bluuebunny/crossref_metadata_2025 huggingface dataset:
‘I can’t believe you said that!’: Social media, democracy and the public good
Authors: Potter Claire Bond
Published: July 2024

Following Elon Musk's acquisition of the Twitter in 2022, the platform has been characterized by an uptick in the trolling and disinformation that are critical tools for illiberal and undemocratic political movements. In The Politics of Small Things, Jeffrey Goldfarb emphasises the importance, not simply of the public sphere, but of the potential and transformative power of the conversations that occur there. Clearly, free speech, as it occurs on social media, may or may not promote democracy. This leads us to what Goldfarb did not predict: that the same technology that helped grassroots movements overthrow authoritarianism would put the politics of small things to the purpose of undemocratic politics. Goldfarb was correct that public conversation leads to action and power. What we all missed, however, was that social media could turn a central tool of democracy, free and fair elections, to bringing about an undemocratic world.
Acting as if: The political power of mimicry
Authors: Dayan Daniel
Published: July 2024

The Politics of Small Things tells the story of a damaged public sphere and shows how expressive means may allow for repairing the damage done to the possibility of free expression. The paper first of all contrasts Goldfarb's argument with Elizabeth Noelle-Neumann's theory of ‘the spiral of silence’, which looks like its inverted image by stressing the banality of acquiescence. Secondly, it discusses the question of oppression. As one of the last resorts available to the powerless, the politics of small things responds to situations of coercion and tragedy. Yet I ask whether Goldfarb's politics of small things risks misapplication when addressing situations where oppression is uncertain.
The intimacy of enemies: Peacebuilding and The Politics of Small Things
Authors: Metz Zachary
Published: July 2024

This article examines how small groups have real power in large-scale, brutal conflicts. Working with Goldfarb’s ‘politics of small things’, I show how a unique, specific, and consequential form of political power is generated in and by local peacebuilding groups. I call this power ‘the intimacy of enemies’. By delving into and analysing a particular narrative of interactions within one such group, I demonstrate the emergence of the ‘intimacy of enemies’. I show how the micro-level efforts of these groups carry significant implications for fostering macro-level transformations. Furthermore, I provide insights into why international actors struggle to grasp, support and utilise this power. I conclude with considerations of how small, local peace efforts can prompt a reevaluation of the dynamics of political power.
Compact modeling of short-channel effects in back-gated 2D negative capacitance (NC) FETs
Authors: Jiang Chunsheng , Lu Qing , Pan Liyang , Li Quanfu , Peng Huiling , Zhang Zhigang , Song Shuxiang , Xu Jun
Published: July 2024

The negative capacitance field-effect transistor with 2D channel material (2D NC-FET) holds significant promise for low-power applications owing to its remarkable resilience against short-channel effects (SCEs) and favorable noise characteristics. In this study, we establish a compact current–voltage (I–V) model for short-channel back-gated 2D NC-FETs with metal-ferroelectric-metal–insulator–semiconductor structure by self-consistently solving the two-dimensional Poisson, drift–diffusion and Landau–Khalatnikov equations. The proposed model is valid and continuous throughout the entire operating regime, including the fully-depleted region, partly-depleted region, and accumulation region. Furthermore, we derive analytical equations for the threshold voltage (

V

TH

) and subthreshold swing (

SS

) of back-gated 2D NC-FETs based on the developed I–V model. Lastly, we elucidate the influence mechanisms of various device parameters and voltage bias on the subthreshold characteristics of short-channel back-gated 2D NC-FETs using the proposed I–V model in conjunction with analytical expressions of

V

T
H

and

SS

. Our findings reveal that back-gated 2D NC-FETs shows unconventional degradation behavior in

V

TH

and SS, resulting from the competition between traditional SCEs and novel negative capacitance effects.
Switchable optical trapping and manipulation enabled by polarization-modulated multifunctional phase-change metasurfaces
Authors: Xu Yaning , Tian Ximin , Xu Junwei , Zhang Shenglan , Huang Yafeng , Li Liang , Liu Jielong , Xu Kun , Yu Zhanjun , Li Zhi-Yuan
Published: July 2024

Optical trapping, a cutting-edge methodology, is pivotal for contactlessly controlling and exploring microscopic objects. However, it encounters formidable challenges such as multiparticle trapping, flexible control, and seamless integration. Here, we employ a polarization-modulated multi-foci technique for versatile nanoparticle trapping using multifunctional metasurfaces relying on geometric phase. Numerical simulations demonstrate the generation of two focused spots with orthogonal polarization distributions through our metasurfaces when illuminated with linearly polarized light, with their polarization distributions be interchanged by orthogonally switching the incident polarizations. We extend this design to an array of multi-foci metasurface tweezers modulated by polarization, highlighting the versatility and robustness of our approach. Furthermore, we demonstrate the simultaneous generation of two distinct focusing cylindrical vector beams using a monolayer metasurface, showcasing the two vector beams possess the interchange ability of their polarization distributions. By leveraging the Maxwell stress tensor, we assess the distinct contributions of the focused beams to longitudinal and transverse optical forces on SiO2 spheres, validating diverse trapping and manipulation behaviors for nanoparticles with the proposed metasurface designs. By manipulating the phase states of Sb2S3 nanopillars, binary-switchable optical trapping and manipulation are facilitated for all proposed metasurface tweezers. Our work underscores the efficacy of polarization-modulation multifunctional metasurface tweezers in consolidating multiple trapping tasks into a single device, paving the way for innovative lab-on-a-chip optical trapping applications in biophysics, nanotechnology, and photonics.
MosViT: towards vision transformers for moving object segmentation based on Lidar point cloud
Authors: Ma Chunyun , Shi Xiaojun , Wang Yingxin , Song Shuai , Pan Zhen , Hu Jiaxiang
Published: July 2024

Moving object segmentation is fundamental for various downstream tasks in robotics and autonomous driving, providing crucial information for them. Effectively extracting spatial-temporal information from consecutive frames and addressing the scarcity of dataset is important for learning-based 3D LiDAR moving object segmentation (LIDAR-MOS). In this work, we propose a novel deep neural network based on vision transformers (ViTs) to tackle this problem. We first validate the feasibility of transformer networks for this task, offering an alternative to CNNs. Specifically, we utilize a dual-branch structure using range (residual) image as input to extract spatial-temporal information from consecutive frames and fuse it using a motion-guided attention mechanism. Furthermore, we employ the ViT as the backbone, keeping its architecture unchanged from what is used for RGB images. This enables us to leverage pre-trained models on RGB images to improve results, addressing the issue of limited LiDAR point cloud data, which is cheaper compared to acquiring and annotating point cloud data. We validate the effectiveness of our approach on the LIDAR-MOS benchmark of SemanticKitti and achieve comparable results to methods that use CNNs on range image data. The source code and trained models will be available at https://github.com/mafangniu/MOSViT.git.
Semi-supervised adaptive anti-noise meta-learning for few-shot industrial gearbox fault diagnosis
Authors: Hu Junwei , Xie Chao
Published: July 2024

Real-time and accurate predictive maintenance of industrial equipment is fundamental for ensuring the safety and stability of advanced manufacturing processes. Current fault diagnosis methods based on data mining rely on a large number of labeled samples, and obtaining sufficient labeled data for diagnosing industrial equipment faults is challenging. Meta-learning can achieve the diagnosis of few-shot samples to a certain extent, but the effect is not ideal. Semi-supervision can effectively leverage a large number of unlabeled samples, which is of great practical significance for handling scenarios involving limited labeled samples. However, noise interference can occur when unlabeled samples appear that do not belong to known categories. Therefore, this study proposes adaptive semi-supervised meta-learning networks (ASMNs) for noisy few-shot gearbox fault diagnosis. Firstly, a residual network with a Morlet Wavelet layer is used to extract signal features. Next, sample-level attention is defined to select unlabeled samples that are more similar to labeled sample prototypes, thereby reducing the influence of noisy samples. The adaptive metric is used to obtain the relational distance functions of labeled samples and unlabeled samples. Adaptive semi-supervised ASMNs uses unlabeled data to refine prototypes for better fault diagnosis. The effectiveness and anti-noise performance of the proposed method are verified by using two gearbox datasets with various few-shot noise scenarios.
An adaptive feature mode decomposition-guided phase space feature extraction method for rolling bearing fault diagnosis
Authors: Xin Jiayi , Jiang Hongkai , Jiang Wenxin , Li Lintao
Published: July 2024

The extraction of fault features from rolling bearings is a challenging and highly important task. Since they have complex operating conditions and are usually under a strong noise background. In this study, a novel approach termed phase space feature extraction guided by an adaptive feature mode decomposition (AFMDPSFE) is proposed to detect subtle faults in rolling bearings. Initially, a new method using Kullback–Leiber divergence is introduced to automatically select the optimal mode number and filter length for the decomposition of vibration signals, facilitating the automatic extraction of optimal components and ensuring efficient screening. This eliminates the need for manual configuration of feature mode decomposition parameters. Furthermore, a criterion that could determine two crucial parameters to capture system dynamics characteristics in phase space reconstruction is embedded into AFMDPSFE algorithm. Subsequently, a series of high-dimensional independent components is derived. The envelope spectrum of the principal component exhibiting the highest kurtosis value is computed to achieve fault identification, consequently enhancing the separation of signal from noise. Both simulations and experimental results confirm the effectiveness of AFMDPSFE approach. A comparison analysis shows the excellent performance of AFMDPSFE in extracting fault features from significant noise interference.
Research on remote reference denoising method based on non-coaxial and non-coplanar tunnel NMR detection
Authors: Sun Yong , Yi Xiaofeng , Li Cong , Yang Zhiqin , Lin Jun
Published: July 2024

The limited space within the tunnel constrains the size of the antenna for NMR detection, thereby significantly impacting the signal-to-noise ratio (SNR) of NMR signals. Insufficient SNR data poses substantial challenges to obtaining reliable NMR signals. The paper presents a novel approach to address the challenge of strong background noise in tunnel environments and low SNR data by incorporating the ground multi-channel remote reference denoising method into tunnel NMR advance detection. Specifically designed for narrow tunnels, a multi-channel non-coaxial and non-coplanar remote reference denoising method is proposed. Firstly, the effectiveness of the non-coaxial, non-coplanar remote reference denoising method is verified in the laboratory environment. Secondly, the correlation between the detector antenna and the reference antenna is calculated theoretically to ensure the significant correlation between the detector antenna and the reference antenna. Finally, two processing methods of reference denoising and non-reference denoising are carried out respectively by combining the tunnel detection data. By comparing the inversion results and the engineering construction results, the effectiveness of non-coaxial and non-coplanar remote reference denoising methods in tunnel NMR detection is proved, which provides relevant research support for expanding the application of tunnel NMR detection technology.
Accelerated relaxation enhancing flows cause total dissipation
Authors: Rowan Keefer
Published: July 2024

We show that by ‘accelerating’ relaxation enhancing flows, one can construct a flow that is smooth on

[
0
,
1
)
×

T

d

but highly singular at t = 1 so that for any positive diffusivity, the advection–diffusion equation associated to the accelerated flow totally dissipates solutions, taking arbitrary initial data to the constant function at t = 1.
Quantifying the effect of pulse-like ground motions on the seismic design of SMA restrained isolation bridges using probabilistic repair cost method
Authors: Zhong Jian , Shu Yiwei , Wang Hao , Xing Chenxi
Published: July 2024

The shape memory alloy (SMA) restrainer serves as an effective but expensive bridge restraining device. However, the impact of pulse effect on SMA design approach under pulse-like ground motions (PLGM) has not been fully quantified in previous studies, which hinders its application in near-fault regions. Therefore, based on the risk probability assessment method throughout the entire life cycle, by accounting for the comprehensive repair cost of each component damage, this paper introduces a parameter design method for SMA restrainer of near-fault bridges that considers structural parameters, pulse parameters, and economic indicators. Firstly, the repair cost ratio (RCR) of bridge system, which means the expenses for repairs expressed as a proportion of bridge replacement costs, was regarded as the life-time optimization goal and overall performance indicator. Secondly, by accounting for near-fault effects, the relationship between RCR and SMA design parameters was established by convolution algorithm of probabilistic seismic hazard analysis, demand analysis and capacity analysis. A novel probabilistic seismic demand model was utilized to quickly determine the RCR of the bridge system under PLGM. Finally, the influence of pulse period on the rational design parameter of SMA restrainer was comprehensively investigated by RCR-based method. A seismic isolation arch bridge was selected as the illustrated case in this article. The results indicate that the rational design parameters of SMA exhibit a pattern of initially rising, then falling as the pulse period increases, reaching the peak value when the pulse period approaches bridge fundamental period. Moreover, the price parameter of SMA significantly affect the optimal design parameters, and the effective range is also recommended.
Energy stabilization of high-charge bunches from laser plasma accelerators
Authors: Shi Xueyan , Xu Haisheng , Li Dazhang , Wang Jia , Zeng Ming
Published: July 2024

Laser plasma accelerators (LPAs) have become one of the frontiers of the accelerator community, mainly because they promise orders of magnitude improvement in the accelerating gradient. However, the energy stability and spread of the high-charge bunched beams (e.g. several hundred pC per bunch) from LPAs still strongly limit their application. In this work, we propose a novel method utilizing magnetic chicanes combined with both active and passive plasma dechirpers to simultaneously reduce the central energy deviation and the energy spread of high-charge bunched beams from LPAs. Start-to-end simulations demonstrate that the central energy deviation and the energy spread of approximately 500 pC bunches can be simultaneously reduced from approximately 2% and 1.2% to 0.1% and 0.5%, respectively, while maintaining almost perfect transmission efficiency (above 97%).
A theoretical perspective on the almost dark galaxy Nube: exploring the fuzzy dark matter model
Authors: Yang Yu-Ming , Bi Xiao-Jun , Yin Peng-Fei
Published: July 2024

In recent astronomical observations, an almost dark galaxy, designated as Nube, has unveiled an intriguing anomaly in its stellar distribution. Specifically, Nube exhibits an exceptionally low central brightness, with the 2D half-light radius of its stars far exceeding the typical values found in dwarf galaxies, and even surpassing those observed in ultra-diffuse galaxies (UDGs). This phenomenon is difficult to explain within the framework of cold dark matter (CDM). Meanwhile, due to its ultralight particle mass, fuzzy dark matter (FDM) exhibits a de Broglie wavelength on the order of kiloparsecs under the typical velocities of galaxies. The interference between different modes of the FDM wave gives rise to fluctuations in the gravitational field, which can lead to the dynamical heating of stars within galaxies, resulting in an expansion of their spatial distribution. In this paper, we aim to interpret the anomalous stellar distribution observed in Nube as a consequence of the dynamical heating effect induced by FDM. Our findings suggest that a FDM particle mass
around 1-2 × 10-23 eV can effectively account for this anomaly. And we propose that the FDM dynamical heating effect provides a new insight into understanding the formation of field UDGs.
Application of AI Models for Determination of Beam Parameters with an Array of Timepix3 Pixel Detectors
Authors: Ivanov Svetoslav ,   PADME Collaboration
Published: July 2024

PADME Run III searched for a resonant production of the X17 particle. The precise knowledge of the beam position is critical for the measurements of X17 and an array of 2 × 6 Timepix3 hybrid pixel detectors were used to measure the parameters of the incident positron beam. During the operation of the Timepix detector, some of the pixels reported missing data which introduced a challenge for the accurate estimation of the center position. A Neural Network Regression algorithm was developed and compared with the conventional Gaussian fitting technique over a simulated data with masked pixels.
Multichannel SiPM test readout system for gamma ray measurements with monolithic inorganic CeBr3
Authors: Asova Veronika , Bistrev Galin , Buchakchiev Valentin , Kozhuharov Venelin
Published: July 2024

Energy resolution and the detection eﬃciency for gamma quanta are fundamental properties in the construction of detectors for ionizing radiation. In this study, a SiPM-based photodetector coupled to a monolithic inorganic CeBr3 crystal is exposed to gamma rays in order to study the performance of the CeBr3 crystal. Measurements are made using three different radioactive sources - 137Cs, 22Na and 60Co. For each source, the measurements are made using a few different values for the Bias voltage of the SiPM. Furthermore, two CeBr3 crystals with different thicknesses are used in order to study how detector eﬃciency is affected by crystal dimensions. A preliminary analysis of the data is presented.
Analysis of the S1 triplet component in the DarkSide-50 experiment
Authors: Sunny Clea ,   the DarkSide-50 collaboration
Published: July 2024

The DarkSide-50 (DS-50) experiment aims at the direct detection of weakly interacting massive particles. It is a dual-phase liquid argon time projection chamber (LAr TPC) where Dark Matter (DM), which constitutes five sixths of all matter in the universe, is expected to interact with an argon nucleus resulting in a nuclear recoil. A scintillation signal (S1) is produced as a result of the ionising events from the DM-Ar interaction. The impurities in LAr, such as O,2, N2, H2O, etc., at the ppm level, quench the scintillation photons, leading to a reduction in the observed lifetime of the triplet state. In this contribution, the effect of impurities on the triplet lifetime is analyzed for individual events using DS-50 data, with a primary focus on nitrogen, one of the candidates for the impurities in LAr hypothesized to cause a suppression of triplet lifetime. This is done by determining the lifetime of the triplet component with a known purity, which can be used as a reference for the purity level of argon used in current and future dark matter searches.
Potential for improving nutrient use efficiencies of human food systems with a circular economy of organic wastes and fertilizer
Authors: Davis Sarah C , Maynard Finn G , Jenkins David , Herman Tess , Reza M Toufiq
Published: July 2024

Waste from the human food system includes a large quantity of nutrients that pose environmental and human health risks. If these nutrients can be captured and repurposed, they could potentially offset synthetic fertilizer demands. This study reviews several technologies—including anaerobic digestion, hydrothermal carbonization (HTC), and composting—that can be used to process wastes from the human food system. This study also assesses the quantity of nutrient resources that are available from wastes, including food waste, biosolids, manure, and yard waste. Three geographic scales were analyzed. At a national level in the United States, up to 27% of nitrogen and 33% of phosphorus demands for agriculture could be met with wastes from the human food system, primarily from food waste and biosolids. Some rural localities have a greater potential for circular economies of nutrients in the food system, with the potential to meet 100% of nitrogen and phosphorus fertilizer demands using waste nutrients, as in the case of Athens County, Ohio. Benefits of offsetting synthetic fertilizer use with waste nutrients include reduced greenhouse gas (GHG) emissions, with up to 64% reduction in GHG emissions per unit of nitrogen fertilizer produced with HTC.
Diverse impacts of the Indian summer monsoon on ENSO among CMIP6 models and its possible causes
Authors: Lin Shuheng , Dong Buwen , Yang Song , Zhang Tuantuan
Published: July 2024

This study examines the performance of 52 models from phase 6 of the Coupled Model Intercomparison Project (CMIP6) in capturing the effects of the Indian summer monsoon on the evolution of El Niño–Southern Oscillation (ENSO). The ISM’s impacts on ENSO show a substantial diversity among the models. While some models simulate the strength of the impacts comparable to observations, others represent much weaker influences. Results indicate that the diversity is highly related to inter-model spread in interannual variability of ISM rainfall (ISMR) among the models. Models with a larger ISMR variability simulate stronger ISM-induced anomalies in precipitation and atmospheric circulation over the western North Pacific during the monsoon season. As a result, these models exhibit larger wind anomalies induced by monsoon on the south flank of the anomalous circulation in the western Pacific, thereby influencing subsequent ENSO evolution more significantly by causing stronger air-sea coupling processes over the tropical Pacific.
The unintended consequences of production bans: the case of the 2018 Kenya logging moratorium
Authors: Bartlett Anne , Alix-García Jennifer , Abarca Alejandro , Walker Sarah , Van Den Hoek Jamon , Murillo-Sandoval Paulo , Friedrich Hannah K
Published: July 2024

Production bans are a common way for governments to address issues of social concern. However, when consumer demand for banned items is insensitive to price changes, cross-border trade may undermine these efforts. We examine the effects of Kenya’s 2018 moratorium on the extraction of wood products, including logs and charcoal, from public and community forests. The data show an immediate 36% increase in the domestic charcoal price in Kenya, where over 80% of consumers use it as their primary energy source. Subsequently, we document an increase of 133% percent in charcoal imports from Uganda to Kenya during the first 6 months of the ban. Further, we estimate that avoided deforestation in Kenya was likely displaced to Uganda such that net carbon emissions increased. These findings demonstrate the ineffectiveness of the ban as a mechanism to decrease greenhouse gas emissions and biodiversity loss from deforestation.
Enhanced lake elevation mapping using a zone-based method
Authors: Fan Meiyi , Wang Yong , She Xiaojun , Liu Xin , Chen Ran , Gong Yulin , Xue Kun , Sun Fangdi , Li Yao
Published: July 2024

Inland lakes play a crucial role in monitoring global climate change and managing responses to extreme weather events, with lake elevation being critical for assessing their regulatory capacities. However, due to the limited temporal resolution of current altimetry satellites, obtaining high-frequency, high-precision elevation data for water bodies remains challenging. Consequently, most studies utilize elevation-area (E-A) models constructed from historical elevation and area records, integrated with area observations from high-temporal resolution optical satellites to infer precise water levels. Yet, the construction of the E-A model often assumes a uniform water level across the lake, thus overlooking potential segmentation during dry periods. To address this, our study implemented a zone-based approach, utilizing hydrological connectivity principles to ensure that elevation data within E-A models are confined to appropriate zonal regions. This method effectively minimized uncertainties by preventing errors from zonal discrepancies, significantly improving accuracy compared to traditional methods. It reduced root mean square errors (RMSE) by 0.71–1.73 m during the dry season, achieving RMSEs of 0.35, 0.64, and 0.37 m across three segments. Furthermore, this method ensures water level data are confined to specific zones, preventing the inconsistencies typically caused by averaging data across multiple stations or selecting data from varying elevations. This consistent domain definition reduces extrapolation errors during the model prediction and inversion. Moreover, the method compensates for time information losses often incurred by relying on multi-year percentile charts, thereby enabling more precise aquatic boundary delineation than traditional regional boundaries.
Influence of topography on nano-mechanical properties of cylindrical magnetron sputtered TiN films
Authors: Atta Sayan , Mathew Arun Tom , Dash Sitaram , Narendra Kumar U
Published: July 2024

Numerous studies on Nano-mechanical behavior of the thin films explained primarily in terms of their film morphology and particle size rather than film topography. Therefore, the current study investigates the effect of film topography on the nano-mechanical characteristics of the film. Ti/TiN multilayer thin films were deposited at varying deposition pressures by using an indigenously developed Cylindrical Magnetron Sputtering (CMS) unit. Surface crystallographic information is characterized by synchrotron-based Grazing Incidence XRD analysis. Film growth follows self-assembled nano hill architecture as revealed by AFM and in situ Scanning Probe Microscopy images. The tribo-mechanical properties of the film is dependent on the height and spacing of its self-assembled structure, which experiences either crushing or buckling under the indenter load, thereby affecting film characteristics. Film deposited at moderate pressure exhibits superior wear behavior, attributed to the interplay between Plasticity Index (PI) and Depth Recovery Ratio (DRR). The study primarily focused on film growth phenomena by using cylindrical targets and their influence on nanomechanical properties of the film.
A statistic of the subseasonal forecast skill windows of 2-meter air temperature
Authors: Liu Xiaolei , Su Jingzhi , Peng Yihao , Liu Xinli
Published: July 2024

The forecast skill on subseasonal time scale is currently limited, inhibiting its effective application broadly. Under some special conditions, the subseasonal-seasonal (S2S) forecast skill would be increased intermittently, namely, the forecast opportunity window. The identification of such forecast windows can increase the credibility of subseasonal prediction results, providing final users the opportunity to make the appropriate decision. To identify the subseasonal forecast window of 2-m air temperature (T2m), based on the S2S multi-model prediction results, this study evaluated the pattern correlation coefficient between the third-week T2m forecasted by S2S models and the observation. When the forecast skills of the majority of models reach the prescribed threshold, this period is defined as a forecast skill window. In this way, the subseasonal forecast skill windows of T2m over different regions of the global lands are identified. From the perspective of seasonal distribution, the forecast skill windows over almost all the continents appear more in boreal winter, while the forecast skill windows of the Australian continent mainly appear in boreal summer. Significant differences can be found in the occurrence frequency of forecast windows during different phases of ENSO. During El Niño events, forecast windows appear more frequently over North America, Asia, and South America, especially during winter-spring from January to April. From the T2m spatial pattern during the window periods, the forecast skill windows have some relevance among several continents, and the windows over the whole global land mainly correspond to those over Asia, Europe, and North America. Deep investigation of the physical mechanism behind the forecast skill windows helps understand the sources of predictability and improves the skill of subseasonal prediction.
Impacts of ash tree removals on summer daytime temperatures in Madison, Wisconsin
Authors: Berg Elizabeth , Kucharik Christopher
Published: July 2024

Maintaining and increasing canopy cover is frequently promoted as a strategy for mitigating excess heat in cities. However, the impact of changing tree cover on surrounding air temperatures is often unpredictable and can depend on tree species, size, shape, and location. In this study, we explore whether the removal of ash trees in one downtown neighborhood in Madison, Wisconsin affected surrounding air temperatures at small spatial scales (15 to 35 m). We used a bicycle-mounted temperature and radiation sensor to repeatedly record high-frequency observations along four transects. We observed no discernible difference between daytime air temperatures near locations surrounded by tree removals and temperatures at locations without any nearby tree removals. Overall, across the four clusters of streets that were monitored, proximity to mature ash trees did not correlate to reduced air temperatures. Attempts to model temperature as a function of surrounding land cover and street tree characteristics all had poor predictive power (R2 ranged from 0.01 to 0.54), and explanatory variables related to tree cover were never statistically significant. The finding that the removal of ash trees did not impact daytime air temperatures patterns at the neighborhood scale suggests that the most densely developed streets in Madison may not easily support sufficient canopy cover to experience tree-induced cooling, underscoring the importance of pursuing a variety of strategies to mitigate urban warming.
Review of memristor based neuromorphic computation: opportunities, challenges and applications
Authors: S Shekinah Archita , V Ravi
Published: July 2024

The memristor is regarded as one of the promising possibilities for next-generation computing systems due to its small size, easy construction, and low power consumption. Memristor-based novel computing architectures have demonstrated considerable promise for replacing or enhancing traditional computing platforms that encounter difficulties in the big-data era. Additionally, the striking resemblance between the mechanisms governing the programming of memristance and the manipulation of synaptic weight at biological synapses may be used to create unique neuromorphic circuits that function according to biological principles. Nevertheless, getting memristor-based computing into practice presents many technological challenges. This paper reviews the potential for memristor research at the device, circuit, and system levels, mainly using memristors to demonstrate neuromorphic computation. Here, the common issues obstructing the development and widespread use of memristor-based computing systems are also carefully investigated. This study speculates on the prospective applications of memristors, which can potentially transform the field of electronics altogether.
Multi-attribute optimization of eco-manufacturing based criteria in CNC manufacturing systems using an evolutionary algorithm
Authors: Ramena Durga Venkata Prasad , Kothapalli Arun Vikram , Rao Maruvada Satya Sankara Srinivas , Lakshmi Vennela Venkata Kanaka , Kanth Tammi Vijay Krishna
Published: July 2024

Manufacturing technology has evolved over the years with the development of CNC manufacturing systems, flexible manufacturing, rapid prototyping, smart manufacturing etc Simultaneously, the development of new and exotic materials to match specific requirements has shaped new problems in manufacturing. The materials developed thus far require special tools, lubricating agents, and extra-care in machining without compromising the quality. Further the study of carbon emissions in manufacturing sector has also gained unusual spotlight in view of their deleterious effect on the ecological balance. The manufacturing systems have to be consequently designed and developed, such that they generate minimal quantity of emissions without forfeiting the prime objectives of quality and tool morphology. The present work is principally intended to analyse the effect of cutting parameters on the emission rate of greenhouse gases, tool wear and work-piece temperature concurrently. These studies are accomplished in both dry and wet conditions on computer numerical control machining system. The machining process involved plain facing of a Ti-6Al-4V hardened material. The experimental studies are realized using both single point and multi-point cutting tools and are supplemented with the application of Multi-Objective Genetic Algorithm (MOGA). The MOGA generated set of pareto-fronts for the four machining conditions were subjected to VIKOR, TOPSIS and LINMAP decision making approaches to arrive at the optimum values of decision variables. The optimum cutting parameters obtained in single point cutting tool machining in dry conditions are speed (873.2 rpm), feed (0.199 mm rev−1) and depth of cut (0.25 mm), while the corresponding values of responses are tool wear (67.19 μm), work-piece temperature (39.36 °C) and carbon emission (0.138 Kg-CO2). The equivalent values for multi-point cutting were determined as 899.8 rpm, 0.195 mm rev−1 and 0.25 mm, while the responses for these optimal conditions are 69.92 μm, 39.48 °C and 0.137 Kg-CO2 in that order.
Complex-valued multi-frequency electrical impedance tomography based on deep neural networks
Authors: Wang Nan , Liu Jinhang , Li Yang , Huang Lan , Wang Zhongyi
Published: July 2024

The utilization of multi-frequency electrical impedance tomography (mfEIT), a non-invasive imaging technique, allows for the visualization of the conductivity distribution in biological tissues across different frequencies. However, the analysis of phase angle information within complex impedance remains a challenge, as most existing deep learning-based mfEIT algorithms are limited to real number processing. To mitigate this limitation, this study proposes a comlex reconstruction method which is inspired by the idea of combining deep learning with traditional reconstruction algorithm. It uses a spare Bayesian learning algorithm in the preprocessing stage that can perform complex arithmetic operations, and fully learns and makes use of the correlation between the real and imaginary parts to reconstruc the distribution of complex-valued conductivity in the measurement area. After that, an altered UNet network is used to further optimize the pre-reconstruction outcomes. The experimental outcomes validate the efficacy of the proposed algorithm in accurately reconstructing the complex-valued conductivity distributions of diverse biological tissues, such as potato and pig kidney, across different frequencies. Furthermore, the algorithm exhibits exceptional performance in mitigating the presence of image artifacts during the reconstruction process.
Climate classification systems for validating Earth System Models
Authors: Navarro Andrés , Tapiador Francisco J
Published: July 2024

Climate classification systems (CCSs) were developed in the 19th century to explain the global distribution of plants and animals, but were given a new life in the Earth physics community in the 21st century as a means to validate Earth System Models (ESMs). The purpose of this paper is to critically review the evolution of this approach to validation and to discuss the current status. It is shown that CCSs can not only measure model performance, but also help identify and deconstruct systematic model biases. CCSs provide a rational and comprehensive zonation of the global environment using quantitative estimates of physical variables such as precipitation, temperature, and humidity. They offer several advantages over single variables due to the high sensitivity of the resulting classes to small changes in input variables and dimensionality reduction. CCSs encompass model behavior on both energy and water balances, allowing for a more comprehensive assessment of ESM performance.
Legal Personhood and Disability
Authors: Arstein-Kerslake Anna
Published: July 2024

This chapter discusses the right to legal personhood in the context of disability. It explores some of the key ways in which legal personhood is denied to disabled people, as well as unique barriers to legal personhood that are being experienced due to intersecting forms of marginalisation for some individuals and groups; for example, guardianship laws that deny legal personhood and their application based on gender and disability. In addition, the denial of legal agency (an element of legal personhood) via mental health law that removes the ability of an individual to choose their own medical treatment and the unique application of these laws in the context of gender, disability, and indigeneity. Similarly, the lasting effects of eugenics resulting in the denial of legal agency, especially for reproductive choices, on the basis of gender and disability. The chapter discusses the state’s explicit resistance to enforcing the right to legal personhood via their reservations, understandings, and declarations (RUDs) on the right in the Convention on the Elimination of Discrimination Against Women (CEDAW) and the Convention on the Rights of Persons with Disabilities (CRPD). It concludes with an argument for how the application of the right to legal personhood in the context of disability can be used as a model for how to apply it to other marginalised groups—as is done throughout the chapters of this book.
Ethics and Religion
Authors: Birch Jonathan
Published: July 2024

‘Sentientist’ ethical outlooks regard sentience as necessary and sufficient for having interests that matter morally in their own right. Sentientism finds expression in at least three major secular ethical theories (classical utilitarianism and the theories of Korsgaard and Nussbaum), as well as in the idea of ahimsa in Indian thought. Sentientism can be contrasted with various ways of denying the necessity and/or sufficiency of sentience for moral status. The possibility of Vulcan-like beings who have the consciousness aspect of sentience without the valence aspect suggests a qualification to pure sentientism may be needed. A more serious challenge comes from agency-centric and rationality-centric positions. One example is orthodox Kantianism, which allows only indirect duties (formally owed to ourselves) concerning non-rational beings. Another challenge comes from the Abrahamic religions, which give only very limited moral standing to non-human sentient beings. We can, however, find in all of them support for duties of stewardship, including the duty to avoid causing gratuitous suffering.
Frontiers of Proportionality
Authors: Birch Jonathan
Published: July 2024

Taking invertebrate welfare seriously involves proposing and debating steps that may be proportionate (permissible-in-principle, adequate, non-excessive, consistent) in relation to specific welfare risks. The growing interest in invertebrates as potentially sustainable protein sources underlines the need for these debates. It would be plausibly proportionate to set up a licensing scheme that requires companies farming sentience candidates and investigation priorities to fund the creation (by independent experts) of codes of good practice, where none yet exists. There is one important exception, namely octopus farming. It is very unlikely that octopus farming could ever meet reasonable expectations regarding animal welfare, and so it would be proportionate to ban it outright. Our current state of knowledge makes it difficult to be confident that slaughter is humane or that stunning is effective. It is easier to be confident about what is inhumane. We should not use live boiling without prior stunning in decapods or insects, since this method needlessly risks extending and intensifying the suffering associated with dying.
The Run-Ahead Principle
Authors: Birch Jonathan
Published: July 2024

Given the rate at which AI is developing, and the risks associated with artificial sentience taking us by surprise, we should apply the run-ahead principle: at any given time, measures to regulate the development of sentient AI should run ahead of what would be proportionate to the risks posed by current technology, considering also the risks posed by credible future trajectories. The run-ahead principle may potentially justify strong regulatory action, but a moratorium may go beyond what is reasonably necessary to manage risk. An alternative proposal, involving regular testing to monitor the sentience of our AI creations, is currently unfeasible, due to the absence of tests that can be applied to large language models and other systems with high potential for gaming our criteria. A third approach involves oversight by means of sector-wide codes of good practice and licensing schemes. This path would require a greater level of transparency than we have seen from the AI industry to date. The overarching imperative is to have democratic debate about these questions now.
Stepping Back
Authors: Birch Jonathan
Published: July 2024

This chapter offers brief concluding remarks, calling on society to prepare for the (perhaps imminent) arrival of artificial sentience candidates by engaging more closely with the sentience candidates that already surround us in the animal kingdom.
‘Contextual Bible Study’ as a Form of Liberation Biblical Interpretation
Authors: West Gerald O
Published: July 2024

The political context of South Africa in the 1980s generated distinct forms of liberation theology, including Black Theology and Contextual Theology. These two South African liberation theologies, in conversation with other liberation theologies, gave birth in the post-State of Emergency (1985) period to a particular form of liberation praxis, what has come to be called ‘Contextual Bible Study’. Forged in South Africa by the conceptual contours of both South African Black Theology and South African Contextual Theology, this approach took its initial conceptual shape from the community-based work of the Centro de Estudos Bíblicos in Brazil, but was regularly reconstituted by actual anti-apartheid collaborative praxis, which provided particular sites in which these different liberation ideo-theological trajectories intersected. This chapter traces the early conceptual contours of Contextual Bible Study as liberation biblical interpretation praxis, with a particular focus on method, tracking the regular rhythmical cycle of action-reflection and its conceptual contributions.
Reclaiming the Stolen Bible One Contextual Bible Study at a Time
Authors: van der Walt Charlene
Published: July 2024

Central to this chapter is the issue of power. Who determines the contours and outcome of a valid and authoritative interpretation of the biblical text? Who has the right to read the text and how is the text used to engage contemporary embodied lived realities when it comes to sexual diversity and gender expression in the African context? The chapter starts by drawing on the Contextual Bible Study work developed by the Ujamaa Centre for Community Development and Research in relation to issues of sexuality and gender. It then offers two examples that illustrate how different interpretive resources can work as entry points to engage reading communities. The chapter argues that beyond the commitment to develop resources for faith communities to engage in issues of gender and sexuality, an important imperative is to allow those who embody sexuality and gender in a counter-normative way to read the text for themselves.
Theological Action Research in Conversation with Contextual Biblical Interpretation
Authors: Cameron Helen , Rogers Andrew P
Published: July 2024

Theological Action Research and contextual biblical interpretation have a shared interest in the use of the Bible. This chapter opens up a dialogue between them by questioning who in any context the readers are, and in what ways they use the Bible as scripture. Theological Action Research as a methodology in practical theology is described and a case study of Theological Action Research in which the Bible features is offered. Gerald West’s characterization of Contextual Bible Study is used to start the conversation. The chapter concludes with questions that Theological Action Research poses to Contextual Bible Study and in return questions that Contextual Bible Study might ask Theological Action Research to consider.
Privilege, Marginality, Voice, and Representation in Contextual Bible Studies and Contextual Biblical Interpretation
Authors: Lawrence Louise J
Published: July 2024

In this chapter, discussions about Contextual Bible Study and contextual biblical interpretation as ‘marginal’ to the assumed more ‘central’ methods and pursuits of biblical studies are critically explored, both in relation to the methods, media, and representations used within the discipline, and the ways in which certain epistemologies are privileged over others. The chapter argues that Southern Theory—which has close connections to feminist and postcolonial theory—is instructive in challenging the hegemony of Global North epistemologies and their links to histories of colonialism. Divisions between so-called marginal and central methods and pursuits in Biblical studies need to be overcome if a more equitable and inclusive vision of the discipline is ever to be achieved.
Is God Revengeful?
Authors: Spronk Klaas
Published: July 2024

The image of the god of the Hebrew Bible as revengeful and violent has puzzled both ancient and modern readers, especially in relation to the more popular image of God as good and loving. In the hymn of Nah. 1 both aspects are closely related, both literary and theological. The history of interpretation of this text shows how much the social and historical context of the reader influences the interpretation. This overview presents and evaluates examples from early Jewish commentaries, ancient Christian interpretation, including the discussion with Marcion, and modern exegesis. It will be demonstrated that next to the progress made in interpreting the text in its historical context, every new interpretation should be read and put into perspective against the background of the interpreter.