bluuebunny/crossref_metadata_2025 huggingface dataset:
VSLAM based on deep learning in low-textured scenes
Authors: Zhu Qiguang , Li Xiang , Zhao Yuchao , Chen WeiDong
Published: September 2024

Traditional visual simultaneous localization and mapping (VSLAM) algorithms often suffer from the low positioning accuracy and robustness of the traditional feature extraction methods. These methods typically require environments with clear features, perform poorly or even fail in low-textured scenes. To solve this problem, we propose an RGB-D VSLAM algorithm that integrates a deep learning feature extraction network. First, to solve the problem in which sufficient feature points cannot be extracted, the proposed algorithm uses the R2D2 feature extraction network to extract keypoints and generate descriptors. We also perform lightweight optimization on the R2D2 network, ensuring accuracy while doubling the inference speed. Subsequently, we employ the L2 distance to measure the distance between descriptors, thereby enhancing the accuracy of keypoint matching. Ultimately, we add a dense mapping thread to obtain a dense 3D point map generated by the RGB-D information and poses of the keyframes. The experimental results on the TUM dataset show that the average absolute trajectory error is reduced by 59% and the relative trajectory error is reduced by 56%. The results demonstrate that our algorithm significantly improves localization accuracy and system robustness in low-textured environments.
Adaptive threshold algorithm for detecting EEG-interburst intervals in extremely preterm neonates
Authors: Mader Johannes , Hartmann Manfred , Dressler Anastasia , Oberdorfer Lisa , Rona Zsofia , Glatter Sarah , Czaba-Hnizdo Christine , Herta Johannes , Kluge Tilmann , Werther Tobias , Berger Angelika , Koren Johannes , Klebermass-Schrehof Katrin , Giordano Vito
Published: September 2024

Objective. This study provides an adaptive threshold algorithm for burst detection in electroencephalograms (EEG) of preterm infantes and evaluates its performance using clinical real-world EEG data. Approach. We developed an adaptive threshold algorithm for burst detection in EEG recordings from preterm infants. To assess its applicability in the real-world, we tested the algorithm on a dataset of 30 clinical EEG recordings which were not preselected for good quality, to ensure a real-world scenario. Main results. Interrater agreement was substantial at a kappa of 0.73 (0.68–0.79 inter-quantile range). The performance of the algorithm showed a similar agreement with one clinical expert of 0.73 (0.67–0.76) and a sensitivity and specificity of 0.90 (0.82–0.94) and 0.95 (0.93–0.97), respectively. Significance. The adaptive threshold algorithm demonstrated robust performance in detecting burst patterns in clinical EEG data from preterm infants, highlighting its practical utility. The fine-tuned algorithm achieved similar performance to human raters. The algorithm proves to be a valuable tool for automated burst detection in the EEG of preterm infants.
A comparative study of fibre Bragg grating for spatially and temporally resolved gas temperature measurements in cold atmospheric pressure plasma jets
Authors: Billeau Jean-Baptiste , Thomas Jyothis , Kashyap Raman , Rosenzweig Derek , Reuter Stephan
Published: September 2024

Cold atmospheric pressure plasma jets (CAP-Jet) are successfully used in medical therapy for healing of chronic wounds and are widely researched in inactivation of pathogens and in assisting in cancer therapy. A crucial parameter for these plasma applications is that CAP-Jets operate at temperatures that are tolerable for biological tissues. While tools characterizing the plasma’s gas temperature are well developed, there are only a few methods that work with an agreeable limit of uncertainty, complexity and limited perturbation properties to accurately determine that the studied plasma jet operates at tissue tolerable temperatures at all times. In the current work, time resolved measurements of the gas temperature in the effluent of a CAP-Jet are performed using the innovative technique of a fibre Bragg grating (FBG), in which the temperature dynamics is measured by a shift of the FBGs resonant wavelength through its thermo-optic coefficient. Comparing with other temporal and spatial diagnostic tools such as thermocouple measurement, Schlieren imaging, and optical emission spectroscopy, we demonstrate reliable calorimetric measurements at different plasma duty cycles. The plasma source maintains tissue tolerable temperatures inside the plasma active zone with values below 35 °C at 1 cm distance from the jet nozzle. The calorimetric measurements have revealed that the heat power dissipation in comparison to electric energy of our plasma source is at least 50%.
Physics and technology of laser lightning control
Authors: Produit Thomas , Kasparian Jérôme , Rachidi Farhad , Rubinstein Marcos , Houard Aurélien , Wolf Jean-Pierre
Published: September 2024

The recent development of high average, high peak power lasers has revived the effort of using lasers as a potential tool to influence natural lightning. Although impressive, the current progress in laser lightning control (LLC) technology may only be the beginning of a new area involving a positive feedback between powerful laser development and atmospheric research. In this review paper, we critically evaluate the past, present and future of LLC, considering both its technological and scientific significance in atmospheric research.
Baseline offset correction technique for terahertz signals based on improved wavelet multiresolution analysis
Authors: Xiong Weihua , Jiang Yufei , Huang Xiaotong , Cao Lixian
Published: September 2024

During the terahertz nondestructive testing of bonded structures, the incomplete discharge of the capacitance in the photoconductive antenna within the terahertz time-domain spectroscopy system results in a shift of the terahertz baseline produced by the antenna. This baseline shift causes variations in the amplitude information of the detected signals. Consequently, when feature imaging of the detection waveforms is performed, the baseline shift can lead to erroneous detection results. In this study, an improved wavelet multiresolution analysis method was used to eliminate high-frequency noise and baseline offset in terahertz detection. The method is based on the frequency characteristics of the detection waveforms, setting thresholds and using similarity as a measurement standard to determine the number of decomposition layers. Ultimately, this achieves the correction of the baseline offset in terahertz signals. Compared with other baseline correction methods, the method presented in this paper achieves the lowest root mean square error of 0.57%, the highest signal-to-noise ratio of 12.64%, and a defect identification accuracy of 96.27% in two-dimensional visualization results.
Azimuthally modulating surface plasmon polaritons
Authors: Ibrahim Muhammad , Rahmatullah  , Qamar Sajid
Published: September 2024

We suggest a scheme for the lossless excitation of surface plasmon polaritons (SPPs) at a metal-dielectric interface using a Laguerre–Gaussian (LG) beam. We consider a three-layer structure consisting of a top transparent medium, a middle metal thin film, and a dielectric bottom layer. The dielectric medium contains three-level atoms exhibiting electromagnetically induced transparency (EIT). By applying a control field, a LG beam, and a microwave field, we induce azimuthally varying permittivity, which leads to the azimuthal modulation of SPPs. The propagation length of SPPs is increased when excited by a LG beam carrying optical angular momentum (OAM). Moreover, the group velocity of SPPs can be effectively controlled by adjusting the OAM and azimuthal angle of the LG beam, allowing for both slow and fast propagation of SPPs.
Analyzing the dynamics and optimal control of a vector-borne model with dual vertical transmission and multiple serotypes
Authors: Qin Yuyan , Yang Lixin , Li Jia
Published: September 2024

Transmission and contact patterns have an important influence on the intensity and trend of disease transmission. Taking into account two different serotypes and the vertical transmission of the disease in both humans and mosquitoes, this paper proposes a novel vector-borne disease model. In order to explore the evolution mechanisms of the model and the impacts of contact pattern on disease transmission. The basic regeneration number of the proposed model is obtained via the next-generation matrix approach. Subsequently, we analyze the conditions of the stabilities and existences of the equilibrium points. Further, the sensitivity of the parameters is studied using numerical simulations. It is observe that the increase of vertical transmission rate of mosquitoes leads to the increase of the basic reproduction number. In addition, we develop vaccination and insecticide control strategies and derive the existence and expression of the optimal solution. Our numerical results show that vaccination has a little effect on preventing the spread of disease among mosquitoes. However, insecticide spraying is effective in reducing the spread of disease between humans and mosquitoes.
Semiconductor-metal transition in TlPbF3 under isotropic pressure and its impact on optical, elastic and mechanical properties: a DFT computation with HSE06
Authors: Ahmad Bilal , Siddique Sofia , Zeba I , Zafar Sana , Shakil M , Gillani S S A
Published: September 2024

This research aims to comprehensively evaluate the structure, elasticity, mechanics, anisotropy, electrical properties, and optical attributes of TlPbF3 at pressures from 0 to 60 GPa. A cubic structure of the material remains same without any phase changes, but there is a reduction in the lattice parameters. The material is determined to be mechanically secure by doing calculations on a variety of mechanical and elastic characteristics, including bulk, shear, and Young’s modulus, stiff, and not particularly flexible. It also shows a significant resistance to shear force. The material’s ability to withstand high pressures, its metallic bond nature, and ductility have been shown by the Kleinman’s parameter, Poisson’s ratio, Cauchy pressure, and Pugh ratio. Anisotropy can be confirmed by activating specific anisotropy factors. When we consider the electronic band structure, we observe a transition from a broad gap in the band (3.719 eV) comparable with a small band distance (0.65 eV), and converts to a metal (0 eV). To explore this, we have estimated the total, partial and elemental partial density of states. Additionally, we have computed the real and imaginary functions of dielectric, absorption factor, refractive index, extinction coefficient, loss function, reflectivity and real/imaginary conductivity to assess the material’s applicability. As pressure is applied, the static values of

ε

1

(
ω
)

and

n
(
ω
)

increase. This material is also well-suited for optoelectronic devices due to its high conductivity, reflectivity, absorption, and refractive index.
Stress transfer paths and damage modes of layered coal-rock mass under static loading
Authors: Li Feng , Wang Bo
Published: September 2024

In order to explore the distribution characteristics of nonlinear mechanical behavior and the tendency of damage and failure of deep in situ coal-rock mass, a layered composite thin plate coal-rock mass model is established based on thin plate theory and finite element method. The continuity of interlayer stress and displacement is maintained by transfer matrix function, and the maximum shear stress is calculated by Mohr-Coulomb strength criterion. The distribution characteristics of stress, displacement, energy and maximum shear stress of coal-rock mass under static load are obtained. The analysis results are as follows : ① The torsional stress concentration areas of τxz and τyz are formed on the boundary of coal-rock interface, and the principal stress concentration areas of σx, σy and σz are formed in the center and center of the boundary, and the shear stress distribution of τxy is formed on the diagonal line. ② The maximum shear stress of the long axis has a strengthening effect on the shear failure, and each layer forms a stress state of alternating tension-shear-compression-shear. It first destroys in the middle of the coal-rock interface and boundary, and then destroys along the long side and short side. ③ The coal-rock mass presents a ′ X ′ -type shear zone along the radial and axial. The shear failure occurs first, followed by the principal stress compression failure. The cracks are preferentially developed in the direction perpendicular to the minimum principal stress, and the stepped ′ V ′ -shaped failure characteristics are formed under the action of shear and tensile stress.
Aero-engine gas path anomaly monitoring based on unsupervised structure and deep slow feature representation
Authors: Li Zhiqiang , Li Dewen , Cai Jing , Wei Jiashun , Li Yang , Zhang Ying
Published: September 2024

Gas path anomaly monitoring holds a crucial position in aero-engine health management due to the dynamic nature of gas path parameters, data imbalance, and the lack of labels, presenting significant challenges. To address these issues, this study proposes a novel method for dynamic anomaly monitoring in aero-engines utilizing Kernel Slow Feature Analysis (KSFA) and Deep Support Vector Data Description (Deep SVDD). In this approach, the original gas path parameter values undergo preprocessing using the KSFA algorithm to extract pertinent features indicative of gradual changes in gas path status. The Deep SVDD model, employing a one-dimensional Convolutional Neural Network (1D-CNN) fused with a feature attention mechanism, is iteratively trained to identify the optimal hypersphere. The Health Indicator (HI) is then determined by quantifying the distance between the test set and the hypersphere’s center, enabling a quantitative assessment of the aero-engine’s performance degradation. Experimental findings demonstrate that this method outperforms alternative evaluation techniques by effectively tracking the aero-engine’s degradation process and anticipating engine anomalies, showcasing its practical value in engineering applications.
The role of Rashba spin-orbit induced spin textures in the anomalous Josephson effect
Authors: Monaghan R D , Tettamanzi G C
Published: September 2024

This work reports the theoretical investigation into the mechanism underpinning the anomalous Josephson effect within ballistic systems; currently, there is no agreed-upon microscopic mechanism behind the origin of this effect. The prototypical system we study is a ballistic two-dimensional junction containing a two-dimensional Rashba spin-orbit interaction. In this paper, we demonstrate how this two-dimensional Rashba interaction mixes the spins of adjacent transverse subbands, leading to significant spin-asymmetry within the junction. Under an external magnetic field, applied perpendicular to both the axis of transport and the normal vector of the junction, the sinusoidal Josephson current can then experience an anomalous phase shift. The role of this spin mixing in the limit of a single sub-band is initially explored by deriving an analytical expression for the resulting anomalous phase shift. The analysis is then extended to systems with multiple occupied sub-bands; in this later section, starting from a microscopic model, we derive an analytic formula for the resulting anomalous phase shift indicating it is linear in both magnetic field and spin-orbit strength. We then verify and validate all findings by comparing them with numerical results evaluated by a tight-binding model.
Synthesis and characterizations of upconverting luminescent Er3+/ Yb3+: Gd2O3 uniform nanospheres for biomedical applications
Authors: Anh Tran Kim , Ha Vu Thi Thai , Huong Nguyen Thanh , Thao Do Thi , Nguyen Tien Dai , Thai Dang Van , Tomala Robert , Minh Le Quoc
Published: September 2024

We present the synthesis of Er3+/ Yb3+ co-doped Gd2O3 nanospheres using the wet-chemical method followed by a synergistic step-by-step calcination process, a novel approach in the field. The nanospheres exhibited red color upconversion luminescence (UCL) after multi-step annealing at temperatures ranging from 650 °C to 1150 °C, achieving a fully spherical morphology. The diameter and surface morphology of the nanospheres were significantly altered by the annealing process, decreasing from 382.77 ± 1.72 nm with a smooth surface to 245.7 ± 1.31 nm with a rougher surface. The UCL intensity increased with the annealing temperature. The influence of Er3+/ Yb3+ co-doped Gd2O3 nanospheres, excited by a 975 nm laser, was investigated, and the decay time for UCL samples was analyzed. The luminescence peak at 1026 nm was attributed to the 4I11/2 (Er3+) + 2F7/2 (Yb3+) → 4I15/2 (Er3+) + 2F5/2 (Yb3+) transition/ or 2F5/2 → 2F7/2 of the Yb3+ ions within the Gd2O3 matrix. Furthermore, the UCL properties of Er3+/ Yb3+ co-doped Gd2O3 nanophosphors were explored to detect the NTERA-2 cancer cells. These findings suggest that the rare earth co-doped Gd2O3 nanospheres might hold significant potential for biomedicine and imaging diagnostics applications, sparking new interest and possibilities in these fields.
Enhanced photocatalytic degradation of Cr (VI) and organic pollutants using novel 3D/2D MoS2/SnS2 heterostructures for water remediation
Authors: Kumari Ritu , Kumar Rakesh
Published: September 2024

In this study, 3D flower-like MoS2 nanostructures were synthesized using a hydrothermal technique to form heterostructures with 2D porous SnS2 nanosheets. The resulting 3D/2D MoS2/SnS2 heterostructures were evaluated for their photocatalytic abilities in removing Cr (VI), tetracycline (TC), and methylene blue (MB) under simulated solar irradiation. The results demonstrate that the MoS2/SnS2 heterostructures significantly outperformed pristine MoS2 and SnS2 in photocatalytic efficiency. Specifically, the MoS2/SnS2 photocatalysts achieved 99.9% degradation of Cr (VI) within 50 min, 96% degradation of TC in the same timeframe, and 99.9% elimination of MB in just 10 min. The reduction rate constant for Cr (VI) reduction by MoS2/SnS2 photocatalysts was 0.117 min−1, surpassing that of pure SnS2 (0.007 min−1) and MoS2 (0.0034 min−1) by 16 and 30 times, respectively. This outstanding performance is attributed to the heterojunction formation between SnS2 and MoS2, which suppresses the recombination of photogenerated charge carriers and provides abundant reactive sites due to their large specific surface area. The proposed photodegradation mechanism illustrates the facilitated migration of photogenerated charge carriers under light irradiation, enabled by the energy band alignment at the MoS2/SnS2 interface. These findings represent a significant advancement in the development of photocatalysts based on 3D flower-like MoS2 and porous SnS2 nanostructures, offering promise for applications in wastewater treatment and environmental remediation.
Synthesis and characterization of Fe3O4@SiO2 core-shell nanoparticles for mirror and efficient magnetic compound fluid polishing of TC4 titanium alloy
Authors: Wang Youliang , Kang Yating , Zhang Wenjuan , Yin Xincheng
Published: September 2024

To fully investigate the polishing performance of the Fe3O4@SiO2 core–shell abrasive for TC4 titanium alloy plate and solve the problem of uneven distribution of abrasive particles in magnetic compound fluid polishing (MCFP) and obtain ultra-smooth titanium alloy surface. In this paper, the functional Fe3O4@SiO2 core–shell abrasives were prepared and characterized by XRD, FTIR, VSM and TEM to demonstrate the successful encapsulation of SiO2 in Fe3O4 first. Second, a new polishing device was built to perform polishing experiments. Four different fractions of Magnetic compound fluid (MCF) were configured and utilized in polishing experiments for MCFP of TC4 titanium alloy to verify the polishing properties. Finally, the contact model between abrasive particles and workpiece is established and the material removal mechanism is discussed. The results show that SiO2 was successfully coated on Fe3O4. The polishing results show that the MCF containing the core–shell structure had the best polishing effect. The surface roughness Ra decreased from 0.201 μm to 0.025 μm after 20 min of polishing. The surface roughness of TC4 titanium alloy with an initial roughness Sa of 0.248 μm is reduced to 0.023 μm after polishing by Fe3O4@SiO2 core–shell abrasive. It is shown that the application of core–shell abrasive to process titanium alloys can obtain smooth and defect-free surfaces with good polishing performance. The surface quality of titanium alloy can be improved effectively by using core–shell abrasive, and a new idea for polishing titanium alloy is proposed. This study plays an important role in solving the problem of uneven particle distribution in MCFP. These results pave the way for further research into the application of core–shell abrasives in precision machining and expand the application scope of particles with core–shell structure.
Enhancing pap smear image classification: integrating transfer learning and attention mechanisms for improved detection of cervical abnormalities
Authors: Sood Tamanna , Khandnor Padmavati , Bhatia Rajesh
Published: September 2024

Cervical cancer remains a major global health challenge, accounting for significant morbidity and mortality among women. Early detection through screening, such as Pap smear tests, is crucial for effective treatment and improved patient outcomes. However, traditional manual analysis of Pap smear images is labor-intensive, subject to human error, and requires extensive expertise. To address these challenges, automated approaches using deep learning techniques have been increasingly explored, offering the potential for enhanced diagnostic accuracy and efficiency. This research focuses on improving cervical cancer detection from Pap smear images using advanced deep-learning techniques. Specifically, we aim to enhance classification performance by leveraging Transfer Learning (TL) combined with an attention mechanism, supplemented by effective preprocessing techniques. Our preprocessing pipeline includes image normalization, resizing, and the application of Histogram of Oriented Gradients (HOG), all of which contribute to better feature extraction and improved model performance. The dataset used in this study is the Mendeley Liquid-Based Cytology (LBC) dataset, which provides a comprehensive collection of cervical cytology images annotated by expert cytopathologists. Initial experiments with the ResNet model on raw data yielded an accuracy of 63.95%. However, by applying our preprocessing techniques and integrating an attention mechanism, the accuracy of the ResNet model increased dramatically to 96.74%. Further, the Xception model, known for its superior feature extraction capabilities, achieved the best performance with an accuracy of 98.95%, along with high precision (0.97), recall (0.99), and F1-Score (0.98) on preprocessed data with an attention mechanism. These results underscore the effectiveness of combining preprocessing techniques, TL, and attention mechanisms to significantly enhance the performance of automated cervical cancer detection systems. Our findings demonstrate the potential of these advanced techniques to provide reliable, accurate, and efficient diagnostic tools, which could greatly benefit clinical practice and improve patient outcomes in cervical cancer screening.
Nanodosimetric investigation of the track structure of therapeutic carbon ion radiation part 1: measurement of ionization cluster size distributions
Authors: Hilgers Gerhard , Schwarze Miriam , Rabus Hans
Published: September 2024

At the Heidelberg Ion-Beam Therapy Center, the track structure of carbon ions of therapeutic energy after penetrating layers of simulated tissue was investigated for the first time. Measurements were conducted with carbon ion beams of different energies and polymethyl methacrylate (PMMA) absorbers of different thicknesses to realize different depths in the phantom along the pristine Bragg peak. Ionization cluster size (ICS) distributions resulting from the mixed radiation field behind the PMMA absorbers were measured using an ion-counting nanodosimeter. Two different measurements were carried out: (i) variation of the PMMA absorber thickness with constant carbon ion beam energy and (ii) combined variation of PMMA absorber thickness and carbon ion beam energy such that the kinetic energy of the carbon ions in the target volume is constant. The data analysis revealed unexpectedly high mean ICS values compared to stopping power calculations and the data measured at lower energies in earlier work. This suggests that in the measurements the carbon ion kinetic energies behind the PMMA absorber may have deviated considerably from the expected values obtained by the calculations. In addition, the results indicate the presence of a marked contribution of nuclear fragments to the measured ICS distributions, especially if the carbon ion does not cross the target volume.
A linear photonic swap test circuit for quantum kernel estimation
Authors: Baldazzi Alessio , Leone Nicolò , Sanna Matteo , Azzini Stefano , Pavesi Lorenzo
Published: September 2024

The swap test is a quantum algorithm capable of computing the absolute value of the scalar product of two arbitrary wavefunctions. Scalar products represent a crucial ingredient to many quantum machine learning (QML) methods, but their evaluation is not straightforward at all. For this reason, many research efforts have been made without achieving an efficient and robust implementation. Here, we present an integrated photonic circuit designed to implement the swap test algorithm. Our approach relies solely on linear optical integrated components and qudits, represented by single photons from an attenuated laser beam propagating through a set of waveguides. By utilizing 23 spatial degrees of freedom for the qudits, we can configure all the necessary arrangements to set any two-qubit state and perform the swap test. This simplifies the requirements on the circuitry elements and eliminates the need for non-linearity, heralding, or post-selection to achieve multi-qubit gates. Our photonic swap test circuit successfully encodes two qubits and estimates their scalar product with a measured root mean square error smaller than 0.05. This result paves the way for the development of integrated photonic architectures capable of performing QML tasks with robust devices operating at room temperature.
The long mid-transition: tracking decades of coastal oil well decommissioning in California
Authors: Partridge Tristan , Barandiaran Javiera
Published: September 2024

This article presents an account of four different experiences of oil well decommissioning and abandonment along the Santa Barbara coast in California, together forming an ongoing process that began over a century ago and which has, more recently, become a component of statewide transition plans. The cases include the re-abandonment of nineteenth century wells in Summerland; offshore oil platform removal in the 1990s; and two different areas of operational closures due to infrastructure failures and bankruptcies. Informed by this history, we suggest that decommissioning must be actively managed through coordinated, well-funded, multi-agency action, grounded in historical awareness of policy trajectories. Additionally, the scale of the need together with the economics and policies in place mean that oil well decommissioning will be happening for a very long time, even if no new wells are built.
Measuring the transition to regenerative agriculture in the UK with a co-designed experiment: design, methods and expected outcomes
Authors: Berthon Katherine , Jaworski Coline C , Beacham Jonathan D , Jackson Peter , Leake Jonathan , McHugh Niamh M , Capstick Lucy , Daniell Tim , Krzywoszynska Anna , Cameron Duncan , Holland John , Hartley Sue , Desneux Nicolas , Jowett Kelly , Zhao Yu , Watt Penelope J , Dicks Lynn V
Published: September 2024

Regenerative agriculture is promoted as a farming system that can improve agricultural sustainability, address soil degradation, and provide ecosystem service benefits. However, there remains limited evidence for the quantifiable benefits of a widespread transition to regenerative agriculture on soil, biodiversity, and crop quality, particularly at the landscape scale, and poor integration of findings across disciplines. Social and cultural aspects of the transition, such as the positioning of regenerative agriculture as a grassroots movement, farmers’ perspectives on defining regenerative practices, and social or political barriers to implementation, are harder to quantify and often overlooked in evidence-based approaches. Here, we present the detailed methodology for our interdisciplinary, co-designed landscape-scale experiment measuring changes in soil health, biodiversity, yield, and grain quality, as well as social and political dimensions of the implementation of regenerative practices. Our unique approach, through the co-production process, the landscape-scale, and the focus on a systemic transition instead of individual practices, will bring strong evidence of the benefits of regenerative agriculture for sustained agricultural productivity, the mitigation of climate change and biodiversity depletion in agroecosystems. Our research aims to guide future studies transforming theoretical ecology into testable hypotheses in real-world systems and provide actionable evidence to inform agricultural policies in the UK and beyond.
Modal Idealism
Authors: Builes David
Published: September 2024

According to Idealism, every fundamental entity is conscious, and moreover every fundamental property is a phenomenal property. The goal of this chapter is to defend “Modal Idealism,” which is the thesis that Idealism is metaphysically necessary. In particular, I give four different arguments for Modal Idealism. First, I argue that, if at least some possible fundamental properties are phenomenal properties, then the denial of Modal Idealism leads to implausible brute necessities. Second, I argue that those who endorse the Eleatic Principle, according to which it is necessary that all concrete objects have causal powers, should endorse Modal Idealism. Third, I argue that Modal Idealism helps us secure our knowledge of our own conscious states in the face of influential “debunking” arguments. Fourth, I argue that Modal Idealism is theoretically fruitful: it allows us to make substantial progress on several perennial metaphysical debates beyond the philosophy of mind.
Idealism and the Best of All (Subjectively Indistinguishable) Possible Worlds
Authors: Yetter-Chappell Helen
Published: September 2024

The space of possible worlds is vast. Some of these possible worlds are materialist worlds, some may be worlds bottoming out in 0s and 1s, or other strange things we cannot even dream of … and some are idealist worlds. From among all of the worlds subjectively indistinguishable from our own, the idealist ones have uniquely compelling virtues. Idealism gives us a world that is just as it appears; a world that’s fit to literally enter our minds when we perceive it. If the world is an idealist world, we live in a perceptual Eden. We did not fall from Eden. Rather, we deluded ourselves into believing that we couldn’t possibly live in Eden when we committed to materialism. Reflecting on these big-picture issues gives us reason to question this commitment and embrace a radically new account of reality and our relation to it.
Naïve Realism, Incorporeal Objects, and the Time-lag Argument
Authors: Fish William
Published: September 2024

The chapter begins by outlining the core aspects of a naïve realist theory of successful visual perception, before introducing an important objection to this view known as the time-lag argument, which uses the fact that light moves at a finite speed to argue that we do not see everyday material objects. The chapter explores and critiques extant responses to this argument, before undertaking a phenomenological investigation of our perception of light sources, which suggests that many familiar light sources that we see are not themselves material objects yet remain objective parts of the material world: they are ‘incorporeal’ objects. Moreover, in cases where we do have a material object that is a light source, the incorporeal object created by the underlying processes in this object typically occludes the material object itself. The chapter explores how these findings provide a novel way of responding to the time-lag argument.
Relationalism, Acquaintance, and SubjectivitySome Metaphysical Implications
Authors: Debus Dorothea
Published: September 2024

The chapter explores one account of acquaintance and subjectivity, namely ‘Relationalism’ about perceptual experience. According to a Relationalist, a subject who perceives an object stands in a direct experiential relation to the relevant object, which gives her a subjective perspective on the object with which she is thereby acquainted. However, or so this chapter aims to show, a Relationalist is committed to a non-reductive account of perceptual experience, and thus of the mind more generally. According to a Relational Account of perceptual experience, the experiential relations which obtain between perceiving subjects and the objects perceived are special: According to Relationalism, perceptual relations are sui generis relations.
Aristotle on Thumos
Authors: Marechal Patricia
Published: September 2024

This chapter argues that Aristotelian thumos is a non-reducible mental phenomenon that plays a central role in Aristotle’s theory of the mind, motivation, and action. For Aristotle, thumos is not, as others have argued, a desire for the noble, social appraisal, or retaliation; rather, it is an inner drive or impulse to act. More precisely, it is an executory urge to implement or enact one’s ends or goals, whatever they are. Thumos accounts for someone’s proneness to spring into action and can contribute to bringing about rational or non-rational first-order desires. It is a second-order motivation, which both human and non-human animals have and that comes in degrees: we can be more or less thumotic, which amounts to being more or less disposed to making first-order desires effective so that they issue in actions. Aristotelian thumos, then, anticipates features of the modern notion of the will.
EmbedGEM: a framework to evaluate the utility of embeddings for genetic discovery
Authors: Mukherjee Sumit , McCaw Zachary R , Pei Jingwen , Merkoulovitch Anna , Soare Tom , Tandon Raghav , Amar David , Somineni Hari , Klein Christoph , Satapati Santhosh , Lloyd David , Probert Christopher ,   Insitro Research Team, Koller Daphne , O’Dushlaine Colm , Karaletsos Theofanis
Published: September 2024

Machine learning-derived embeddings are a compressed representation of high content data modalities. Embeddings can capture detailed information about disease states and have been qualitatively shown to be useful in genetic discovery. Despite their promise, embeddings have a major limitation: it is unclear if genetic variants associated with embeddings are relevant to the disease or trait of interest. In this work, we describe EmbedGEM (Embedding Genetic Evaluation Methods), a framework to systematically evaluate the utility of embeddings in genetic discovery. EmbedGEM focuses on comparing embeddings along two axes: heritability and disease relevance. As measures of heritability, we consider the number of genome-wide significant associations and the mean χ2 statistic at significant loci. For disease relevance, we compute polygenic risk scores for each embedding principal component, then evaluate their association with high-confidence disease or trait labels in a held-out evaluation patient set. While our development of EmbedGEM is motivated by embeddings, the approach is generally applicable to multivariate traits and can readily be extended to accommodate additional metrics along the evaluation axes. We demonstrate EmbedGEM’s utility by evaluating embeddings and multivariate traits in two separate datasets: (i) a synthetic dataset simulated to demonstrate the ability of the framework to correctly rank traits based on their heritability and disease relevance and (ii) a real data from the UK Biobank, including metabolic and liver-related traits. Importantly, we show that greater disease relevance does not automatically follow from greater heritability.

Availability and implementation

https://github.com/insitro/EmbedGEM.
Sensitivity of CT-derived radiomic features to extraction libraries and gray-level discretization in the context of immune biomarker discovery
Authors: Ebrahimpour Leyla , Lemaréchal Yannick , Yolchuyeva Sevinj , Orain Michèle , Lamaze Fabien , Driussi Arnaud , Coulombe François , Joubert Philippe , Després Philippe , Manem Venkata S K
Published: September 2024

Objectives

Radiomics can predict patient outcomes by automatically extracting a large number of features from medical images. This study is aimed to investigate the sensitivity of radiomics features extracted from 2 different pipelines, namely, Pyradiomics and RaCat, as well as the impact of gray-level discretization on the discovery of immune checkpoint inhibitors (ICIs) biomarkers.

Methods

A retrospective cohort of 164 non-small cell lung cancer patients administered with ICIs was used in this study. Radiomic features were extracted from the pre-treatment CT scans. Univariate models were used to assess the association of common radiomics features between 2 libraries with progression-free survival (PFS), programmed death ligand 1 (PD-L1), and tumour infiltrating lymphocytes (CD8 counts). In addition, we also examined the impact of gray-level discretization incorporated in Pyradiomics on the robustness of features across various clinical endpoints.

Results

We extracted 1224, 441 radiomic features using Pyradiomics and RaCat, respectively. Among these, 75 features were found to be common between the 2 libraries. Our analysis revealed that the directionality of association between radiomic features and clinical endpoints is highly dependent on the library. Notably, a larger number of Pyradiomics features were statistically associated with PFS, whereas RaCat features showed a stronger association with PD-L1 expression. Furthermore, intensity-based features were found to have a consistent association with clinical endpoints regardless of the gray-level discretization parameters in Pyradiomics-extracted features.

Conclusions

This study highlights the heterogeneity of radiomics libraries and the gray-level discretization parameters that will impact the feature selection and predictive model development for biomarkers. Importantly, our work highlights the significance of standardizing radiomic features to facilitate translational studies that use imaging as an endpoint.

Advances in knowledge

Our study emphasizes the need to select stable CT-derived handcrafted features to build immunotherapy biomarkers, which is a necessary precursor for multi-institutional validation of imaging biomarkers.
External validation of a deep learning model for automatic segmentation of skeletal muscle and adipose tissue on abdominal CT images
Authors: van Dijk David P J , Volmer Leroy F , Brecheisen Ralph , Martens Bibi , Dolan Ross D , Bryce Adam S , Chang David K , McMillan Donald C , Stoot Jan H M B , West Malcolm A , Rensen Sander S , Dekker Andre , Wee Leonard , Olde Damink Steven W M ,   the Body Composition Collaborative, Tweed Thais T T , Tummers Stan , van der Kroft Gregory , Ligthart Marjolein A P , Aberle Merel R , Tim Lubbers , Bongers Bart C , Ubachs Jorne , Kruitwagen Roy F P M , Pugh Siân , Primrose John N , Bridgewater John A , Pucher Philip H , Curtis Nathan J , Dreyer Stephan B , Kazmierski Michael
Published: September 2024

Objectives

Body composition assessment using CT images at the L3-level is increasingly applied in cancer research and has been shown to be strongly associated with long-term survival. Robust high-throughput automated segmentation is key to assess large patient cohorts and to support implementation of body composition analysis into routine clinical practice. We trained and externally validated a deep learning neural network (DLNN) to automatically segment L3-CT images.

Methods

Expert-drawn segmentations of visceral and subcutaneous adipose tissue (VAT/SAT) and skeletal muscle (SM) of L3-CT-images of 3187 patients undergoing abdominal surgery were used to train a DLNN. The external validation cohort was comprised of 2535 patients with abdominal cancer. DLNN performance was evaluated with (geometric) dice similarity (DS) and Lin’s concordance correlation coefficient.

Results

There was a strong concordance between automatic and manual segmentations with median DS for SM, VAT, and SAT of 0.97 (IQR: 0.95-0.98), 0.98 (IQR: 0.95-0.98), and 0.95 (IQR: 0.92-0.97), respectively. Concordance correlations were excellent: SM 0.964 (0.959-0.968), VAT 0.998 (0.998-0.998), and SAT 0.992 (0.991-0.993). Bland-Altman metrics indicated only small and clinically insignificant systematic offsets; SM radiodensity: 0.23 Hounsfield units (0.5%), SM: 1.26 cm2.m−2 (2.8%), VAT: −1.02 cm2.m−2 (1.7%), and SAT: 3.24 cm2.m−2 (4.6%).

Conclusion

A robustly-performing and independently externally validated DLNN for automated body composition analysis was developed.

Advances in knowledge

This DLNN was successfully trained and externally validated on several large patient cohorts. The trained algorithm could facilitate large-scale population studies and implementation of body composition analysis into clinical practice.
Yttrium cuprates modification in linear generator application for power generation
Authors: Emetere Moses Eterigho
Published: September 2024

Yttrium barium copper oxide (YBCO) is used for special applications in linear generators because of its excitation loss, lower weight, and higher efficiency. These qualities enable the compound to operate better than the conventional copper wire coil in the stator unit of the linear generator. However, the continuous use of YBCO in linear generators has a fundamental challenge that affects industrial production and material stability after prolonged use. This paper seeks to sustain the adoption of YBCO by improving its quality for linear generator applications. The yttrium cuprates modification (YBYbCO) was synthesized using the solid-state reaction technique by doping YBCO with ytterbium. The crystalline structure, microstructural pattern, and stability of the new sample were adequately measured and found to be structurally stable to ensure durability. It was reported that applying YBYbCO in the linear generator would lead to a 200% increase in energy generation. The higher number of particles and lower individual particulate resistance enable it to withstand chemical pressure, thereby prolonging the lifespan of the linear generator.
Site- and frequency-specific enhancement of visual search performance with online individual alpha frequency (IAF) repetitive transcranial magnetic stimulation (rTMS) to the inferior frontal junction
Authors: Luber Bruce , Beynel Lysianne , Deng Zhi-De , Appelbaum Lawrence Gregory , Jones Tristan , Harrison Austin , Murphy David L K , Lo Eric , McKinley Richard A , Lisanby Sarah H
Published: September 2024

In this study, repetitive transcranial magnetic stimulation was applied to either the right inferior frontal junction or the right inferior parietal cortex during a difficult aerial reconnaissance search task to test its capacity to improve search performance. Two stimulation strategies previously found to enhance cognitive performance were tested: The first is called “addition by subtraction,” and the second condition utilizes a direct excitatory approach by applying brief trains of high-frequency repetitive transcranial magnetic stimulation immediately before task trials. In a within-subjects design, participants were given active or sham repetitive transcranial magnetic stimulation at either 1 Hz or at 1 Hz above their individual peak alpha frequency (IAF + 1, mean 11.5 Hz), delivered to either the right inferior frontal junction or the right inferior parietal cortex, both defined with individualized peak functional magnetic resonance imaging (fMRI) activation obtained during the visual search task. Results indicated that among the 13 participants who completed the protocol, only active IAF + 1 stimulation to inferior frontal junction resulted in significant speeding of reaction time compared to sham. This site- and frequency-specific enhancement of performance with IAF + 1 repetitive transcranial magnetic stimulation applied immediately prior to task trials provides evidence for the involvement of inferior frontal junction in guiding difficult visual search, and more generally for the use of online repetitive transcranial magnetic stimulation directed at specific functional networks to enhance visual search performance.
Tin oxides as a negative electrode material for Mg-Ion batteries
Authors: Yamamoto Keito , Kawai Takuya , Shimizu Masahiro
Published: September 2024

In this study, SnO as a negative electrode material for Mg-ion batteries exhibits a larger capacity of 540 mA h g−1 at the first cycle than that of pure Sn, despite the lower 88 wt.% Sn content. XRD patterns and XPS spectra reveal alloying/de-alloying, with Sn formed by the reduction during the first charging. The greater capacity is attributed to the shorter Mg diffusion length in the resulting fine Sn particles. The MgO matrix played a role in maintaining the high capacity for more than 10 cycles by diminishing the Sn agglomeration.
Clinical Decision-Making Suffers from Inequivalent Measurement Results and Inadequate Reference Intervals
Authors: van Schrojenstein Lantman Marith , van Berkel Miranda , Kuijper Philip , Langelaan Marloes , Brouwer Nannette , Thelen Marc
Published: September 2024

Background

Appropriate clinical decision-making relies on the interpretation of equivalent measurement results in the context of valid clinical decision limits. Besides guideline-based decision limits, reference intervals (RIs) are commonly used to discriminate between abnormal results and results from “healthy” individuals. This study evaluated the suitability of RIs in light of the analytical bias for laboratories in the Netherlands using one standardized, one harmonized, and one unharmonized measurand (creatinine, hemoglobin, and ferritin, respectively).

Methods

Three types of data were collected: (a) external quality assessment (EQA) performance data from the Dutch Foundation for Quality Assurance in Laboratory Medicine (SKML); (b) the RIs reported by laboratories for a 55-year-old female; and (c) harmonized RIs established by using unique routine patient results using RefineR. Routinely used RIs (b) were compared to the harmonized RIs (c) and evaluated in combination with the analytical bias at the lower and upper reference limits.

Results

Laboratories reported a variety of routinely used RIs that were inconsistent with the analytical bias, with differences between measurement procedures. The use of assays that perform within allowable bias limits does not automatically guarantee that the appropriate RI is used, allowing potential for structural misinterpretation of important diagnoses in patients.

Conclusions

The use of RIs that are inconsistent with the analytical bias causes unnecessary between-laboratory differences in clinical decision-making. Adopting harmonized RIs facilitates similar interpretation of results across facilities. Harmonized RIs can be adopted immediately if the observed bias is acceptable or eliminated, or after standardization/harmonization of measurands without complete metrological traceability.