To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
This study explores the visual aesthetics of organizational space by contrasting coworking spaces with traditional open-plan offices. Drawing on signaling theory and symbolic interactionism, we examine how ambience communicates symbolic meaning. Employing an archaeological approach to retrieve large-scale online photo data from Coworker and Pinterest, we then apply AI-driven deep learning visual contrast analysis to reveal clear aesthetic distinctions in organizational space. Coworking spaces evoke a homely, dining-room-like ambiance, with artwork, plants, warmer color palettes, and a more homely and hospitable ambience. Traditional open-plan offices, by contrast, tend toward cooler colors and industrial design elements. Findings suggest that coworking spaces visually signal greater affective and sensory value, promoting belonging, creativity, and warmth. The study contributes to organizational space theory by theorizing how visual aesthetics act as symbolic cues that shape workplace experiences and by introducing a methodological framework that integrates AI-based analysis with interpretive meaning-making.
Prior research indicates that both structural and functional networks are compromised in older adults experiencing depressive symptoms. However, the potential impact of abnormal interactions between brain structure and function remains unclear. This study investigates alterations in structural–functional connectivity coupling (SFC) among older adults with depressive symptoms, and explores how these changes differ depending on the presence of physiological comorbidities.
Methods
We used multimodal neuroimaging data (dMRI/rs-fMRI) from 415 older adults with depressive symptoms and 415 age-matched normal controls. Subgroups were established within the depressive group based on the presence of hypertension, hyperlipidemia, diabetes, cerebrovascular disease, and sleep disorders. We examined group and subgroup differences in SFC and tracked its alterations in relation to symptom progression.
Results
Older adults with depressive symptoms showed significantly increased SFC in the ventral attention network compared with normal controls. Moreover, changes in SFC within the subcortical network, especially in the left amygdala, were closely linked to symptom progression. Subgroup analyses further revealed heterogeneity in SFC changes, with certain physiological health factors, such as metabolic diseases and sleep disorders, contributing to distinct neural mechanisms underlying depressive symptoms in this population.
Conclusions
This study identifies alterations in SFC related to depressive symptoms in older adults, primarily within the ventral attention and subcortical networks. Subgroup analyses highlight the heterogeneous SFC changes associated with metabolic diseases and sleep disorders. These findings highlight SFC may serve as potential markers for more personalized interventions, ultimately improving the clinical management of depression in older adults.
Anthracological studies of preserved wooden building materials can help reveal ancient networks of resource mobilisation. Here, the authors report on the analysis of 657 charred timbers from four ancillary pits at the UNESCO World Heritage Site of the Mausoleum of the First Qin Emperor. The frequent use of dark coniferous wood (fir, spruce and hemlock) indicates sophisticated logistical planning and labour organisation—matching historic records of Qin administrative ascendency—because these species required sourcing from across many kilometres of rugged terrain. Identification of a temporal shift towards the use of higher-elevation species points to the ecological impact of large-scale timber harvesting.
The global C0 linearization theorem on Banach spaces was first proposed by Pugh [26], but it requires that the nonlinear term is globally bounded. In the present paper, we discuss global linearization of semilinear autonomous ordinary differential equations on Banach spaces assuming that the linear part is hyperbolic (including contraction as a particular case) and that the nonlinear term is only Lipschitz with a sufficiently small Lipschitz constant. To overcome the difficulties arising in this problem, in this paper, we rely on a splitting lemma to decouple the hyperbolic system into a contractive system along the stable manifold and an expansive system along the unstable manifold. We then construct a transformation to linearize a contractive/expansive system, which is defined by the crossing time with respect to the unit sphere. To demonstrate the strength of our result, we apply our results to a nonlinear Duffing oscillator without external excitation.
Perimenopausal women often experience physiological and psychological decline due to the effects of oestrogen fluctuations and the decline of ovarian function, leading to significantly increased depression rates, decreases in the quality of life and mental health issues. Studies have shown that the gut microbiota exerts anti-perimenopausal depression (PMD) effects via the microbiota-gut-brain (MGB) axis, the mechanisms of which may be related to inflammation. In this review, we discuss the effects and mechanisms of gut microbiota in PMD and provide new insights for future PMD treatment.
Methods
This review elaborates on the role of MGB axis in PMD from different aspects of inflammation, including gut microbiota metabolites, inflammatory signaling pathways, and clinical applications.
Results
Disorders of gut microbiota and decreased levels of gut microbiota metabolites (short-chain fatty acids, monoamine neurotransmitters) may cause PMD. The mechanism of intestinal microbiota-mediated inflammation may be related to TLR4/NF-κB pathway, NOD-like receptor protein 3 (NLRP3) inflammasome pathway and JAK-STAT pathway. At the same time, it was found that gut microbiota (probiotics, prebiotics, etc.) had good therapeutic potential in the treatment of PMD.
Conclusions
MGB axis mediated inflammation may play an important role in PMD. The application of gut microbiota in the treatment of PMD patients has profound clinical transformation value, but a lot of efforts are still needed.
Spodoptera frugiperda (Lepidoptera: Noctuidae), commonly known as the fall armyworm (FAW), is an invasive pest known for its rapid migration, strong adaptability, and wide host range. Small heat shock proteins (sHsps) are a specific class of Hsps associated with the molecular mechanisms of insect growth and development and the response to abiotic stresses, such as extreme temperatures, ultraviolet (UV) rays, and pesticides. Herein, six sHsps, SfsHsp11.2, SfsHsp15.8, SfsHsp20.2, SfsHsp21.4, SfsHsp22, and SfsHsp26.6, were successfully cloned and identified from FAW. The six SfsHsps all have an α-crystallin domain in their amino acid sequences. Furthermore, we investigated the expression patterns of these six SfsHsps in different tissues and developmental stages of FAW using real-time quantitative polymerase chain reaction. Their expression levels in adult FAW were also analysed under extreme temperatures (36°C and 4°C) and UV-A stress for different durations (0, 30, 60, 90, and 120 min). Our findings revealed distinct expression profiles for the six SfsHsps in different FAW tissues and developmental stages. Notably, under temperature and UV-A stress, most SfsHsp genes were significantly upregulated in adults. Our findings strongly indicate that SfsHsps are crucial in the development and stress response of S. frugiperda.
This study aims to explore the association between Health-Related Quality of Life (HRQoL) and people’s willingness to receive the coronavirus disease 2019 (COVID-19) vaccination.
Methods
This survey was conducted in November 2020. 1461 participants (convenient sampling method) completed the online questionnaire. HRQoL was assessed using the 12-item Short Form Survey (SF-12) which included Physical and Mental Component Summary (PCS and MCS). The relationship between HRQoL and the willingness of COVID-19 vaccination was assessed by multivariate logistic regression.
Results
25.67% of respondents intended to be vaccinated immediately, 61.05% hesitated, and 13.28% refused. The mean score of PCS was 51.27 ± 6.30 and MCS was 47.72 ± 9.26. The multivariate logistic regression analysis showed the correlation between HRQoL and the willingness of vaccination (Ρ<0.05). Based on Z-score standardization, for 1 standard deviation (SD) increase in PCS, the odds ratio (OR) was 0.854 (95% confidence interval [CI]: 0.753-0.969) for hesitant vaccination vs. immediate vaccination. For 1 SD increase in MCS, the OR was 0.810 (95% CI: 0.677-0.970) for reluctant vaccination (refusal of COVID-19 vaccination) vs immediate vaccination, and the OR was 0.808 (95% CI: 0.710-0.919) for hesitant vaccination vs immediate vaccination.
Conclusions
People with better HRQoL preferred to receive the COVID-19 vaccine immediately.
Electronic Health Record (EHR) data are critical for advancing translational research and AI technologies. The ENACT network offers access to structured EHR data across 57 CTSA hubs. However, substantial information is contained in clinical narratives, requiring natural language processing (NLP) for research. The ENACT NLP Working Group was formed to make NLP-derived clinical information accessible and queryable across the network.
Methods:
We established the ENACT NLP Working Group with 13 sites selected based on criteria including clinical notes access, IT infrastructure, NLP expertise, and institutional support. We divided sites into five focus groups targeting clinical tasks within disease contexts. Each focus group consisted of two development sites and two validation sites. We extended the ENACT ontology to standardize NLP-derived data and conducted multisite evaluations using the Open Health Natural Language Processing (OHNLP) Toolkit.
Results:
The working group achieved 100% site retention and deployed NLP infrastructure across all sites. We developed and validated NLP algorithms for rare disease phenotyping, social determinants of health, opioid use disorder, sleep phenotyping, and delirium phenotyping. Performance varied across sites (F1 scores 0.53–0.96), highlighting data heterogeneity impacts. We extended the ENACT common data model and ontology to incorporate NLP-derived data while maintaining Shared Health Research Informatics NEtwork (SHRINE) compatibility.
Conclusion:
This demonstrates feasibility of deploying NLP infrastructure across large, federated networks. The focus group approach proved more practical than general-purpose approaches. Key lessons include the challenge of data heterogeneity and importance of collaborative governance. This work also provides a foundation that other networks can build on to implement NLP capabilities for translational research.
Triceps skinfold thickness (TSF) is a surrogate marker of subcutaneous fat. Evidence is limited about the association of sex-specific TSF with the risk of all-cause mortality among maintenance hemodialysis (MHD) patients. We aimed to investigate the longitudinal relationship of TSF with all-cause mortality among MHD patients. A multicenter prospective cohort study was performed in 1034 patients undergoing MHD. The primary outcome was all-cause mortality. Multivariable Cox proportional hazards models were used to evaluate the association of TSF with the risk of mortality. The mean (standard deviation) age of the study population was 54.1 (15.1) years. 599 (57.9%) of the participants were male. The median (interquartile range) of TSF was 9.7 (6.3–13.3 mm) in males and 12.7 (10.0–18.0 mm) in females. Over a median follow up of 4.4 years (interquartile range, 2.4-7.9 years), there were 548 (53.0%) deaths. When TSF was assessed as sex-specific quartiles, compared with those in quartile 1, the adjusted HRs (95%CIs) of all-cause mortality in quartile 2, quartile 3 and quartile 4 were 0.93 (0.73, 1.19), 0.75 (0.58, 0.97) and 0.69 (0.52, 0.92), respectively (P for trend =0.005). Moreover, when analyzed by sex, increased TSF (≥9.7 mm for males and ≥18mm for females) was significantly associated with a reduced risk of all-cause mortality (quartile 3-4 vs. quartile 1-2; HR, 0.70; 95%CI: 0.55, 0.90 in males; quartile 4 vs. Quartile 1-3; HR, 0.69; 95%CI: 0.48, 1.00 in females). In conclusion, high TSF was significantly associated with lower risk of all-cause mortality in MHD patients.
Xiangranggounan is an intensively occupied settlement associated with the Kayue culture on the north-eastern Qinghai-Tibet Plateau. Excavations in 2022 and 2023 revealed five house types with clear stratigraphic relationships that help to expand current understanding of the evolution of prehistoric settlement patterns in harsh plateau environments.
Suicidal ideation (SI) is very common in patients with major depressive disorder (MDD). However, its neural mechanisms remain unclear. The anterior cingulate cortex (ACC) region may be associated with SI in MDD patients. This study aimed to elucidate the neural mechanisms of SI in MDD patients by analyzing changes in gray matter volume (GMV) in brain structures in the ACC region, which has not been adequately studied to date.
Methods
According to the REST-meta-MDD project, this study subjects consisted of 235 healthy controls and 246 MDD patients, including 123 MDD patients with and 123 without SI, and their structural magnetic resonance imaging data were analyzed. The 17-item Hamilton Depression Rating Scale (HAMD) was used to assess depressive symptoms. Correlation analysis and logistic regression analysis were used to determine whether there was a correlation between GMV of ACC and SI in MDD patients.
Results
MDD patients with SI had higher HAMD scores and greater GMV in bilateral ACC compared to MDD patients without SI (all p < 0.001). GMV of bilateral ACC was positively correlated with SI in MDD patients and entered the regression equation in the subsequent logistic regression analysis.
Conclusions
Our findings suggest that GMV of ACC may be associated with SI in patients with MDD and is a sensitive biomarker of SI.
The emotion regulation network (ERN) in the brain provides a framework for understanding the neuropathology of affective disorders. Although previous neuroimaging studies have investigated the neurobiological correlates of the ERN in major depressive disorder (MDD), whether patients with MDD exhibit abnormal functional connectivity (FC) patterns in the ERN and whether the abnormal FC in the ERN can serve as a therapeutic response signature remain unclear.
Methods
A large functional magnetic resonance imaging dataset comprising 709 patients with MDD and 725 healthy controls (HCs) recruited across five sites was analyzed. Using a seed-based FC approach, we first investigated the group differences in whole-brain resting-state FC of the 14 ERN seeds between participants with and without MDD. Furthermore, an independent sample (45 MDD patients) was used to evaluate the relationship between the aforementioned abnormal FC in the ERN and symptom improvement after 8 weeks of antidepressant monotherapy.
Results
Compared to the HCs, patients with MDD exhibited aberrant FC between 7 ERN seeds and several cortical and subcortical areas, including the bilateral middle temporal gyrus, bilateral occipital gyrus, right thalamus, calcarine cortex, middle frontal gyrus, and the bilateral superior temporal gyrus. In an independent sample, these aberrant FCs in the ERN were negatively correlated with the reduction rate of the HAMD17 score among MDD patients.
Conclusions
These results might extend our understanding of the neurobiological underpinnings underlying unadaptable or inflexible emotional processing in MDD patients and help to elucidate the mechanisms of therapeutic response.
In this article, we delve into the optimal scheduling challenge for many-to-many on-orbit services, taking into account variations in target accessibility. The scenario assumes that each servicing satellite is equipped with singular or multiple service capabilities, tasked with providing on-orbit services to multiple targets, each characterised by distinct service requirements. The mission’s primary objective is to determine the optimal service sequence, orbital transfer duration and on-orbit service time for each servicing satellite, with the ultimate goal of minimising the overall cost. We frame the optimal scheduling dilemma as a time-related colored travelling salesman problem (TRCTSP) and propose an enhanced firefly algorithm (EFA) to address it. Finally, experimental results across various scenarios validate the effectiveness and superiority of the proposed algorithm. The principal contribution of this work lies in the modeling and resolution of the many-to-many on-orbit service challenge, considering accessibility variations — a domain that has, until now, remained unexplored.
In certain scenarios, the large footprint of a robot is not conducive to multi-robot cooperative operations. This paper presents a generalized single-loop parallel manipulator with remote center of motion (GSLPM-RCM), which addresses this issue by incorporating a reconfigurable base. The footprint of this RCM manipulator can be adjusted by varying the parameters of the reconfigurable base. First, utilizing configuration evolution, a reconfigurable base is constructed based on the principle of forming RCM motion. Then, according to the modular analysis method, the inverse kinematics of this parallel RCM manipulator is analyzed, and the workspace is also analyzed. Subsequently, the motion/force transmissibility of this RCM manipulator is analyzed by considering its single-loop and multi-degree of freedom characteristics. Leveraging the workspace index and transmissibility indices, dimension optimization of the manipulator is implemented. Finally, the influence of the reconfigurable base on the workspace and the transmissibility performance of the optimized manipulator is studied.
Traditional bulky and complex control devices such as remote control and ground station cannot meet the requirement of fast and flexible control of unmanned aerial vehicles (UAVs) in complex environments. Therefore, a data glove based on multi-sensor fusion is designed in this paper. In order to achieve the goal of gesture control of UAVs, the method can accurately recognize various gestures and convert them into corresponding UAV control commands. First, the wireless data glove fuses flexible fiber optic sensors and inertial sensors to construct a gesture dataset. Then, the trained neural network model is deployed to the STM32 microcontroller-based data glove for real-time gesture recognition, in which the convolutional neural network-Attention mechanism (CNN-Attention) network is used for static gesture recognition, and the convolutional neural network-bidirectional long and short-term memory (CNN-Bi-LSTM) network is used for dynamic gesture recognition. Finally, the gestures are converted into control commands and sent to the vehicle terminal to control the UAV. Through the UAV simulation test on the simulation platform, the average recognition accuracy of 32 static gestures reaches 99.7%, and the average recognition accuracy of 13 dynamic gestures reaches 99.9%, which indicates that the system’s gesture recognition effect is perfect. The task test in the scene constructed in the real environment shows that the UAV can respond to the gestures quickly, and the method proposed in this paper can realize the real-time stable control of the UAV on the terminal side.
Soft robots show an advantage when conducting tasks in complex environments due to their enormous flexibility and adaptability. However, soft robots suffer interactions and nonlinear deformation when interacting with soft and fluid materials. The reason behind is the free boundary interactions, which refers to undetermined contact between soft materials, specifically containing nonlinear deformation in air and nonlinear interactions in fluid for soft robot simulation. Therefore, we propose a new approach using material point method (MPM), which can solve the free boundary interactions problem, to simulate soft robots under such environments. The proposed approach can autonomously predict the flexible and versatile behaviors of soft robots. Our approach entails incorporating automatic differentiation into the algorithm of MPM to simplify the computation and implement an efficient implicit time integration algorithm. We perform two groups of experiments with an ordinary pneumatic soft finger in different free boundary interactions. The results indicate that it is possible to simulate soft robots with nonlinear interactions and deformation, and such environmental effects on soft robots can be restored.
In contemporary neuroimaging studies, it has been observed that patients with major depressive disorder (MDD) exhibit aberrant spontaneous neural activity, commonly quantified through the amplitude of low-frequency fluctuations (ALFF). However, the substantial individual heterogeneity among patients poses a challenge to reaching a unified conclusion.
Methods
To address this variability, our study adopts a novel framework to parse individualized ALFF abnormalities. We hypothesize that individualized ALFF abnormalities can be portrayed as a unique linear combination of shared differential factors. Our study involved two large multi-center datasets, comprising 2424 patients with MDD and 2183 healthy controls. In patients, individualized ALFF abnormalities were derived through normative modeling and further deconstructed into differential factors using non-negative matrix factorization.
Results
Two positive and two negative factors were identified. These factors were closely linked to clinical characteristics and explained group-level ALFF abnormalities in the two datasets. Moreover, these factors exhibited distinct associations with the distribution of neurotransmitter receptors/transporters, transcriptional profiles of inflammation-related genes, and connectome-informed epicenters, underscoring their neurobiological relevance. Additionally, factor compositions facilitated the identification of four distinct depressive subtypes, each characterized by unique abnormal ALFF patterns and clinical features. Importantly, these findings were successfully replicated in another dataset with different acquisition equipment, protocols, preprocessing strategies, and medication statuses, validating their robustness and generalizability.
Conclusions
This research identifies shared differential factors underlying individual spontaneous neural activity abnormalities in MDD and contributes novel insights into the heterogeneity of spontaneous neural activity abnormalities in MDD.
This study aims to evaluate the impact of low-carbohydrate diet, balanced dietary guidance and pharmacotherapy on weight loss among individuals with overweight or obesity over a period of 3 months. The study involves 339 individuals with overweight or obesity and received weight loss treatment at the Department of Clinical Nutrition at the Second Affiliated Hospital of Zhejiang University, School of Medicine, between 1 January 2020 and 31 December 2023. The primary outcome is the percentage weight loss. Among the studied patients, the majority chose low-carbohydrate diet as their primary treatment (168 (49·56 %)), followed by balanced dietary guidance (139 (41·00 %)) and pharmacotherapy (32 (9·44 %)). The total percentage weight loss for patients who were followed up for 1 month, 2 months and 3 months was 4·98 (3·04, 6·29) %, 7·93 (5·42, 7·93) % and 10·71 (7·74, 13·83) %, respectively. Multivariable logistic regression analysis identified low-carbohydrate diet as an independent factor associated with percentage weight loss of ≥ 3 % and ≥ 5 % at 1 month (OR = 0·461, P < 0·05; OR = 0·349, P < 0·001). The results showed that a low-carbohydrate diet was an effective weight loss strategy in the short term. However, its long-term effects were comparable to those observed with balanced dietary guidance and pharmacotherapy.
Text readability assessment aims to automatically evaluate the degree of reading difficulty of a given text for a specific group of readers. Most of the previous studies considered it as a classification task and explored a wide range of linguistic features to express the readability of a text from different aspects, such as semantic-based and syntactic-based features. Intuitively, when the external form of a text becomes more complex, individuals will experience more reading difficulties. Based on this motivation, our research attempts to separate the textual external form from the text and investigate its efficiency in determining readability. Specifically, in this paper, we introduce a new concept, namely textual form complexity, to provide a novel insight into text readability. The main idea is that the readability of a text can be measured by the degree to which it is challenging for readers to overcome the distractions of external textual form and obtain the text’s core semantics. To this end, we propose a set of textual form features to express the complexity of the outer form of a text and characterize its readability. Findings show that the proposed external textual form features can be used as effective evaluation indexes to indicate the readability of text. It brings a new perspective to the existing research and provides a new complement to the existing rich features.
Characterised by the extensive use of obsidian, a blade-based tool inventory and microblade technology, the late Upper Palaeolithic lithic assemblages of the Changbaishan Mountains are associated with the increasingly cold climatic conditions of Marine Isotope Stage 2, yet most remain poorly dated. Here, the authors present new radiocarbon dates associated with evolving blade and microblade toolkits at Helong Dadong, north-east China. At 27 300–24 100 BP, the lower cultural layers contain some of the earliest microblade technology in north-east Asia and highlight the importance of the Changbaishan Mountains in understanding changing hunter-gatherer lifeways in this region during MIS 2.