Heterogeneous Blocks Research Articles

Two- and Three-Dimensional Ag-Au Nanoalloying: Heterogeneous Building Blocks Enhancing Near-Field Focusing.

In this study, we report a strategy for fabricating binary surface-enhanced Raman scattering (SERS) substrates composed of plasmonic Pt@Ag and Pt@Au truncated-octahedral (TOh) dual-rim nanoframes (DNFs) functioning as a "nanoalloy." Pt TOh frameworks act as a scaffold to develop nanoarchitectures with surface decoration using plasmonically active materials (i.e., Au or Ag), resulting in identical sizes and shapes for the two distinct plasmonic elements, facilitating the fabrication of a "nanoalloy" blend of two shape-complex building blocks. The structural complexity from the dual-rim on (111) facets, combined with the mirror charge effect (i.e., enhanced polarization between Ag and Au) at the interface of heterogeneous components, significantly amplifies SERS activity. We carefully investigated near-field focusing of binary SERS substrates through single-particle and bulk SERS measurements corroborated by finite element method (FEM) calculations. Crucially, we developed free-standing superpowders (SPs) in which each heterogeneous building block formed micron-sized supercrystals with adjustable component ratios. These plasmonic SPs were applied to contaminated areas for analyte detection, demonstrating their potential for practical SERS applications.

Interdependence of heterogeneous blockholders: Evidence from China

The co-holding of interdependent pairs of heterogeneous blocks can provide firms with stable financial support. The interdependence of heterogeneous blockholders’ investment decision has become an important frontier in the financial literature on large shareholders. In this paper, we study the interdependence of heterogeneous blocks in China. We find significant positive interdependence among blockholders of the same type. In heterogeneous block pairs, the financial–private pair shows positive interdependence. The findings are in contrast to those observed in the US. Under the mixed-ownership reform in China, our findings suggest the potential for cooperation among multiple blocks of the same type rather than between heterogeneous strategic partners.

Structural imbalance and integrated economic development of RCEP countries on perspective of industrial network

In the decade of the RCEP negotiations, structural changes and imbalance have occurred in the regional economic system. For this problem, the paper analyzed structural imbalance and its impacts on integrated economic development of the RCEP countries and India from perspective of industrial network. We designed structural indicators describing imbalance of industrial system and impact of imbalance on integrated development. Empirical analysis was based on the world input-output data for 2010, 2015 and 2019. It can be found that economic imbalance reflected in China's dominant role, structural deviation, weak and excessive stability, hierarchy. So RCEP region is integrated relying on three heterogeneous economic blocks, including the power center, affiliated members, and sub centers and their partners, which produce centripetal integration, segmentation and decentralization effects. This imbalance is a double-edged sword for regional integration, and the adaptability and flexibility of the structure are key. Further, some implications were given for promoting strategic economic path of related countries and improving the RCEP protocol.

A duplex transform heterogeneous feature fusion network for road segmentation

Detecting roads in automatic driving environments poses a challenge due to issues such as boundary fuzziness, occlusion, and glare from light. We believe that two factors are instrumental in addressing these challenges and enhancing detection performance: global context dependency and effective feature representation that prioritizes important feature channels. To tackle these issues, we introduce DTRoadseg, a novel duplex Transformer-based heterogeneous feature fusion network designed for road segmentation. DTRoadseg leverages a duplex encoder architecture to extract heterogeneous features from both RGB images and point-cloud depth images. Subsequently, we introduce a multi-source Heterogeneous Feature Reinforcement Block (HFRB) for fusion of the encoded features, comprising a Heterogeneous Feature Fusion Module (HFFM) and a Reinforcement Fusion Module (RFM). The HFFM leverages the self-attention mechanisms of Transformers to achieve effective fusion through token interactions, while the RFM focuses on emphasizing informative features while downplaying less important ones, thereby reinforcing feature fusion. Finally, a Transformer decoder is utilized to produce the final semantic prediction. Furthermore, we employ a boundary loss function to optimize the segmentation structure area, reduce false detection areas, and improve model accuracy. Extensive experiments are carried out on the KITTI road dataset. The results demonstrate that, compared with state-of-the-art methods, DTRoadseg exhibits superior performance, achieving an average accuracy of 97.01%, a Recall of 96.35%, and runs at a speed of 0.09 s per picture.

Tectonic Structure and Evolution of the Lithosphere in the Antarctic Part of the South Atlantic

Based on the analysis of global digital models, the distribution of fracture zones of the oceanic crust, global and regional models of evolution, and published geological and geophysical data, the structural features of the ocean floor in the junction area of the Indian and Atlantic oceans are considered. Tectonic zoning of the region’s crust has been carried out. Heterogeneous blocks of the lithosphere with crust formed on different spreading ridges, separated by structural boundaries, which are pseudo faults, fixing traces of propagating rift zones, jumping and dying off of spreading ridges, are identified. The main stages in the evolution of the lithosphere associated with the activation of plume magmatism and kinematic reorganizations of plate boundaries are identified.

A Heterogeneous Group CNN for Image Super-Resolution.

Convolutional neural networks (CNNs) have obtained remarkable performance via deep architectures. However, these CNNs often achieve poor robustness for image super-resolution (SR) under complex scenes. In this article, we present a heterogeneous group SR CNN (HGSRCNN) via leveraging structure information of different types to obtain a high-quality image. Specifically, each heterogeneous group block (HGB) of HGSRCNN uses a heterogeneous architecture containing a symmetric group convolutional block and a complementary convolutional block in a parallel way to enhance the internal and external relations of different channels for facilitating richer low-frequency structure information of different types. To prevent the appearance of obtained redundant features, a refinement block (RB) with signal enhancements in a serial way is designed to filter useless information. To prevent the loss of original information, a multilevel enhancement mechanism guides a CNN to achieve a symmetric architecture for promoting expressive ability of HGSRCNN. Besides, a parallel upsampling mechanism is developed to train a blind SR model. Extensive experiments illustrate that the proposed HGSRCNN has obtained excellent SR performance in terms of both quantitative and qualitative analysis. Codes can be accessed at https://github.com/hellloxiaotian/HGSRCNN.

Advances in Traditional Electrical Validation of High-Speed Serial Connections Using Innovative Debugging Methods and Machine Learning Models.

As technology continues to shrink and more heterogeneous blocks are combined into single System on a chip (SOCs), the design of high-performance integrated circuits is getting more and more difficult. In the course of silicon validation, which includes testing (Wafer Testing, Automatic Test Equipment), digital validation (Functional Data route, FSM), analogue bench validation (Electrical, Interoperability), and system validation, a number of challenges that arise from the complicated design are uncovered. The process, methods, and constraints of each domain are unique. Electrical problems that have already passed through earlier stages of design are the primary focus of analogue validation. The analogue signal or mix signal nature of IPs makes it impossible for digital validation or any of the other post-silicon domains to discover electrical flaws on its own. As a result, studies focusing on analogue bench validation have grown in prominence. Recent developments in analogue bench validation, focusing on high-speed serial interface in particular, are highlighted in the proposed study. In addition, this article summarises recent technological developments that provide avenues for further study regarding analogue bench validation.

A Security Information Transmission Method Based on DHR for Seafloor Observation Network.

A seafloor observation network (SON) consists of a large number of heterogeneous devices that monitor the deep sea and communicate with onshore data centers. Due to the long-distance information transmission and the risk of malicious attacks, ensuring the integrity of data in transit is essential. A cryptographically secure frame check sequence (FCS) has shown great advantages in protecting data integrity. However, the commonly used FCS has a collision possibility, which poses a security risk; furthermore, reducing the encryption calculation cost is a challenge. In this paper, we propose a secure, lightweight encryption scheme for transmitted data inspired by mimic defense from dynamic heterogeneous redundancy theory. Specifically, we use dynamic keys to encrypt a data block and generate multiple encrypted heterogeneous blocks for transmission. These continuously changing encrypted data blocks increase the confusion regarding the original encoded data, making it challenging for attackers to interpret and modify the data blocks. Additionally, the redundant information from the multiple blocks can identify and recover tampered data. Our proposed scheme is suitable for resource-constrained environments where lightweight encryption is crucial. Through experimental demonstrations and analysis methods, we determine the effectiveness of our encryption scheme in reducing computational costs and improving security performance to protect data integrity.

Crustal block-controlled contrasts in deformation, uplift, and exhumation in the Santa Cruz Mountains, California, USA, imaged through apatite (U-Th)/He thermochronology and 3-D geological modeling

Deformation along strike-slip plate margins often accumulates within structurally partitioned and rheologically heterogeneous crustal blocks within the plate boundary. In these cases, contrasts in the physical properties and state of juxtaposed crustal blocks may play an important role in accommodation of deformation. Near the San Francisco Bay Area, California, USA, the Pacific−North American plate-bounding San Andreas fault bisects the Santa Cruz Mountains (SCM), which host numerous distinct, fault-bounded lithotectonic blocks that surround the San Andreas fault zone. In the SCM, a restraining bend in the San Andreas fault (the SCM bend) caused recent uplift of the mountain range since ca. 4 Ma. To understand how rheologic heterogeneity within a complex fault zone might influence deformation, we quantified plausible bounds on deformation and uplift across two adjacent SCM lithotectonic blocks on the Pacific Plate whose stratigraphic and tectonic histories differ. This was accomplished by combining 31 new apatite (U-Th)/He ages with existing thermochronological datasets to constrain exhumation of these two blocks. Additionally, surface exposures of the latest Miocene to late Pliocene Purisima Formation interpreted in 18 structural cross sections spanning the SCM allowed construction and restoration of Pliocene deformation in a three-dimensional geologic model. We found that rock uplift and deformation concentrated within individual Pacific Plate lithotectonic blocks in the SCM. Since 4 Ma, maximum principal strain computed for the more deformed block adjacent to the fault exceeded that computed for the less deformed block by at least 375%, and cumulative uplift has been more spatially extensive and higher in magnitude. We attribute the difference in uplift and deformation between the two blocks primarily to contrasts in lithotectonic structure, which resulted from diverging geologic histories along the evolving plate boundary.

Design and Analysis of High Performance Heterogeneous Block-based Approximate Adders

Approximate computing is an emerging paradigm to improve the power and performance efficiency of error-resilient applications. As adders are one of the key components in almost all processing systems, a significant amount of research has been carried out toward designing approximate adders that can offer better efficiency than conventional designs; however, at the cost of some accuracy loss. In this article, we highlight a new class of energy-efficient approximate adders, namely, Heterogeneous Block-based Approximate Adders (HBAAs), and propose a generic configurable adder model that can be configured to represent a particular HBAA configuration. An HBAA, in general, is composed of heterogeneous sub-adder blocks of equal length, where each sub-adder can be an approximate sub-adder and have a different configuration. The sub-adders are mainly approximated through inexact logic and carry truncation. Compared to the existing design space, HBAAs provide additional design points that fall on the Pareto-front and offer a better quality-efficiency tradeoff in certain scenarios. Furthermore, to enable efficient design space exploration based on user-defined constraints, we propose an analytical model to efficiently evaluate the Probability Mass Function (PMF) of approximation error and other error metrics, such as Mean Error Distance (MED), Normalized Mean Error Distance (NMED), and Error Rate (ER) of HBAAs. The results show that HBAA configurations can provide around 15% reduction in area and up to 17% reduction in energy compared to state-of-the-art approximate adders.

Analytical Placement with 3D Poisson’s Equation and ADMM-based Optimization for Large-scale 2.5D Heterogeneous FPGAs

As design complexity keeps increasing, the 2.5D field-programmable gate array (FPGA) with large logic capacity has become popular in modern circuit applications. A 2.5D FPGA consists of multiple dies connected through super long lines (SLLs) on an interposer. Each die contains heterogeneous logic blocks and ASIC-like clocking architectures to achieve better skew and timing. Existing works consider these problems separately and thus may lead to serious timing issues or routing failure. This article presents an analytical placement algorithm for the 2.5D FPGA to simultaneously minimize the number of inter-die SLL signals and intra-die clocking violations. Using a lifting dimension technique, we first formulate the 2.5D global placement problem as a three-dimensional continuous and differential minimization problem, where the SLL-aware block distribution is modeled by 3D Poisson’s equation and directly solved to obtain an analytical solution. Then, we further reformulate the minimization problem as a separable optimization problem with linear constraints. Based on the proximal alternating direction method of multipliers optimization method, we efficiently optimize the separable subproblems one by one in an alternating fashion. Finally, clock-aware legalization and detailed placement are applied to legalize and improve our placement results. Compared with the state-of-the-art works, experimental results show that our algorithm can resolve all clocking constraints and reduce the number of SLL crossing signals by 36.9% with similar wirelength in a comparable running time.

Experimental validation of a 4D dynamic dose calculation model for proton pencil beam scanning without spot time stamp considering free-breathing motion.

We developed a 4-dimensional dynamic dose (4DDD) calculation model for proton pencil beam scanning (PBS). This model incorporates the spill start time for all energies and uses the remaining irradiated spot time model instead of irradiated spot time logs. This study aimed to validate the calculation accuracy of a log file-based 4DDD model by comparing it with dose measurements performed under free-breathing conditions, thereby serving as an alternative approach to the conventional log file-based system. Three cubic verification plans were created using a heterogeneous block phantom; these plans were created using 10 phase 4D-CT datasets of the phantom. The CIRS dynamic platform was used to simulate motion with amplitudes of 2.5, 3.75, and 5.0mm. These plans consisted of eight- and two-layered rescanning techniques. The lateral profiles were measured using a 2D ionization chamber array (2D-array) and EBT3 Gafchromic films at four starting phases, including three sinusoidal curves (periods of 3, 4, and 6s) and a representative patient curve during actual treatment. 4DDDs were calculated using in-house scripting that assigned a time stamp to each spot and performed dose accumulation using deformable image registration. Furthermore, to evaluate the impact of parameter selection on our 4DDD model calculations, simulations were performed assuming a ±10% change in irradiation time stamp (0.8±0.08s) and spot scan speed. We evaluated the 2D gamma index and the absolute point doses between the calculated values and the measurements. The 2D-array measurements revealed that the gamma scores for the static plans (no motion) and 4DDD plans exceeded 97.5% and 93.9% at 3%/3mm, respectively. The average gamma score of the 4DDD plans was at least 96.1%. When using EBT3 films, the gamma scores of the 4DDD model exceeded 92.4% and 98.7% at 2%/2mm and 3%/3mm, respectively. Regarding the 4DDD point dose differences, more than 95% of the dose regions exhibited discrepancies within ±5.0% for 97.7% of the total points across all plans. The spot time assignment accuracy of our 4DDD model was acceptable even with ±10% sensitivity. However, the accuracy of the scan speed, when varied within ±10%sensitivity, was not acceptable (minimum gamma scores of 82.6% and maximum dose difference of 12.9%). Our 4DDD calculations under free-breathing conditions using amplitudes of less than 5.0mm were in good agreement with the measurements regardless of the starting phases, breathing curve patterns (between 3 and 6s periods), and varying numbers of layered rescanning. The proposed system allows us to evaluate actual irradiated doses in various breathing periods, amplitudes, and starting phases, even on PBS machines without the ability to record spot logs.

The multiple phonological activation in Chinese spoken word production: An ERP study supporting cascaded model

A central issue in spoken word production concerns how activation is transmitted from semantic to phonological levels. The current study investigated the issue of seriality and cascadedness in Chinese spoken word production, via the combined semantic blocked paradigm (with homogeneous and heterogeneous blocks) and picture-word interference paradigm (with phonologically related, mediated and unrelated distractors). Naming latencies data showed a mediated effect via comparing mediated and unrelated distractors in homogeneous blocks, a phonological facilitation effect via comparing phonologically related and unrelated distractors in homogeneous and heterogeneous blocks, and a semantic interference effect via comparing homogeneous and heterogeneous blocks. Critically, cluster-based permutation test of ERP data demonstrated a mediated effect around 266-326ms and an overlapped pattern of semantic interference effect around 264-418ms and phonological facilitation effect around 210-310ms in homogeneous or around 236-316ms in heterogeneous blocks. These findings indicated that speakers activate phonological nodes of non-targets, and present a cascadedness pattern of the transmission from semantics to phonology in Chinese spoken production. The present study sheds new insight on the neural correlates of semantic and phonological effects, and provides behavioral and electrophysiological evidences for the cascaded model within a theoretical framework of lexical competition in speech production.

NEOTECTONIC DISLOCATIONS AT THE BARENTS SEA SHELF AND THEIR GENESIS ACCORDING TO THE MORPHOMETRY OF BATHYMETRY, SEISMIC SECTIONS AND THE DEEP MANTLE STRUCTURE

The paper provides a comprehensive analysis of the morphometric attribute “general curvature” for the bathymetry of the Barents Sea, seismic and seismoacoustic data containing in the wave field patterns tectonic faults emerging to the surface, a fault network of the sedimentary cover confirmed by seismic surveys, and seismotomographic data showing the heterogeneous deep structure by the distribution of seismic wave velocities in the upper mantle. The analysis of these data showed the presence of a causal relation between rheologically heterogeneous and mobile blocks of the upper mantle and the crystalline part of the Earth’s crust with the deep fault network, emerging on the bottom surface and being a relief-forming factor that forms characteristic domains with different textures performed by the morphometric attribute “general curvature”.

LS-HH: A Learning-Based Selection Hyper-Heuristic for Distributed Heterogeneous Hybrid Blocking Flow-Shop Scheduling

As the development of economic globalization, the distributed manufacturing has become common in modern industries. The scheduling of production resources in multiple production centers becomes an emerging topic. This paper is the first attempt to address a distributed heterogeneous hybrid blocking flow-shop scheduling problem (DHHFSP-B) with the minimization of makespan. Compared with the traditional single flow-shop scheduling, DHHFSP-B considers the collaborative production of multiple hybrid flow lines with heterogeneous layout and processing performance as well as no intermediate buffers. We firstly present a mixed-integer linear programming model to formulate DHHFSP-B and then propose a learning-based selection hyper-heuristic framework (LS-HH) for solving it. The LS-HH contains high-level strategy and low-level heuristics. In the high-level strategy, a learning probability model is built to provide the guidance to choose the suitable perturbation heuristic during the optimization process. A simulated annealing-like move acceptance is employed to determine the updating of incumbent domain solution and prevent the search from trapping into local optimum. In the low-level heuristics, a constructive heuristic is proposed based on a novel assignment rule to create the initial domain solution. Four problem-specific perturbation heuristics and a variable neighborhood search-based improvement operator are employed to search the solution space. A comprehensive computational experiment is conducted. The comparative results show that the LS-HH significantly outperforms the Gurobi solver and several closely relevant optimization methods in solving the DHHFSP-B.

Структурное районирование Африкано-Антарктического сектора Южного океана на основе анализа аномальных гравитационного и магнитного полей

The African-Antarctic sector of the Southern Ocean is the least studied part of the World Ocean, the structure and evolution of the tectonosphere of which remains debatable. The complex history of the development of the region under study, accompanied by manifestations of intense magmatic and tectonic activity, has contributed to the formation of a number of large underwater ridges and rises. Identifying the features of the deep structure of the tectonosphere on the basis of the analysis of geophysical information and understanding the geodynamic nature of the morphostructures of the studied region is an urgent problem of marine geophysics and geodynamics. Structural analysis of the anomalous gravitational and magnetic fields of the studied region was carried out. Zoning scheme by the anomalous fields as well as a generalized scheme are constructed. The results of the sestudiesmadeit possible to identify heterogeneous blocks of the lithosphere, which for medon different spreading ridges and are separated by submarine rises.

К ВОПРОСУ О МЕХАНИЗМЕ ИЗМЕНЕНИЯ ХИМИЧЕСКОГО СОСТАВА ВОДЫ САМОИЗЛИВАЮЩИХСЯ СКВАЖИН В УСЛОВИЯХ НЕСТАЦИОНАРНОГО РЕЖИМА (НА ПРИМЕРЕ СКВАЖИНЫ ГК-1, ПОЛУОСТРОВ КАМЧАТКА)

The ГК-1 self-discharging well is located in the southeastern part of the Kamchatka Peninsula. The well is part of a network of continuous observations of the groundwater regime, conducted in order to identify and study the hydrogeochemical precursors of strong Kamchatka earthquakes. The article discusses data on changes in the flow rate and chemical composition of well water for the period from 1970 to 2022. The subject of the analysis is the hydrogeochemical effects appearing under the conditions of non-stationary regime arising due to drainage of the pressure reservoir by the well and as a result of changes in bottom-hole pressure. The mechanisms of formation of long-term (decades) and relatively short-term (tens of days) changes in the chemical composition of water at the mouth of the ГК-1 self-discharging well are discussed within the framework of the concepts of water-bearing rocks as a heterogeneous block medium with double porosity.

Neural operator search

Existing neural architecture search (NAS) methods usually explore a limited feature-transformation-only search space, ignoring other advanced feature operations such as feature self-calibration by attention and dynamic convolutions. This disables the NAS algorithms to discover more advanced network architectures. We address this limitation by additionally exploiting feature self-calibration operations, resulting in a heterogeneous search space. To solve the challenges of operation heterogeneity and significantly larger search space, we formulate a neural operator search (NOS) method. NOS presents a novel heterogeneous residual block for integrating the heterogeneous operations in a unified structure, and an attention guided search strategy for facilitating the search process over a vast space. Extensive experiments show that NOS can search novel cell architectures with highly competitive performance on the CIFAR and ImageNet benchmarks.

Energy-efficient distributed heterogeneous blocking flowshop scheduling problem using a knowledge-based iterated Pareto greedy algorithm

Energy-efficient distributed heterogeneous blocking flowshop scheduling problem using a knowledge-based iterated Pareto greedy algorithm

Investigation of the shear band evolution in soil-rock mixture using the assumed enhanced strain method with the meshes of improved numerical manifold method

Falling into the framework of the Petrov-Galerkin finite element formulation with embedded discontinuity, the assumed enhanced strain (AES) method could simulate the structural localization phenomenon and the associated loss of bearing capacity in a way insensitive to mesh alignment and refinement. For another hand, the improved numerical manifold method (INMM) naturally excels at dealing with heterogeneous problems such as the soil-rock mixture (SRM) slope with embedded soft soil region. Therefore, to simulate the shear band evolution in heterogeneous slope more efficiently, precisely and also mesh independently, this paper proposes to invoke the AES method with the meshes of the INMM. Beside, this paper proposes a simple and efficient method to address the constitutive integration for multi-surface plasticity induced by cutting the tensile part of the Drucker Prager model. Finally, the efficiency and accuracy of the proposed approaches are tested on some typical examples including heterogeneous block and slope.