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In the era of the green economy, the Chinese government has advocated for natural environmental protection and innovation in rural areas, making the sustainable development of small rural businesses into a focal point. Currently, whether natural environmental protection promotes the sustainable development of small rural businesses remains debatable, and the roles of regional innovation climate, entrepreneurs’ cognition of green development, and technological innovation in production on the sustainable development of small rural businesses are often overlooked. Addressing this gap, this study draws inspiration from Upper Echelons Theory and Sustainable Development Theory to construct a structural equation model (SEM) and proposes 10 hypotheses. Primary data was collected from rural entrepreneurs across 17 provinces in China, yielding 439 valid samples. The data were analyzed using AMOS 28.0, SMARTPLS 4.0, and SPSS 28.0. The findings revealed that natural environmental protection did not positively influence the sustainable development of small rural businesses (β = 0.104, p > 0.05). In contrast, the regional innovation climate (β = 0.189, p = 0.001) and rural small business entrepreneurs’ cognition of green development (β = 0.261, p < 0.001) significantly affected the sustainable development of small rural businesses. Technological innovation in production (β = 0.034, p < 0.01) played a partial mediating role between the regional innovation climate and the sustainable development of small rural businesses. And, the mediating role of technological innovation in production was significant in the relationship between entrepreneurs’ cognition of green development and the sustainable development of small rural businesses (β = 0.059, p < 0.01). As a representative developing country, China’s findings in rural areas provide valuable insights for other developing countries undergoing green development transitions. This study not only questions the applicability of Porter’s hypothesis in rural contexts but also offers implications for relevant policymakers and small business entrepreneurs.

Abstract Empathy relies on brain systems that support the interaction between an observer’s mental state and cues about the others’ experience. Beyond the core brain areas typically activated in pain empathy studies (insular and anterior cingulate cortices), the diversity of paradigms used may reveal secondary networks that subserve other more specific processes. A coordinate-based meta-analysis of fMRI experiments on pain empathy was conducted to obtain activation likelihood estimates along three factors and seven conditions: visual cues (body parts, facial expressions), visuospatial (first-person, thirdperson), and cognitive (self-, stimuli-, other-oriented tasks) perspectives. The core network was found across cues and perspectives, and common activation was observed in higher-order visual areas. Body-parts distinctly activated areas related with sensorimotor processing (superior and inferior parietal lobules, anterior insula) while facial expression distinctly involved the inferior frontal gyrus. Self- compared to other-perspective produced distinct activations in the left insula while stimulus- versus other-perspective produced distinctive responses in the inferior frontal and parietal lobules, precentral gyrus, and cerebellum. Pain empathy relies on a core network which is modulated by several secondary networks. The involvement of the latter seems to depend on the visual cues available and the observer's mental state that can be influenced by specific instructions.

Stability is a physical attribute that stands opposite the change. However, it is still unclear how the arrangement of links called topology affects network stability. In this study, we tackled this issue in the resting-state brain network using structural balance. Structural balance theory employs the quality of triadic associations between signed links to determine the network stability. In this study, we showed that negative links of the resting-state network make hubs to reduce balance-energy and push the network into a more stable state compared to null-networks with trivial topologies. In this regard, we created a global measure entitled ‘tendency to make hub’ to assess the hubness of the network. Besides, we revealed nodal degrees of negative links have an exponential distribution that confirms the existence of negative hubs. Our findings indicate that the arrangement of negative links plays an important role in the balance (stability) of the resting-state brain network.

Nonprofit organizations are critical actors in the Sustainable Development Goals as they provide a wide range of social services to the community and contribute to creating a sustainable future. They must compete for funding or government contracts by showing high social performance. Among the top factors influencing social performance is capacity, and it has received considerable attention in public and nonprofit literature. Capacity refers to the resources, capabilities, and practices required to perform their functions to achieve the social mission and high social performance. However, studies concerning capacity linked with social performance remain controversial. Understanding the linkage between capacity and social performance is relevant to funders, board directors, and management as it helps them enhance organizational performance. This research aims to assess the flow of knowledge in the study field and make recommendations for future research. The study focuses on capacity of nonprofits and thoroughly reviews the literature using complementary bibliometric analysis: co-occurrence analysis of keywords, sources, and authors and bibliographic coupling analysis of documents. We conduct a systematic analysis of peer-reviewed journal articles published between 1955 and 2022. Seven significant themes emerge among the most prominent researchers: (1) the link between capacity and social performance; (2) dimensions of capacity; (3) human resource capacity linked with social performance: (4) financial capacity linked with social performance; (5) capacity building linked with social performance; (6) collaboration and capacity; and (7) factors affecting capacity–social performance. The literature on nonprofits is determined to have inconsistent findings regarding the relationship between capacity and social performance. Research on various factors influencing capacity–social performance relationships is also scarce. This article highlights major principles in the discipline and identifies significant theoretical gaps in the body of knowledge. It also outlines the conceptual foundation for the study and makes recommendations for further research. From a managerial standpoint, the study sheds light on whether capacity is linked to higher performance levels and provides policymakers with guidelines on the implications of capacity building and collaboration.

Many studies have focused on neural changes and neuroplasticity, while the signaling demand for neural modification needs to be explored. In this study, we traced this issue in the organization of brain functional links where the conflictual arrangement of signed links makes a request to change. We introduced the number of frustrations (unsatisfied closed triadic interactions) as a measure for assessing \"requirement to change\" of functional brain network. We revealed that the requirement to change of the resting-state network has a u-shape functionality over the lifespan with a minimum in early adulthood, and it’s correlated with the presence of negative links. Also, we discovered that brain negative subnetwork has a special topology with a log-normal degree distribution in all stages, however, its global measures are altered by adulthood. Our results highlight the study of collective behavior of functional negative links as the source of the brain’s between-regions conflicts and we propose exploring the attribute of the requirement to change besides other neural change factors.

Generally, first and second generations of photovoltaic (PV) cells are including mono‐crystalline silicon, amorphous silicon, and dye‐synthesized solar cells. Investigating the electrical current behavior of these sorts of PV cells shows that a modified multi‐ or single diode(s) model with shunt and series resistance can use as a good choice in a specific range of the current. For other constructions such as multi‐junction PV cells that consist of the third generation, the network models are the best choice. Also, the network models can be used for the first and second generations to improve the validity of model in the wider range of current. In addition to existing generations, PV array and modules, which are serial and parallel arrays of PV cells, will lead to a higher current or voltage. The main disadvantage of using these sorts of systems is their more space occupation. This problem can be solved by using the concentrated PV (CPV) systems that focus the received irradiation on a smaller surface. By considering the generated current, voltage, power, temperature effect, and financial analysis, it seems third‐generation PV systems are more efficient among all the generations. Finally, by considering the ratio of generated current on the occupied space, the CPV systems will be a better choice. One of the best energy resources that can affect CO2 emission is photovoltaic energy. Photovoltaic systems are different in structure and materials. It is an effective choice to use current models to investigate the efficiency of photovoltaic systems. By the results, considering the type of combination, array systems can lead to more power due to more number of solar cells, but by considering the less number and surface, the concentrated solar cell systems will be a better choice.

The spinal cord is important for sensory guidance and execution of skilled movements. Yet its role in human motor learning is not well understood. Despite evidence revealing an active involvement of spinal circuits in the early phase of motor learning, whether long-term learning engages similar changes in spinal cord activation and functional connectivity remains unknown. Here, we investigated spinal–cerebral functional plasticity associated with learning of a specific sequence of visually-guided joystick movements (sequence task) over six days of training. On the first and last training days, we acquired high-resolution functional images of the brain and cervical cord simultaneously, while participants practiced the sequence or a random task while electromyography was recorded from wrist muscles. After six days of training, the subjects’ motor performance improved in the sequence compared to the control condition. These behavioral changes were associated with decreased co-contractions and increased reciprocal activations between antagonist wrist muscles. Importantly, early learning was characterized by activation in the C8 level, whereas a more rostral activation in the C6-C7 was found during the later learning phase. Motor sequence learning was also supported by increased spinal cord functional connectivity with distinct brain networks, including the motor cortex, superior parietal lobule, and the cerebellum at the early stage, and the angular gyrus and cerebellum at a later stage of learning. Our results suggest that the early vs. late shift in spinal activation from caudal to rostral cervical segments synchronized with distinct brain networks, including parietal and cerebellar regions, is related to progressive changes reflecting the increasing fine control of wrist muscles during motor sequence learning.

Motor learning underpins successful motor skill acquisition. Although it is well known that pain changes the way we move, it’s impact on motor learning is less clear. The aim of this systematic review was to synthesize evidence on the impact of experimental and clinical pain on task performance and activity-dependent plasticity measures across learning and explore these findings in relation to different pain and motor learning paradigms. Five databases were searched: Web of Science, Scopus, MEDLINE, Embase and CINAHL. Two reviewers independently screened the studies, extracted data, and assessed risk of bias using the Cochrane ROB2 and ROBIN-I. The overall strength of evidence was rated using the GRADE guidelines. Due to the heterogeneity of study methodologies a narrative synthesis was employed. Twenty studies were included in the review: fifteen experimental pain and five clinical pain studies, covering multiple motor paradigms. GRADE scores for all outcome measures suggested limited confidence in the reported effect for experimental pain and clinical pain, on motor learning. There was no impact of pain on any of the task performance measures following acquisition except for ‘accuracy’ during a tongue protrusion visuomotor task and ‘timing of errors’ during a motor adaptation locomotion task. Task performance measures at retention, and activity dependent measures at both acquisition and retention showed conflicting results. This review delivers a detailed synthesis of research studies exploring the impact of pain on motor learning. This is despite the challenges provided by the heterogeneity of motor learning paradigms, outcome measures and pain paradigms employed in these studies. The results highlight important questions for further research with the goal of strengthening the confidence of findings in this area.

The effective receptive field (ERF) is a crucial concept in object detection, as it captures rich semantic information about the target, including its position and class. Existing methods typically associate the ERF with the depth, size, and nonlinear operations of the convolutional network in a static manner, such that the feature maps at each layer of the convolutional neural network correspond to a fixed ERF size. However, in fact images, multiple objects with varying scales, shapes, and other characteristics can influence the ERF, and the ERF often follows Gaussian distribution. In this paper, we propose a dynamic and real-time region-oriented ERF computation method, named GERF (Gaussian-based Effective Receptive Fields). We apply GERF to the BRA (Bi-Level Routing Attention) module of BiFormer, and refer to the method as GERF-BRA. Our approach can predict the ERF for each window in feature map and capture the weighted features of adjacent windows using Gaussian distribution. We integrate GERF-BRA into the detection heads of YOLOv8n, and experimental results on the COCO 2017 dataset demonstrate the effectiveness of GERF-BRA, achieving an improvement of 2.5 AP. Meanwhile, our method also demonstrates remarkable efficacy on proprietary agricultural and medical datasets.

Noxious events that can cause physical damage to the body are perceived as threats. In the brainstem, the periaqueductal gray (PAG) ensures survival by generating an appropriate response to these threats. Hence, the experience of pain is coupled with threat signaling and interfaces in the dl/l and vlPAG columns. In this study, we triangulate the functional circuits of the dl/l and vlPAG by using static and time-varying functional connectivity (FC) in multiple fMRI scans in healthy participants (n = 37, 21 female). The dl/l and vlPAG were activated during cue, heat, and rating periods when the cue signaled a high threat of experiencing heat pain and when the incoming intensity of heat pain was unknown. Responses were significantly lower after low threat cues. The two regions responded similarly to the cued conditions but showed prominent distinctions in the extent of FC with other brain regions. Thus, both static and time-varying FC showed significant differences in the functional circuits of dl/l and vlPAG in rest and task scans. The dl/lPAG consistently synchronized with the salience network and the thalamus, suggesting a role in threat detection, while the vlPAG exhibited more widespread synchronization and frequently connected with memory/language and sensory regions. Hence, these two PAG regions process heat pain when stronger pain is expected or when it is uncertain, and preferentially synchronize with distinct brain circuits in a reproducible manner. The dl/lPAG seems more directly involved in salience detection, while the vlPAG seems engaged in contextualizing threats.