Local Modification Research Articles

A modified vision transformer architecture with scratch learning capabilities for effective fire detection

Fire is considered to be one of the major influencing factors that cause fatalities, property damage, and economic, and ecological disruption. To perform the early detection of fire using data from vision sensors and prevent or reduce the damage that fires cause, deep learning models have been widely adopted to overcome the limitations of conventional methods. However, mainstream convolutional neural network (CNN) models have limited generalisation abilities in unseen scenarios and struggle to obtain a good trade-off among the accuracy, inference speed, and model size. Currently, vision transformers (ViT) outperform conventional CNN models; however, they are computationally expensive and required more data for training. They provide a limited performance for small and medium-sized datasets, which are very common in the fire scene classification domain. In this work, we employ a novel ViT architecture by combining shifted patch tokenisation and local self-attention modules for efficient fire scene classification and enable the model to learn from scratch even on small and medium-sized datasets. Furthermore, to make the model suitable for real-time inferencing, we modify the transformer encoder and eventually achieve a reduced number of floating-point operations and a reduced model size. Additionally, in this work, a medium-scale fire dataset is developed that contains complex real-world scenarios. Our model is assessed on three benchmark and a self-created datasets using several evaluation metrics, including a novel cross-corpse evaluation metric, as well as a robustness evaluation metric. The experimental results indicate that our model achieved an overwhelmingly better performance compared to existing methods in terms of the accuracy and model complexity.

Attention-based convolution neural network for magnetic tile surface defect classification and detection

Effectively identifying surface defects in magnetic tiles has proven to be highly challenging due to limited sample availability and irrelevant background interference, which also plays a crucial role in significantly influencing the lifespan and reliability of permanent magnet motors. To address these challenges, our study draws inspiration from a comprehensive analysis of the retinal attention mechanism and proposes three guiding criteria: multi-level resolution, what to look for, and where to look at. These criteria are utilized as foundational principles to enhance the representation learning capability of designed neural network structures through the incorporation of the retinal attention mechanism. Subsequently, based on these guiding criteria, we introduce a novel convolutional retinal attention block (CRAB) to learn discriminative and robust feature representations for magnetic tile surface defect classification and detection. The proposed CRAB comprises three modules: multi-resolution module (MRM), global attention aggregation module (GAAM), and local attention aggregation module (LAAM), designed to extract discriminative and robust features by refining meaningful information and suppressing redundant ones. Comprehensive experimental results across image classification and object detection tasks demonstrate that the proposed CRAB outperforms existing methods such as SE, ECA, and CBAM, and can effectively amplify the representation power across various backbone networks, including VGG-16, GoogLeNet, ResNet-18, and ResNet-50. An evaluation on surface defect classification and detection tasks for industrial magnetic tiles further shows that CRAB achieves accuracies of 99.50% and 96.98%, respectively. These results emphasize the promising application prospects of the proposed method in detecting industrial surface defects amid expansive and inconsequential backgrounds. The code of the proposed method is available at: https://github.com/KWflyer/CRAB.

Anomalously low vacancy formation energies and migration barriers at Cu/AlN interfaces from ab initio calculations

It is well known that interfaces in nanomaterials can act as ultra-fast short-circuit diffusion paths, as originating from local structural, chemical and/or electronic modifications at the interface. For example, the interface diffusivity of Cu in Cu/AlN nanomultilayers can be up to two orders of magnitude higher as compared to the bulk, which may promote interfacial premelting of Cu. Extensive ab initio calculations of vacancy formation and migration energies in Cu/AlN nanomultilayers were performed to arrive at the fundamental understanding of such anomalously fast interface diffusion phenomena. It was found that both the metallic Al-terminated interface and the mixed-bonded N-terminated interface promote high atomic interface mobilities by lowering the vacancy formation and vacancy migration energies in the interfacial Cu planes. Moreover, the out-of-plane vacancy migration energies highlight a strong tendency of vacancy segregation toward both interfaces.

Suspended particulate matter influence on dissolved Nd concentration and isotopic composition along GEOTRACES section GP16

The role of suspended particulate matter in the biogeochemical cycling of neodymium (Nd) in the ocean is not well understood. This study reports the measurement of dissolved Nd concentrations and isotopes (<0.2 um), and particulate Nd concentrations along the Eastern Pacific Zonal Transect (EPZT, GP16) as part of the GEOTRACES program. The western part of the EPZT cruise track is influenced by a hydrothermal plume, observed between 2200 and 2800 m, originating at the southern East Pacific Rise. This setting allows for the investigation of the role of particulate matter in Nd biogeochemical cycling and its contribution in modifying the distribution of dissolved Nd. Results show that the highest removal of dissolved Nd (∼ 21 %) was observed near the hydrothermal ridge crest, decreasing to ∼ 8 % at the westernmost station. Here, we report the partition coefficient (Kd) of each particle constituent (e.g., lithics, CaCO3, POM, Opal, Fe-phase, Mn-phase) to show that particle composition plays an important role in Nd removal alongside particle mass. Along the plume, both particulate Mn and Fe contributed to the removal of Nd, with Mn playing the dominant role in sites closest to the vent. At the western stations, below the plume, the concentration of both dissolved and particulate Nd increased with depth, with particulate Nd one to two orders of magnitude lower than measured in the dissolved phase. The increase in dissolved Nd with depth in the interval below the plume could result either from the continuing remineralization of raining particles or the influx of dissolved Nd from bottom sediments. Close to the ridge crest, where the hydrothermal Nd input is at its highest, there is a hint of local modification of dissolved εNd signature, however not large enough to affect the use of εNd as a water mass tracer.

Remote Sensing Image Dehazing via a Local Context-Enriched Transformer

Remote sensing image dehazing is a well-known remote sensing image processing task focused on restoring clean images from hazy images. The Transformer network, based on the self-attention mechanism, has demonstrated remarkable advantages in various image restoration tasks, due to its capacity to capture long-range dependencies within images. However, it is weak at modeling local context. Conversely, convolutional neural networks (CNNs) are adept at capturing local contextual information. Local contextual information could provide more details, while long-range dependencies capture global structure information. The combination of long-range dependencies and local context modeling is beneficial for remote sensing image dehazing. Therefore, in this paper, we propose a CNN-based adaptive local context enrichment module (ALCEM) to extract contextual information within local regions. Subsequently, we integrate our proposed ALCEM into the multi-head self-attention and feed-forward network of the Transformer, constructing a novel locally enhanced attention (LEA) and a local continuous-enhancement feed-forward network (LCFN). The LEA utilizes the ALCEM to inject local context information that is complementary to the long-range relationship modeled by multi-head self-attention, which is beneficial to removing haze and restoring details. The LCFN extracts multi-scale spatial information and selectively fuses them by the the ALCEM, which supplements more informative information compared with existing regular feed-forward networks with only position-specific information flow. Powered by the LEA and LCFN, a novel Transformer-based dehazing network termed LCEFormer is proposed to restore clear images from hazy remote sensing images, which combines the advantages of CNN and Transformer. Experiments conducted on three distinct datasets, namely DHID, ERICE, and RSID, demonstrate that our proposed LCEFormer achieves the state-of-the-art performance in hazy scenes. Specifically, our LCEFormer outperforms DCIL by 0.78 dB and 0.018 for PSNR and SSIM on the DHID dataset.

Terrestrial density of strongly-coupled relics

The simplest cosmologies motivate the consideration of dark matter subcomponents that interact significantly with normal matter. Moreover, such strongly coupled relics may have evaded detection to date if upon encountering the Earth they rapidly thermalize down to terrestrial temperatures, T⊕∼300 K∼25 meV, well below the thresholds of most existing dark matter detectors. This shedding of kinetic energy implies a drastic enhancement to the local density, motivating the consideration of alternative detection techniques sensitive to a large density of slowly moving dark matter particles. In this work, we provide a rigorous semianalytic derivation of the terrestrial overdensities of strongly coupled relics, with a particular focus on millicharged particles (MCPs). We go beyond previous studies by incorporating improved estimates of the MCP-atomic scattering cross section, new contributions to the terrestrial density of sub-GeV relics that are independent of the Earth’s gravitational field, and local modifications that can arise due to the cryogenic environments of precision sensors. We also generalize our analysis in order to estimate the terrestrial density of thermalized MCPs that are produced from the collisions of high-energy cosmic rays and become bound by the Earth’s electric field. Published by the American Physical Society 2024

Transitions of nitrogen optical centers induced by femtosecond laser pulses in treated natural diamond

Diamond is a unique optical material with ultra-hard lattice, which properties can be altered by optically active doping defects combined with carbon interstitials and vacancies. Direct laser writing by focused ultrashort laser pulses enables local modification of color centers in diamonds with excellent three-dimensional positioning accuracy, providing unique capabilities for quantum technologies, magnetometry, laser generation and photoluminescence (PL) micromarking. To shed light on currently unknown underlying atomistic transformations, we exposed electron-irradiated and annealed natural IaAB1-type diamond with an initially high content of various nitrogen-vacancy centers (NV, H3, N3 and H4) to millions of 0.2-ps, 525-nm laser pulses focused inside the sample. The modified areas were characterized by Fourier-transform infrared (FT-IR) and ultraviolet–visible transmission spectroscopy and confocal Raman/PL microspectroscopy with excitation wavelengths of 405 nm and 532 nm. We report on a local decrease in originally strong PL yield of NV, H3 and H4 centers with a monotonic dependence on both pulse energy and exposure time, as well as a rise of H1b and H1c lines in the FT-IR spectra accompanied by a drop in the concentration of H1a center. The results indicate that laser-induced processes make possible both creation and destruction of NV, H3 and H4 centers influenced by their initial concentration and the parameters of laser modification, which can be useful for adjusting of laser writing regimes for PL micromark inscription and other local modification of diamond for photonics applications.

Intensifying electrified flow-through water treatment technologies via local environment modification

Removing high-risk and persistent contaminants from water is challenging, because they typically exist at low concentrations in complex water matrices. Electrified flow-through technologies are viable to overcome the limitations induced by mass transport for efficient contaminant removal. Modifying the local environment of the flow-through electrodes offers opportunities to further improve the reaction kinetics and selectivity for achieving near-complete removal of these contaminants from water. Here, we present state-of-the-art local environment modification approaches that can be incorporated into electrified flow-through technologies to intensify water treatment. We first show methods of nanospace incorporation, local geometry adjustment, and microporous structure optimization that can induce spatial confinement, enhanced local electric field, and microperiodic vortex, respectively, for local environment modification. We then discuss why local environment modification can complement the flow-through electrodes for improving the reaction rate and selectivity. Finally, we outline appropriate scenarios of intensifying electrified flow-through technologies through local environment modification for fit-for-purpose water treatment applications.

Another role of CO-formation catalyst in acidic tandem CO2 electroreduction: Local pH modulator

Another role of CO-formation catalyst in acidic tandem CO2 electroreduction: Local pH modulator

A Hybrid Deep Learning Model Utilizing Cross-Structural Multi-Behavioral Comparative Recommendation for Sustainable Electric Transportation Infrastructure

Ensuring the sustainability of transportation infrastructure for electric vehicles (e-trans) is increasingly imperative in the pursuit of decarbonization goals and addressing the pressing energy shortage. By prioritizing the development and maintenance of resilient e-trans platforms through the optimization of the public charging network, electric vehicle businesses can effectively meet the needs of users, thereby contributing to efforts aimed at improving environmental quality. To achieve this goal, researching the dynamics of vehicle user behaviors plays a crucial role. In this paper, we propose cross-structure multi-behavior contrastive learning for recommendation (C-MBR), which takes into account the dynamic preferences of users, and develops model profiles from the global structure module, local structure module, cross-behavior contrastive learning module, cross-structure contrastive learning module, and model prediction and optimization. C-MBR is mainly designed to learn user preferences from the diversity of users’ behaviors in the process of interacting with the project, so as to grasp the different behavioral intentions of users. The experimental and analytical research is further conducted and validated for dealing with cold start problems. The results indicate that C-MBR has a strong ability to deal with the problem of sparse data. Compared with the ablation experiment, the model performance of C-MBR is significantly enhanced, showing that the C-MBR model can fully apply the information of a global structure and local structure in cross-structure comparative learning and multi-behavioral comparative learning to further alleviate the problem of data sparsity. As a result, the e-trans infrastructure will be significantly enhanced by addressing the issue of data-driven disruption.

Assessing chemostratigraphic and biostratigraphic correlation of Ediacaran phosphorites (Bocaina, Khesen and Doushantuo Formations): Diachronic, local signals of the Neoproterozoic phosphogenic-taphonomic event

The Neoproterozoic phosphogenic event records biotic and biogeochemical changes that seem to indicate intrinsic relationships between phosphogenesis and phosphatic fossil preservation. However, chemo-litho and biostratigraphic correlations conducted on fossiliferous, phosphatic successions of the Doushantuo Formation, South China, evidence a highly heterogeneous record, featuring diachronic depositional ages, variable taxonomic diversity and inconsistent, “noisy” δ13C records. Similar detailed chemo-litho and biostratigraphic correlations targeted in high-grade phosphorite strata have not been performed along Ediacaran units elsewhere. Considering the significance and scarcity of Ediacaran high-grade phosphorite strata, establishing a comprehensive correlation framework within and between those units is fundamental to understanding Ediacaran biogeochemical and biotic evolution. This work aims to integrate new δ13C isotope stratigraphy, and existing Doushantuo-Pertatataka acritarch assemblages and geochronological records from Bocaina (Brazil), Khesen (Mongolia) and Doushantuo (China) Formations. Phosphate rich strata in those units feature inconsistent δ13C signatures characterized by negative values showing large bed-to-bed variations, possibly reflecting local modification of original marine signals by phosphogenesis, suggesting caution against the use in global/regional chemostratigraphic correlation. The record of phosphatized acritarch assemblages shows contrastive taxonomic diversities, and a small number of common taxa including Megasphaera. Whereas the presence of biozonal Doushantuo Formation taxa on Khsesen Fm, resonates with growing views of strong environmental resilience and large temporal ranges of acanthomorph acritarchs throughout the Ediacaran-early Cambrian, the scarcity of similar taxa in the Bocaina Fm may question the reliability of Doushantuo Fm acritarch biozones in other paleogeographic or paleoenvironmental scenarios. Alternatively, the low taxonomic diversity recorded in Bocaina and Khesen Fms may also reflect the effects of the late Ediacaran decline in acritarch diversity. Further, combined evidence of selective paleoenvironmental phosphatization, local geochemical signals, narrow time spans and heterogeneous taxonomic diversity found in phosphatized DPK acanthomorph assemblages indicate the local nature of Ediacaran phosphatic fossil preservation events. Finally, evidence for diachronic preservation between high-grade phosphatic strata and phosphatized microfossils show non-causal relationships between Ediacaran phosphogenesis and phosphatic fossil preservation, highlighting the punctuated, intrinsic local nature of those events.

Dynamic localization of the chromosomal passenger complex in trypanosomes is controlled by the orphan kinesins KIN-A and KIN-B.

The chromosomal passenger complex (CPC) is an important regulator of cell division, which shows dynamic subcellular localization throughout mitosis, including kinetochores and the spindle midzone. In traditional model eukaryotes such as yeasts and humans, the CPC consists of the catalytic subunit Aurora B kinase, its activator INCENP, and the localization module proteins Borealin and Survivin. Intriguingly, Aurora B and INCENP as well as their localization pattern are conserved in kinetoplastids, an evolutionarily divergent group of eukaryotes that possess unique kinetochore proteins and lack homologs of Borealin or Survivin. It is not understood how the kinetoplastid CPC assembles nor how it is targeted to its subcellular destinations during the cell cycle. Here, we identify two orphan kinesins, KIN-A and KIN-B, as bona fide CPC proteins in Trypanosoma brucei, the kinetoplastid parasite that causes African sleeping sickness. KIN-A and KIN-B form a scaffold for the assembly of the remaining CPC subunits. We show that the C-terminal unstructured tail of KIN-A interacts with the KKT8 complex at kinetochores, while its N-terminal motor domain promotes CPC translocation to spindle microtubules. Thus, the KIN-A:KIN-B complex constitutes a unique 'two-in-one' CPC localization module, which directs the CPC to kinetochores from S phase until metaphase and to the central spindle in anaphase. Our findings highlight the evolutionary diversity of CPC proteins and raise the possibility that kinesins may have served as the original transport vehicles for Aurora kinases in early eukaryotes.

Dynamic localization of the chromosomal passenger complex in trypanosomes is controlled by the orphan kinesins KIN-A and KIN-B

The chromosomal passenger complex (CPC) is an important regulator of cell division, which shows dynamic subcellular localization throughout mitosis, including kinetochores and the spindle midzone. In traditional model eukaryotes such as yeasts and humans, the CPC consists of the catalytic subunit Aurora B kinase, its activator INCENP, and the localization module proteins Borealin and Survivin. Intriguingly, Aurora B and INCENP as well as their localization pattern are conserved in kinetoplastids, an evolutionarily divergent group of eukaryotes that possess unique kinetochore proteins and lack homologs of Borealin or Survivin. It is not understood how the kinetoplastid CPC assembles nor how it is targeted to its subcellular destinations during the cell cycle. Here, we identify two orphan kinesins, KIN-A and KIN-B, as bona fide CPC proteins in Trypanosoma brucei, the kinetoplastid parasite that causes African sleeping sickness. KIN-A and KIN-B form a scaffold for the assembly of the remaining CPC subunits. We show that the C-terminal unstructured tail of KIN-A interacts with the KKT8 complex at kinetochores, while its N-terminal motor domain promotes CPC translocation to spindle microtubules. Thus, the KIN-A:KIN-B complex constitutes a unique ‘two-in-one’ CPC localization module, which directs the CPC to kinetochores from S phase until metaphase and to the central spindle in anaphase. Our findings highlight the evolutionary diversity of CPC proteins and raise the possibility that kinesins may have served as the original transport vehicles for Aurora kinases in early eukaryotes.

A Formalism of F-modules for Rings with Complete Local Finite F-Representation Type

Abstract We develop a formalism of unit $F$-modules in the style of Lyubeznik and Emerton-Kisin for rings that have finite $F$-representation type after localization and completion at every prime ideal. As applications, we show that if $R$ is such a ring then the iterated local cohomology modules $H^{n_{1}}_{I_{1}} \circ \cdots \circ H^{n_{s}}_{I_{s}}(R)$ have finitely many associated primes, and that all local cohomology modules $H^{n}_{I}(R / gR)$ have closed support when $g$ is a nonzerodivisor on $R$.

1: Local energy band and charge carrier modulation by ferro‐/piezo‐phototronic effect in optoelectronic devices

1: Local energy band and charge carrier modulation by ferro‐/piezo‐phototronic effect in optoelectronic devices

Assessing the Possibility of Implementing Distributed Diagnostic Systems for Hydrogen Fuel Cells Using Local and Global Telecommunication Networks

The development of effective methods and means for diagnosing hydrogen fuel cells during their operation is an urgent task, since their implementation will improve the energy characteristics and stability of operation by detecting incorrect operating modes and malfunctions at the early stages of development. This problem can be solved by using various approaches based on the analysis of impedance, relaxation or fluctuation-noise characteristics. All of these methods require the implementation of rather complex computational procedures and the accumulation of fairly large amount of statistical data, which makes it difficult to implement diagnostic devices on inexpensive embedded microprocessor tools. To overcome this drawback, this work proposes the use of distributed diagnostic systems with high-performance server devices connected to local modules via global or local telecommunication networks. Such an implementation will significantly simplify the requirements for local diagnostic modules and reduce their cost, but this raises the question of the efficiency of making diagnostic decisions by such systems.The work carried out, is a study of delays in making diagnostic and control decisions when using remote server devices for signal processing. It has been shown that the use of such systems makes it possible to achieve delays of less than one second even when using intercontinental communication lines. It should be noted that in applications critical to time delays, the distance between the client and server systems should be reduced. The advantages of the proposed implementation of a diagnostic system for electrochemical energy sources are the possibility of simplifying local measurement systems installed on individual sources, the possibility of accelerating signal processing through the use of more productive computing tools and the accumulation of statistical data.

The Effectiveness of the Local Knowledge-Based Module (LKBM) to Improve Students’ Scientific Literacy and Thinking Skills

The Effectiveness of the Local Knowledge-Based Module (LKBM) to Improve Students’ Scientific Literacy and Thinking Skills

Local modification of the crystalline structure due to co-doping with RE3+ in cadmium metasilicate

Persistent emission is a well-known property of cadmium metasilicate (CdSiO3) doped and co-doped with rare earth ions due to the ease of choosing the desired luminescence colour, as well as the possibility of adjusting the emission colour and the luminescence duration. Experimental work has demonstrated that combinations of different rare earth ions can produce different emission spectra colours as well as modify the lifetime of emissions. Theoretical work demonstrated a preference of single dopants to substitute cadmium sites with a Cd-vacancy as a compensation mechanism. To help elucidate the luminescent mechanisms through structural modification and consequently modification of the crystal field generated in the material by the defective region, in this work, several configurations for combined defects were tested considering the distance and preferential configuration of all the defects that comprise the system, as well as the possibility of a high concentration of these defects. Results showed a preferential arrangement for the incorporation of a Cd-vacancy as a form of charge compensation. The arrangement forms an angle closer to 180° considering the Cd-vacancy as vertex and presents a distance of around 7 Å between rare earth ions. It was also identified that the formation of a single pair with two different RE3+ ions close to a cadmium vacancy are minimally energetically more favourable to be formed in relation to clusters of dopants and co-dopants. This indicates that at low doping concentrations, RE3+ dopant pairs will form separately, but by increasing the concentration it is possible to form a cluster of defects involving RE3+. This may explain the low concentrations of dopants in this matrix. The distortion caused in the local lattice by the presence of a RE3+ pair of different dopants is bigger than the distortion caused by a RE3+ pair of dopants of the same chemical species. Therefore, CdSiO3: RE13+, RE23+ has a crystal field that is different from the crystal field experienced by RE3+ as a single dopant and the presence of the co-dopant ion will modify the luminescence of the system even though the generating defect of the luminescent centre remains the same.

Dual-former: Hybrid self-attention transformer for efficient image restoration

Recently, image restoration transformers have achieved comparable performance with previous state-of-the-art CNNs. In this work, we present Dual-former whose critical insight is to combine the powerful global modeling ability of self-attention modules and the local modeling ability of convolutions in an overall architecture. With convolution-based Local Feature Extraction modules equipped in the encoder and the decoder, we only adopt a novel Hybrid Transformer Block in the latent layer to model the long-distance dependence in spatial dimensions and handle the uneven distribution between channels. Such a design eliminates the substantial computational complexity in previous image restoration transformers and achieves superior performance on multiple image restoration tasks. Experiments demonstrate that Dual-former achieves a 1.91 dB gain over the state-of-the-art MAXIM method on the Indoor dataset for single image dehazing while consuming only 4.2% GFLOPs as MAXIM. For single image deraining, it exceeds the SOTA method by 0.1 dB PSNR on the average results of five datasets with only 21.5% GFLOPs. Dual-former also substantially surpasses the latest methods on various tasks, with fewer parameters.

LIFNS: Design of a novel Lidar-IMU fusion navigation system for AGVs in smart factories

Traditional Automated Guided Vehicle (AGV) robots commonly employ 2D plane navigation systems. However, with the expansion of AGV application scenarios and the increasing complexity of structures, the limitations of existing 2D navigation systems have become more pronounced, rendering them inadequate for addressing these challenges. To tackle this issue, this paper proposes a novel navigation system suitable for AGV robots composed of fused Lidar and Inertial Measurement Unit (IMU), named as Lidar-IMU Fusion Navigation System (LIFNS). LIFNS primarily comprises mapping, localization, and fused path planning modules. In the mapping module, a 3D point cloud map for precise 3D localization and a 2D grid map for path planning are constructed using multiple-line Lidar and IMU. For the localization module, a fusion localization approach is introduced, combining IMU data with Normal Distributions Transform (NDT) point cloud registration through Unscented Kalman Filtering (UKF). Finally, global path planning is executed using the A* algorithm on the grid map, while local path planning utilizes the Timed-Elastic Band (TEB) algorithm. The effectiveness and universality of LIFNS are validated through simulation experiments and real-world deployment tests. The experimental results demonstrate that LIFNS achieves centimeter-level accuracy in both mapping and localization, effectively alleviating the issues of low precision and significant limitations present in traditional AGV robots. This positions LIFNS with promising applications in enclosed settings such as smart factories, industrial parks, and healthcare facilities.