Integration Task Research Articles

Mechanical design and analysis of a reconfigurable variable stiffness mechanism based on permanent magnetic springs and swing guide mechanism

Stiffness control of an actuator is important to ensure stable contact motion and collision safety for human-robot integration tasks. The variable stiffness mechanism (VSM) is an important part of the variable stiffness actuator. We propose a novel reconfigurable rotational VSM that uses magnet springs and swing guide mechanisms in this paper. Magnet springs are used as elastic elements that are driven by the cable, and the initial stiffness of the mechanism can be regulated by adjusting the air gap distance between the magnets. The mathematical stiffness model of the VSM is developed, and the numerical calculation simulation and experiments are conducted to verify the feasibility of the proposed VSM.

Inefficient white matter activity in Schizophrenia evoked during intra and inter-hemispheric communication

Intensive cognitive tasks induce inefficient regional and network responses in schizophrenia (SCZ). fMRI-based studies have naturally focused on gray matter, but appropriately titrated visuo-motor integration tasks reliably activate inter- and intra-hemispheric white matter pathways. Such tasks can assess network inefficiency without demanding intensive cognitive effort. Here, we provide the first application of this framework to the study of white matter functional responses in SCZ. Event-related fMRI data were acquired from 28 patients (nine females, mean age 43.3, ±11.7) and 28 age- and gender-comparable controls (nine females, mean age 42.1 ± 10.1), using the Poffenberger paradigm, a rapid visual detection task used to induce intra- (ipsi-lateral visual and motor cortex) or inter-hemispheric (contra-lateral visual and motor cortex) transfer. fMRI data were pre- and post-processed to reliably isolate activations in white matter, using probabilistic tractography-based white matter tracts. For intra- and inter-hemispheric transfer conditions, SCZ evinced hyper-activations in longitudinal and transverse white matter tracts, with hyper-activation in sub-regions of the corpus callosum primarily observed during inter-hemispheric transfer. Evidence for the functional inefficiency of white matter was observed in conjunction with small (~50 ms) but significant increases in response times. Functional inefficiencies in SCZ are (1) observable in white matter, with the degree of inefficiency contextually related to task-conditions, and (2) are evoked by simple detection tasks without intense cognitive processing. These cumulative results while expanding our understanding of this dys-connection syndrome, also extend the search of biomarkers beyond the traditional realm of fMRI studies of gray matter.

지역사회 통합돌봄의 구현을 위한 법제적 과제

The new government is implementing Integrated Community Care as a national task in the field of health and welfare, and continuing the previous government's policy, materializing and its legalization is under way. Currently, two bills are pending in the National Assembly and the Ministry of Health and Welfare is drafting another bill, but jurists are not interested in them. The purpose of this article is to approach Integrated Community Care from a legal point of view and to present in what direction the affairs and organizations related to Integrated Community Care should be legislated and reorganized. First, I clarified the background and implications of the promotion of Integrated Community Care and defined the its legal concept as the basis of legislation. In addition to enacting a basic law and reorganizing individual laws as a legislative task for Integrated Community Care, I suggested the direction of legal reform in terms of the connection of integrated care affairs, organization, finance, and administrative plans. Furthermore, as legal tasks for integration and linkage, 1) integration and linkage of medical care and care, 2) improvement of legislation for connection with housing support, and 3) Establishment of Integrated Information System and Standardization of Information were presented. Finally, as community integration care entails a change in the social security system and may cause confusion in legal aspects, it was emphasized again that the state should promote legislation through close review not only in policy but also in related legislation.

Generating distant analogies facilitates relational integration: Intermediary role of relational mindset and cognitive load.

Relational integration is essential for learning, working, and living, as we must encode enormous volumes of information and extract their relations to construct knowledge about the environment. Recent research hints that generating distant analogies can temporarily facilitate learners’ state-based relational integration. This study aimed to investigate the internal mechanism underlying the facilitation effect and preliminarily confirm its application in education. First, we adopted the classical n-term premise integration task (Experiment 1a) and the Latin Square Task (Experiment 1b) to explore the robustness of the facilitation effect. Then we employed an emerging multidimensional relational reasoning task to further explore the internal mechanism underlying this facilitation effect (Experiment 2). Finally, we verified the practical role of the facilitation effect in learning the interaction concept in statistics (Experiment 3). The results showed that generating distant analogies did facilitate students’ relational integration performance, both in classical cognitive tasks and in a practical learning task, and a relational mindset and cognitive load play an intermediary role in the facilitation, supporting the cognitive load theory. The results suggest that generating distant analogies can be a useful warm-up activity to assist educators in promoting students’ relational integration.

Relative advantage and complexity: Predicting the rate of adoption of agricultural innovations

The adoption of new technologies and practices is fundamental to having the capacity to adapt to climate change and ameliorate resource degradation. Consequently, having the ability to predict the scale and rate of adoption by farmers of agricultural innovations is central to gauging their adaptive capacity. It is also crucial to assessing the likely compliance of farmers with change-seeking incentives and regulations. In this paper we describe a novel approach to predicting rates of adoption with respect to agricultural technologies and practices drawing on a dual-process model of consumer decision-making and a method for describing the complexity of innovations in farm systems. We tested the approach using data collected through a survey of dairy farmers in the Waikato and Waipa regions of New Zealand. In the survey we asked 200 farmers, chosen at random, about their perceptions of the complexity and relative advantage of various agricultural and resource management practices, and collected information as to how long it took them to try, and then adopt, the practices. Our results confirm that the process of forming an intention to try or adopt a technology or practice may take several months for relatively simple technologies and practices, and several years for more complex ones. Importantly, we found that novelty in terms of the originality in the components and architecture of a technology or practice does not necessarily correlate with its complexity in terms of integrating it into farm systems. This means that apparently simple technologies and practices that are promoted to reduce resource degradation can be quite difficult to integrate into farm systems and, as a consequence, the costs of integration may act as a strong deterrent to adopting them. A logical implication of our findings is that a deep understanding of the nature of the integration task is essential to anticipating how long it might take for adoption (or compliance) to occur in agriculture and, therefore, to appreciate limits on the adaptive capacity of farmers. Such an understanding requires an intimate knowledge of the, sometimes diverse, farm systems and sub-systems in which the technology or practice is to be integrated.

The relationships between computational and mathematical thinking: A review study on tasks

This review study synthesises the literature on how computational thinking (CT) and mathematical thinking (MT) are integrated into mathematics education research with a focus on tasks. A review of 28 relevant articles on the Web of Science Core Collection database indicated that (1) CT helps students develop and apply mathematical concepts and competence using software or programming; (2) MT helps students solve problems in CT, not necessarily including programming; (3) a reciprocal relationship between CT and MT embeds CT into mathematics learning, where CT is involved in problem-solving, and MT is developed to improve student performance on debugging or reflection; (4) tasks rarely involve creative thinking for creating computational artefacts in CT practices; and (5) tasks rarely involve critical thinking for constructing viable arguments and critiquing the reasoning of others in MT practices. Subsequently, features (including relationship, entry, and what to do) of tasks for integration between CT and MT are proposed.

Event-Related Potential Assessment of Visual Perception Abnormality in Patients With Obstructive Sleep Apnea: A Preliminary Study

This study investigated the effect of obstructive sleep apnea (OSA) on the neural mechanism of visual perception. A preliminary case-control study was conducted. Seventeen patients with moderate to severe OSA in the sleep center of Civil Aviation General Hospital and 20 healthy controls matched for age, sex, and education were recruited. The participants accepted the perceptual contour integration task, compared the differences in behavioral indicators between the two groups, and compared the differences in electroencephalography (EEG) data between the two groups through event-related potential (ERP) technology. The groups did not differ significantly in age and gender, but they differed significantly in body mass index (BMI) (OSA higher than healthy controls, p < 0.05). The groups were not statistically different in terms of sleep structure and total sleep time. AHI, sleep efficiency, and minimal SaO2 value in the OSA group were significantly different from those of the control group. The results showed that the average reaction time of the OSA group was significantly longer than that of the healthy control group in the contour integration task. There was no significant difference in the accuracy rate. The results of EEG showed that the amplitudes of N100 of the OSA group were significantly higher than those of the control group at O1, Oz, and O2 electrodes. There was no significant difference in latency between the two groups. At the FCz electrode, the amplitudes of N200 of the OSA group were significantly higher than those of the control group. Therefore, we concluded that in the early stage of the perceptual integration task, although the neural response activity of patients with moderate and severe OSA was not accelerated, they need to call on more psychological resources, activate more neurons in the contour global recognition processing stage, and the compensatory effect of frontal lobe appeared in the stage of visual perception.

Can you hear/see me? Multisensory integration of signals does not always facilitate mate choice

Abstract Females of many species choose mates using multiple sensory modalities. Multimodal noise may arise, however, in dense aggregations of animals communicating via multiple sensory modalities. Some evidence suggests multimodal signals may not always improve receiver decision-making performance. When sensory systems process input from multimodal signal sources, multimodal noise may arise and potentially complicate decision-making due to the demands on cognitive integration tasks. We tested female túngara frog, Physalaemus (=Engystomops) pustulosus, responses to male mating signals in noise from multiple sensory modalities (acoustic and visual). Noise treatments were partitioned into three categories: acoustic, visual, and multimodal. We used natural calls from conspecifics and heterospecifics for acoustic noise. Robotic frogs were employed as either visual signal components (synchronous vocal sac inflation with call) or visual noise (asynchronous vocal sac inflation with call). Females expressed a preference for the typically more attractive call in the presence of unimodal noise. However, during multimodal signal and noise treatments (robofrogs employed with background noise), females failed to express a preference for the typically attractive call in the presence of conspecific chorus noise. We found that social context and temporal synchrony of multimodal signaling components are important for multimodal communication. Our results demonstrate that multimodal signals have the potential to increase the complexity of the sensory scene and reduce the efficacy of female decision making.

Executive Functions and Rapid Automatized Naming: A New Tele-Rehabilitation Approach in Children with Language and Learning Disorders.

Executive function deficits are documented in many neurodevelopmental disorders and may contribute to clinical complexity or rehabilitation resilience. The present research was primarily aimed at presenting and evaluating the feasibility and effectiveness of a telerehabilitation program used during the pandemic period. MemoRAN (Anastasis), a computerised cognitive training to improve executive control during visual-verbal integration tasks was used in a sample of 42 children (5–11 years old) with specific learning or language disorders. The MemoRAN training was based on exercises of inhibition, cognitive flexibility and updating in working memory for three months, with a frequency of approximately three sessions per week. Afterwards, a comparison between a subgroup of children using Memo-RAN and an active control group, using a tele-rehabilitation program directed on reading was conducted. Effect size analysis in pre-post measurements suggests an average effect of MemoRAN in measurements that require control processes, such as accuracy in dictation, reading, inhibition and working memory testing. Comparison with the active control group and the clinical utility implications of these types of treatment will be discussed.

Relational integration predicted numerical inductive reasoning: ERP Evidence from the N400 and LNC.

As relational integration performance can be used to predict reasoning ability, the present study aimed to provide electrophysiological evidence for numerical inductive reasoning. Number series with two levels of relational complexity were utilized, including simple and hierarchical problems (such as "15-16-17" versus "15-16-18"). Two tasks were adopted: a relational integration task that required to determine whether the numerical relations were changed across numbers; a number series task that required to determine whether a hidden rule was acquired (Experiment 1) or to predict the subsequent number (Experiment 2), whose phases were divided as rule searching, rule discovery, and rule following. The event-related potential (ERP) results of both experiments indicated that, in contrast to simple problems, hierarchical problems triggered enhanced N400 and late negative component (LNC), reflecting numerical fact retrieval, and generalizing novel hypotheses about the hidden rules by integrating adjacent numerical relations, respectively; relational integration showed similar N400 and LNC activation patterns to rule discovery (Experiment 1) or rule searching (Experiment 2). Additionally, the N400 and LNC elicited by relational integration showed strong positive correlations and even were able to predict the ones triggered by rule discovery (Experiment 1) or rule searching (Experiment 2). Therefore, the results supported the role of relational integration in numerical inductive reasoning and thereby in intelligence.

Automatic Speech Recognition Training Software for Joint Terminal Attack Controller Close Air Support Requests

Close air support (CAS) is a crucial element of joint fire support that requires intricate planning, coordination, and training of various ground and supporting air forces for safe and effective execution. Based on the nature of the target and the availability of additional fire support, synchronizing CAS in time, space, and purpose with supported ground forces is one of the most detailed and continuous integration tasks performed in concert by the joint force, component commanders, and staffs (Joint Publication, 2014). Using SpeechZero, a novel interface that allows non-expert users to customize Automated Speech Recognition (ASR) systems for Department of Defense training applications, SoarTech is creating a training software for Joint Terminal Attack Controller (JTAC) CAS requests. These requests follow a structured verbal protocol called a 9-line. The training software utilizes ASR and generation, which allows trainees to practice verbal communication skills in representative training environments without the need for human role players. However, these technologies have yet to become a feature of most training systems. Using SoarTech’s SpeechZero ASR software, an individual speaks their 9-line request into a tablet or smartphone which will parse the speech and use AI algorithms to categorize it within the 9-line framework. The utilization of this software for CAS 9-line requests has the potential to produce more effective training and documentation of CAS events which is critical in ensuring the safety of civilians and friendly forces alike.&#x0D; References&#x0D; Joint Publication (JP) 3-09.3. Close Air Support, 25 November 2014.

Generalized supervised meta-blocking

Entity Resolution is a core data integration task that relies on Blocking to scale to large datasets. Schema-agnostic blocking achieves very high recall, requires no domain knowledge and applies to data of any structuredness and schema heterogeneity. This comes at the cost of many irrelevant candidate pairs (i.e., comparisons), which can be significantly reduced by Meta-blocking techniques that leverage the entity co-occurrence patterns inside blocks: first, pairs of candidate entities are weighted in proportion to their matching likelihood, and then, pruning discards the pairs with the lowest scores. Supervised Meta-blocking goes beyond this approach by combining multiple scores per comparison into a feature vector that is fed to a binary classifier. By using probabilistic classifiers, Generalized Supervised Meta-blocking associates every pair of candidates with a score that can be used by any pruning algorithm. For higher effectiveness, new weighting schemes are examined as features. Through extensive experiments, we identify the best pruning algorithms, their optimal sets of features, as well as the minimum possible size of the training set.

Open data and model integration through generic model agent toolkit in CyberWater framework

The CyberWater project is created to develop an open data and open model integration framework for studying complex environmental and water problems, where diverse online data sources can be directly accessed by diverse models without any need of users’ extra effort on the tedious tasks of data preparation for their models. We present our design and development of a novel generic model agent toolkit in the context of CyberWater, which enables users to integrate their models into the CyberWater system without writing any new code, significantly simplifying the data and model integration task. CyberWater adopts a visual scientific workflow system, VisTrails, which also supports provenance and reproducible computing. Our approach and the developed generic model agent toolkit are demonstrated, via CyberWater framework, with automated and flexible workflows through integrating data and models using real-world use cases. Two popular hydrological models, VIC and DHSVM, are used for illustrations.

Role of Digital Skills in Refugee Integration

Two concurrent 21st-century phenomena—the nearly unprecedented number of forced migrants and the near ubiquity of information and communications technology—have given rise to increased scholarship in “digital migration studies.” One area of investigation in this emergent interdisciplinary field is the role of digital skills in refugee integration. Given the accelerated global reliance on technology resulting from the COVID-19 pandemic, the author conducted a state-of-the-art literature review to identify emerging issues and highlight research needs in this area. A search of 10 databases yielded 39 studies spanning the major resettlement regions (North America, Western Europe, Oceania), and including refugees from across the globe. The inclusion criteria were studies focused on refugees’ practical use of digital technology in integration, published from January 2020-April 2021. Exclusion criteria were studies on refugees in transit or protracted displacement, digital connectivity and accessibility, use of digital technology by humanitarian actors, software development, analyses of digital representations of refugees, public attitudes toward refugees as expressed in digital media, and literature reviews. Ndofor-Tah et al.’s (2019) Refugee Integration Framework was used to organize and synthesize the findings. The studies demonstrated how digital skills affect all domains of integration. Additionally, the studies confirm that many refugees in resettlement have limited digital skills for necessary integration tasks, such as navigating websites and assessing the credibility of online information. Limitations of this state-of-the-art review include its cross-sectional nature, having only one reviewer, and only published literature accessible online through public websites or subscription databases. An important emerging issue for future research is assessing, teaching, and learning digital skills among this population. The study's contributions to the knowledge base and theory, and its implications for information science scholars and practitioners and those in allied disciplines within digital migration studies, are discussed.

Whether attentional loads influence audiovisual integration depends on semantic associations.

Neuronal studies have shown that selectively attending to a common object in one sensory modality results in facilitated processing of that object's representations in the ignored sensory modality. Thus, the audiovisual (AV) integration of common objects can be observed under modality-specific selective attention. However, little is known about whether this AV integration can also occur under increased attentional load conditions. Additionally, whether semantic associations between multisensory features of common objects modulate the influence of increased attentional loads on this cross-modal integration remains unknown. In the present study, participants completed an AV integration task (ignored auditory stimuli) under various attentional load conditions: no load, low load, and high load. The semantic associations between AV stimuli were composed of animal pictures presented concurrently with semantically congruent, semantically incongruent, or semantically unrelated auditory stimuli. Our results demonstrated that attentional loads did not disrupt the integration of semantically congruent AV stimuli but suppressed the potential alertness effects induced by incongruent or unrelated auditory stimuli under the condition of modality-specific selective attention. These findings highlight the critical role of semantic association between AV stimuli in modulating the effect of attentional loads on the AV integration of modality-specific selective attention.

Multiomics Topic Modeling for Breast Cancer Classification.

Simple SummaryTopic models are algorithms introduced for discovering hidden topics or latent variables in large, unstructured text corpora. Leveraging on analogies between texts and gene expression profiles, these algorithms can be used to find structures in expression data. This work presents an application of topic modeling techniques for the identification of breast cancer subtypes. In particular, we extended a specific class of topic models to allow a multiomics approach. As an illustrative example, considering both messenger RNA and microRNA expression levels, we were able to clearly distinguish healthy from tumor samples as well as the different breast cancer subtypes. The integration of different layers of information is crucial for the observed classification accuracy. Our approach naturally provides the genes and the microRNAs associated to the specific topics that are used for sample organization. We show that indeed these topics often contain genes involved in breast cancer development and are associated to different survival probabilities.The integration of transcriptional data with other layers of information, such as the post-transcriptional regulation mediated by microRNAs, can be crucial to identify the driver genes and the subtypes of complex and heterogeneous diseases such as cancer. This paper presents an approach based on topic modeling to accomplish this integration task. More specifically, we show how an algorithm based on a hierarchical version of stochastic block modeling can be naturally extended to integrate any combination of ’omics data. We test this approach on breast cancer samples from the TCGA database, integrating data on messenger RNA, microRNAs, and copy number variations. We show that the inclusion of the microRNA layer significantly improves the accuracy of subtype classification. Moreover, some of the hidden structures or “topics” that the algorithm extracts actually correspond to genes and microRNAs involved in breast cancer development and are associated to the survival probability.

Disruption of the grid cell network in a mouse model of early Alzheimer\u2019s disease

Early-onset familial Alzheimer’s disease (AD) is marked by an aggressive buildup of amyloid beta (Aβ) proteins, yet the neural circuit operations impacted during the initial stages of Aβ pathogenesis remain elusive. Here, we report a coding impairment of the medial entorhinal cortex (MEC) grid cell network in the J20 transgenic mouse model of familial AD that over-expresses Aβ throughout the hippocampus and entorhinal cortex. Grid cells showed reduced spatial periodicity, spatial stability, and synchrony with interneurons and head-direction cells. In contrast, the spatial coding of non-grid cells within the MEC, and place cells within the hippocampus, remained intact. Grid cell deficits emerged at the earliest incidence of Aβ fibril deposition and coincided with impaired spatial memory performance in a path integration task. These results demonstrate that widespread Aβ-mediated damage to the entorhinal-hippocampal circuit results in an early impairment of the entorhinal grid cell network.

Ukraine’s European Integration in the Context of War

The relevance of the study is due to the need to conduct an investigation of the conditions, features, and prospects of Ukraine’s European integration during the war, and an examination of the status of a candidate country for EU membership, granted to it on June 23, 2022. The purpose of the study is to establish the conditions and features of Ukraine’s European integration in the context of the war and the problems and requirements that arise on the way to EU membership. Within the framework of the study, the following methods were used: dialectical, historical, and hermeneutical, formal-legal, legal-cognitive, logical, induction and deduction, modelling and system analysis, axiomatic etc. The results of the study are the definition of the main concepts and terms, namely: “European Union”, “European integration”, “status of a candidate for EU membership”; the features and purpose of the activities of European Union are established; the analysis of the European integration process of Ukraine during all the years of its independence is investigated and analysed; the achievements that Ukraine has already accomplished in cooperation with the European Union are clarified; the existing problems and obstacles to joining the European Union are established; the analysis of the features of Ukraine’s European integration in the conditions of war is conducted; the features of the status of a candidate for membership in the European Union is investigated and established; the prospects and advantages that arise in connection with granting Ukraine the status of a candidate country for membership are established; the tasks and conditions that Ukraine must fulfill to join the EU are investigated and clarified; the experience of countries that have joined the European Union is analysed. The provisions in the study are of practical value primarily for the authorities and authorised persons, whose duties include conducting reforms and performing tasks for European integration of Ukraine

Solving certain integration tasks in forensic handwriting analysis

Economic system reforms and corresponding crime evolution in recent years have determined relevance of further theoretical development of diagnostic issues of handwriting research. Due to significant expansion of scientific knowledge boundaries about the laws of writing and methods of forensic examination of handwriting objects, current state of forensic handwriting examination allows to solve a wide range of issues of identification and diagnostic nature.&#x0D; The aim of the authors was to demonstrate complexity of handwriting diagnostic research of signaturehandwriting, constant importance of such examinations for the practice of judicial and investigative bodies of Ukraine. This publication is devoted to modern issues of research of the handwriting realizations performed through changed movements and the decision of identification and diagnostic tasks on such objects.&#x0D; The main provisions of forensic handwriting theory on research on handwriting objects made by altered movements, mainly due to confusing factors of natural character. Examples from forensic practice of National Scientific Center «Hon. Prof. M. S. Bokarius Forensic Science Institute» (Kharkov, Ukraine). The research proved possibility of solving integration tasks of forensic handwriting analysis of the above handwriting realizations.&#x0D; The following methods: dialectical, empirical research, system-structural analysis and synthesis, observation, comparison, qualitative-descriptive, graphic, experiment and modeling ones were used to consider asked questions.

Benchmarking atlas-level data integration in single-cell genomics

Single-cell atlases often include samples that span locations, laboratories and conditions, leading to complex, nested batch effects in data. Thus, joint analysis of atlas datasets requires reliable data integration. To guide integration method choice, we benchmarked 68 method and preprocessing combinations on 85 batches of gene expression, chromatin accessibility and simulation data from 23 publications, altogether representing >1.2 million cells distributed in 13 atlas-level integration tasks. We evaluated methods according to scalability, usability and their ability to remove batch effects while retaining biological variation using 14 evaluation metrics. We show that highly variable gene selection improves the performance of data integration methods, whereas scaling pushes methods to prioritize batch removal over conservation of biological variation. Overall, scANVI, Scanorama, scVI and scGen perform well, particularly on complex integration tasks, while single-cell ATAC-sequencing integration performance is strongly affected by choice of feature space. Our freely available Python module and benchmarking pipeline can identify optimal data integration methods for new data, benchmark new methods and improve method development.