Modulating effects of interactional contexts on bilinguals’ cognitive control: Evidence for the Adaptive Control Hypothesis

AIMS & OBJECTS: The Adaptive Control Hypothesis (ACH) proposed that different interactional contexts place different demands on cognitive processes for bilinguals. However, how cognitive control processes dynamically adapt to comprehending and producing languages in different interactional contexts is still poorly understood. This study investigated how different language interactional contexts (i.e., single-language, dual-language, and dense code-switching) modulate cognitive control in bilingual language comprehension. METHODOLOGY:Inhibitory control in 36 Chinese -English bilinguals was examined through flanker tasks. Participants’ language and cognitive control statuses in the three interactional contexts were manipulated through three different types of dialogue-listening. After they listened to each type of dialogue, they were instructed to complete the flanker task and answer 10 comprehension questions related to the dialogue. DATA AND ANALYSIS: Repeated-measures analysis of variance (ANOVA) compared participants’ reaction times and response accuracy in flanker tasks across the three interactional contexts. Similarly, their language comprehension performances across different interactional contexts were also compared. FINDING/CONCLUSIONS: Both the dual-language and Chinese single-language contexts showed significant facilitatory effects on participants’ inhibitory control efficiency. Furthermore, participants performed more accurately on answering comprehension questions in the Chinese single-language context, indicating the dominant language effects on modulating bilinguals’ language comprehension performance. Such effects were not found in the dense code-switching and dual-language contexts. ORIGINALITY: This study provided empirical evidence for the facilitatory effects of dual-language contexts on cognitive control in bilingual language comprehension process, which further extends the ACH to bilingual’s cognitive process associated with language comprehension. SIGNIFICANCE/IMPLICATIONS: In general, it is an attempt to explore the associations between interactional contexts and cognitive control through bilingual language and cognitive processing manipulations

The effects of habitual code-switching in bilingual language production on cognitive control

This study explored how bilingual code-switching habits affect cognitive shifting and inhibition. Habitual code-switching from 31 Mandarin–English bilingual adults were collected through the Language and Social Background Questionnaire (Anderson, Mak, Keyvani Chahi & Bialystok, 2018) and the Bilingual Switching Questionnaire (Rodriguez-Fornells, Krämer, Lorenzo-Seva, Festman & Münte, 2012). All participants performed verbal and nonverbal switching tasks, including the verbal fluency task, a bilingual picture-naming and colour-shape switching task. A Go/No-go task was administered to measure the inhibitory control of participants. Frequent bilingual switchers showed higher efficiency in both English to Chinese verbal switching and nonverbal cognitive shifting. Additionally, bilinguals with intensive dense code-switching experience outperformed in the Go/No-go task. In general, the study revealed the connections between bilinguals’ intensity of single-language context experience and goal maintenance efficiency, which partially supported the Adaptive Control Hypothesis’ prediction (Green & Abutalebi, 2013). Besides, it also indicated the facilitations of bilinguals’ dense code-switching experience on their conflicts monitoring and response inhibition

On the Performance Trade-off of Distributed Integrated Sensing and Communication Networks

In this letter, we analyze the performance trade-off in distributed integrated sensing and communication (ISAC) networks. Specifically, with the aid of stochastic geometry theory, we derive the probability of detection of that of the coverage given user number. Based on the analytical derivations, we provide a quantitative description of the performance limits and the performance trade-off between sensing and communication in a distributed ISAC network under the given transmit power and bandwidth budget. Extensive simulations are conducted and the numerical results validate the accuracy of our derivations

DAT++: Spatially Dynamic Vision Transformer with Deformable Attention

Transformers have shown superior performance on various vision tasks. Their large receptive field endows Transformer models with higher representation power than their CNN counterparts. Nevertheless, simply enlarging the receptive field also raises several concerns. On the one hand, using dense attention in ViT leads to excessive memory and computational cost, and features can be influenced by irrelevant parts that are beyond the region of interests. On the other hand, the handcrafted attention adopted in PVT or Swin Transformer is data agnostic and may limit the ability to model long-range relations. To solve this dilemma, we propose a novel deformable multi-head attention module, where the positions of key and value pairs in self-attention are adaptively allocated in a data-dependent way. This flexible scheme enables the proposed deformable attention to dynamically focus on relevant regions while maintains the representation power of global attention. On this basis, we present Deformable Attention Transformer (DAT), a general vision backbone efficient and effective for visual recognition. We further build an enhanced version DAT++. Extensive experiments show that our DAT++ achieves state-of-the-art results on various visual recognition benchmarks, with 85.9% ImageNet accuracy, 54.5 and 47.0 MS-COCO instance segmentation mAP, and 51.5 ADE20K semantic segmentation mIoU.Comment: 17 pages, 6 figures, 11 table

Is Blockchain for Internet of Medical Things a Panacea for COVID-19 Pandemic?

The outbreak of the COVID-19 pandemic has deeply influenced the lifestyle of the general public and the healthcare system of the society. As a promising approach to address the emerging challenges caused by the epidemic of infectious diseases like COVID-19, Internet of Medical Things (IoMT) deployed in hospitals, clinics, and healthcare centers can save the diagnosis time and improve the efficiency of medical resources though privacy and security concerns of IoMT stall the wide adoption. In order to tackle the privacy, security, and interoperability issues of IoMT, we propose a framework of blockchain-enabled IoMT by introducing blockchain to incumbent IoMT systems. In this paper, we review the benefits of this architecture and illustrate the opportunities brought by blockchain-enabled IoMT. We also provide use cases of blockchain-enabled IoMT on fighting against the COVID-19 pandemic, including the prevention of infectious diseases, location sharing and contact tracing, and the supply chain of injectable medicines. We also outline future work in this area.Comment: 15 pages, 8 figure

Ameliorative effects on osteoporosis of small extracellular vesicles derived from bone marrow mesenchymal stem cells

Objective·To investigate the effects of small extracellular vesicles (sEVs) derived from human bone marrow mesenchymal stem cells (BMSCs) on the regulation of osteoclast differentiation and macrophage polarization in mice, and mouse model of osteoporosis.Methods·BMSCs were cultured and sEVs were isolated through differential centrifugation. The isolated sEVs were identified by transmission electron microscopy (TEM) and nanoparticle tracking analysis (NTA). RAW264.7 cells were cultured and stimulated with macrophage colony-stimulating factor (M-CSF) and receptor activator of nuclear factor-κB ligand (RANKL) to differentiate the cells into osteoclasts. Tartrate-resistant acid phosphatase (TRAP) staining and phalloidin staining were performed to assess the effect of sEVs on osteoclast formation. The expression levels of osteoclast marker genes, i.e., cAMP-response element binding protein (CREB), cathepsin K (CTSK), and Jun proto-oncogene (c-Jun) were examined by real-time quantitative PCR. To polarize RAW264.7 cells to M1 phenotype, they were cultured with lipopolysaccharides; to polarize them to M2 phenotype, they were cultured with interleukin-4 (IL-4) and IL-13. Flow cytometry was performed to detect the effect of sEVs on macrophage polarization. Micro-computed tomography (micro-CT) and TRAP staining were performed to investigate the effect of sEVs on the bone tissues of lumbar vertebrae in osteoporosis mouse models.Results·TEM and NTA demonstrated that the isolated sEVs had a typical globular structure with a diameter ranging from 30‒150 nm. TRAP staining and phalloidin staining showed that BMSC-derived sEVs inhibited the fusion of RAW264.7 cells to form osteoblasts. PCR revealed that sEVs could decrease the expression of CREB, CTSK, and c-Jun (all P<0.05). Flow cytometry analysis indicated that BMSC-derived sEVs inhibited RAW264.7 macrophages polarization to M1 phenotype and induced RAW264.7 macrophages polarization to M2 phenotype. Micro-CT indicated that the number of trabeculae and the bone volume fraction of lumbar vertebrae were significantly higher in the sEV-intervened group than those in the control group (both P<0.05). TRAP staining revealed a reduction of osteoclast number in the lumbar vertebrae after intervention with sEVs.Conclusion·The sEVs from human BMSCs can delay bone loss in osteoporosis mice, which may be related to its effects of inhibiting osteoclast differentiation and promoting the polarization of M2 type macrophages

The Double-Edged Sword of Input Perturbations to Robust Accurate Fairness

Deep neural networks (DNNs) are known to be sensitive to adversarial input perturbations, leading to a reduction in either prediction accuracy or individual fairness. To jointly characterize the susceptibility of prediction accuracy and individual fairness to adversarial perturbations, we introduce a novel robustness definition termed robust accurate fairness. Informally, robust accurate fairness requires that predictions for an instance and its similar counterparts consistently align with the ground truth when subjected to input perturbations. We propose an adversarial attack approach dubbed RAFair to expose false or biased adversarial defects in DNN, which either deceive accuracy or compromise individual fairness. Then, we show that such adversarial instances can be effectively addressed by carefully designed benign perturbations, correcting their predictions to be accurate and fair. Our work explores the double-edged sword of input perturbations to robust accurate fairness in DNN and the potential of using benign perturbations to correct adversarial instances

Modulating effects of interactional contexts on bilinguals’ cognitive control: Evidence for the Adaptive Control Hypothesis

Aims and Objects: The Adaptive Control Hypothesis (ACH) proposed that different interactional contexts place different demands on cognitive processes for bilinguals. However, how cognitive control processes dynamically adapt to comprehending and producing languages in different interactional contexts is still poorly understood. This study investigated how different language interactional contexts (i.e., single-language, dual-language, and dense code-switching) modulate cognitive control in bilingual language comprehension. Methodology: Inhibitory control in 36 Chinese -English bilinguals was examined through flanker tasks. Participants’ language and cognitive control statuses in the three interactional contexts were manipulated through three different types of dialogue-listening. After they listened to each type of dialogue, they were instructed to complete the flanker task and answer 10 comprehension questions related to the dialogue. Data and analysis: Repeated-measures analysis of variance (ANOVA) compared participants’ reaction times and response accuracy in flanker tasks across the three interactional contexts. Similarly, their language comprehension performances across different interactional contexts were also compared. Findings/conclusions: Both the dual-language and Chinese single-language contexts showed significant facilitatory effects on participants’ inhibitory control efficiency. Furthermore, participants performed more accurately on answering comprehension questions in the Chinese single-language context, indicating the dominant language effects on modulating bilinguals’ language comprehension performance. Such effects were not found in the dense code-switching and dual-language contexts. Originality: This study provided empirical evidence for the facilitatory effects of dual-language contexts on cognitive control in bilingual language comprehension process, which further extends the ACH to bilingual’s cognitive process associated with language comprehension. Significance/implications: In general, it is an attempt to explore the associations between interactional contexts and cognitive control through bilingual language and cognitive processing manipulations

Modulating bilingual language production and cognitive control: how bilingual language experience matters

The Adaptive Control Hypothesis and the Control Process Model propose that bilingual language use in different interactional contexts requires control processes that can adapt in different ways to linguistic demands. This study explored the effects of language experience on cognitive flexibility and inhibition among 41 Chinese–English bilingual adults. In particular, it aimed to investigate the relationship between spontaneous language production (i.e., bilingual conversation and narration tasks) and cognitive control. Participants’ inhibitory control and cognitive flexibility efficiency was measured through verbal and spatial Stroop tasks, and a colour-shape switching task. Overall, it showed that frequent practices of intersentential switching in speech production resulted in significant facilitatory effects in both verbal and nonverbal inhibitory control. This study provides new evidence for the importance of bilingual language experience in adaptive cognitive control in naturalistic speech production and furthers our theoretical knowledge of the relationship between the language system and crucial domain-general cognitive processes