spectral range. Finally, the signal processing techniques applied to the diagnostic signal are introduced and first measurements of 2D

T

i

maps are presented and validated against standard Charge eXchange Recombination Spectroscopy

T

i

profiles, finding excellent agreement.
Insights on seasonal solifluction processes in warm permafrost Arctic landscape using a dense monitoring approach across adjacent hillslopes
Authors: Fiolleau Sylvain , Uhlemann Sebastian , Shirley Ian A , Wang Chen , Wielandt Stijn , Rowland Joel , Dafflon Baptiste 
Published: February 2024

Abstract
Solifluction processes in the Arctic are highly complex, introducing uncertainties in estimating current and future soil carbon storage and fluxes, and assessment of hillslope and infrastructure stability. This study aims to enhance our understanding of triggers and drivers of soil movement of permafrost-affected hillslopes in the Arctic. To achieve this, we established an extensive soil deformation and temperature sensor network, covering 48 locations across multiple hillslopes within a 1 km² watershed on the Seward Peninsula, AK. We report depth-resolved measurements down to 1.8 m depth for May to September 2022, a period conducive to soil movement due to deepening thaw layers and frequent rain events. Over this period, surface movements of up to 334 mm were recorded. In general, these movements occur close to the thawing front, and are initiated as thawing reaches depths of 0.4 to 0.75 m. The largest movements were observed at the top of the south-east facing slope, where soil temperatures are cold (mean annual soil temperatures averaging -1.13°C) and slopes are steeper than 15°. Our analysis highlights three primary factors influencing movements: slope angle, soil thermal conditions, and thaw depth. The latter two significantly impact the generation of pore water pressures at the thaw–freeze interface. Specifically, soil thermal conditions govern the liquid water content, while thaw depth influences both the height of the water column and, consequently, the pressure at the thawing front. These factors affect soil properties, such as cohesion and internal friction angle, which are crucial determinants of slope stability. This underscores the significance of a precise understanding of subsurface thermal conditions, including spatial and temporal variability in soil temperature and thaw depth, when assessing and predicting slope instabilities. Based on our observations, we developed a Factor of Safety proxy that consistently falls below the triggering threshold for all probes exhibiting displacements exceeding 50 mm. This study offers novel insights into patterns and triggers of hillslope movements in the Arctic and provides a venue to evaluate their impact on soil redistribution.
Branching laws for spherical harmonics on superspaces in exceptional cases
Authors: Lávička Roman 
Published: February 2024

Abstract
It turns out that harmonic analysis on the superspace

R

m

|

2
n

is quite parallel to the classical theory on the Euclidean space

R

m

unless the superdimension

M
:=
m
−
2
n

is even and non-positive. The underlying symmetry is given by the orthosymplectic superalgebra

o
s
p

(
m

|

2
n
)

. In this paper, when the symmetry is reduced to

o
s
p

(
m
−
1

|

2
n
)

we describe explicitly the corresponding branching laws for spherical harmonics on

R

m

|

2
n

also in exceptional cases, i.e, when

M
−
1
∈
−
2

N

0

. In unexceptional cases, these branching laws are well-known and quite analogous as in the Euclidean framework.
Revisiting anapoles in a single high-index dielectric structure
Authors: Wang Longxiao , Huang Lujun 
Published: February 2024

Abstract
High-index dielectric structures support electric and magnetic Mie resonance. Through careful manipulation of geometric parameters, destructive interference can be induced between electric multipole moments and toroidal multipole moments. This leads to the formation of anapoles, which are characterized by quenched scattering in the far field and giant enhancement in the near field. Here, we revisit the formation mechanism of anapole states in a single dielectric structure with a high refractive index from an eigenmode perspective. We find that scattering efficiency is mainly determined by the intrinsic phase governed by the leaky mode of the structure and the extrinsic phase induced by the frequency deviation from resonance. It is also demonstrated that the anapole modes in a two-dimensional cylinder and a three-dimensional sphere can only occur in the following two situations: (1) when only one mode is involved, the combined phase of intrinsic and extrinsic phase should be equal to 2π at a certain frequency (anapole frequency), which is very close to the resonance frequency. Generally, these types of anapoles are low-order anapoles since low-order resonant modes (i.e., magnetic (electric) dipole and quadrupole) are well separated. (2) If two or more leaky modes are involved, the combined phase for each mode must be 2π at the same frequency located between the two resonances. This corresponds to the high-order anapoles. It is also found that more anapole states will emerge with increasing refractive index. Our results may provide new perspectives for designing high-order anapoles with more freedom.
Bandgap engineering and amplification in photonic time crystals
Authors: Sadhukhan Snehashis , Ghosh Somnath 
Published: February 2024

Abstract
Recently, there has been a growing interest in time-varying photonic media owing to their significant potential in the field of wave manipulation. Here, we explore the exotic characteristics of wave amplification in a photonic time crystal (PTC) made of a spatially homogeneous medium where the refractive index varies periodically in time. Based on qualitative and quantitative analysis of the amplification, we show that the amplification not only depends on the choice of wave vector of a propagating light but also attains different values in different bandgaps. Our approach further extends towards achieving the minimum amount of variation of permittivity required to open momentum gaps to facilitate the phase-dependent amplification of PTCs. Further, we investigate the impact of permittivity variation and choice of number of temporal unit cells to truncate a PTC to mimic the properties of infinite PTC and offer new opportunities to manipulate and control the amplification of light for applications including highly tunable PTC lasers and devices.
Parity-time imbalance induced by balanced gain and loss medium in non-Hermitian photonic crystals
Authors: Wang Qianxing , Liu Bobo , Ying Lei 
Published: February 2024

Abstract
Photonic crystals, including gain and loss materials, show numerous intriguing features than the ordinary photonic crystals. In this work, using the full wave simulation, we numerically investigate the photonic crystals with gain and loss which are satisfying the parity-time (PT) symmetry condition to reveal the effect of PT symmetry on the optical properties of photonic crystals, including the exceptional point, distribution of electromagnetic fields and edge states. This work reveals a novel mechanism of coexistence and competition between topological states and non-Hermiticity in all-dielectric photonic crystals and provides an innovative understanding of non-Hermiticity in topological photonic systems.
Compact and efficient lossy mode resonant refractive index sensor for aqueous environment
Authors: Sharma Vinod K 
Published: February 2024

Abstract
A very short length high sensitivity, large figure of merit and very high resolution integrated-photonic refractometer for aqueous environment operating in visible region of wavelength is proposed. The sensor design depends on the periodic coupling of the guided dielectric optical waveguide mode field and the lossy mode field of the conducting indium-tin-oxide thin film. Various layer thicknesses can be optimized to provide power transfer to the lossy layer and lossy mode resonance, resulting in a strong guided mode power absorption in the lossy layer occurs. The sensor has been designed to operate in both the TE and TM polarizations with different optimized layer frthicknesses. The optimized thicknesses are different for TE and TM polarizations. The obtained numerical results show that a spectral sensitivity of 2200 nm/RIU/2645 nm/RIU for TE/TM mode could be achieved with a very high resolution. Also, the sensors can operate in power interrogation mode with a maximum sensitivity nearly 5 × 107 dB RIU−1.
A review of fetal cell lines used during drug development: Focus on COVID-19 vaccines, transplant medications, and biologics
Authors: Durant Karin M , Whitesell Ashlyn , Dasse Kathy D 
Published: February 2024

Abstract

Purpose
The recent coronavirus disease 2019 (COVID-19) pandemic and vaccine mandates have increased the number of patient questions related to how fetal cell lines are used during drug development and final manufacturing. This article describes our literature search and review of COVID-19 vaccines, transplant medications, and biologics whose development included use of fetal cell lines.

Summary
A detailed literature search was conducted to identify the common fetal cell lines used in COVID-19 vaccine development; the two most prevalent fetal cell lines identified were HEK-293 and PER.C6. Subsequent literatures searches were conducted to identify transplant medications and biologics whose development included use of the HEK-293 or PER.C6 cell lines. For the COVID-19 vaccines, only the viral vector vaccine by Janssen was found to contain proteins produced by PER.C6 in the final preparation administered to patients, and Novavax is the only vaccine for which fetal cell lines were not directly involved in any portion of drug development. For transplant medications, many medications were studied in fetal cell lines in postmarketing studies after Food and Drug Administration approval; however, none of these medications contained fetal cells or would expose a patient to a fetal cell line. Many new biologics and cellular therapies for genetic diseases and malignancies have been directly developed from HEK-293 fetal cells or contain proteins produced directly from fetal cell lines.

Conclusion
There were very few drugs reviewed that were found to contain HEK-293 or PER.C6 fetal cells or proteins derived directly from fetal cell lines; however, use of fetal cell lines in biologics and gene therapies will continue to increase. Healthcare providers should be mindful of patients’ beliefs while also correcting common misconceptions about how these fetal cell lines are used throughout drug development and manufacturing.
Self-supervised deep learning of gene–gene interactions for improved gene expression recovery
Authors: Wei Qingyue , Islam Md Tauhidul , Zhou Yuyin , Xing Lei 
Published: February 2024

Abstract
Single-cell RNA sequencing (scRNA-seq) has emerged as a powerful tool to gain biological insights at the cellular level. However, due to technical limitations of the existing sequencing technologies, low gene expression values are often omitted, leading to inaccurate gene counts. Existing methods, including advanced deep learning techniques, struggle to reliably impute gene expressions due to a lack of mechanisms that explicitly consider the underlying biological knowledge of the system. In reality, it has long been recognized that gene–gene interactions may serve as reflective indicators of underlying biology processes, presenting discriminative signatures of the cells. A genomic data analysis framework that is capable of leveraging the underlying gene–gene interactions is thus highly desirable and could allow for more reliable identification of distinctive patterns of the genomic data through extraction and integration of intricate biological characteristics of the genomic data. Here we tackle the problem in two steps to exploit the gene–gene interactions of the system. We first reposition the genes into a 2D grid such that their spatial configuration reflects their interactive relationships. To alleviate the need for labeled ground truth gene expression datasets, a self-supervised 2D convolutional neural network is employed to extract the contextual features of the interactions from the spatially configured genes and impute the omitted values. Extensive experiments with both simulated and experimental scRNA-seq datasets are carried out to demonstrate the superior performance of the proposed strategy against the existing imputation methods.
Regression analysis of group-tested current status data
Authors: Li Shuwei , Hu Tao , Wang Lianming , McMahan Christopher S , Tebbs Joshua M 
Published: February 2024

Summary
Group testing is an effective way to reduce the time and cost associated with conducting large-scale screening for infectious diseases. Benefits are realized through testing pools formed by combining specimens, such as blood or urine, from different individuals. In some studies, individuals are assessed only once and a time-to-event endpoint is recorded, for example, the time until infection. Combining group testing with this type of endpoint results in group-tested current status data (Petito & Jewell, 2016). To analyse these complex data, we propose methods that estimate a proportional hazard regression model based on test outcomes from measuring the pools. A sieve maximum likelihood estimation approach is developed that approximates the cumulative baseline hazard function with a piecewise constant function. To identify the sieve estimator, a computationally efficient expectation-maximization algorithm is derived by using data augmentation. Asymptotic properties of both the parametric and nonparametric components of the sieve estimator are then established by applying modern empirical process theory. Numerical results from simulation studies show that our proposed method performs nominally and has advantages over the corresponding estimation method based on individual testing results. We illustrate our work by analysing a chlamydia dataset collected by the State Hygienic Laboratory at the University of Iowa.
Methodologies for smellwalks and scentwalks—a critical review
Authors: Parker Murray , Spennemann Dirk H R , Bond Jennifer 
Published: February 2024

AbstractOlfactory elements of the human environment are essential with respect to culture, society, and heritage, and robust methodological approaches are necessary to identify and describe aspects of this sensory component. To accurately investigate and advance knowledge of olfactory composition of spaces and places, that is, a smellscape—an olfactory contextualized landscape—innovative methodologies such as smellwalks can be employed as part of the research approach. Despite the increasing use of smellwalks, there is no current standard methodology for this investigative method in practice.We identify major themes including variance of group size, participant versus researcher-led walking techniques, reinvention of smellwalking process, and methodological discussion and theory. Limitations and future research potential are suggested, including that of group dynamics, attribute focus, the extension of smellwalk attribute data beyond traditional hedonic attributes, and avenues for development of future processes and protocols for multisensory sensewalks.