bluuebunny/crossref_metadata_2025 huggingface dataset:
ACnerf: enhancement of neural radiance field by alignment and correction of pose to reconstruct new views from a single x-ray*
Authors: Sun Mengcheng , Zhu Yu , Li Hangyu , Ye Jiongyao , Li Nan
Published: January 2024

Objective. Computed tomography (CT) is widely used in medical research and clinical diagnosis. However, acquiring CT data requires patients to be exposed to considerable ionizing radiance, leading to physical harm. Recent studies have considered using neural radiance field (NERF) techniques to infer the full-view CT projections from single-view x-ray projection, thus aiding physician judgment and reducing Radiance hazards. This paper enhances this technique in two directions: (1) accurate generalization capabilities for control models. (2) Consider different ranges of viewpoints. Approach. Building upon generative radiance fields (GRAF), we propose a method called ACnerf to enhance the generalization of the NERF through alignment and pose correction. ACnerf aligns with a reference single x-ray by utilizing a combination of positional encoding with Gaussian random noise (latent code) obtained from GRAF training. This approach avoids compromising the 3D structure caused by altering the generator. During inference, a pose judgment network is employed to correct the pose and optimize the rendered viewpoint. Additionally, when generating a narrow range of views, ACnerf employs frequency-domain regularization to fine-tune the generator and achieve precise projections. Main results. The proposed ACnerf method surpasses the state-of-the-art NERF technique in terms of rendering quality for knee and chest data with varying contrasts. It achieved an average improvement of 2.496 dB in PSNR and 41% in LPIPS for 0°–360° projections. Additionally, for −15° to 15° projections, ACnerf achieved an average improvement of 0.691 dB in PSNR and 25.8% in LPIPS. Significance. With adjustments in alignment, inference, and rendering range, our experiments and evaluations on knee and chest data of different contrasts show that ACnerf effectively reduces artifacts and aberrations in the new view. ACnerf’s ability to recover more accurate 3D structures from single x-rays has excellent potential for reducing damage from ionising radiation in clinical diagnostics.
Electromechanical coupling of a 3.88 W harvester with circumferential step-size field: modeling, validation and self-powered wearable applications
Authors: Peng Yan , Xu Wanqing , Gong Ying , Peng Xuzhang , Li Zhongjie
Published: January 2024

The fast advances in wearable electronic devices require clean and wearable power sources. This study presents a wearable electromagnetic energy harvester (EMEH) with high output performance mounted on the knee to obtain human vibration energy. The design forms a circumferential step-change magnetic field with high electromechanical coupling for high-efficiency energy conversion. We first formulate a theoretical model and simulate the analytical voltage via MATLAB. To predict the output performance of the EMEH, we conduct simulations via ANSYS. Subsequently, experiments are conducted to explore the output performance of the harvester in terms of the voltage, the output power, and the charging rate. The prototype generates a peak power of 3.88 W with a 449 Ω resistor under the excitation of 2.0 Hz. Additionally, the prototype charges a battery to 33.9% within 300 s at a running speed of 8 km h−1. This study provides a new perspective for advancing the development of watt-level self-powered wearables.
Andreev reflection in Euler materials
Authors: Morris Arthur S , Bouhon Adrien , Slager Robert-Jan
Published: January 2024

Many previous studies of Andreev reflection have demonstrated that unusual effects can occur in media which have a nontrivial bulk topology. Following this line of investigation, we study Andreev reflection by analysing a simple model of a bulk node with a generic winding number n > 0, where the even cases directly relate to topological Euler materials. We find that the magnitudes of the resultant reflection coefficients depend strongly on whether the winding is even or odd. Moreover this parity dependence is reflected in the differential conductance curves, which are highly suppressed for n even but not n odd. This gives a possible route through which the recently discovered Euler topology could be probed experimentally.
Strongly coupled fermionic probe for nonequilibrium thermometry
Authors: Ravell Rodríguez Ricard , Mehboudi Mohammad , Horodecki Michał , Perarnau-Llobet Martí
Published: January 2024

We characterise the measurement sensitivity, quantified by the quantum Fisher information (QFI), of a single-fermionic thermometric probe strongly coupled to the sample of interest, a fermionic bath, at temperature T. For nonequilibrium protocols, in which the probe is measured before reaching equilibrium with the sample, we find new behaviour of the measurement sensitivity arising due to non-Markovian dynamics. First, we show that the QFI displays a highly non-monotonic behaviour in time, in contrast to the Markovian case where it grows monotonically until equilibrium, so that non-Markovian revivals can be exploited to reach a higher QFI. Second, the QFI rate is maximised at a finite interrogation time

t
∗

, which we characterize, in contrast to the solution

t
∗

→
0

known in the Markovian limit (Pavel Sekatski and Martí Perarnau-Llobet 2022 Quantum
6 869). Finally, we consider probes make up of few fermions and discuss different collective enhancements in the measurement precision.
Time series synchronization in cross-recurrence networks: uncovering a homomorphic law across diverse complex systems
Authors: Song Shijia , Li Handong
Published: January 2024

Exploring the synchronicity between time series, especially the similar patterns during extreme events, has been a focal point of research in academia. This is due to the fact that such special dependence occurring between pairs of time series often plays a crucial role in triggering emergent behaviors in the underlying systems and is closely related to systemic risks. In this paper, we investigate the relationship between the synchronicity of time series and the corresponding topological properties of the cross-recurrence network (CRN). We discover a positive linear relationship between the probability of pairwise time series event synchronicity and the corresponding CRN’s clustering coefficient. We first provide theoretical proof, then demonstrate this relationship through simulation experiments by coupled map lattices. Finally, we empirically analyze three instances from financial systems, Earth’s ecological systems, and human interactive behavioral systems to validate that this regularity is a homomorphic law in different complex systems. The discovered regularity holds significant potential for applications in monitoring financial system risks, extreme weather events, and more.
Bifurcation analysis of a tristable system with fractional derivative under colored noise excitation
Authors: Guo Qin , Ning Lijuan
Published: January 2024

Stochastic bifurcation has received much attention recently and is of great significance in the research on the dynamics of nonlinear systems. In this paper, we study the bifurcation of a self-sustained tristable system containing fractional derivative under the excitation of two colored noises, where the self-sustained tristable system consists of stable limit cycles and a stable state. The multiple scale method and generalized harmonic function are used to convert the original system into an equal system without obvious time delay and fractional derivative. Then the stationary probability density function (SPDF) of the system is obtained by using the stochastic averaging method to discuss stochastic bifurcation. Based on singularity theory, the equation satisfying amplitude is obtained to derive the corresponding bifurcation diagram. From the bifurcation analysis of the system, it is revealed that fractional order, fractional coefficient, and the intensity and correlation time of colored noise can be utilized as bifurcation parameters, causing peculiar stochastic bifurcation phenomena and regulating the output of the system, as well as the relatively big colored noise intensity and relatively small correlation time facilitate the realization of large magnitude limit cycle. Monte Carlo numerical results verify the validity of the theoretical approach. In addition, appropriately changing the delayed feedback parameter helps to govern the bifurcation range and causes richer bifurcation phenomena. The results of this paper contribute to a better understanding of self-sustained tristable systems with fractional derivative and may provide reference value in resolving the problems of chattering in high-speed aircraft and applications to viscoelastic materials.
Tunable electronic and optical properties of WSe2/Si2H heterojunction via electric field
Authors: Liang Xianxiao , Zhao Hongquan , Zhao Yang , Deng Xueyi , Xiao Zeyun , Peng Xiaoyu , Yuan Hongkuan , Shi Xuan
Published: January 2024

Van der Waals heterojunctions based on two-dimensional (2D) materials hold great potential applications in photodetectors. Using the density functional theory (DFT) method, the structures, electronic and optical properties of van der Waals WSe2/Si2H heterojunction are investigated. 1.32 eV of indirect bandgap is calculated from the WSe2/Si2H heterojunction, which is 0.3 eV and 0.1 eV smaller than those of its monolayer WSe2 and Si2H. This contributes to the photocarrier generations, and the Type-II heterojunction also benefits to the separation of the photogenerated electron and hole pairs. A significant hole mobility 1.05 × 104 cm2 V−1 s−1 of the heterojunction along the y-direction is obtained. Moreover, a high Ultraviolet light (UV) absorption coefficient is presented in the heterojunction. The heterojunction transforms to Type-I under a vertical electric field, with the bandgap, orientation and amount of transfer electrons modulated sufficiently. As a result, the optical absorption coefficient of the heterojunction is also improved significantly, leading to the red-shift of the absorption spectrum. These excellent properties address the WSe2/Si2H heterojunction one of the good candidates for UV detectors.
Patchy screening of the CMB from dark photons
Authors: Pîrvu Dalila , Huang Junwu , Johnson Matthew C.
Published: January 2024

We study anisotropic (patchy) screening induced by the resonant conversion of cosmic microwave background (CMB) photons into dark-sector massive vector bosons (dark photons) as they cross non-linear large scale structure (LSS). Resonant conversion takes place through the kinetic mixing of the photon with the dark photon, one of the simplest low energy extensions to the Standard Model. In the early Universe, resonant conversion can occur when the photon plasma mass, obtained as the photon propagates through the ionized interstellar and intergalactic media, matches the dark photon mass. After the epoch of reionization, resonant conversion occurs mainly in the ionized gas that occupies virialized dark matter halos, for a range of dark photon masses between 10-13 eV ≲ m
A' ≲ 10-11 eV. This leads to new CMB anisotropies that are correlated with LSS, which we refer to as patchy dark screening, in analogy with anisotropies from Thomson screening. Its unique frequency dependence allows it to be distinguished from the blackbody CMB. In this paper, we use a halo model approach to predict the imprint of dark screening on the CMB temperature and polarization anisotropies, as well as their correlation with LSS. We then examine the two- and three-point correlation functions of the dark-screened CMB, as well as correlation functions between CMB and LSS observables, to project the sensitivity of future measurements to the kinetic mixing parameter and dark photon mass. We demonstrate that an analysis with existing CMB data can improve upon current constraints on the kinetic mixing parameter by two orders of magnitude with the two-point correlation functions, while data from upcoming CMB experiments and LSS surveys can further improve the reach by another order of magnitude with two- and three-point correlation functions.
Phase diagram of muonium hydride: the significant effect of dimensionality
Authors: Hu Jieru , Boninsegni Massimo
Published: January 2024

We carry out a theoretical investigation of the low-temperature phase diagram of muonium hydride in two dimensions, using numerical simulations. It is shown that the phase diagram of this substance is qualitatively different in two and three dimensions. Specifically, while in three dimensions it is essentially identical to that of parahydrogen, i.e., only displaying a single (crystalline) phase. In two dimensions it is very similar to that of 4He, with an equilibrium liquid phase that turns superfluid at a temperature as high as ∼2.2 K, and crystallizes under applied pressure. This is a well-described case of a continuous-space condensed matter system whose ground state equilibrium phase is qualitatively altered by dimensional reduction.
Proton-neutron symplectic model description of 106Cd
Authors: Ganev H. G.
Published: January 2024

In this study, a microscopic shell-model description of the low-lying collective states in the weakly deformed nucleus

Cd within the recently proposed microscopic version of the Bohr-Mottelson model is provided. A good description of the excitation energies of the lowest ground, γ, and β quasibands is obtained without the adjustable kinetic energy term. Furthermore, γ degrees of freedom are shown to play a crucial role in the description of spectroscopy of this nucleus. A modified

preserving high-order interaction is used to produce a γ-unstable type of odd-even staggering, observed experimentally between the states of the quasi-γ band. The current approach enables the characterization of observed intraband and interband quadrupole collectivity. The findings of this study propose an alternative interpretation of the fundamental question regarding the nature of low-energy vibrations, as well as the emergence of deformation and collectivity in weakly deformed atomic nuclei.
MEP and TEP features variability: is it just the brain-state?
Authors: Bigoni Claudia , Pagnamenta Sara , Cadic-Melchior Andéol , Bevilacqua Michele , Harquel Sylvain , Raffin Estelle , Hummel Friedhelm C
Published: January 2024

Objective. The literature investigating the effects of alpha oscillations on corticospinal excitability is divergent. We believe inconsistency in the findings may arise, among others, from the electroencephalography (EEG) processing for brain-state determination. Here, we provide further insights in the effects of the brain-state on cortical and corticospinal excitability and quantify the impact of different EEG processing. Approach. Corticospinal excitability was measured using motor evoked potential (MEP) peak-to-peak amplitudes elicited with transcranial magnetic stimulation (TMS); cortical responses were studied through TMS-evoked potentials’ TEPs features. A TMS-EEG-electromyography (EMG) dataset of 18 young healthy subjects who received 180 single-pulse (SP) and 180 paired pulses (PP) to determine short-intracortical inhibition (SICI) was investigated. To study the effect of different EEG processing, we compared the brain-state estimation deriving from three published methods. The influence of presence of neural oscillations was also investigated. To evaluate the effect of the brain-state on MEP and TEP features variability, we defined the brain-state based on specific EEG phase and power combinations, only in trials where neural oscillations were present. The relationship between TEPs and MEPs was further evaluated. Main results. The presence of neural oscillations resulted in more consistent results regardless of the EEG processing approach. Nonetheless, the latter still critically affected the outcomes, making conclusive claims complex. With our approach, the MEP amplitude was positively modulated by the alpha power and phase, with stronger responses during the trough phase and high power. Power and phase also affected TEP features. Importantly, similar effects were observed in both TMS conditions. Significance. These findings support the view that the brain state of alpha oscillations is associated with the variability observed in cortical and corticospinal responses to TMS, with a tight correlation between the two. The results further highlight the importance of closed-loop stimulation approaches while underlining that care is needed in designing experiments and choosing the analytical approaches, which should be based on knowledge from offline studies to control for the heterogeneity originating from different EEG processing strategies.
Observation of resonant tearing mode induced by energetic-ion redistribution due to sawtooth collapse in HL-2A NBI plasmas
Authors: Yu L.M. , Zhu X.L. , Chen W. , Shi P.W. , Ji X.Q. , Shi Z.B. , Ma R.R. , He X.F. , Yan X.Y. , He X.X. , Hou Y.M. , Li Y.G. , Huang Y. , Deng W. , Gou W.P. , Cao J.Y. , Zhang Y.P. , Liu Yi , Yu D.L. , Wang Z.X. , Zhong W.L. , Xu M.
Published: January 2024

Recent observations on the HL-2A tokamak give new experimental evidence of resonant tearing modes (r-TMs) caused by the redistribution of energetic ions (EIs) due to sawtooth collapses in neutral beam injection plasmas. The

m

/

n
=
2

/

1

(m and n are the poloidal and toroidal mode numbers) r-TMs with frequencies chirping down rapidly are found after strong bursts of fishbone modes and closely followed strong sawtooth collapses. The frequencies of fishbone modes and r-TMs chirp down from 10 to 7 kHz and 5 to 2 kHz rapidly, higher and lower than the 4–6 kHz existing weak resistive TMs. The fishbone modes propagate in ion diamagnetic drift directions in poloidal. In contrast, r-TMs propagate in the electron diamagnetic drift direction, though r-TMs are excited by EIs. It is suggested that counter-passing EIs, which originated from redistribution of EIs due to fishbone modes and combined with sawtooth collapses, excite r-TMs. Simulation results from the M3D-K code reveal that the counter-passing EIs play an important role in the excitation of r-TMs. The results can help broaden understanding of the interaction mechanisms between energetic particles and TMs, and open up a new perspective on the excitation mechanism of r-TMs.
On multiple solutions of the Grad–Shafranov equation
Authors: Ham C.J. , Farrell P.E.
Published: January 2024

The Grad–Shafranov equation (GSE) for axisymmetric MHD equilibria is a nonlinear, scalar PDE which in principle can have zero, one or more non-trivial solutions. The conditions for the existence of multiple solutions has been little explored in the literature so far. We develop a simple analytic model to calculate multiple solutions in the large aspect ratio limit. We compare the results to the recently developed deflated continuation method to find multiple solutions in a realistic geometry and right-hand side of the GSE using the finite element method. The analytic model is surprisingly accurate in calculating multiple solutions of the GSE for given boundary conditions and the two methods agree well in limiting cases. We examine the effect of plasma shaping and aspect ratio on the multiple solutions and show that shaping generally does not alter the number of solutions. We discuss implications for predictive modelling, equilibrium reconstruction, plasma stability and disruptions.
In-flight imaging of aerosol jet printer droplets to enable spatially resolved flow rate measurements
Authors: Meredith Anna , Beuting Matthias , Trujillo Mario , Sanders Scott , Andrews Joseph
Published: January 2024

The effect of process drift in aerosol jet (AJ) printing has been a hindering factor in its large-scale adoption in printed electronics. In this study, we developed an in situ droplet imaging system using a double-pulse laser to quantify the distribution and velocity of sparse droplets between the AJ printer nozzle and the substrate. The droplet velocity and distribution were then used to evaluate a spatially resolved droplet flow rate that was capable of detecting and quantifying process drift over time. Using the droplet imaging system, the effect of different focus ratios was analyzed. The droplet flow rate was shown to be indicative of the deposited line morphology for low to moderate focus ratios. At a high focus ratio, the tool was able to identify non-idealities in the fluid properties which are explained in a detailed analysis. AJ printing demonstrates significant promise for the additive manufacturing of electronics, and this work represents a step toward non-invasive, in-flight monitoring in real time.
A geometry dependent directivity analysis of an optical structure based on NV center in diamond
Authors: Roy Subhankar , Momeen M Ummal
Published: January 2024

We present and investigate a highly directional diamond based optical nanostructure embedded with an elliptical solid immersion lens (e-SIL). An in depth analysis of the far field evolution is elucidated with respect to geometrical modification. This design is capable of producing a maximum directivity of ∼11 dB at its optimized position. Geometrical tolerance and directional behavior has been studied within a wide range of dipole variation. The incident light source noise is neutralized with the manipulation of e-SIL geometry by considering an experimental simulation environment. Enhancement in directivity near NV center zero phonon line (ZPL) region with reduced excitation light source noise can improve the overall efficiency of the NV single photon emitter and can be useful for multiple photonic applications.
Extreme in-plane thermal conductivity anisotropy in Rhenium-based dichalcogenides
Authors: Tahbaz Sina , Pisana Simone
Published: January 2024

Anisotropies in thermal conductivity are important for thermal management in a variety of applications, but also provide insight on the physics of nanoscale heat transfer. As materials are discovered with more extreme transport properties, it is interesting to ask what the limits are for how dissimilar the thermal conductivity can be along different directions in a crystal. Here we report on the thermal properties of rhenium-based transition metal dichalcogenides (TMDs), specifically rhenium disulfide (ReS2) and rhenium diselenide (ReSe2), highlighting their extraordinary thermal conductivity anisotropy. Along the basal crystal plane of ReS2, a maximum of

169
±
11

 W mK−1 is detected along the b-axis and a minimum of

53
±
4

 W mK−1 perpendicular to it. For ReSe2, the maximum and minimum values of

116
±
3

 W mK−1 and

27
±
1

 W mK−1 are found to lie 60° and 150° away from the b-axis, along the polarization direction of some of the principal Raman modes. These measurements demonstrate a remarkable anisotropy of 3.2 × and 4.3 × in the conductivity within the crystal basal planes, respectively. The through-plane thermal conductivities, recorded at

0.66
±
0.01

 W mK−1 for ReS2 and

2.31
±
0.01

 W mK−1 for ReSe2, highlight the impact of their layered structures, contributing to notably high in-plane to through-plane thermal conductivity ratios of 256 × for ReS2 and 50 × for ReSe2. This research demonstrates the unique thermal properties that these comparatively underexplored TMDs have, shedding light on the need for further exploration into the intricate thermal behavior of such materials, while underscoring their potential significance for future applications in the fields of semiconductor devices and nanotechnology.
Pitfalls of machine learning models for protein–protein interaction networks
Authors: Lannelongue Loïc , Inouye Michael
Published: January 2024

Motivation

Protein–protein interactions (PPIs) are essential to understanding biological pathways as well as their roles in development and disease. Computational tools, based on classic machine learning, have been successful at predicting PPIs in silico, but the lack of consistent and reliable frameworks for this task has led to network models that are difficult to compare and discrepancies between algorithms that remain unexplained.

Results

To better understand the underlying inference mechanisms that underpin these models, we designed an open-source framework for benchmarking that accounts for a range of biological and statistical pitfalls while facilitating reproducibility. We use it to shed light on the impact of network topology and how different algorithms deal with highly connected proteins. By studying functional genomics-based and sequence-based models on human PPIs, we show their complementarity as the former performs best on lone proteins while the latter specializes in interactions involving hubs. We also show that algorithm design has little impact on performance with functional genomic data. We replicate our results between both human and S. cerevisiae data and demonstrate that models using functional genomics are better suited to PPI prediction across species. With rapidly increasing amounts of sequence and functional genomics data, our study provides a principled foundation for future construction, comparison, and application of PPI networks.

Availability and implementation

The code and data are available on GitHub: https://github.com/Llannelongue/B4PPI.
Enzyme-mimetic catalyst architectures: the role of second coordination sphere in catalytic activity
Authors: Roy Bappaditya , Govindaraju Thimmaiah
Published: January 2024

Enzymes with well-defined three-dimensional structure have in-built information for molecular organization in the near vicinity of the active sites—popularly known as enzyme architecture. Over the past few years, molecular assembly has been exploited in creating artificial enzyme or catalyst architectures. Emergent spatiotemporal structure and catalytic activity can be achieved through controlled assembly of suitable molecular building blocks. The programmed molecular assembly governed by the scheme of molecule architectonics can generate enzyme-mimetic catalyst assembly architecture. Apart from the conventional ligand-metal interaction in the first coordination sphere of a catalyst, a second coordination sphere plays a key role in the catalytic activity of enzymes. This review attempts to unravel the balancing act between molecular architectonics and second coordination spheres in catalyst assembly architecture development. Judicious design and exploitation of state-of-the-art biomimetic catalyst architecture derived from small molecules, sugars, nucleic acids, peptides, and proteins are discussed under the above-mentioned framework. Metal-coordinated molecular assembly architectures of specific catalytic properties are considered with respect to the nature of molecular assembly and experimental conditions. The concise and critical discussion provides a holistic view of enzyme-mimetic architectures and their second coordination spheres through a reductionistic approach based on the molecular architectonics of simple and modular molecular building blocks.
The effect of a dermoscopy training programme on diagnostic accuracy and management decisions regarding pigmented skin lesions: a comparison between dermal therapists and general practitioners
Authors: Barten Amber H J , Beyers Cornelis P , Vondenhoff Mark F R , Stergioulas Lampros , Kukutsch Nicole A
Published: January 2024

Background

Dermoscopy is known to increase the diagnostic accuracy of pigmented skin lesions (PSLs) when used by trained professionals. The effect of dermoscopy training on the diagnostic ability of dermal therapists (DTs) has not been studied so far.

Objectives

This study aimed to investigate whether DTs, in comparison with general practitioners (GPs), benefited from a training programme including dermoscopy, in both their ability to differentiate between different forms of PSL and to assign the correct therapeutic strategy.

Methods

In total, 24 DTs and 96 GPs attended a training programme on PSLs. Diagnostic skills as well as therapeutic strategy were assessed, prior to the training (pretest) and after the training (post-test) using clinical images alone, as well as after the addition of dermatoscopic images (integrated post-test). Bayesian hypothesis testing was used to determine statistical significance of differences between pretest, post-test and integrated post-test scores.

Results

Both the DTs and the GPs demonstrated benefit from the training: at the integrated post-test, the median proportion of correctly diagnosed PSLs was 73% (range 30–90) for GPs and 63% (range 27–80) for DTs. A statistically significant difference between pretest results and integrated test results was seen, with a Bayes factor > 100. At 12 percentage points higher, the GPs outperformed DTs in the accuracy of detecting PSLs.

Conclusions

The study shows that a training programme focusing on PSLs while including dermoscopy positively impacts detection of PSLs by DTs and GPs. This training programme could form an integral part of the training of DTs in screening procedures, although additional research is needed.
Parallel cognitive maps for multiple knowledge structures in the hippocampal formation
Authors: Zheng Xiaochen Y , Hebart Martin N , Grill Filip , Dolan Raymond J , Doeller Christian F , Cools Roshan , Garvert Mona M
Published: January 2024

The hippocampal-entorhinal system uses cognitive maps to represent spatial knowledge and other types of relational information. However, objects can often be characterized by different types of relations simultaneously. How does the hippocampal formation handle the embedding of stimuli in multiple relational structures that differ vastly in their mode and timescale of acquisition? Does the hippocampal formation integrate different stimulus dimensions into one conjunctive map or is each dimension represented in a parallel map? Here, we reanalyzed human functional magnetic resonance imaging data from Garvert et al. (2017) that had previously revealed a map in the hippocampal formation coding for a newly learnt transition structure. Using functional magnetic resonance imaging adaptation analysis, we found that the degree of representational similarity in the bilateral hippocampus also decreased as a function of the semantic distance between presented objects. Importantly, while both map-like structures localized to the hippocampal formation, the semantic map was located in more posterior regions of the hippocampal formation than the transition structure and thus anatomically distinct. This finding supports the idea that the hippocampal-entorhinal system forms parallel cognitive maps that reflect the embedding of objects in diverse relational structures.
Human Disease due to Mycobacterium bovis Linked to Free-Ranging Deer in Michigan
Authors: Sunstrum James , Power Laura E , Fligiel Helene M , Lauter Carl , Kawam Rayanah , Dado Christopher , Weatherhead Matthew , Denbesten Karen , Bott Jonathan , Cinti Sandro , Maxwell Daniel , Signs Kimberly , Stobierski Mary Grace , Cosgrove Melinda , Moriarty Megan , Vanderklok Michael , Meyerson Joshua , Thacker Tyler , Robbe-Austerman Suelee
Published: January 2024

Background

A unique enzootic focus of Mycobacterium bovis in free-ranging deer was identified in northern lower Michigan in 1994, with subsequent evidence of transmission to local cattle herds. Between 2002 and 2017, 3 Michigan deer hunters with M. bovis disease were previously reported. We present 4 additional human cases linked to the zoonotic focus in deer, utilizing genomic epidemiology to confirm close molecular associations among human, deer and cattle M. bovis isolates.

Methods

Identification of human tuberculosis (TB) cases with cultures of M. bovis was provided from the Michigan Department of Health and Human Services (MDHHS) tuberculosis database. Clinical review and interviews focused on risk factors for contact with wildlife and cattle. Whole genome sequences of human isolates were compared with a veterinary library of M. bovis strains to identify those linked to the enzootic focus.

Results

Three confirmed and 1 probable human case with M. bovis disease were identified between 2019 and 2022, including cutaneous disease, 2 severe pulmonary disease cases, and human-to-human transmission. The 3 human isolates had 0–3 single-nucleotide polymorphisms (SNPs) with M. bovis strains circulating in wild deer and domestic cattle in Michigan.

Conclusions

Spillover of enzootic M. bovis from deer to humans and cattle continues to occur in Michigan. Future studies should examine the routes of transmission and degree of risk to humans through expanded epidemiological surveys. A One Health approach linking human, veterinary and environmental health should address screening for TB infection, public education, and mitigation of transmission.
Territorial identity and left-behind places: evidence from the central Italian Apennines from a time perspective
Authors: Morettini Gabriele , Compagnucci Fabiano
Published: January 2024

This paper aims to link the issue of left-behind places with spatial inequalities and demonstrate how, in these places, different territorial identities have contributed to responding to external shocks. By applying principal component and cluster analyses to a set of Italian mountain municipalities, we identified different typologies of these left-behind places as of the early 1950s and examined how they reacted to external shocks in two subsequent periods (1951–1981 and 1981–2011). The results suggest the changing importance of the cognitive, cultural and relational domains in coping with the different phases of Italian economic development.
A Light Weight Depthwise Separable Layer Optimized CNN Architecture for Object-Based Forgery Detection in Surveillance Videos
Authors: Sandhya  , Kashyap Abhishek
Published: January 2024

The present era is at the peak of technological advancement in image and video processing techniques, with user-friendly accessible tools/techniques. This immersive technology development makes video forensics enormously challenging. Specifically, the passive approaches to object-based forgeries in videos are crucial for legal and judicial matters. Hence, to ensure the integrity of the videos, a scientific, statistical and passive investigation of videos is required to maintain the spatial and temporal information content. This paper aims to develop a passive approach for digging out the forgery traces by applying the motion residue windowing technique for object removal forgery in surveillance videos. The novel max averaging windowing techniques improve visual imprints of the object removal forgery in the videos from the existing methods in the literature. A deep learning approach is the next step for achieving forgery detection in surveillance videos. The proposed lightweight depth-separable layer-optimized CNN has fast execution speed, optimized in terms of parameters without compromising the desired accuracy. This network is trained at a frame level with 98.60% testing accuracy, followed by a pipeline architecture of the proposed model for detection of forgery at video level with 99.01% accuracy. The suggested model works better than current models regarding post-processing operations, compression rates, forged video detection accuracy, precision, recall and F1 score.
Bank lending policies and monetary policy: some lessons from the negative interest era
Authors: Arce Oscar , García-Posada Miguel , Mayordomo Sergio , Ongena Steven
Published: January 2024

What is the long-term impact of negative interest rates on bank lending? To answer this question, we construct a unique summary measure of negative rate exposure by individual banks based on exclusive survey data and banks’ balance sheets and couple it with the credit register of Spain and firms’ balance sheets to identify this impact on the supply of credit to firms. We find that only when deposit rates reached the zero lower bound did affected banks (relative to non-affected banks) decrease their supply, especially when undercapitalized and lending to risky firms. The adverse effects of the negative rates on banks’ intermediation capacity only took place after a protracted period of time.
Does information reduce interpersonal violence? Evidence from prisons
Authors: Szekely Aron
Published: January 2024

Why does interpersonal violence erupt? A key source is conflict over resources and a little-studied mechanism for solving such cases concerns the availability of credible information about individuals’ abilities and willingness to use force. Its core prediction is that when such credible information abounds, the outcome of a potential struggle can be anticipated and thus there is no need to fight. I test this prediction using a nationally representative survey of male prisoners (Ninmates = 10,768, Nfacilities = 207) incarcerated in US state correctional facilities. I also make two methodologically orientated contributions. First, recent research highlights the important consequences that data analysis choices can have in determining quantitative findings. To overcome this, I draw on multiverse analysis and specification curve analysis to map out the key analytical decisions I make and run 262,144 plausible regression models. By doing so, I classify associations that are robust, mixed, or entirely frail according to analytic decisions and find partial support for the informational mechanism of interpersonal violence. Second, in contrast to much quantitative prison research, which uses only official or institutionally punished assaults data, I compare self-recognized fights to self-reported institutionally punished fights and highlight key differences.
Cannabis for chronic pain: cardiovascular safety in a nationwide Danish study
Authors: Holt Anders , Nouhravesh Nina , Strange Jarl E , Kinnberg Nielsen Sebastian , Schjerning Anne-Marie , Vibe Rasmussen Peter , Torp-Pedersen Christian , Gislason Gunnar H , Schou Morten , McGettigan Patricia , Lamberts Morten
Published: January 2024

Background and Aims

A rising number of countries allow physicians to treat chronic pain with medical cannabis. However, recreational cannabis use has been linked with cardiovascular side effects, necessitating investigations concerning the safety of prescribed medical cannabis.

Methods

Using nationwide Danish registers, patients with chronic pain initiating first-time treatment with medical cannabis during 2018–21 were identified and matched 1:5 to corresponding control patients on age, sex, chronic pain diagnosis, and concomitant use of other pain medication. The absolute risks of first-time arrhythmia (atrial fibrillation/flutter, conduction disorders, paroxysmal tachycardias, and ventricular arrhythmias) and acute coronary syndrome were reported comparing medical cannabis use with no use.

Results

Among 1.88 million patients with chronic pain (46% musculoskeletal, 11% cancer, 13% neurological, and 30% unspecified pain), 5391 patients claimed a prescription of medical cannabis [63.2% women, median age: 59 (inter-quartile range 48–70) years] and were compared with 26 941 control patients of equal sex- and age composition. Arrhythmia was observed in 42 and 107 individuals, respectively, within 180 days. Medical cannabis use was associated with an elevated risk of new-onset arrhythmia {180-day absolute risk: 0.8% [95% confidence interval (CI) 0.6%–1.1%]} compared with no use [180-day absolute risk: 0.4% (95% CI 0.3%–0.5%)]: a risk ratio of 2.07 (95% CI 1.34–2.80) and a 1-year risk ratio of 1.36 (95% CI 1.00–1.73). No significant association was found for acute coronary syndrome [180-day risk ratio: 1.20 (95% CI 0.35–2.04)].

Conclusions

In patients with chronic pain, the use of prescribed medical cannabis was associated with an elevated risk of new-onset arrhythmia compared with no use—most pronounced in the 180 days following the initiation of treatment.
Toward greater realism in inclusive fitness models: the case of caste fate conflict in insect societies
Authors: Ferreira Helena Mendes , Alves Denise Araujo , Cool Lloyd , Oi Cintia Akemi , Oliveira Ricardo Caliari , Wenseleers Tom
Published: January 2024

In the field of social evolution, inclusive fitness theory has been successful in making a wide range of qualitative predictions on expected patterns of cooperation and conflict. Nevertheless, outside of sex ratio theory, inclusive fitness models that make accurate quantitative predictions remain relatively rare. Past models dealing with caste fate conflict in insect societies, for example, successfully predicted that if female larvae can control their own caste fate, an excess should opt to selfishly develop as queens. Available models, however, were unable to accurately predict levels of queen production observed in Melipona bees—a genus of stingless bees where caste is self-determined—as empirically observed levels of queen production are approximately two times lower than the theoretically predicted ones. Here, we show that this discrepancy can be resolved by explicitly deriving the colony-level cost of queen overproduction from a dynamic model of colony growth, requiring the incorporation of parameters of colony growth and demography, such as the per-capita rate at which new brood cells are built and provisioned, the percentage of the queen’s eggs that are female, costs linked with worker reproduction and worker mortality. Our revised model predicts queen overproduction to more severely impact colony productivity, resulting in an evolutionarily stable strategy that is approximately half that of the original model, and is shown to accurately predict actual levels of queen overproduction observed in different Melipona species. Altogether, this shows how inclusive fitness models can provide accurate quantitative predictions, provided that costs and benefits are modeled in sufficient detail and are measured precisely.
Modeling a new taper curve and form factor of tree branches using terrestrial laser scanning
Authors: Bazezew Muluken N , Fehrmann Lutz , Kleinn Christoph , Nölke Nils
Published: January 2024

Modeling branch taper curve and form factor contributes to increasing the efficiency of tree crown reconstructions: the branch taper, defined as the sequential measure of diameters along the course of the branch, is pivotal to accurately estimate key branch variables such as biomass and volume. Branch diameters or volumes have commonly been estimated from terrestrial laser scanning (TLS) based on automatized voxelization or cylinder-fitting approaches, given the whole branch length is sufficiently covered by laser reflections. The results are, however, often affected by ample variations in point cloud characteristics caused by varying point density, occlusions, and noise. As these characteristics of TLS can hardly be sufficiently controlled or eliminated in automatized techniques, we proposed a new branch taper curve model and form factor, which can be employed directly from the laser reflections and under variable point cloud characteristics. In this paper, the approach is demonstrated on primary branches using a set of TLS-derived datasets from a sample of 20 trees (six species). The results showed an R2 of 0.86 and a mean relative absolute error of 1.03 cm (29%) when validated with field-measured diameters. The approach improved the accuracy of diameter estimates for the fine branch scales (<10 cm) as compared to the quantitative structural model (QSM). Our approach also allowed branch diameter estimation for a relatively larger number of manually recognized primary branches (>85%) from point clouds when validated with panoramic images acquired simultaneously with laser scanning. Frequently used automatized crown reconstructions from QSM, on the other hand, were affected by gaps in the point clouds due to obstruction, with the crown-tops and finer branches being the most critical. Our approach reports mean form factors across the examined species of 0.35 and 0.49, with the diameters determined at 5% and 10% of the total branch length, respectively. Our approach may have the potential to produce branch volume information with reasonable accuracy from only knowing the length and respective diameter of each branch. Our model delivers a first approximation for the taper curve and form factor for primary branches but was developed on a relatively small set of samples. We believe that our approach holds the potential to improve the accuracy of the assessment of branch diameter and volume from TLS data. The approach may also be extended to other branch orders. This could expand the horizon for volumetric calculations and biomass estimates from non-destructive TLS proxies in tree crowns.
Inhibitory effect and mechanism of tannic acid against two starch digestive enzymes
Authors: Zhong Yuxiu , Ni Derang , Yang Yubo , Li Yuanyi , Wang Li , Tian Jinhu , Yang Fan , Ye Xingqian
Published: January 2024

Backgrounds

Tannic acid (TA), as a plant-derived phenolic substance, is involved in regulating the activity of starch digestive enzymes, but its underlying mechanism remains unclear.

Methods and Results

In the present study, inhibition rate and inhibition kinetics assays were performed and confirmed that TA had a strong inhibitory effect on both α-amylase and α-glucosidase with IC50 values of 0.1585 mg/mL and 0.00542 mg/mL, respectively, through a mixed inhibition mode. The secondary structures of both enzymes were confirmed to be modified by TA through circular dichroism (CD) spectra. Fluorescence quenching analysis revealed that the interaction between TA and two enzymes was a static process of pontaneous complex formation. Finally, molecular docking revealed that non-covalent bonds were the main interaction forces between TA and both enzymes.

Conclusions

Thus, TA was a promising candidate for the inhibition of starch-digesting enzymes, and the present research provided insight into postprandial glucose regulation through polyphenols.
Research on likelihood ratio evaluation method of fingerprint evidence based on parameter estimation method
Authors: Li Kang , Han Yishi , Luo Yaping
Published: January 2024

Fingerprints with similar morphological characteristics but from different individuals can lead to errors in individual identification, especially when dealing with large databases containing millions of fingerprints. To address this issue and enhance the accuracy of similar fingerprint identification, the use of the likelihood ratio (LR) model for quantitative evaluation of fingerprint evidence has emerged as an effective research method. In this study, the LR fingerprint evidence evaluation model was established by using mathematical statistical methods, such as parameter estimation and hypothesis testing. This involved various steps, including database construction, scoring, fitting, calculation, and visual evaluation. Under the same-source conditions, the optimal parameter methods selected by different number of minutiae are gamma and Weibull distribution, while normal, Weibull, and lognormal distributions were the fitting parameters selected for minutiae configurations. The fitting parameters selected by different number of minutiae under different-source conditions are lognormal distribution, and the parameter methods selected for different minutiae configurations include Weibull, gamma, and lognormal distributions. The results of the LR model showed increased accuracy as the number of minutiae increased, indicating strong discriminative and corrective power. However, the accuracy of the LR evaluation based on different configurations was comparatively lower. In addition, the LR models with different numbers of minutiae outperformed those with different minutiae configurations. Our study shows that the use of LR models based on parametric methods is favoured in reducing the risk of fingerprint evidence misidentification, improving the quantitative assessment methods of fingerprint evidence, and promoting fingerprint identification from experience to science.

Key points