Inherent Feature Research Articles

Turnover importance: Operationalizing beta diversity to quantify the generalism continuum

Abstract Generalization is difficult to quantify, and many classifications exist. A beta diversity framework can be used to establish a numeric measure of generalist tendencies that jointly describes many important features of species interactions, namely spatiotemporal heterogeneity. This framework is promising for studying generalized symbiotic relationships of any form. We formulated a novel index, turnover importance (T). T describes spatiotemporal heterogeneity in interactor assemblages, an inherent feature of generalist relationships that is not captured by available metrics. We simulated the behaviour of T relative to other available metrics, calculated T for native North American orchid‐insect relationships, and tested correlations between T and eco‐geographic variables. We performed case studies to demonstrate applications of T for conservation and eco‐evolutionary studies. T behaves predictably across simulations, and dynamically interacts with site number, gamma diversity, and species range sizes. T is moderately sensitive to sampling depth. Orchids with higher T scores occupy larger ranges and broader climatic niches. Alternative interactor‐specific measures of generalism are best employed for local‐level community networks over short timespans. While these interactor metrics can assess use versus availability in local communities, T can be used to measure spatiotemporal patterns of variation in interactor assemblages across a focal species' range. This study provides a roadmap for future work focused on better understanding the patterns and consequences of generalized relationships.

The role of the paraspinal muscles in the development of adolescent idiopathic scoliosis based on surface electromyography and radiographic analysis

BackgroundPatients with idiopathic scoliosis commonly present with an imbalance of the paraspinal muscles. However, it is unclear whether this muscle imbalance is an underlying cause or a result of idiopathic scoliosis. This study aimed to investigate the role of paraspinal muscles in the development of idiopathic scoliosis based on surface electromyography (sEMG) and radiographic analyses.MethodsThis was a single-center prospective study of 27 patients with single-curve idiopathic scoliosis. Posteroanterior whole-spine radiographs and sEMG activity of the erector spinae muscles were obtained for all patients in the habitual standing position (HSP), relaxed prone position (RPP), and prone extension position (PEP). The Cobb angle, symmetrical index (SI) of the sEMG activity (convex/concave), and correlation between the two factors were analyzed.ResultsIn the total cohort, the mean Cobb angle in the HSP was significantly greater than the mean Cobb angle in the RPP (RPP-Cobb) (p < 0.001), whereas the mean Cobb angle in the PEP (PEP-Cobb) did not differ from the RPP-Cobb. Thirteen patients had a PEP-Cobb that was significantly smaller than their RPP-Cobb (p = 0.007), while 14 patients had a PEP-Cobb that was significantly larger than their RPP-Cobb (p < 0.001). In the total cohort and two subgroups, the SI of sEMG activity at the apex vertebra (AVSI) in the PEP was significantly greater than 1, revealing significant asymmetry, and was also significantly larger than the AVSI in the RPP. In the RPP, the AVSI was close to 1 in the total cohort and two subgroups, revealing no significant asymmetry.ConclusionThe coronal Cobb angle and the SI of paraspinal muscle activity in AIS patients vary with posture changes. Asymmetrical sEMG activity of the paraspinal muscles may be not an inherent feature of AIS patients, but is evident in the challenging tasks. The potential significance of asymmetric paraspinal muscle activity need to be explored in further research.

Data-Driven Modeling and Operation Optimization With Inherent Feature Extraction for Complex Industrial Processes

In response to the tenets of Industry 4.0, operation optimization in industrial processes has become a significant research topic. However, the uncertainties prevailing in the process pose challenges to production operations, especially the feedstock properties. In this work, the operation optimization study is performed on a distillation unit (DU), a typical plant in the industrial process. To enhance production performance, a modeling and operation optimization strategy based on feedstock property and production features is presented. One of the difficulties is how to uncover features from high-dimensional and imperfect data, where imperfect data refers to product quality data that is unavailable online. In the strategy, we inject the inherent characteristic of the process into the data-driven method to extract the feedstock property in a data-based and knowledge-oriented manner. Further, optimal feature representation and process modeling can be achieved by customizing the network structure. The operation optimization problem is formulated to adjust the top temperature of the distillation column (TTDC) to achieve satisfactory production under varying feedstock properties. Experimental results illustrate that the process model based on feedstock property and production features (PM-FP-PF) can better fit the physical process mechanism even based on incomplete information in industrial data. Industrial experiments have shown the proposed strategy has advanced generalization ability to the different feedstock properties. The proposed operation optimization strategy (OOS) improves the product qualification rate and has broad application prospects in industrial processes with similar features. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —Industrial processes suffer from a variety of disturbances that interrupt the smooth operation of the system, such as varying feedstock properties. How to deal with them is the key to improve the product qualification rate. In this work, we propose a data-driven modeling and operation optimization framework to improve product quality under varying feedstock properties. The dynamic variation characteristics of the feedstock properties can be obtained by analyzing the physical properties of the production unit. This is used as a basis for representing and extracting feedstock properties in a data-driven way. Further, a process model based on feedstock property and production features (PM-FP-PF) is built to predict product quality. An operation optimization strategy with production capacity consideration is established. It can determine the optimal operation action required by the current system, mitigating the uncertainty of feedstock property. This operation optimization system has been applied to a distillation unit in the hydrofining process. The application results show that the process model achieves satisfactory estimation accuracy, and the operation optimization strategy has improved production performance.

Robust Polar Amplification in Ice-Free Climates Relies on Ocean Heat Transport and Cloud Radiative Effects

Abstract A fundamental divide exists between previous studies that conclude that polar amplification does not occur without sea ice and studies that find that polar amplification is an inherent feature of the atmosphere independent of sea ice. We hypothesize that a representation of climatological ocean heat transport is key for simulating polar amplification in ice-free climates. To investigate this, we run a suite of targeted experiments in the slab ocean aquaplanet configuration of CESM2-CAM6 with different profiles of prescribed ocean heat transport, which are invariant under CO2 quadrupling. In simulations without climatological ocean heat transport, polar amplification does not occur. In contrast, in simulations with climatological ocean heat transport, robust polar amplification occurs in all seasons. What is causing this dependence of polar amplification on ocean heat transport? Energy-balance model theory is incapable of explaining our results and in fact would predict that introducing ocean heat transport leads to less polar amplification. We instead demonstrate that shortwave cloud radiative feedbacks can explain the divergent polar climate responses simulated by CESM2-CAM6. Targeted cloud locking experiments in the zero ocean heat transport simulations are able to reproduce the polar amplification of the climatological ocean heat transport simulations, solely by prescribing high-latitude cloud radiative feedbacks. We conclude that polar amplification in ice-free climates is underpinned by ocean–atmosphere coupling, through a less negative high latitude shortwave cloud radiative feedback that facilitates enhanced polar warming. In addition to reconciling previous disparities, these results have important implications for interpreting past equable climates and climate projections under high-emissions scenarios. Significance Statement Polar amplification is a robust feature of climate change in the modern-day climate. However, previous climate modeling studies fundamentally do not agree on whether polar amplification occurs in ice-free climates. In this study, we find in a state-of-the-art climate model that, if ocean heat transport is neglected, the response to an increase in CO2 is not polar amplified, whereas robust polar amplification occurs if ocean heat transport is included. Using targeted model experiments, we diagnose cloud radiative effects as the driver of this divergent behavior. We conclude that polar amplification is a robust feature of the atmosphere–ocean system. Our results have important implications for interpreting past warm climates and future projections under high-emissions scenarios.

A low-profile high-isolation endfire MIMO antenna based on spoof surface plasmon polaritons for X-band applications

This work proposes a three-port, low-profile, coplanar endfire multiple-input-multiple-output (MIMO) antenna based on spoof surface plasmon polaritons (SSPPs). The proposed antenna comprises a coplanar waveguide (CPW)-fed SSPPs transmission line (TL). A transition to transform the CPW quasi-TEM mode to the SSPPs mode. The radiator section with asymmetric discontinuities converts the bounded SSPPs waves into radiating waves. The proposed MIMO antenna exploits the inherent feature of high isolation in the SSPPs TL due to its strong field confinement competency. Wider beamwidths for ample azimuth and elevation coverage with a stable pattern in the endfire direction are achieved in the 9.52–11.23 GHz operating band. In the operating band, the MIMO antenna has an average realized gain of 6 dBi. Mainly, it has high isolation below -35 dB (measured) in the operating range, a maximum envelope correlation coefficient (ECC) of 1.5 × 10−3, and a total active reflection coefficient (TARC) value below 0.3. The measured results are closely matched with the simulated ones in terms of S-parameters, radiation pattern, ECC, TARC, and CCL.

GDUI: Guided Diffusion Model for Unlabeled Images

The diffusion model has made progress in the field of image synthesis, especially in the area of conditional image synthesis. However, this improvement is highly dependent on large annotated datasets. To tackle this challenge, we present the Guided Diffusion model for Unlabeled Images (GDUI) framework in this article. It utilizes the inherent feature similarity and semantic differences in the data, as well as the downstream transferability of Contrastive Language-Image Pretraining (CLIP), to guide the diffusion model in generating high-quality images. We design two semantic-aware algorithms, namely, the pseudo-label-matching algorithm and label-matching refinement algorithm, to match the clustering results with the true semantic information and provide more accurate guidance for the diffusion model. First, GDUI encodes the image into a semantically meaningful latent vector through clustering. Then, pseudo-label matching is used to complete the matching of the true semantic information of the image. Finally, the label-matching refinement algorithm is used to adjust the irrelevant semantic information in the data, thereby improving the quality of the guided diffusion model image generation. Our experiments on labeled datasets show that GDUI outperforms diffusion models without any guidance and significantly reduces the gap between it and models guided by ground-truth labels.

Enhancing Incipient Fault Detection for Interface Converter Sensors through Signal Correlation Analysis

Incipient faults in interface converters can potentially lead to catastrophic failures. Detection of incipient faults contributes to proactive fault management and predictive maintenance, which effectively improves system reliability. In this paper, a detection method in correlation space is proposed to address this problem, which is based on the inherent feature of correlation changes when a fault occurs. First, a convolution process is used to weaken noise and highlight the correlation feature. Second, the current signals are transmitted to correlation space by using the Pearson correlation coefficient. Third, an accumulation and a reference compensation method are designed for enhancing the features and equalizing influence of reference adjustment. Finally, a fault detection rule is designed based on correlation features and fault excitation. Experiments on a hardware‐in‐loop(HIL) semi‐physical platform indicate that the proposed method outperforms three commonly used correlation analysis algorithms. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

OXPHOS-targeted nanoparticles for boosting photodynamic therapy against hypoxia tumor

Hypoxia as an inherent feature in tumors is firmly associated with unsatisfactory clinical outcomes of photodynamic therapy (PDT) since the lack of oxygen leads to ineffective reactive oxygen species (ROS) productivity for tumor eradication. In this study, an oxidative phosphorylation (OXPHOS) targeting nanoplatform was fabricated to alleviate hypoxia and enhance the performance of PDT by encapsulating IR780 and OXPHOS inhibitor atovaquone (ATO) in triphenylphosphine (TPP) modified poly(ethylene glycol) methyl ether-block-poly(L-lactide-co-glycolide) (mPEG-PLGA) nanocarriers (TNPs/IA). ATO by interrupting the electron transfer in OXPHOS could suppress mitochondrial respiration of tumor cells, economising on oxygen for the generation of ROS. Benefiting from the mitochondrial targeting function of TPP, ATO was directly delivered to its site of action to obtain highlighted effect at a lower dosage. Furthermore, positioning the photosensitizer IR780 to mitochondria, a more vulnerable organelle to ROS, was a promising method to attenuate the spatiotemporal limitation of ROS caused by its short half-life and narrow diffusion radius. As a result, TNPs/IA exhibited accurate subcellular localization, lead to the collapse of ATP production by damaging mitochondrion and elicited significant antitumor efficacy via oxygen-augmented PDT in the HeLa subcutaneous xenograft model. Overall, TNPs/IA was a potential strategy in photodynamic eradication of tumors.

Heterogeneity in Measures of Illness among Patients with Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Is Not Explained by Clinical Practice: A Study in Seven U.S. Specialty Clinics.

Background: One of the goals of the Multi-site Clinical Assessment of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (MCAM) study was to evaluate whether clinicians experienced in diagnosing and caring for patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) recognized the same clinical entity. Methods: We enrolled participants from seven specialty clinics in the United States. We used baseline data (n = 465) on standardized questions measuring general clinical characteristics, functional impairment, post-exertional malaise, fatigue, sleep, neurocognitive/autonomic symptoms, pain, and other symptoms to evaluate whether patient characteristics differed by clinic. Results: We found few statistically significant and no clinically significant differences between clinics in their patients' standardized measures of ME/CFS symptoms and function. Strikingly, patients in each clinic sample and overall showed a wide distribution in all scores and measures. Conclusions: Illness heterogeneity may be an inherent feature of ME/CFS. Presenting research data in scatter plots or histograms will help clarify the challenge. Relying on case-control study designs without subgrouping or stratification of ME/CFS illness characteristics may limit the reproducibility of research findings and could obscure underlying mechanisms.

A comparison study of high purity nickel fabricated by laser powder bed fusion and subjected to dynamic plastic deformation

High density additively manufactured (AM) pure Ni samples were fabricated by laser powder bed fusion with 46 sets of processing parameters. The microstructure, thermal stability, and tensile properties of the sample with the optimized set of parameters were evaluated. To compare the inherent size effects related to dislocation cells and grain boundaries on thermal stability and strengthening, ultrafine-grained Ni samples with an identical chemical composition were also prepared by dynamic plastic deformation (DPD) with strain levels ranging from 0.2 to 2.2. The dislocation cells in AM Ni tended to coarsen between 400 and 600 °C, and partially disentangled and recovered at 700 °C−1200 °C but were reluctant to fully recrystallize even at 1200 °C due to the existence of oxide particles. These oxides were unexpected in high purity Ni. Consequentially, the yield strength of AM Ni continuously decreased with the increase of annealing temperature but remained higher than that of the fully recrystallized samples. The DPD Ni samples exhibited a higher strength level than AM Ni but with a poor uniform elongation. Meanwhile, their full recrystallization occurred at 500 °C for all strain levels, indicating inferior thermal stability compared to AM Ni. Fitting the inherent feature size with strength in the Hall-Petch relationship indicated that dislocation cell boundaries were weaker barriers to glissile dislocations compared to grain boundaries. The Taylor's hardening equation also correlated well with the dislocation cell strengthening in AM Ni. The AM Ni filled in a spot on the strength-ductility map that coarse-grained Ni and DPD Ni were unable to access.

An Analysis of Online Perceptions in Response to Microsoft’s and Google’s Sexual Harassment Scandals

This study contributes to the literature on corporate diversity and crisis management by analyzing stakeholder perceptions in the aftermath of Google’s and Microsoft’s sexual harassment scandals. The results reveal that both scandals were construed from the perspective of activism, an inherent feature of social media communication. While users made demands for additional corrective action from both companies, Google’s scandal was predominantly defined from the frames of controllability and perceived injustice, possibly eroding corporate reputation. By contrast, the frame of severity prevailed in the online discourse around Microsoft and showed a delineation between perceptions of senior leadership and HR. The findings have implications for the practice of communication management with respect to scandals.

Environment geometry alters subiculum boundary vector cell receptive fields in adulthood and early development

Boundaries to movement form a specific class of landmark information used for navigation: Boundary Vector Cells (BVCs) are neurons which encode an animal’s location as a vector displacement from boundaries. Here we characterise the prevalence and spatial tuning of subiculum BVCs in adult and developing male rats, and investigate the relationship between BVC spatial firing and boundary geometry. BVC directional tunings align with environment walls in squares, but are uniformly distributed in circles, demonstrating that environmental geometry alters BVC receptive fields. Inserted barriers uncover both excitatory and inhibitory components to BVC receptive fields, demonstrating that inhibitory inputs contribute to BVC field formation. During post-natal development, subiculum BVCs mature slowly, contrasting with the earlier maturation of boundary-responsive cells in upstream Entorhinal Cortex. However, Subiculum and Entorhinal BVC receptive fields are altered by boundary geometry as early as tested, suggesting this is an inherent feature of the hippocampal representation of space.

A Curriculum-style Self-training Approach for Source-Free Semantic Segmentation.

Source-free domain adaptation has developed rapidly in recent years, where the well-trained source model is adapted to the target domain instead of the source data, offering the potential for privacy concerns and intellectual property protection. However, a number of feature alignment techniques in prior domain adaptation methods are not feasible in this challenging problem setting. Thereby, we resort to probing inherent domain-invariant feature learning and propose a curriculum-style self-training approach for source-free domain adaptive semantic segmentation. In particular, we introduce a curriculum-style entropy minimization method to explore the implicit knowledge from the source model, which fits the trained source model to the target data using certain information from easy-to-hard predictions. We then train the segmentation network by the proposed complementary curriculum-style self-training, which utilizes the negative and positive pseudo labels following the curriculum-learning manner. Although negative pseudo-labels with high uncertainty cannot be identified with the correct labels, they can definitely indicate absent classes. Moreover, we employ an information propagation scheme to further reduce the intra-domain discrepancy within the target domain, which could act as a standard post-processing method for the domain adaptation field. Furthermore, we extend the proposed method to a more challenging black-box source model scenario where only the source model's predictions are available. Extensive experiments validate that our method yields state-of-the-art performance on source-free semantic segmentation tasks for both synthetic-to-real and adverse conditions datasets. The code and corresponding trained models are released at https://github.com/yxiwang/ATP.

Multiband Convolutional Riemannian Network with Band-wise Riemannian Triplet Loss for Motor Imagery Classification.

This paper presents a novel motor imagery classification algorithm that uses an overlapping multiscale multiband convolutional Riemannian network with band-wise Riemannian triplet loss to improve classification performance. Despite the superior performance of the Riemannian approach over the common spatial pattern filter approach, deep learning methods that generalize the Riemannian approach have received less attention. The proposed algorithm develops a state-of-the-art multiband Riemannian network that reduces the potential overfitting problem of Riemannian networks, a drawback of Riemannian networks due to their inherent large feature dimension from covariance matrix, by using fewer subbands with discriminative frequency diversity, by inserting convolutional layers before computing the subband covariance matrix, and by regularizing subband networks with Riemannian triplet loss. The proposed method is evaluated using the publicly available datasets, the BCI Competition IV dataset 2a and the OpenBMI dataset. The experimental results confirm that the proposed method improves performance, in particular achieving state-of-the-art classification accuracy among the currently studied Riemannian networks.

Predicting dynamic stability from static features in power grid models using machine learning.

A reliable supply with electric power is vital for our society. Transmission line failures are among the biggest threats for power grid stability as they may lead to a splitting of the grid into mutual asynchronous fragments. New conceptual methods are needed to assess system stability that complement existing simulation models. In this article, we propose a combination of network science metrics and machine learning models to predict the risk of desynchronization events. Network science provides metrics for essential properties of transmission lines such as their redundancy or centrality. Machine learning models perform inherent feature selection and, thus, reveal key factors that determine network robustness and vulnerability. As a case study, we train and test such models on simulated data from several synthetic test grids. We find that the integrated models are capable of predicting desynchronization events after line failures with an average precision greater than 0.996 when averaging over all datasets. Learning transfer between different datasets is generally possible, at a slight loss of prediction performance. Our results suggest that power grid desynchronization is essentially governed by only a few network metrics that quantify the networks' ability to reroute the flow without creating exceedingly high static line loadings.

Legal Culture as a Functional System

The whole process of the origin and development of human civilization and well-known historical facts give reason to believe that social processes in ancient society were accompanied not only by the accumulation of knowledge about the world around them, but also, more importantly, the emergence of a wider class of phenomena — the phenomenon of culture, which, with historical and modern expansive interpretation, covers both the spiritual and material spheres It represents the result of physical and spiritual creative activity of people. The phenomenon of culture has become the subject of research in the totality of not only social sciences and attracts the attention of researchers in various scientific fields. The existing multitude of theories and various definitions that reveal individual aspects, moments and sides of culture reflect the complexity and versatility of the phenomenon itself. This factor explains the lack of a generally accepted theory of culture and mutually agreed definitions in science. This situation in science is also caused by subjective moments, which boil down to the fact that the concept of culture denotes a variety of phenomena and objects. The ontological aspects of culture as a systemic phenomenon lead to important conclusions. Firstly, like any social phenomenon, culture appears as an unbalanced, open system in continuous information exchange with the external environment. Secondly, culture has an inherent feature of development due to the interaction between the components of the system and the external environment. Thirdly, culture is an organic system, where the components that make up it acquire additional new qualities so that the system as a whole has broader functional capabilities compared to a mechanistic system. Culture can be considered as a historically conditioned self-organizing system. Its components, being homogeneous, are combined into a whole around the core of culture. This core is represented by a set of certain basic phenomena — cultural universals. They are the ultimate foundations of culture as existing in a given historical epoch.

Conceptualising Extraterritoriality. Public International Law and Private International Law Considerations

Abstract The aim of this article is to analyse extraterritoriality from public international law and private international law perspectives. Although many scholars relate the exercise of extraterritorial jurisdiction to both private and public international law, in practice the topic is mainly considered as belonging to the latter. Moreover, extraterritorial jurisdiction is not a common notion under private international law. Perhaps because the extraterritorial norm is intended to regulate first and foremost state conduct and not relationships between private persons, but this vision does not take into account that the latter are frequently affected by the norm. It is argued here that from a public international law perspective, the legal framework of extraterritorial jurisdiction is unsettled and incomplete. The bottom line is that states are largely free to unfold their power, given that international law does not really regulate extraterritorial jurisdiction but only establishes the negative obligation not to trespass on state sovereignty. Thus, considering extraterritorial jurisdiction from a national perspective, in this paper, under the general framework of private international law is not only necessary but also justified. In addressing the above, this article will first analyse extraterritoriality as an exception under public international law (2). It will reflect on the lawful/unlawful grounds for the exercise of extraterritorial jurisdiction and will show that the abandonment of territoriality in jurisdictional assertions is more desirable than feasible. Then extraterritoriality will be analysed as an inherent feature of private international law, that can be traced in all three domains regulated by the private international law (3). It will also make a case on the extraterritorial reach of national constitutions.

MULTIFRACTAL CHARACTERISTICS OF THE MITOCHONDRIAL BK CHANNEL ACTIVITY IN THE PRESENCE OF THE CHANNEL-ACTIVATING FLAVONOIDS

Over the years, the (multi)fractal nature of signals describing the activity of ion channels has been observed both at the level of single-channel currents and the temporal scaling of the corresponding sojourns in conducting and non-conducting states. The recognized nonlinear and self-similar properties were interpreted regarding the underlying channel gating machinery. Nevertheless, the literature lacks in (multi)fractal description of the biochemical stimulation of ion channels. Therefore, in this work, we provide a multifractal description of the effects exerted by two different flavonoids — naringenin (Nar) and quercetin (Que) — being the regulators of the large-conductance voltage- and Ca[Formula: see text]-activated K[Formula: see text] channels from the inner mitochondrial membrane (mitoBK). Toward this aim, the focus-based multifractal detrended fluctuation analysis (MFDFA) was applied to the patch-clamp data obtained in the presence of Nar and Que in micromolar concentrations and the corresponding controls. Our results show that mitoBK channel activity has well-pronounced multifractal characteristics and long-range memory (measured by the generalized Hurst exponent) under biochemical stimulation by Nar and Que and in the absence of these substances. The spectral properties significantly change after the randomization of the analyzed series. Therefore, multifractality is an inherent feature of the mitoBK channel currents, which stems from their statistical distribution and temporal organization. Both flavonoids have similar structures and exert channel-activating effects, but they differently affect the parameters of the multifractal spectra of the corresponding patch-clamp signals. Coordination of Que leads to more prominent changes in signal complexity than Nar at membrane hyper- and depolarization. It suggests that this flavonoid has a stronger impact on the conformational dynamics of the mitoBK channels in comparison with naringenin.

CMFAN: Cross-Modal Feature Alignment Network for Few-Shot Single-View 3D Reconstruction.

Few-shot single-view 3D reconstruction learns to reconstruct the novel category objects based on a query image and a few support shapes. However, since the query image and the support shapes are of different modalities, there is an inherent feature misalignment problem damaging the reconstruction. Previous works in the literature do not consider this problem. To this end, we propose the cross-modal feature alignment network (CMFAN) with two novel techniques. One is a strategy for model pretraining, namely, cross-modal contrastive learning (CMCL), here the 2D images and 3D shapes of the same objects compose the positives, and those from different objects form the negatives. With CMCL, the model learns to embed the 2D and 3D modalities of the same object into a tight area in the feature space and push away those from different objects, thus effectively aligning the global cross-modal features. The other is cross-modal feature fusion (CMFF), which further aligns and fuses the local features. Specifically, it first re-represents the local features with the cross-attention operation, making the local features share more information. Then, CMFF generates a descriptor for the support features and attaches it to each local feature vector of the query image with dense concatenation. Moreover, CMFF can be applied to multilevel local features and brings further advantages. We conduct extensive experiments to evaluate the effectiveness of our designs, and CMFAN sets new state-of-the-art performance in all of the 1-/10-/25-shot tasks of ShapeNet and ModelNet datasets.

Strategies of consecutive interpretation in joint press conferences

This article deals with problems of interpretation of political discourse in joint press conference. Novelty of research is identified by the lack of domestic publications in the field of Translation studies on press conferences in the context of Kazakhstan’s foreign policy. Article examines characteristic features of consecutive interpretation of political media discourse. The need of effective strategies that help to provide adequate interpretation is identified and justified. On the basis of the study the authors suggest that backgroundknowledge on communicative situation enables interpreter to solve tasks caused by time deficiency and different semantic structures. It is proved that use of compression, decompression and re-ordering string in consecutive interpretation is key to reach communicative equivalence in target text. Results show that juxtaposition of strategies in one discursive segment illustrates that inherent cognitive feature of interpretation process. Article consists of literature review, methods of research, description and analyses of research material.