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Achieving global climate change mitigation targets requires low-carbon production in agriculture. In such an endeavor, a new classification of climate-adaptive technology is defined to affect agriculture towards the low-carbon direction, but such an impact has seldom been empirically tested in the literature. In this paper, we investigate the impact of climate-adaptive technological innovation on agricultural carbon efficiency, a proxy for low-carbon agriculture. We use a stochastic directional distance function framework and a cross-country dataset covering 38 OECD countries. Additionally, we test the heterogeneous impact, considering that regional economic development is a crucial condition for deploying advanced technologies. The findings show that climate-adaptive technological innovation can promote carbon efficiency in agriculture, and this aggregate effect hides significant heterogeneity at different levels of economic development. The higher the economic development level is, the better climate-adaptive technological innovation contributes to improving agricultural carbon efficiency. Then, related policy implications are set forth.

Telehealth technology can create a disruptive communication environment for frontline care providers who mediate virtual communication with specialists in electronic consultations. As providers are dealing with various technology features when communicating with specialists, their flexible attitude and behaviors to use various telehealth-related technology features can change the outcome of virtual care service. The objective of this study is to examine frontline care providers' technology adaptation behaviors in the electronic consultation context. From the perspective of frontline care providers, we reapply and retest a theoretical model, reflecting a mechanism through which technology users' personal characteristics and technology adaptation behavior enhance virtual service performance, which is an important performance enabler in this online meeting context. In provider-to-provider communication, particularly, we explore the association among providers' information technology (IT)-related personal characteristics, adaptive telehealth technology use, and virtual service performance. An online survey was administered to collect individual providers' personal traits, IT adaptation, and perception on virtual service performance. Partial least squares-structural equation modeling was used to estimate our predictive model of personal traits-IT adaptation, such as exploitative use (use the telehealth technology in a standard way), and exploratory use (use the telehealth technology as innovative way)-and virtual service performance. We collected 147 responses from graduate nursing students who were training to be nurse practitioners in their master's program, resulting in 121 valid responses from the cross-section online survey. Our theoretical model explained 60.0% of the variance in exploitative use of telehealth technology, 44% of the variance in exploratory use of telehealth technology, and 66% of the variance in virtual service performance. We found that exploitative IT use is an important driver to increase virtual service performance (β=0.762, P<.001), and personal characteristics such as habit are positively associated with both exploitative (β=0.293, P=.008) and exploratory use behaviors (β=0.414, P=.006), while computer self-efficacy is positively associated with exploitative use of telehealth technology (β=0.311, P=.047). This study discusses the unique role of frontline care providers in a virtual care service context and highlights the importance of their telehealth adaptation behavior in provider-to-provider communication. We showed that providers perceive that telehealth technologies should function as intended, otherwise it may create frustration or avoidance of the telehealth technology. Moreover, providers' habitual use of various technologies in daily lives also motivates them to adaptively use telehealth technology for improving virtual care service. Understanding providers' technology habit and adaptation can inform health care policy and further provide a better view of the design of telehealth technology for online communication.

This systematic review of research on adaptive learning used a strategic search process to synthesize research on adaptive learning based on publication trends, instructional context, research methodology components, research focus, adaptive strategies, and technologies. A total of 61 articles on adaptive learning were analyzed to describe the current state of research and identify gaps in the literature. Descriptive characteristics were recorded, including publication patterns, instructional context, and research methodology components. The count of adaptive learning articles published fluctuated across the decade and peaked in 2015. During this time, the largest concentration of adaptive learning articles appeared in Computers and Education. The majority of the studies occurred in higher education in Taiwan and the United States, with the highest concentration in the computer science discipline. The research focus, adaptive strategies, and adaptive technologies used in these studies were also reviewed. The research was aligned with various instructional design phases, with more studies examining design and development, and implementation and evaluation. For examining adaptive strategies, the authors examined both adaptive sources based on learner model and adaptive targets based on content and instructional model. Learning style was the most observed learner characteristic, while adaptive feedback and adaptive navigation were the most investigated adaptive targets. This study has implications for adaptive learning designers and future researchers regarding the gaps in adaptive learning research. Future studies might focus on the increasing availability and capacities of adaptive learning as a learning technology to assist individual learning and personalized growth.

With the rapid development of industrial manufacturing, bearing defect detection has become a key link to ensure the safe operation of equipment and improve production efficiency. Aiming at the problems of low accuracy and large parameters of traditional bearing defect detection models, this paper proposes a lightweight bearing defect detection method based on collaborative attention and domain adaptive technology. Firstly, the collaborative attention mechanism uses multiple parallel attention heads to extract the features of different regions in the image respectively. Each attention head can independently extract and weigh the features of specific regions, which can capture the complex features of bearing defects more comprehensively, including shape, texture, edge and other key information. At the same time, the domain adaptation technology aims to make the model adapt to the data distribution of different domains. It reduces the difference between the source domain and the object domain by aligning the feature distribution between the source domain and the object domain during the training process, thereby improving the performance of the model on the object domain. The experimental results show that the proposed method is 2.75% higher than the mAP@0.5 of YOLOv7, and has higher computational efficiency and better generalization ability than the traditional method.

Quantifying the functional relations between the nodes in a network based on local observations is a key challenge in studying complex systems. Most existing time series analysis techniques for this purpose provide static estimates of the network properties, pertain to stationary Gaussian data, or do not take into account the ubiquitous sparsity in the underlying functional networks. When applied to spike recordings from neuronal ensembles undergoing rapid task-dependent dynamics, they thus hinder a precise statistical characterization of the dynamic neuronal functional networks underlying adaptive behavior. We develop a dynamic estimation and inference paradigm for extracting functional neuronal network dynamics in the sense of Granger, by integrating techniques from adaptive filtering, compressed sensing, point process theory, and high-dimensional statistics. We demonstrate the utility of our proposed paradigm through theoretical analysis, algorithm development, and application to synthetic and real data. Application of our techniques to two-photon Ca2+ imaging experiments from the mouse auditory cortex reveals unique features of the functional neuronal network structures underlying spontaneous activity at unprecedented spatiotemporal resolution. Our analysis of simultaneous recordings from the ferret auditory and prefrontal cortical areas suggests evidence for the role of rapid top-down and bottom-up functional dynamics across these areas involved in robust attentive behavior.

The commitment to increase the inclusion of students with disabilities has ensured that the concept of Assistive Technology (AT) has become increasingly widespread in education. The main objective of this paper focuses on conducting a systematic review of studies regarding the impact of Assistive Technology for the inclusion of students with disabilities. In order to achieve the above, a review of relevant empirical studies published between 2009 and 2020 in four databases (Web of Science (WoS), Scopus, ERIC and PsycINFO) was carried out. The sample consists of 31 articles that met the inclusion criteria of this review, out of a total of 216 identified. Findings of this study include that the use of Assistive Technologies is successful in increasing the inclusion and accessibility of students with disabilities, although barriers such as teacher education, lack of information or accessibility are found.

Humans interact with computers through various devices. Such interactions may not require any physical movement, thus aiding people with severe motor disabilities in communicating with external devices. The brain–computer interface (BCI) has turned into a field involving new elements for assistive and rehabilitative technologies. This systematic literature review (SLR) aims to help BCI investigator and investors to decide which devices to select or which studies to support based on the current market examination. This examination of noninvasive EEG devices is based on published BCI studies in different research areas. In this SLR, the research area of noninvasive BCIs using electroencephalography (EEG) was analyzed by examining the types of equipment used for assistive, adaptive, and rehabilitative BCIs. For this SLR, candidate studies were selected from the IEEE digital library, PubMed, Scopus, and ScienceDirect. The inclusion criteria (IC) were limited to studies focusing on applications and devices of the BCI technology. The data used herein were selected using IC and exclusion criteria to ensure quality assessment. The selected articles were divided into four main research areas: education, engineering, entertainment, and medicine. Overall, 238 papers were selected based on IC. Moreover, 28 companies were identified that developed wired and wireless equipment as means of BCI assistive technology. The findings of this review indicate that the implications of using BCIs for assistive, adaptive, and rehabilitative technologies are encouraging for people with severe motor disabilities and healthy people. With an increasing number of healthy people using BCIs, other research areas, such as the motivation of players when participating in games or the security of soldiers when observing certain areas, can be studied and collaborated using the BCI technology. However, such BCI systems must be simple (wearable), convenient (sensor fabrics and self-adjusting abilities), and inexpensive.

Vanderburgh shares her experience with prosthetic knee breaking down, leading to a reflection on the parallels between disabled life and creative practice. She navigates tensions and contradictions in critiquing and relying on prosthetic technology, highlighting systemic inequities in access to prosthetic care. She also explores the representation of disability in society, focusing on the oversimplified notion of the \"amputee cyborg\" and the fetishization of assistive devices. Her artistic projects, Floral Fasciation and The Disabled Body in Motion, use irony to convey messages about disability and challenge traditional narratives. Furthermore, she emphasizes the importance of acknowledging loss, change, and instability in disabled representation, and the need to re-historicize disability to create a new framework of understanding.