bluuebunny/crossref_metadata_2025 huggingface dataset:
Evaluation of lossy compression algorithms using discrete cosine transform for sounding rocket vibration data
Authors: Pinto A C , Maciel M D , Pinho M S , Medeiros R R , Motta S F , Moraes A O
Published: October 2022

This work evaluates the performance of compression algorithms based on discrete cosine transform (DCT) when used to encode sounding rockets’ vibration signals. Different compression methods that use the three-step strategy (transform, quantization, and entropy encoder) are presented. The performances are evaluated using the relationship between the compression rate and distortion, the latter being measured using the peak signal-to-noise ratio (PSNR) and the difference observed in the power spectral density. The focus of the work is on vibration signals from rocket launches conducted by the Institute of Aeronautics and Space of the Brazilian Air Force. The obtained results present a great variation for the vibration data in the test set. Compressors operating with PSNR close to 50 dB can achieve very high compression rates (over 100) for low power signals. However, if the vibration signal strength increases significantly, the compression rate can be much lower. For the worst case in the test set (signal with the highest power), the work shows that the best proposed method needs a rate of 9.8 to achieve a PSNR of 48.2 dB. When compared to the performance of recently published DCT-based compression algorithms, the proposed technique shows significant improvements. Given a PSNR around 50 dB, for signal with moderate power, improvements above 100% are observed in compression rate.
Evaluation of single-sided nuclear magnetic resonance technology for usage in geosciences
Authors: Costabel Stephan , Hiller Thomas , Dlugosch Raphael , Kruschwitz Sabine , Müller-Petke Mike
Published: October 2022

Because of its mobility and ability to investigate exposed surfaces, single-sided (SiS) nuclear magnetic resonance (NMR) technology enables new application fields in geosciences. To test and assess its corresponding potential, we compare longitudinal (T
1) and transverse (T
2) data measured by SiS NMR with those of conventional geoscientific laboratory NMR. We use reference sandstone samples covering a broad range of pore sizes. Our study demonstrates that the lower signal-to-noise ratio of SiS NMR data generally tends to slightly overestimated widths of relaxation time distributions and consequently pore size distributions. While SiS and conventional NMR produce very similar T
1 relaxation data, unbiased SiS NMR results for T
2 measurements can only be expected for fine material, i.e. clayey or silty sediments and soils with main relaxation times below

0.05

s

. This limit is given by the diffusion relaxation rate due to the gradient in the primary magnetic field associated with the SiS NMR. Above that limit, i.e. for coarse material, the relaxation data is strongly attenuated. If considering the diffusion relaxation time of 0.2 s in the numerical data inversion process, the information content

>

0.2

s

is blurred over a range larger than that of conventional NMR. However, our results show that principle range and magnitudes of the relaxation time distributions are reconstructed to some extent. Regarding these findings, SiS NMR can be helpful to solve geoscientific issues, e.g. to assess the hydro-mechanical properties of the walls of underground facilities or to provide local soil moisture data sets for calibrating indirect remote techniques on the regional scale. The greatest opportunity provided by the SiS NMR technology is the acquisition of profile relaxation data for rocks with significant bedding structures at the μm scale. With this unique feature, SiS NMR can support the understanding and modeling of hydraulic and diffusional anisotropy behavior of sedimentary rocks.
Carbon black nanoparticles modified gelatin composite-based thin film for rapid-response humidity sensing
Authors: Yu Wei , Huang Chun , Xia Cao , Wang Zhuqing
Published: October 2022

Humidity monitoring is essential for food processing, pharmaceutical, and precision electronics industries. Conventional humidity sensors based on metal oxides and ceramics show an ideal response to variation humidity. However, long response time and complex manufacturing processes pose a challenge for their more comprehensive application and further development. Resistive polymers show promise in antistatic materials and sensor applications. In this study, gelatin composite, a popular water-soluble polymer, is mixed with carbon black nanoparticles for better humidity sensitivity. Using the state-of-the-art thin film deposition method, the designed interdigitated electrode is covered by a nano-scale thin film of the prepared composite film. The relative humidity (RH) range between 20.3% and 83.2% can be well detected according to the evaluation of a customized chemical vapors measurement system. Furthermore, an extreme linear relation and high sensitivity of 0.35 mV/%RH are achieved for the range from the RH of 20%–65.2%. Highly repeatable performance can be demonstrated by repeated experiments with several humidities. Rapid response and recovery features are found during the characterization, while the response and recovery time are lower than 10 s.
3D printed multi-material polylactic acid (PLA) origami-inspired structures for quasi-static and impact applications
Authors: Wickeler Anastasia L , Naguib Hani E
Published: October 2022

Origami patterns can be used to inspire the designs of structural materials with beneficial properties, such as low strength-to-weight ratios. This study explores the design, manufacturing, and mechanical properties of three different origami-inspired shapes, as well as three different material combinations for each shape, through dynamic impact testing and quasi-static compression testing. The commonly studied Miura origami pattern will be compared to two uncommon patterns: a square-based pattern and a triangular-based pattern. The samples are 3D printed and the material combinations include one rigid and one flexible polylactic acid (PLA) sample, and one multi-material configuration with flexible PLA crease areas and rigid PLA origami faces. The rigid square sample was the most effective at absorbing a single drop-weight impact load and the flexible Miura pattern was most effective at absorbing impact loads when multiple drops were performed on the same sample. The rigid triangular structure withstood the highest loads during the quasi-static compression testing. A finite element model of the quasi-static compression test was built to enhance the analysis of the various tested configurations.
Signature of superconducting onset in presence of large magnetoresistance in type-II Dirac semimetal candidate Ir2In8S
Authors: Malavi Pallavi , Kumar Prakash , Jakhar Navita , Singh Surjeet , Karmakar S
Published: October 2022

Since the discovery of type-II Dirac semimetal (DSM) as the potential candidate for topological superconductor, magneto-transport studies on diverse type-II DSMs have been of tremendous research interest. Here we report the structural and magneto-transport properties of type-II DSM candidate Ir2In8S under high pressure. With increasing pressure, this shows dramatic suppression of its characteristic large magneto-resistance, which is however partially regained upon release of pressure. No superconductivity has emerged with increasing pressures up to ∼20 GPa. However, in the pressure-released sample a significant resistivity drop below ∼4 K has been detected. The field dependent resistivity and dc magnetization measurements confirm this as superconducting onset. Ir2In8S thus becomes a unique system exhibiting large MR above the superconducting transition. X-ray diffraction results show that the ambient tetragonal structure (P42/mnm) remains stable up to ∼7 GPa, above which this undergoes a reversible structural transition into an orthorhombic structure (Pnnm). The observed enhanced residual resistivity and concurrent increase in carrier density of the normal metal state of the pressure-cycled sample indicate that the enhanced impurity scattering plays a significant role in the emergence of superconductivity.
Biharmonic (ω, 2ω) ionization of atoms by elliptically-polarized light. Carving the photoelectron angular distributions
Authors: Fritzsche S , Hofbrucker J
Published: October 2022

The biharmonic (ω, 2ω) photoionization of atomic inner-shell electrons opens up new perspectives for studying nonlinear light–atom interactions at intensities in the transition regime from weak to strong-field physics. In particular, the control of the frequency and polarization of biharmonic beams enables one to carve the photoelectron angular distribution and to enhance the resolution of ionization measurements by the (simultaneous) absorption of photons. Apart from its quite obvious polarization dependence, the photoelectron angular distributions are sensitive also to the (relative) intensity, the phase difference and the temporal structure of the incoming beam components, both at resonant and nonresonant frequencies. Here, we describe and analyze several characteristic features of biharmonic ionization in the framework of second-order perturbation theory and (so-called) ionization pathways, as they are readily derived from the interaction of inner-shell electrons with the electric-dipole field of the incident beam. We show how the photoelectron angular distribution and elliptical dichroism can be shaped in rather an unprecedented way by just tuning the properties of the biharmonic field. Since such fields are nowadays accessible from high-harmonic sources or free-electron lasers, these and further investigations might help extract photoionization amplitudes or the phase difference of incoming beams.
Probabilistic learning for pulsar classification
Authors: Andrianomena Sambatra
Published: October 2022

In this work, we explore the possibility of using probabilistic learning to identify pulsar candidates. We make use of Deep Gaussian Process (DGP) and Deep Kernel Learning (DKL). Trained on a balanced training set in order to avoid the effect of class imbalance, the performance of the models, achieving relatively high probability of differentiating the positive class from the negative one (roc-auc ∼ 0.98), is very promising overall. We estimate the predictive entropy of each model predictions and find that DKL is more confident than DGP in its predictions and provides better uncertainty calibration. Upon investigating the effect of training with imbalanced dataset on the models, results show that each model performance decreases with an increasing number of the majority class in the training set. Interestingly, with a number of negative class 10× that of positive class, the models still provide reasonably well calibrated uncertainty, i.e. an expected Uncertainty Calibration Error (UCE) less than 6%. We also show in this study how, in the case of relatively small amount of training dataset, a convolutional neural network based classifier trained via Bayesian Active Learning by Disagreement (BALD) performs. We find that, with an optimized number of training examples, the model — being the most confident in its predictions — generalizes relatively well and produces the best uncertainty calibration which corresponds to UCE = 3.118%.
Effect of the divertor configuration on the JET edge radial electric field
Authors: Silva C. , Solano E.R. , Hillesheim J.C. , Delabie E. , Birkenmeier G. , Gil L. , Giroud C. , Morales R.B. , Nina D. ,   JET Contributors
Published: October 2022

The role of the divertor configuration and divertor plasma physics on the L–H transition is poorly understood, leading to large uncertainties in predicting the L–H power threshold in future devices. This contribution reports on edge perpendicular plasma flow measurements by Doppler backscattering in JET L–H transition experiments with the outer divertor strike-point at different positions: horizontal target (HT), vertical target (VT), and in the corner configuration (between the HT and VTs). The edge perpendicular flow was found to be significantly affected by changes in the divertor configuration in the region inside the separatrix. Our results do not show evidence for the existence of a critical edge flow shear needed to achieve H-mode for different divertor configurations, with a larger shear observed for the VT configuration. No significant change in the shear flow and in the density fluctuation level is measured preceding the L–H transition in the region just inside the separatrix. The dynamics of the L–H transitions are also influenced by the divertor configuration with divertor oscillations (DOs) observed only in the HT configuration. Interestingly, DOs are associated with marked changes in the edge perpendicular flow around the separatrix.
Design, fabrication, optimization and characterization of memantine-loaded biodegradable PLGA nanoscaffolds for treatment of Alzheimer’s disease
Authors: Rani Varsha , Chawla Ruchi
Published: October 2022

This study aimed to design and develop nanoscaffolds for the controlled release of memantine by non-solvent-induced phase separation (N-TIPS) method. The development and optimization of nanoscaffolds was performed by Box–Behnken Design in which two independent formulation variables and one independent process variable: poly(lactic-co-glycolic acid) (PLGA) (X
1), Pluronics F-127 (X
2), and rotation speed (X
3) were used. The design provided 15 formulation designs which were prepared to determine the response: percentage porosity (Y
1) and drug loading (Y
2). Polynomial equations were generated and analyzed statistically to establish a relationship between independent and dependent variables and develop an optimal formulation with maximized porosity (%) and drug loading (%). The optimized formulation batch was prepared using 19.18% w/v PLGA, 4.98% w/v Pluronics at 500 rpm rotation speed and exhibited drug loading of 11.66% and porosity of 82.62%. Further, correlation between the independent and dependent variables were established and statistically analyzed by using model generated mathematical regression equations, ANOVA, residual plots, interaction plot, main effect plot, contour plot and response surface designs. The analysis of model showed the significant individual effect of PLGA and significant interactive effect of Pluronics F-127 and rotation speed on drug loading and porosity. Further, its physicochemical characterization, and in-vitro (drug release kinetics, and PAMPA study), ex-vivo (enzyme inhibition assay and pro-inflammatory cytokines study) and in-vivo (neurobehavioral and histological study) studies were performed to evaluate the potential of memantine-loaded nanoscaffolds in the treatment of Alzheimer’s disease (AD).
Winter runoff events pose an unquantified continental-scale risk of high wintertime nutrient export
Authors: Seybold Erin C , Dwivedi Ravindra , Musselman Keith N , Kincaid Dustin W , Schroth Andrew W , Classen Aimee T , Perdrial Julia N , Adair E Carol
Published: October 2022

Winters in snow-covered regions have warmed, likely shifting the timing and magnitude of nutrient export, leading to unquantified changes in water quality. Intermittent, seasonal, and permanent snow covers more than half of the global land surface. Warming has reduced the cold conditions that limit winter runoff and nutrient transport, while cold season snowmelt, the amount of winter precipitation falling as rain, and rain-on-snow have increased. We used existing geospatial datasets (rain-on-snow frequency overlain on nitrogen and phosphorous inventories) to identify areas of the contiguous United States (US) where water quality could be threatened by this change. Next, to illustrate the potential export impacts of these events, we examined flow and turbidity data from a large regional rain-on-snow event in the United States’ largest river basin, the Mississippi River Basin. We show that rain-on-snow, a major flood-generating mechanism for large areas of the globe (Berghuijs et al 2019 Water Resour. Res.
55 4582–93; Berghuijs et al 2016 Geophys. Res. Lett.
43 4382–90), affects 53% of the contiguous US and puts 50% of US nitrogen and phosphorus pools (43% of the contiguous US) at risk of export to groundwater and surface water. Further, the 2019 rain-on-snow event in the Mississippi River Basin demonstrates that these events could have large, cascading impacts on winter nutrient transport. We suggest that the assumption of low wintertime discharge and nutrient transport in historically snow-covered regions no longer holds. Critically, however, we lack sufficient data to accurately measure and predict these episodic and potentially large wintertime nutrient export events at regional to continental scales.
Gaps in adoption and implementation limit the current and potential effectiveness of zero-deforestation supply chain policies for soy
Authors: Gollnow Florian , Cammelli Federico , Carlson Kimberly M , Garrett Rachael D
Published: October 2022

Tropical deforestation continues despite global efforts to curb forest loss. Corporate zero-deforestation supply chain commitments (ZDCs) have the potential to address this deforestation, especially if strong state-led forest governance is absent. Yet, because ZDC adoption is limited to particular locations and supply chains, these commitments may fall short at reducing regional deforestation and protecting biodiverse ecosystems. Here, we leverage timeseries of spatially explicit corporate commodity sourcing data and ZDCs to assess the current and potential effect of ZDCs within soybean supply chains on forest loss and biodiversity. We focus on the Brazilian Amazon, where the first ZDC (soy moratorium (SoyM)) was implemented, and the Cerrado, where companies have adopted but not implemented ZDCs. We found that in the Amazon, SoyM signatories that controlled the market caused a 57% reduction in direct deforestation for soy from 2006 to 2015. In the Cerrado, if companies had implemented their ZDCs with the same relative effectiveness as in the Amazon, deforestation for soy could have been reduced by 46%. Thus, ZDC implementation in the Cerrado via stringent monitoring and enforcement could contribute substantially to forest and habitat conservation. Yet, incomplete ZDC adoption leaves >50% of soy-suitable forests and the biodiversity that they harbor outside the reach of ZDCs. To protect these forests, it is vital to incentivize more companies—including smaller, less publicly exposed traders—to make and implement ZDCs, while also promoting forest governance through public policy.
Changes in surface water dynamics across northwestern Canada are influenced by wildfire and permafrost thaw
Authors: Travers-Smith H , Lantz T C , Fraser R H , Kokelj S V
Published: October 2022

The abundance and distribution of surface water at high latitudes is shifting rapidly in response to both climate change and permafrost thaw. In particular, the expansion and drainage of lakes and ponds is widespread but spatially variable, and more research is needed to understand factors driving these processes. In this study we used medium resolution (30 m) remote sensing data to analyse changes in lake area in permafrost-rich lowland regions across northwestern Canada. First, we used the Global Surface Water Dataset developed by the GLAD research group to map the absolute area of different land–water transitions across a 1.4 million km2 study domain. Next, we selected six regional study areas representing a range of climatic, geologic and hydrologic conditions. Within these regional study areas, we used the Landsat satellite archive to map annual trends in the area of 27 755 lakes between 1985 and 2020. We trained a random forests model to classify lakes exhibiting significant increasing or decreasing trends in area, and assessed the relative importance of climate, disturbance and environmental variables in determining the direction of change. Our analysis shows that significant increases in lake area were 5.6 times more frequent than decreases during the study period. Wildfire and ground ice abundance were the most important predictors of the direction of change. Greater ground ice content was associated with regions that experienced increases in lake area, while wildfire was associated with regions that experienced decreases in lake area. The effects of climate, including trends in mean annual temperature and total annual precipitation were smaller than disturbance and environmental factors, indicating that climate has likely had indirect effects on lake area changes over our period of study.
Elevation dependence of projected hydro-climatic change in eastern Siberia
Authors: Finnegan Joseph M , Miller James R
Published: October 2022

Over the last several decades, eastern Siberia has experienced some of the largest temperature increases worldwide. We use the RCP8.5 simulation of the Community Climate System Model version 4 to examine how projected monthly changes in temperature and hydro-climatic variables in eastern Siberia depend on latitude and elevation. Temperature increases are largest at the highest latitudes in winter and late fall and are smaller at higher elevations. For precipitation and snowfall, there is a latitudinal dependence in autumn and spring, with precipitation, snowfall, and snow depth mostly increasing between 60 and 70° N. Although snow cover extent (SCE) decreases almost everywhere, the largest changes occur during the transition seasons which we define as spring and autumn, and the timing of the changes depends on latitude, elevation, and the specific month within seasons. The decreases in SCE are larger at lower latitudes and lower elevations in April and November and larger at higher elevations and higher latitudes in June and September. For the highest latitudes, snow depth actually increases, and increases more at higher elevations. These projections are generally consistent with those of four other climate models. For precipitation, all models project increases in non-summer seasons, but they are not consistent with respect to the direction of the elevation dependence of precipitation. We discuss the complex interactions among the projected changes in all the variables.
A vectorial binary Darboux transformation for the first member of the negative part of the AKNS hierarchy
Authors: Müller-Hoissen Folkert
Published: October 2022

Using bidifferential calculus, we derive a vectorial binary Darboux transformation for the first member of the ‘negative’ part of the AKNS hierarchy. A reduction leads to the first ‘negative flow’ of the NLS hierarchy, which in turn is a reduction of a rather simple nonlinear complex PDE in two dimensions, with a leading mixed third derivative. This PDE may be regarded as describing geometric dynamics of a complex scalar field in one dimension, since it is invariant under coordinate transformations in one of the two independent variables. We exploit the correspondingly reduced vectorial binary Darboux transformation to generate multi-soliton solutions of the PDE, also with additional rational dependence on the independent variables, and on a plane wave background. This includes rogue waves.
RF-EMF Measurement for 5G over C-band and mm-Wave frequency band: Exposure assessment and Procedures
Authors: Qahtan Wali S
Published: October 2022

The 5G network is intended to accommodate a significant quantity of mobile data traffic as well as a great number of wireless connections. It improves cost, power consumption, and offers ultra-low latency and ultra-high dependability to enable new services in a variety of sectors. However, the general public is concerned about the possible health dangers linked with 5G equipment's Radio Frequency (RF) radiation, and numerous localities are actively lobbying to prevent 5G implementation. This aims to demonstrate the cause of increasing the amount of RF-EMF exposure, and the international standards of RF-EMF accepted limits. In addition, it aims to illustrate some measurement procedures to conduct RF-EMF measurement for different researchers and two other procedures and the result of the maximum exposure emitted by a 5G base station operating on 3.5 GHz and the mm-Wave frequency band by the author of this paper.
Recent trends for 5G in vitro exposure systems dosimetry and setup
Authors: Arnaud-Cormos D , Orlacchio R , Leveque P
Published: October 2022

5G wireless communications networks are being massively studied and developed. This new technology introduces new operating frequencies and employs smart adaptative antennas that allow focusing electromagnetic waves in specific directions. Bioelectromagnetic investigations to assess exposure and interactions with living entities of these new 5G signals are carried out. This contribution aims to present current trends on exposure systems designs for bioelectromagnetic studies with associated computational and experimental dosimetry. The extension to 5G signals of classical exposure systems such as transverse electromagnetic cells (TEM cells) and new innovative designs are discussed.
Design, implementation and preliminary testing of an automated system for the evaluation of ionospheric channels
Authors: Șorecău E , Șorecău M , Craiu N , Sârbu A , Bechet P
Published: October 2022

Radio communications in the High Frequency (HF) range are used to transmit information over long distances between one or more correspondents. Techniques and methodsto improve the capacity and reliability of HF communications become key objectives as they are generally limited to narrow bandwidths and low transfer rates. This work aims to implement an automated system for real-time measurement of ionospheric radio channel parameters under Near Vertical Incidence Skywave (NVIS) propagation conditions using Software Define Radio (SDR) platforms. Preliminary testing of the system was carried out both under laboratory conditions using signal generators and high-performance spectral vector analyzers and under real propagation conditions by installation at the established sites. The results showed that the system is capable of performing real-time measurements of signal power, noise power and calculating signal-to-noise ratio for bandwidths up to 24 kHz.
Limitations of using electro-optical probes for the measurement of the electromagnetic field emitted by the new generations of wireless communication devices
Authors: Sârbu A , Bechet P , Miclăuş S
Published: October 2022

The rapid evolution of communication standards caused a paradigm shift in electromagnetic field (EMF) measurement campaigns, as exposure is more likely to take place in the proximity of the device. With the increased spatial variability of EMF exposure, electro-optical (EO) technology stands out as a promising alternative to conventional near field measurement instrumentation due to their miniature sizes and dielectric structure that does not interfere with the measured field. Motivated by the recent progress in the EO sensing technology, it is this article purpose to quantify the limitations of using a set of commercially available EO probes for measurement of EMF emitted by an IEEE 802.11ax router and a VoLTE mobile phone. To our knowledge, this is the first attempt to characterize the capabilities of this emerging sensing technology for EMF exposure assessment in real world communication situations. Present findings suggest that the sensitivity of the investigated EO probes is insufficient for measuring broadband signals at field levels that characterize state-of-the-art communication devices used by the public in common usage scenarios. This work also documents the EO probes suitability and response with respect to frequency, electric field strength and signal bandwidth.
Investigation of a radio-frequency temperature transducer with a thermosensitive resistive element based on a complex compound of heterometallic β-diketonate
Authors: Osadchuk O V , Osadchuk V S , Osadchuk I O , Semenov A O , Martyniuk V V , Prytula M O
Published: October 2022

The article considers a new electrical circuit of a microelectronicradio-frequency measuring temperature transducer with a thermosensitive resistive element based on a complex compound of heterometallicβ-diketonate.The main characteristics of the researched radio-frequency temperature transducer with a thermosensitive resistive element based on a complex compound of heterometallic β-diketonate are obtained: the dependences of the active and reactive components of the full impedance of the radio-frequency measuring temperature transducer, the conversion function and the sensitivity equation.
Expending the power of artificial intelligence in preclinical research: an overview
Authors: Diaconu A , Cojocaru F D , Gardikiotis I , Agrigoroaie L , Furcea D M , Pasat A , Suciu G , Rezuş C , Dodi G
Published: October 2022

Artificial intelligence (AI) is described as the joint set of data entry, able to receive inputs, interpret and learn from such feedbacks, and display related and flexible independent actions that help the entity reach a specific aim over a period of time. By extending its health-care applications continuously, the ultimate AI target is to use machine simulation of human intelligence processes such as learning, reasoning, and self-correction, to mimic human behaviour. AI is extensively used in diverse sectors of medicine, including clinical trials, drug discovery and development, understanding of target-disease associations, disease prediction, imaging, and precision medicine. In this review, we firstly describe the limitations and challenges of the AI tools and techniques utilized in medicine, followed by current uses and applications of AI in the translational field, highlighting the cardio-renal preclinical models with potential to contribute to future clinical research.
Convergence of restricted additive Schwarz with impedance transmission conditions for discretised Helmholtz problems
Authors: Gong Shihua , Graham Ivan , Spence Euan
Published: October 2022

The Restricted Additive Schwarz method with impedance transmission conditions, also known as the Optimised Restricted Additive Schwarz (ORAS) method, is a simple overlapping one-level parallel domain decomposition method, which has been successfully used as an iterative solver and as a preconditioner for discretised Helmholtz boundary-value problems. In this paper, we give, for the first time, a convergence analysis for ORAS as an iterative solver—and also as a preconditioner—for nodal finite element Helmholtz systems of any polynomial order. The analysis starts by showing (for general domain decompositions) that ORAS is an unconventional finite element approximation of a classical parallel iterative Schwarz method, formulated at the PDE (non-discrete) level. This non-discrete Schwarz method was recently analysed in [Gong, Gander, Graham, Lafontaine, and Spence, Convergence of parallel overlapping domain decomposition methods for the Helmholtz equation], and the present paper gives a corresponding discrete version of this analysis. In particular, for domain decompositions in strips in 2-d, we show that, when the mesh size is small enough, ORAS inherits the convergence properties of the Schwarz method, independent of polynomial order. The proof relies on characterising the ORAS iteration in terms of discrete ‘impedance-to-impedance maps’, which we prove (via a novel weighted finite-element error analysis) converge as

h
→
0

h\rightarrow 0

in the operator norm to their non-discrete counterparts.
Quantum variance for dihedral Maass forms
Authors: Huang Bingrong , Lester Stephen
Published: October 2022

We establish an asymptotic formula for the weighted quantum variance of dihedral Maass forms on

Γ
0

(
D
)
∖

H

\Gamma _0(D) \backslash \mathbb H

in the large eigenvalue limit, for certain fixed

D
D

. As predicted in the physics literature, the resulting quadratic form is related to the classical variance of the geodesic flow on

Γ
0

(
D
)
∖

H

\Gamma _0(D) \backslash \mathbb H

, but also includes factors that are sensitive to underlying arithmetic of the number field

Q

(

D

)

\mathbb Q(\sqrt {D})

.
Compact retractions and Schauder decompositions in Banach spaces
Authors: Hájek Petr , Medina Rubén
Published: October 2022

Let

X
X

be a separable Banach space. We give an almost characterization of the existence of a Finite Dimensional Decomposition (FDD for short) for

X
X

in terms of Lipschitz retractions onto generating compact subsets

K
K

of

X
X

.

In one direction, if

X
X

admits an FDD then we construct a Lipschitz retraction onto a small generating convex and compact set

K
K

. On the other hand, we prove that if

X
X

admits a “small” generating compact Lipschitz retract then

X
X

has the

π
\pi

-property. It is still unknown if the

π
\pi

-property is isomorphically equivalent to the existence of an FDD.

For dual Banach spaces this is true, so our results give a characterization of the FDD property for dual Banach spaces

X
X

.

We give an example of a small generating convex compact set which is not a Lipschitz retract of

C
[
0
,
1
]

C[0,1]

, although it is contained in a small convex Lipschitz retract and contains another one.

We characterize isomorphically Hilbertian spaces as those Banach spaces

X
X

for which every convex and compact subset is a Lipschitz retract of

X
X

.

Finally, we prove that a convex and compact set

K
K

in any Banach space with a Uniformly Rotund in Every Direction norm is a uniform retract, of every bounded set containing it, via the nearest point map.
KAP is the neuronal organelle adaptor for Kinesin-2 KIF3AB and KIF3AC
Authors: Garbouchian Alex , Montgomery Andrew C. , Gilbert Susan P. , Bentley Marvin
Published: October 2022

The neuronal functions of KIF3AB and KIF3AC are not well understood. A novel microscopy-based assay was developed to define protein-protein interactions in intact neurons, and it was found that KAP binds both. Live-cell imaging in cultured hippocampal neurons was used to define the localization and trafficking parameters of KIF3AB and KIF3AC organelle populations.
Proactive Health Support: a randomised controlled trial of telephone-based self-management support for persons at risk of hospital admission
Authors: Benthien Kirstine Skov , Rasmussen Knud , Nielsen Camilla Palmhøj , Kidholm Kristian , Grønkjær Mette , Toft Ulla
Published: October 2022

Background

Persons with frequent hospital admissions have a disease burden that may exceed their self-management skills. The evidence base of telephone-based interventions to support self-management is poor with mixed results. The aim of this study is to evaluate the effect of Proactive Health Support (PaHS): telephone-based self-management support for persons with risk of hospitalizations.

Methods

This study is a national randomised controlled trial of PaHS versus usual universal tax-funded healthcare. Participants were persons at risk of emergency hospital admissions. The intervention began with a physical start-up session followed by telephone sessions of self-management support. The two co-primary outcomes were Health-Related Quality of Life (HRQoL) (Mental Health Component Summary Score of SF36v2) analysed with mixed models and hospital admissions analysed with Poisson regression at 6 months. Secondary outcomes were at 3- and 12-month follow-up and disease subgroup analyses.

Results

During the study period, 6,402 persons were randomised (3,190 intervention, 3,212 control). HRQoL was significantly improved at 6 months (Est. 1.4992, P = <0.0001) and at 3 and 12 months on all 10 scales. There was no overall effect on hospital admissions at 6 months with an adjusted estimate of 0.0074 (P = 0.8691). Persons with diabetes had significant improvement of HRQoL and reduced hospital admissions.

Conclusions

The PaHS intervention improved HRQoL for all participants and reduced hospital admissions for persons with diabetes only.
Line graph attention networks for predicting disease-associated Piwi-interacting RNAs
Authors: Zheng Kai , Zhang Xin-Lu , Wang Lei , You Zhu-Hong , Zhan Zhao-Hui , Li Hao-Yuan
Published: October 2022

PIWI proteins and Piwi-Interacting RNAs (piRNAs) are commonly detected in human cancers, especially in germline and somatic tissues, and correlate with poorer clinical outcomes, suggesting that they play a functional role in cancer. As the problem of combinatorial explosions between ncRNA and disease exposes gradually, new bioinformatics methods for large-scale identification and prioritization of potential associations are therefore of interest. However, in the real world, the network of interactions between molecules is enormously intricate and noisy, which poses a problem for efficient graph mining. Line graphs can extend many heterogeneous networks to replace dichotomous networks. In this study, we present a new graph neural network framework, line graph attention networks (LGAT). And we apply it to predict PiRNA disease association (GAPDA). In the experiment, GAPDA performs excellently in 5-fold cross-validation with an AUC of 0.9038. Not only that, it still has superior performance compared with methods based on collaborative filtering and attribute features. The experimental results show that GAPDA ensures the prospect of the graph neural network on such problems and can be an excellent supplement for future biomedical research.
Deep learning radiomics under multimodality explore association between muscle/fat and metastasis and survival in breast cancer patients
Authors: Miao Shidi , Jia Haobo , Cheng Ke , Hu Xiaohui , Li Jing , Huang Wenjuan , Wang Ruitao
Published: October 2022

Sarcopenia is correlated with poor clinical outcomes in breast cancer (BC) patients. However, there is no precise quantitative study on the correlation between body composition changes and BC metastasis and survival. The present study proposed a deep learning radiomics (DLR) approach to investigate the effects of muscle and fat on distant metastasis and death outcomes in BC patients. Image feature extraction was performed on 4th thoracic vertebra (T4) and 11th thoracic vertebra (T11) on computed tomography (CT) image levels by DLR, and image features were combined with clinical information to predict distant metastasis in BC patients. Clinical information combined with DLR significantly predicted distant metastasis in BC patients. In the test cohort, the area under the curve of model performance on clinical information combined with DLR was 0.960 (95% CI: 0.942–0.979, P < 0.001). The patients with distant metastases had a lower pectoral muscle index in T4 (PMI/T4) than in patients without metastases. PMI/T4 and visceral fat tissue area in T11 (VFA/T11) were independent prognostic factors for the overall survival in BC patients. The pectoralis muscle area in T4 (PMA/T4) and PMI/T4 is an independent prognostic factor for distant metastasis-free survival in BC patients. The current study further confirmed that muscle/fat of T4 and T11 levels have a significant effect on the distant metastasis of BC. Appending the network features of T4 and T11 to the model significantly enhances the prediction performance of distant metastasis of BC, providing a valuable biomarker for the early treatment of BC patients.
Inflammatory brain injury after severe viral infection is not unique to COVID-19
Authors: Bauer Angelika , Reindl Markus
Published: October 2022

This scientific commentary refers to ‘Brain injury in COVID-19 is associated with dysregulated innate and adaptive immune responses’ by Needham et al. (https://doi.org/10.1093/brain/awac321).
Neighbourhood opposition to relocation of people with disabilities in Lithuania: ‘fake ethics’ in the community discourse
Authors: Mataityte-Dirziene Jurga , Geniene Rasa , Gevorgianiene Violeta , Sumskiene Egle
Published: October 2022

Like other post-Soviet countries, Lithuania inherited large residential care institutions for people with intellectual and psychosocial disabilities. The reform aimed at relocating these people to community-based group homes has been met with opposition, and the communities see it as a threat to their habitus. The news media has become an important actor in this process, in its attempt to reproduce public discourse accompanying such social change.

Research using case study methodology was implemented to explore the ethical aspects of community participation in deinstitutionalization. It involved observation of different public meetings between central government and communities, content analysis of gathered data and discourse analysis of the news media publications on a resonant case of opposition to the deinstitutionalization. Although other accounts of ethics privilege those of the individual worker or organization, this article looks at the ethics of multiple actors—including the community as an actor, and thus understands ethics as multiple, dynamic and intersecting. In this sense, the account is less about individual workers and more about communities and how they change and develop.

Different ethical attitudes of the main actors—Ministry of Social Security and Labour, local authorities, social care institutions and communities, shaping public and news media discourses about deinstitutionalization—were identified in the data collected. Initial unethical community discourse was met with critique from the society at large, and it forced communities to switch to ‘fake’ ethics arguments for opposing deinstitutionalization. Fake ethics was manifested as intentional disguise of prejudices against people with disabilities through citing ethical phrases of the Convention on the Rights of Persons with Disabilities, even though these words contradicted the actions of all parties participating in the discourse. Moreover, people with disabilities themselves, directly affected by the community prejudices, were absent both in public and media discourses, and this entails a risk for their successful inclusion into the community.
Settling Preference of Two Coexisting Aphid Species on the Adaxial and Abaxial Surfaces of Walnut Leaves
Authors: Wang Ting , Zhang Ping , Ahmed Zeeshan , Gao Guizhen , Ali Abid , Lu Zhaozhi
Published: October 2022

Walnut dusky-veined aphid Panaphis juglandis (Goeze) and walnut green aphid Chromaphis juglandicola (Kaltenbach) cause economic losses and co-occur on walnut trees, but they have separate niche. Panaphis juglandis feeds on the upper (adaxial) surface of leaves while C. juglandicola feeds on the lower (abaxial) surface. Field surveys and controlled experiments in the field and laboratory were conducted to determine microhabitat selection by P. juglandis and C. juglandicola and the factors associated with this behavior. In the field, the two aphid species colonized a leaflet as follows: P. juglandis only, 16.5%; C. juglandicola only, 44.5%; and both species on same leaflet, 39%. C. juglandicola settled on the abaxial surface earlier than P. juglandis settled on the adaxial surface. P. juglandis showed the highest reproduction rate when they were in the erect position on the adaxial surface. C. juglandicola exhibited the highest reproduction rate when they were inverted and on the abaxial surface. Under a light intensity of 50,000 lux, 60.5% of C. juglandicola remained on the illuminated surface, while P. juglandis did not move from the illuminated surface. Through field and laboratory experiments, we found that P. juglandis preferred to settle on the adaxial surface and C. juglandicola preferred to settle on the abaxial surface. Leaf surface, gravity, and light were three physical factors affecting microhabitat selection by the two aphid species but light intensity was the key factor. This information will help to better understand the habitats of two aphid species, which may be helpful for walnut aphids management strategies such as the usage of insecticides option and spraying.
Regression discontinuity designs in agricultural and environmental economics
Authors: Wuepper David , Finger Robert
Published: October 2022

Regression discontinuity designs (RDD) are increasingly being employed in agricultural and environmental economics to identify causal effects. Here, we showcase recent applications, identify best practices, discuss commonly invoked identifying assumptions and show how these can be tested. We discuss basic empirical issues and more advanced topics, including how to exploit the availability of panel data, models to explain heterogeneous treatment effects and extrapolation of local estimates. Moreover, we show how agricultural economists can leverage RDD in combination with remote sensing and environmental modelling. Finally, we highlight three areas of emerging opportunities and draw conclusions for research and policy.
Aldosterone in chronic kidney disease and renal outcomes
Authors: Verma Ashish , Vaidya Anand , Subudhi Sonu , Waikar Sushrut S
Published: October 2022

Aims

Randomized controlled trials have demonstrated the efficacy of mineralocorticoid receptor (MR) antagonism in delaying chronic kidney disease (CKD) progression in diabetes; however, they have not investigated the role of aldosterone or whether these beneficial effects could be achieved in individuals without diabetes.

Methods and results

The association between serum aldosterone concentrations and kidney disease progression was investigated among 3680 participants in the Chronic Renal Insufficiency Cohort. The primary outcome was CKD progression [defined as the composite of 50% decline in estimated glomerular filtration rate (eGFR) or end-stage kidney disease, whichever occurred first]. The associations between serum aldosterone and kidney disease outcomes were assessed using Cox proportional hazard models. At baseline, higher aldosterone concentrations were associated with a lower eGFR, lower serum potassium, greater urinary potassium, and protein excretion. Over a median follow-up of 9.6 years, 1412 participants developed CKD progression. In adjusted models, each doubling of serum aldosterone was associated with a 11% increased risk of CKD progression [hazard ratio (HR) 1.11, 95% confidence interval (CI) 1.04–1.18]. Individuals with the highest quartile of serum aldosterone had a 45% increased risk of CKD progression (HR 1.45, 95% CI 1.22–1.73) compared with the lowest quartile. The risk for CKD progression was similar regardless of whether patients had concomitant diabetes (P-interaction = 0.10).

Conclusion

Higher serum aldosterone levels among individuals with CKD are independently associated with an increased risk for kidney disease progression, irrespective of concomitant diabetes. These findings provide mechanistic support for MR antagonists in delaying CKD progression and suggest that they may also have a role in those without diabetes.