bluuebunny/crossref_metadata_2025 huggingface dataset:
Geometry transition in spinfoams
Authors: Christodoulou Marios , D’Ambrosio Fabio , Theofilis Charalampos
Published: July 2024

We show how the fixed-spin asymptotics of the EPRL model can be used to perform the spin-sum for spin foam amplitudes defined on fixed two-complexes without interior faces and contracted with coherent spin-network states peaked on a discrete simplicial geometry with macroscopic areas. We work in the representation given in (Han and Krajewski 2014 Class. Quantum Grav.
31 01500). We first rederive the latter in a different way suitable for our purposes. We then extend this representation to 2-complexes with a boundary and derive its relation to the coherent state representation. We give the measure providing the resolution of the identity for Thiemann’s state in the twisted geometry parametrization. We then piece together these with other results in the literature and show how the spin sum can be performed analytically using the model asymptotics. These results are relevant to analytic investigations regarding the transition of a black hole to a white hole geometry. In particular, this work was the basis of the calculation presented in Christodoulou and D’Ambrosio (2018 (arXiv:1801.03027)).
Design, development, and testing of active valve piezo-hydraulic pump
Authors: Nayak Sandesh , Rao Muralidhara
Published: July 2024

Valves play a major role in rectifying the fluid flow through piezo-hydraulic pumps, which may be active or passive. Passive valves operate due to changes in the fluid pressure whereas active valves are operated through control signals. This paper presents a novel design of an active valve chamber assembly for a piezo-hydraulic pump. It is a novel design since none of the research publications has addressed the application of a Flexurally amplified piezoelectric actuator (FAPA) for valve actuation in active valve chamber assembly. The piezo-hydraulic pump design is done using solid edge design software. FAPA’s are used for pumping and valve actuation. Structural analysis with experimental verification for the valve chamber component is presented. The valve opening and the pumping displacement are mathematically modeled in MATLAB Simulink software. Also, mathematical simulations for pump flow rates at different actuation frequencies and voltage are discussed. The piezo-hydraulic pump components are fabricated and assembled with the actuators. Experimental investigations on the flow rate performance of the active valve piezo-hydraulic pump are carried out with changing frequency and voltage amplitude of actuators. The interpretation of results is done by comparing the experimental and simulation results. During experiments, the pump delivered a maximum flow rate of 4.5 ml min−1 at 140 V when actuated at 0.25 Hz actuation frequency.
Immobilizing antibody biorecognition layers on Au–TiO2 thin films: direct (physisorption) vs. DSP-crosslinking (chemisorption) surface functionalization
Authors: Meira Diana I , Barbosa Ana I , Proença Manuela , Pereira-Silva Patrícia , Borges Joel , Correlo Vitor M , Reis Rui L , Vaz Filipe
Published: July 2024

The immobilization design strategy plays an important role in biosensor development and its sensing performance. Both adsorption (physisorption) and cross-linker functionalization (chemisorption) are common approaches for immobilizing a bioreceptor layer. In this work, these two approaches were studied and compared, envisaging a functional and strongly attached bioreceptor layer onto sputtered Au–TiO2 thin films. DSP cross-linker (Lomant’s reagent) was used in the thin film’s functionalization, and the effect of different concentrations on the development of an adhesion layer was investigated. Surface morphology analysis of functionalized thin films suggested the development of uniformly coated self-assembled layers. However, DSP islands with a fractal structure were found for a concentration of 4 mg ml−1. Infrared spectroscopy confirmed the cross-linker functionalization at the thin film’s surface. Confocal microscopy of immobilized fluorescent antibodies revealed that DSP islands improve the chemical surface area available for bioreceptor immobilization. Moreover, an immunoassay using mouse IgG interaction with fluorescent anti-mouse IgG (Fab specific), working as capture and detection antibody, respectively, showed that DSP functionalization favors antibodies orientation and adhesion strength to the surface, when compared to physisorption.
Cooling of hadronic stars with dark matter components
Authors: Fibger Matheus , Negreiros Rodrigo , Lourenço Odilon , Dutra Mariana
Published: July 2024

Neutron stars, due to their extreme densities and pressures, act as unique laboratories for the study of dense matter. Recent research has introduced the notion of dark matter (DM) particles being part of neutron stars’ composition, thus providing a novel path for investigating this mysterious universe component. This research builds on previous studies and shifts the focus towards exploring the effects of DM mixed with hadrons on the thermal evolution of stars. It involves analyzing the cooling curves of these stars and matching them with observed data from thermally emitting compact objects. This study will demonstrate that, despite being thermally inert, DM as postulated in this model can indirectly influence the thermal evolution of neutron stars. It will be illustrated that DM has the potential to modify the thermal relaxation time and expand the range of temperatures that neutron stars of various masses can exhibit. Through this comparative analysis, the model’s precision will be evaluated, and the properties of DM particles will be further delineated. The goal of this study is to deepen our comprehension of neutron stars and the influence of DM on their thermal evolution.
Exploring charge transport dynamics in a cryogenic P-type germanium detector
Authors: Acharya P , Fritts M , Mei D-M , Wang G-J , Mahapatra R , Platt M
Published: July 2024

This study explores the dynamics of charge transport within a cryogenic P-type Ge particle detector, fabricated from a crystal cultivated at the University of South Dakota. By subjecting the detector to cryogenic temperatures and an Am-241 source, we observe evolving charge dynamics and the emergence of cluster dipole states, leading to the impact ionization process at 40 mK. Our analysis focuses on crucial parameters: the zero-field cross-section of cluster dipole states and the binding energy of these states. For the Ge detector in our investigation, the zero-field cross-section of cluster dipole states is determined to be 8.45 × 10−11 ± 4.22 × 10−12 cm2. Examination of the binding energy associated with cluster dipole states, formed by charge trapping onto dipole states during the freeze-out process, reveals a value of 0.034 ± 0.0017 meV. These findings shed light on the intricate charge states influenced by the interplay of temperature and electric field, with potential implications for the sensitivity in detecting low-mass dark matter.
Multi-weighted symbolic sequence entropy: a novel approach to fault diagnosis and degradation monitoring of rotary machinery
Authors: Wu Hongan , Yuan Rui , Lv Yong , Stein Dalton L , Zhu Weihang
Published: July 2024

Structural health monitoring relies heavily on measurements. Entropy theory is emerging as a critical quantitative analysis technique for interpreting measured data for both health monitoring and fault identification of structural systems. This paper introduces the algorithms of weighted symbolic sequence entropy (WSSE) and its multi-weighted derivation, termed multi-weighted symbolic sequence entropy (MWSSE). WSSE optimizes the existing algorithms, including symbolic sequence entropy and improved symbolic sequence entropy, by introducing a weighting factor in the computation process of the algorithm. WSSE significantly contributes to enlarging the difference between normal and fault sequences of signals in rotary machinery. The multi-weighted derivation of WSSE, namely MWSSE, more effectively depicts the dynamical characteristics of rotary machinery by utilizing entropy values of multiple weighting factors as health indicators. The MWSSE-based degradation monitoring and fault identification approaches developed by the authors are validated through application research and comparative analysis. These novel entropy algorithms offer innovative quantitative analysis techniques for fault diagnosis in rotary machinery and structural health monitoring and hold potential for application in broader research fields.
REDef-DETR: real-time and efficient DETR for industrial surface defect detection
Authors: Li Dejian , Jiang Changhong , Liang Tielin
Published: July 2024

Industrial surface defect detection is an important part of industrial production, which aims to identify and detecting various defects on the surface of product to ensure quality and meet customer requirements. With the development of deep learning and image processing technologies, the surface defect detection methods based on computer vision has become the mainstream method. However, the prevalent convolutional neural network-based defect detection methods also have many problems. For example, these methods rely on post-processing of Non-Maximum Suppression and have poor detection ability for small targets, which affects the speed and accuracy of surface defect detection in industrial scenarios. Therefore, we propose a novel DEtection TRansformer-based surface defect detection method. Firstly, we propose a Multi-scale Contextual Information Dilated module and fuse it into the backbone. The module is mainly composed of large kernel convolutions, which aims to expand the receptive field of the model, thus reducing the leakage rate of the model. Moreover, we design an efficient encoder which mainly contains two important modules, namely feature enhancement based on cascaded group attention module and efficient feature fusion module based on content-aware. The former module effectively enhances the high-level semantic information extracted by the backbone, thus enabling the model to better interpret features, and it can improve the problem of high computational cost of transformer encoder, thus increasing the detection speed. The latter module performs multi-scale feature fusion across the feature information of various scales, thus improving the detection accuracy of the model for small-size defects. Experimental results show that the proposed method achieves 80.6%mAP and 80.3FPS on NEU-DET, and 98.0%mAP and 79.4FPS on PCB-DET. Our proposed method exhibits excellent detection performance and achieves real-time and efficient surface defect detection capability to meet the needs of industrial surface defect detection.
A route for tunable C-VO doped perovskite SrTiO3 functionalities through epitaxial strain engineering
Authors: AL-Hamadany Raied A S , Goss J P , Briddon P R
Published: July 2024

Using density functional theory calculations, the interaction between oxygen vacancies and carbon in bi-axially strained SrTiO3 has been investigated. CTi-Vo binding energy and reorientation of CTi have been examined for ±1%, ±2%, ±3% and ±4% compressive and tensile strains. The results show that compressive strain is an effective route to restrict the diffusion of electrically active Vo in the presence of CTi dopants. According to our results the reorientation barrier volumetric and bi-axial strain dependences differ in the compression and tension regimes and is expected to affect dielectric characteristics of SrTiO3 under an alternating electric field.
Atomic layer deposition of Al-doped ZnO nanomembrane with in situ monitoring
Authors: Wang Jinlong , Gu Zilong , Zhao Zhe , Mei Yu , Ke Xinyi , Chen Yihao , Huang Gaoshan , Mei Yongfeng
Published: July 2024

Due to shortcomings such as poor homogeneity of Al doping, precisely controlling the thickness, inability to conformally deposit on high aspect ratio devices and high pinhole rate, the applications of Al-doped ZnO (AZO) nanomembrane in integrated optoelectronic devices are remarkably influenced. Here, we report in situ monitoring during the atomic layer deposition (ALD) of AZO nanomembrane by using an integrated spectroscopic ellipsometer. AZO nanomembranes with different compositions were deposited with real-time and precise atomic level monitoring of the deposition process. We specifically investigate the half-reaction and thickness evolution during the ALD processes and the influence of the chamber temperature is also disclosed. Structural characterizations demonstrate that the obtained AZO nanomembranes without any post-treatment are uniform, dense and pinhole-free. The transmittances of the nanomembranes in visible range are >94%, and the optimal conductivity can reach up to 1210 S cm−1. The output of current research may pave the way for AZO nanomembrane to become promising in integrated optoelectronic devices.
DeCoGAN: MVCT image denoising via coupled generative adversarial network
Authors: Zhang Kunpeng , Niu Tianye , Xu Lei
Published: July 2024

Objective. In helical tomotherapy, image-guided radiotherapy employs megavoltage computed tomography (MVCT) for precise targeting. However, the high voltage of megavoltage radiation introduces substantial noise, significantly compromising MVCT image clarity. This study aims to enhance MVCT image quality using a deep learning-based denoising method. Approach. We propose an unpaired MVCT denoising network using a coupled generative adversarial network framework (DeCoGAN). Our approach assumes that a universal latent code within a shared latent space can reconstruct any given pair of images. By employing an encoder, we enforce this shared-latent space constraint, facilitating the conversion of low-quality (noisy) MVCT images into high-quality (denoised) counterparts. The network learns the joint distribution of images from both domains by leveraging samples from their respective marginal distributions, enhanced by adversarial training for effective denoising. Main Results. Compared to an analytical algorithm (BM3D) and three deep learning-based methods (RED-CNN, WGAN-VGG and CycleGAN), the proposed method excels in preserving image details and enhancing human visual perception by removing most noise and retaining structural features. Quantitative analysis demonstrates that our method achieves the highest peak signal-to-noise ratio and Structural Similarity Index Measurement values, indicating superior denoising performance. Significance. The proposed DeCoGAN method shows remarkable MVCT denoising performance, making it a promising tool in the field of radiation therapy.
GWO+RuleFit: rule-based explainable machine-learning combined with heuristics to predict mid-treatment FDG PET response to chemoradiation for locally advanced non-small cell lung cancer
Authors: Duan Chunyan , Liu Qiantuo , Wang Jiajie , Tong Qianqian , Bai Fangyun , Han Jie , Wang Shouyi , Hippe Daniel S , Zeng Jing , Bowen Stephen R
Published: July 2024

Objective. Vital rules learned from fluorodeoxyglucose positron emission tomography (FDG-PET) radiomics of tumor subregional response can provide clinical decision support for precise treatment adaptation. We combined a rule-based machine learning (ML) model (RuleFit) with a heuristic algorithm (gray wolf optimizer, GWO) for mid-chemoradiation FDG-PET response prediction in patients with locally advanced non-small cell lung cancer. Approach. Tumors subregions were identified using K-means clustering. GWO+RuleFit consists of three main parts: (i) a random forest is constructed based on conventional features or radiomic features extracted from tumor regions or subregions in FDG-PET images, from which the initial rules are generated; (ii) GWO is used for iterative rule selection; (iii) the selected rules are fit to a linear model to make predictions about the target variable. Two target variables were considered: a binary response measure (ΔSUVmean ⩾ 20% decline) for classification and a continuous response measure (ΔSUVmean) for regression. GWO+RuleFit was benchmarked against common ML algorithms and RuleFit, with leave-one-out cross-validated performance evaluated by the area under the receiver operating characteristic curve (AUC) in classification and root-mean-square error (RMSE) in regression. Main results. GWO+RuleFit selected 15 rules from the radiomic feature dataset of 23 patients. For treatment response classification, GWO+RuleFit attained numerically better cross-validated performance than RuleFit across tumor regions and sets of features (AUC: 0.58–0.86 vs. 0.52–0.78, p = 0.170–0.925). GWO+Rulefit also had the best or second-best performance numerically compared to all other algorithms for all conditions. For treatment response regression prediction, GWO+RuleFit (RMSE: 0.162–0.192) performed better numerically for low-dimensional models (p = 0.097–0.614) and significantly better for high-dimensional models across all tumor regions except one (RMSE: 0.189–0.219, p < 0.004). Significance. The GWO+RuleFit selected rules were interpretable, highlighting distinct radiomic phenotypes that modulated treatment response. GWO+Rulefit achieved parsimonious models while maintaining utility for treatment response prediction, which can aid clinical decisions for patient risk stratification, treatment selection, and biologically driven adaptation. Clinical trial: NCT02773238.
Uncertainty quantification via localized gradients for deep learning-based medical image assessments
Authors: Schott Brayden , Pinchuk Dmitry , Santoro-Fernandes Victor , Klaneček Žan , Rivetti Luciano , Deatsch Alison , Perlman Scott , Li Yixuan , Jeraj Robert
Published: July 2024

Objective. Deep learning models that aid in medical image assessment tasks must be both accurate and reliable to be deployed within clinical settings. While deep learning models have been shown to be highly accurate across a variety of tasks, measures that indicate the reliability of these models are less established. Increasingly, uncertainty quantification (UQ) methods are being introduced to inform users on the reliability of model outputs. However, most existing methods cannot be augmented to previously validated models because they are not post hoc, and they change a model’s output. In this work, we overcome these limitations by introducing a novel post hoc UQ method, termed Local Gradients UQ, and demonstrate its utility for deep learning-based metastatic disease delineation. Approach. This method leverages a trained model’s localized gradient space to assess sensitivities to trained model parameters. We compared the Local Gradients UQ method to non-gradient measures defined using model probability outputs. The performance of each uncertainty measure was assessed in four clinically relevant experiments: (1) response to artificially degraded image quality, (2) comparison between matched high- and low-quality clinical images, (3) false positive (FP) filtering, and (4) correspondence with physician-rated disease likelihood. Main results. (1) Response to artificially degraded image quality was enhanced by the Local Gradients UQ method, where the median percent difference between matching lesions in non-degraded and most degraded images was consistently higher for the Local Gradients uncertainty measure than the non-gradient uncertainty measures (e.g. 62.35% vs. 2.16% for additive Gaussian noise). (2) The Local Gradients UQ measure responded better to high- and low-quality clinical images (p < 0.05 vs p > 0.1 for both non-gradient uncertainty measures). (3) FP filtering performance was enhanced by the Local Gradients UQ method when compared to the non-gradient methods, increasing the area under the receiver operating characteristic curve (ROC AUC) by 20.1% and decreasing the false positive rate by 26%. (4) The Local Gradients UQ method also showed more favorable correspondence with physician-rated likelihood for malignant lesions by increasing ROC AUC for correspondence with physician-rated disease likelihood by 16.2%. Significance. In summary, this work introduces and validates a novel gradient-based UQ method for deep learning-based medical image assessments to enhance user trust when using deployed clinical models.
Mathematical analysis of FLASH effect models based on theoretical hypotheses
Authors: Hu Ankang , Zhou Wanyi , Qiu Rui , Li Junli
Published: July 2024

Objective. Clinical applications of FLASH radiotherapy require formulas to describe how the FLASH radiation features and other related factors determine the FLASH effect. Mathematical analysis of the models can connect the theoretical hypotheses with the radiobiological effect, which provides the foundation for establishing clinical application models. Moreover, experimental and clinical data can be used to explore the key factors through mathematical analysis. Approach. We abstract the complex models of the oxygen depletion hypothesis and radical recombination-antioxidants hypothesis into concise mathematical equations. The equations are solved to analyze how the radiation features and other factors influence the FLASH effect. Then we propose methodologies for determining the parameters in the models and utilizing the models to predict the FLASH effect. Main results. The formulas linking the physical, chemical and biological factors to the FLASH effect are obtained through mathematical derivation of the equation. The analysis indicates that the initial oxygen concentration, radiolytic oxygen consumption and oxygen recovery are key factors for the oxygen depletion hypothesis and that the level of antioxidants is the key factor for the radical recombination-antioxidants hypothesis. According to the model derivations and analysis, the methodologies for determining parameters and predicting the FLASH effect are proposed: (1) the criteria for data filtration, (2) the strategy of hybrid FLASH and conventional dose rate (CONV) irradiation to ensure the acquisition of effective experimental data across a wide dose range, (3) the pipelines of fitting parameters and predicting the FLASH effect. Significance. This study establishes the quantitative relationship between the FLASH effect and key factors. The derived formulas can be used to calculate the FLASH effect in future clinical FLASH radiotherapy. The proposed methodologies guide to obtain sufficient high-quality datasets and utilize them to predict the FLASH effect. Furthermore, this study indicates the key factors of the FLASH effect and offers clues to further explore the FLASH mechanism.
Interference-induced suppression of particle emission from a Bose–Einstein condensate in lattice with time-periodic modulations
Authors: Lai 赖 Long-Quan 龙泉 , Li 李 Zhao 照
Published: July 2024

Emission of matter-wave jets from a parametrically driven condensate has attracted significant experimental and theoretical attention due to the appealing visual effects and potential metrological applications. In this work, we investigate the collective particle emission from a Bose–Einstein condensate confined in a one-dimensional lattice with periodically modulated interparticle interactions. We give the regimes for discrete modes, and find that the emission can be distinctly suppressed. The configuration induces a broad band, but few particles are ejected due to the interference of the matter waves. We further qualitatively model the emission process and demonstrate the short-time behaviors. This engineering provides a way to manipulate the propagation of particles and the corresponding dynamics of condensates in lattices, and may find application in the dynamical excitation control of other nonequilibrium problems with time-periodic driving.
Refueling of field-reversed configuration core via axial plasmoids injection
Authors: Asai T. , Takahashi T. , Kobayashi D. , Seki T. , Takeuchi Y. , Mitarai O. , Morelli J. , Mizuguchi N. , Dettrick S. , Gota H. , Roche T. , Matsumoto T. , Binderbauer M. , Tajima T. , Inomoto M. , Takahashi T.
Published: July 2024

This study successfully developed a refueling technique for a field-reversed configuration (FRC) via axial plasmoid injection and demonstrated it on the FAT-CM device at Nihon University. The target FRC is generated using the collisional-merging formation technique combined with conical theta-pinch formation. Plasmoids with an FRC-like configuration are coaxially injected from both ends of the FAT-CM device toward the preexisting target FRC. Postinjection, the system achieves equilibrium, resulting in increases by factors of 1.8 and 2.4 in the total inventory and plasma energy, respectively, compared to cases without injection. This method effectively accomplishes FRC refueling while preserving the intrinsic characteristics of a simply connected, axisymmetric configuration and a high beta value approaching unity. Therefore, this approach offers potential for repetitive refueling in the reactor stage having a FRC plasma core. Experimental outcomes are compared with magnetohydrodynamic simulation results. In the collisional merging process, the characteristics of the pre-collision plasmoids, such as the strong toroidal rotation and coherent FRC-like magnetic field structures of the FRC, are not preserved. Experimental environments have been constructed to investigate such unique properties of the resulting FRCs.
Current benefits of wildfire smoke for yields in the US Midwest may dissipate by 2050
Authors: Behrer A Patrick , Wang Sherrie
Published: July 2024

Wildfires throughout western North America produce smoke plumes that can stretch across the agricultural regions of the American Midwest. Climate change may increase the number and size of these fires and subsequent smoke plumes. These smoke plumes change solar radiation, meteorological conditions, and surface pollutant concentrations during the crop growing season and consequently influence yields of both corn and soybeans. We use a twelve-year panel of county-level yields from all counties east of the 100th meridian combined with measures of exposure to smoke plumes of low and high-density during the growing season to show that low-density plumes enhance yields while high-density plumes decrease yields. These effects appear to be driven by different changes in solar radiation induced by each type of plume but we observe changes in surface pollutants and precipitation as well. Because there are more low-density plumes today, the net effect is a slight increase in yields on average. As climate change makes wildfires larger and more frequent, the overall impact of smoke on yields would be be substantially more negative.
Little evidence of hysteresis in regional precipitation, when indexed by global temperature rise and fall in an overshoot climate simulation
Authors: Walton Jeremy , Huntingford Chris
Published: July 2024

Society is aiming to stabilise climate at key temperature thresholds, such as global warming at or below 1.5 °C or 2.0 °C above preindustrial levels. However, greenhouse gas emissions are failing to decline, and if they continue on their current trajectory it is likely that such thresholds will be crossed in the decades ahead. Because of this risk, there is an emerging focus on overshoot, where, for a temporary period, global warming is allowed to cross critical thresholds to reach a peak value before decreasing to the desired limit. A key question about overshoots is whether there are hysteresis effects—that is, whether global or regional climate has properties that differ between the phase of global warming increase and the phase of decreasing. Here, we analyse temperature and precipitation data from five Earth System Models (ESMs) forced by the SSP5-3.4-OS CMIP6 overshoot scenario. We look at the level of precipitation during two periods of near-identical global warming: one whilst temperatures are rising, and the other when they are falling. For global means, we find a statistically significant difference between precipitation values during the two periods. This is an example of hysteresis, as the reversion to an earlier global warming state results in a level of global rainfall which is different from that observed when warming was increasing. Spatial disaggregation of rainfall differences between the two near-identical warming levels shows the largest differences in the tropical region, which are statistically significant for four of the five ESMs. When considering much smaller regions, including parts of the tropics, there remains some evidence of hysteresis. However, the differences are no longer statistically significant against a background of substantial interannual rainfall variability. We discuss the implications of our findings for climate impacts assesments.
Mitigation of laser plasma filamentation by rotating beam smoothing scheme
Authors: Nie Hongbin , Xiong Hao , Zhong Zheqiang , Zhang Bin
Published: July 2024

The propagation of intense laser beams in plasma inevitably gives rise to laser plasma instabilities, which have a significant impact on the illumination uniformity of the focused spot on the target in inertial confinement fusion (ICF) facilities. Here we propose an ultrafast smoothing scheme using a rotating beam (RB) to mitigate the laser plasma filamentation. Using the propagation model of the rotating beam in plasma for the laser-plasma self-focusing (SF) and filamentation, the filamentation characteristics of laser spots were analyzed. The results indicate that the rotating beam smoothing scheme, operating at picosecond timescale, exhibits superior mitigation effect of laser plasma filamentation.
Simple equation predicts how quickly animals flap their wings
Authors: Harris Margaret
Published: July 2024

Animals flap their wings and fins at a rate determined by the same simple mathematical expression that is valid regardless of the animal’s size or flying style.
David Charbonneau and Sara Seager win Kavli Prize
Authors: Banks Michael
Published: July 2024

Exoplanet researchers David Charbonneau from Harvard University and Sara Seager from the Massachusetts Institute of Technology have won the 2024 Kavli Prize in Astrophysics.
Fusion’s tritium challenge
Authors: Evans John
Published: July 2024

John Evans says that the issue of producing fuel for fusion power plants will need to be solved before the technology can become a viable energy source.
Ask me anything: Daniel Hook
Authors: Durrani Matin
Published: July 2024

Daniel Hook is chief executive of Digital Science, a co-founder of the research-information management provider Symplectic, and of the Research on Research Institute. A theoretical physicist by training, he still does research in his spare time, with visiting positions at Imperial College London and Washington University in St Louis.
Software installation threat detection based on attention mechanism and improved convolutional neural network in IOT platform
Authors: Liu Chongwei , Pang Jinlong
Published: July 2024

With of the Internet of Things (IoT) developing and the network technique progressing, malware attacks continue to occur, seriously endangering the information and property security of Internet of Things device users. To ensure the security of the Internet of Things platform and improve the efficiency of malware and vulnerability detection, a software installation threat detection model based on attention mechanism and improved convolutional neural network is constructed. Firstly, the enhanced dynamic symbolic execution module and forward program slicing algorithm are used to extract dynamic features, and then the improved convolutional neural network is utilized to classify malware. In the existing software of IoT devices, the inlining correlation function is studied using the inlining strategy, and the weight between the target pixel and the global pixel is calculated using the attention mechanism, through which the logic and correlation between the triples are correlated. Then, deep residual network is used to detect software vulnerabilities. This enables threat detection before and after software installation. In comparison with the current popular vulnerability detection model experiments, the accuracy, recall rate, accuracy rate and running time of the constructed model in the process of vulnerability detection are 0.975, 0.970, 0.968 and 0.02 s, respectively. Compared with other models, the research design model has better performance. This shows that this built model can effectively detect software installation threats, and has high detection accuracy and operation efficiency, which can provide strong support for the Internet of Things platform’s security protection.
Introducing Environmental Research: Food Systems—cultivating multidisciplinary solutions to transform food systems in an era of global change
Authors: Mueller Nathaniel D
Published: July 2024

Environmental Research: Food Systems is a new multidisciplinary, open-access, and society-run journal from IOP Publishing dedicated to informing solutions to the considerable environmental, social, and economic challenges facing food systems. The journal’s scope covers the entirety of food systems, from production to consumption, with research on the interactions between food systems and the environment particularly encouraged. Supported by a distinguished Editorial Board with diverse disciplinary backgrounds, the inaugural issue features studies on sustainable agricultural practices, global food trade, crop modeling, climate change adaptation, and sustainable consumption for climate change mitigation. The journal is committed to rigorous peer review, the highest standards of research integrity, and open access publications. By providing a new community-supported venue for food systems researchers, Environmental Research: Food
Systems aims to drive innovation, inform policy, and foster sustainable food systems worldwide.
On varieties with Ulrich twisted conormal bundles
Authors: Antonelli Vincenzo , Casnati Gianfranco , Lopez Angelo , Raychaudhury Debaditya
Published: July 2024

We study varieties

X
⊂

P

r

X \subset \mathbb {P}^r

such that

N
X
∗

(
k
)

N_X^*(k)

is an Ulrich vector bundle for some integer

k
k

. We first prove that such an

X
X

must be a curve. Then we give several examples of curves with

N
X
∗

(
k
)

N_X^*(k)

an Ulrich vector bundle.
One-ended spanning trees and definable combinatorics
Authors: Bowen Matt , Poulin Antoine , Zomback Jenna
Published: July 2024

Let

(
X
,
τ
)

(X,\tau )

be a Polish space with Borel probability measure

μ
\mu

, and

G
G

a locally finite one-ended Borel graph on

X
X

. We show that

G
G

admits a Borel one-ended spanning tree generically. If

G
G

is induced by a free Borel action of an amenable (resp., polynomial growth) group then we show the same result

μ
\mu

-a.e. (resp., everywhere). Our results generalize recent work of Timár, as well as of Conley, Gaboriau, Marks, and Tucker-Drob, who proved this in the probability measure preserving setting. We apply our theorem to find Borel orientations in even-degree graphs and measurable and Baire measurable perfect matchings in regular bipartite graphs, refining theorems that were previously only known to hold for measure preserving graphs. In particular, we prove that bipartite one-ended

d
d

-regular Borel graphs admit Baire measurable perfect matchings.
Markov additive friendships
Authors: Döring Leif , Trottner Lukas , Watson Alexander
Published: July 2024

The Wiener–Hopf factorisation of a Lévy or Markov additive process describes the way that it attains new extrema in terms of a pair of so-called ladder height processes. Vigon’s theory of friendship for Lévy processes addresses the inverse problem: when does a process exist which has certain prescribed ladder height processes? We give a complete answer to this problem for Markov additive processes, provide simpler sufficient conditions for constructing processes using friendship, and address in part the question of the uniqueness of the Wiener–Hopf factorisation for Markov additive processes.
The Manifold Faces of Political Resistance: The Woman, Life, Freedom Movement
Authors: Orazani Nima , Teymoori Ali
Published: July 2024

The Woman, Life, Freedom (WLF) movement in Iran embodies radical and progressive ideals (e.g., a secular constitution, autonomy for women, right to bodily integrity and a decent life) in a country with a repressive, patriarchal, and electoral authoritarian political system. We describe the WLF movement and explain how a diverse range of creative acts of resistance has provided the movement with a rich repertoire of cultural and symbolic capital. We discuss three main qualities of the WLF—its lack of centralized leadership and organizational structure, its spontaneity, and its informal cooperative nature—and highlight how oppositional lifestyle and identities preceded the WLF movement. Finally, we discuss two neglected theoretical issues in psychological literature on collective action: (a) the body as a site of resistance, and (b) the role of articulation in resistance. We discuss the implications of the focus on the body and articulation for the social psychology of resistance.
Gendering Democratic Resistance to Authoritarianism: Leni Robredo’s Presidential Campaign
Authors: Montiel Cristina Jayme , Delos Santos Junix Jerald I , Uyheng Joshua
Published: July 2024

Women-led democratic movements in repressive contexts confront gendered discourses at the nexus of authoritarianism and patriarchy. However, the role of gender in resistance to authoritarian populism remains understudied. Additionally, less is known about how women in new democracies resist, outside Western feminist discourse. Through a discursive view of resistance, we examine how a Filipina presidential candidate draws on gendered discourses to enact democratic resistance during her electoral campaign. Cosmopolitan discourses of gender equality and traditional discourses of motherhood were employed across various junctures of the campaign. While the former asserts Robredo’s political worthiness independent of her late husband, the latter frames social reforms within a relational language of maternal care. The “radical love” discourse transcends binaries of the two, mobilizing an electoral campaign at the crossroads of patriarchy and authoritarianism. Findings hold implications for contemporary psychologies of gendered political resistance in the contexts of new and hybrid democracies.
“They Should Take Care of Themselves, We Have Our Own Problems!”
Authors: Messanga Gustave Adolphe , Ekango Nzekaih Hermann Kevin , Taffo Nemboué Willy , Npiane Ngongueu Sonia , Nzeuta Lontio Sylvestre , Fotso Magne Pamela , Yoh Fopa Donald Brice
Published: July 2024

In the literature on sympathetic resistance (also referred to as ally activism, bystander interventions, or outgroup activism), bystanders’ action against violent oppression is theorized to have substantial political impacts. However, much work in this area reveals bias, assuming a negative set of moral and psychological attributes (e.g., passivity). We argue that this bias arises partly from not sufficiently accounting for the socio-political context. Applying a situated perspective to the case of the Rwandan genocide—an example of ethnopolitical violence in a multi-ethnic, institutionally authoritarian context—we posit that two systemic strategies (instrumentalization of ethnicity and systematic terror) shape bystanders’ subjective perceptions of an outgroup’s oppression, thereby repressing sympathetic resistance and demobilizing solidarity with ethnic outgroups to facilitate bystander passivity in ethnic conflicts. We call for future research to test our theoretical ideas and to better situate the psychology of sympathetic resistance in its sociopolitical context.
The Psychology of Resistance in Violent and Repressive Contexts: A Conclusion and a Beginning
Authors: Bou Zeineddine Fouad , Vollhardt Johanna Ray
Published: July 2024

In this chapter, we provide a synthesis of this volume’s contributions to understanding the psychology of resistance in violent, repressive contexts. We argue that these contributions challenge the assumptions of social psychological research on resistance conducted in Western democratic nations. Taken together, the chapters in this volume offer a richer understanding of the dynamics and relational aspects of resistance in contexts of violence and repression, and a more thorough understanding of the continuous intragroup and intergroup negotiation of resistance strategies in changing contexts. They contextualize the psychology of resistance further by considering the conditions necessary for resistance to arise or be suppressed, as well as explaining support for different resistance tactics. We also discuss the limitations of this volume and their connections to disciplinary and theoretical gaps in social psychology. We outline future directions for research on the psychology of resistance in violent and repressive contexts and beyond.
The Dhobis of Old Delhi
Authors: Mitra Channa Subhadra
Published: July 2024

This chapter describes the community of Sheheri dhobis who were part of the city of Old Delhi at the time of its foundation in the seventeenth century. It also gives a history of the city as seen through the eyes of the dhobis, whose association with the urban landscape, their ghats for washing clothes, their katras, and their traditional relationship with the river Yamuna form the focus of this study. The history of Delhi from various sources, along with the communities that belong to it, the river, and the people in relation to the river are described as a backdrop to the rest of the work. The expansion of Delhi and the process of urbanization and gentrification of the city, the demographic changes and major historical events that transformed and traumatized the city are also described.
Living Life as a Dhobi (Man and Woman)
Authors: Mitra Channa Subhadra
Published: July 2024

The dhobis can be taken to represent a collective identity, but each person lives a life of his or her own. In this chapter the various phases of growing up as a dhobi are described, with examples taken from actual people. The approach is gendered, and the different experiences of being a man or a woman as well as the changes taking place over time are described through thick ethnography. Family life, power equations in the family, the relative lack of patriarchy among them, the roles played by women and men, and the changes in lifestyle are all described in detail with the help of examples. The chapter also describes the migrant dhobis, their relations with native dhobis, as well as the internal stratification of the community. The dhobi’s forays into education and taking up jobs outside of the dhobi occupation, through reservation and otherwise, and the discrimination faced by them as untouchables all find a place in this chapter.
Negotiating Power in the Realm of the Sacred
Authors: Mitra Channa Subhadra
Published: July 2024

For those at the bottom of society, the supernatural powers are sources of succour and support. Being untouchables, the dhobis have not had access to the services of the Brahmins and have been kept out of the upper-caste temples. They, like other Dalits, had found the Sufi shrines and modes of personal devotion a way of alleviating their suffering and desire for spiritual solace. With changing times and a relative increase in prosperity, they are now turning more towards mainstream Hinduism but prefer those deities to whom they can relate, especially those they feel represent the downtrodden and take care of injustice. They have begun to perform rituals for their dhobi deities with great pomp and show—not to follow the path of the upper castes, but to assert their own identity as dhobis. The political dimension of ritual performance is reflected in their choice of deities such as Bhairon and Sai Baba. There is also a movement away from overt association with Sufi shrines and the Ala that had played a significant role in their lives and to which they still adhere covertly, and these remain at the core of their beliefs in spite of ostentatious acceptance of Hinduism.
The Political Realm
Authors: Mitra Channa Subhadra
Published: July 2024

The dhobis have never engaged in any militant oppositional political activities like the Dalits of the Dalit Panther movement, nor do they subscribe to the Dalit identity. This chapter discusses in detail the reasons for the dhobis to launch their protest from within the caste system rather than trying to reject it. The tie-up of their caste and occupation and the viability of the latter even within the modern capitalist system makes them reluctant to give up their dhobi identity, which they now flaunt as a difference and a skill and not as subordinated. They have never subscribed to the upper-caste versions of caste hierarchy and now are more vocal in making their claims to equality, largely through their rituals. They have a personalized relation with their clients, and their traditional work is more of a one-to-one relation, unlike that of scavengers, who work in the public realm and have therefore developed class consciousness, which is absent among the dhobis. The conjunction of economy and politics makes the dhobis take a different path to identity than some other lower castes.
Conclusion
Authors: Mitra Channa Subhadra
Published: July 2024

This concluding chapter describes the changing patterns of aspirations and seeking of a new identity by the dhobis as they wish to establish that they are respectable and equal citizens of a democracy. The major change is negotiated on the bodies of women, who are the first to be withdrawn from the public space and reinstated within the domestic realm or in jobs that take them out of the dhobi identity. This is in recognition of the exploitable status to which the bodies of lower-caste women have traditionally been assigned. The chapter also describes the way the future of the city is being shaped through corporate interests, the needs of a global market, and the distorted vision of policymakers who fail to recognize the requirements of those at the margins and bottom of society. Their visualization of a modern global city is not informed by the realities of India but by borrowed images from other cities around the world, irrespective of how poorly such images fit in with the local reality.
Physiological and structural traits contribute to thermotolerance in wild Australian cotton species
Authors: Dubey Garima , Phillips Aaron L , Kemp Darrell J , Atwell Brian J
Published: July 2024

Background and Aims

Five species of cotton (Gossypium) were exposed to 38 °C days during early vegetative development. Commercial cotton (Gossypium hirsutum) was contrasted with four wild cotton species (Gossypium australe, G. bickii, G. robinsonii and G. sturtianum) that are endemic to central and northern Australia.

Methods

Plants were grown at daytime maxima of 30 or 38 °C for 25 days, commencing at the four-leaf stage. Leaf areas and shoot biomass were used to calculate relative rates of growth and specific leaf areas. Leaf gas exchange measurements revealed assimilation and transpiration rates, in addition to electron transport rates and carboxylation efficiency in steady-state conditions. Finally, leaf morphological traits (mean leaf area and leaf shape) were quantified, along with leaf surface decorations, imaged using scanning electron microscopy.

Key Results

Shoot morphology was differentially affected by heat, with three of the four wild species growing faster at 38 than at 30 °C, whereas early growth in G. hirsutum was severely inhibited by heat. Areas of individual leaves and the number of leaves both contributed to these contrasting growth responses, with fewer, smaller leaves at 38 °C in G. hirsutum. CO2 assimilation and transpiration rates of G. hirsutum were also dramatically reduced by heat. Cultivated cotton failed to achieve evaporative cooling, contrasting with the transpiration-driven cooling in the wild species. Heat substantially reduced electron transport rates and carboxylation efficiency in G. hirsutum, with much smaller effects in the wild species. We speculate that leaf shape, as assessed by invaginations of leaf margins, and leaf size contributed to heat dispersal differentially among the five species. Likewise, reflectance of light radiation was also highly distinctive for each species.

Conclusions

These four wild Australian relatives of cotton have adapted to hot days that are inhibitory to commercial cotton, deploying a range of physiological and structural adaptations to achieve accelerated growth at 38 °C.