bluuebunny/crossref_metadata_2025_split huggingface dataset:
Synchronized affect in shared experiences strengthens social connection
Authors: Cheong Jin Hyun , Molani Zainab , Sadhukha Sushmita , Chang Luke J. 
Published: October 2023

AbstractPeople structure their days to experience events with others. We gather to eat meals, watch TV, and attend concerts together. What constitutes a shared experience and how does it manifest in dyadic behavior? The present study investigates how shared experiences—measured through emotional, motoric, physiological, and cognitive alignment—promote social bonding. We recorded the facial expressions and electrodermal activity (EDA) of participants as they watched four episodes of a TV show for a total of 4 h with another participant. Participants displayed temporally synchronized and spatially aligned emotional facial expressions and the degree of synchronization predicted the self-reported social connection ratings between viewing partners. We observed a similar pattern of results for dyadic physiological synchrony measured via EDA and their cognitive impressions of the characters. All four of these factors, temporal synchrony of positive facial expressions, spatial alignment of expressions, EDA synchrony, and character impression similarity, contributed to a latent factor of a shared experience that predicted social connection. Our findings suggest that the development of interpersonal affiliations in shared experiences emerges from shared affective experiences comprising synchronous processes and demonstrate that these complex interpersonal processes can be studied in a holistic and multi-modal framework leveraging naturalistic experimental designs.
Imagining the future of optical microscopy: everything, everywhere, all at once
Authors: Balasubramanian Harikrushnan , Hobson Chad M. , Chew Teng-Leong , Aaron Jesse S. 
Published: October 2023

AbstractThe optical microscope has revolutionized biology since at least the 17th Century. Since then, it has progressed from a largely observational tool to a powerful bioanalytical platform. However, realizing its full potential to study live specimens is hindered by a daunting array of technical challenges. Here, we delve into the current state of live imaging to explore the barriers that must be overcome and the possibilities that lie ahead. We venture to envision a future where we can visualize and study everything, everywhere, all at once – from the intricate inner workings of a single cell to the dynamic interplay across entire organisms, and a world where scientists could access the necessary microscopy technologies anywhere.
Long-term viable chimeric nephrons generated from progenitor cells are a reliable model in cisplatin-induced toxicity
Authors: Matsui Kenji , Yamanaka Shuichiro , Chen Sandy , Matsumoto Naoto , Morimoto Keita , Kinoshita Yoshitaka , Inage Yuka , Saito Yatsumu , Takamura Tsuyoshi , Fujimoto Toshinari , Tajiri Susumu , Matsumoto Kei , Kobayashi Eiji , Yokoo Takashi 
Published: October 2023

AbstractKidney organoids have shown promise as evaluation tools, but their in vitro maturity remains limited. Transplantation into adult mice has aided in maturation; however, their lack of urinary tract connection limits long-term viability. Thus, long-term viable generated nephrons have not been demonstrated. In this study, we present an approachable method in which mouse and rat renal progenitor cells are injected into the developing kidneys of neonatal mice, resulting in the generation of chimeric nephrons integrated with the host urinary tracts. These chimeric nephrons exhibit similar maturation to the host nephrons, long-term viability with excretion and reabsorption functions, and cisplatin-induced renal injury in both acute and chronic phases, as confirmed by single-cell RNA-sequencing. Additionally, induced human nephron progenitor cells differentiate into nephrons within the neonatal kidneys. Collectively, neonatal injection represents a promising approach for in vivo nephron generation, with potential applications in kidney regeneration, drug screening, and pathological analysis.
Topological links in predicted protein complex structures reveal limitations of AlphaFold
Authors: Hou Yingnan , Xie Tengyu , He Liuqing , Tao Liang , Huang Jing 
Published: October 2023

AbstractAlphaFold is making great progress in protein structure prediction, not only for single-chain proteins but also for multi-chain protein complexes. When using AlphaFold-Multimer to predict protein‒protein complexes, we observed some unusual structures in which chains are looped around each other to form topologically intertwining links at the interface. Based on physical principles, such topological links should generally not exist in native protein complex structures unless covalent modifications of residues are involved. Although it is well known and has been well studied that protein structures may have topologically complex shapes such as knots and links, existing methods are hampered by the chain closure problem and show poor performance in identifying topologically linked structures in protein‒protein complexes. Therefore, we address the chain closure problem by using sliding windows from a local perspective and propose an algorithm to measure the topological–geometric features that can be used to identify topologically linked structures. An application of the method to AlphaFold-Multimer-predicted protein complex structures finds that approximately 1.72% of the predicted structures contain topological links. The method presented in this work will facilitate the computational study of protein‒protein interactions and help further improve the structural prediction of multi-chain protein complexes.
Systematic review of the effectiveness of interventions used in the management of obesity
Authors: O’Meara S , Glenny A‐M , Sheldon T , Melville A , Wilson C 
Published: October 2023

This paper briefly describes the principles of undertaking a systematic review of the effectiveness of obesity management interventions. Objective: To assess the effectiveness of interventions used in the prevention and treatment of obesity and the maintenance of weight loss. Background: Obesity represents a serious public health problem due to the associated risks of disease and mortality. Prevalence of the condition is increasing and the relevant Health of the Nation target is unlikely to be met. Methods and search strategy: A qualitative systematic review of the research literature, using electronic databases and contact with experts. Inclusion criteria: Randomized controlled trials evaluating the effectiveness of interventions used in managing obesity in which participants were observed for a minimum of 1 year. For studies of prevention, non‐randomized controlled trials with a concurrent control group were also eligible. Results: Ninety‐nine studies were included, most of which had been performed in North America. The methodological quality of many of the studies was poor. Family therapy and community education programmes were shown to be effective in preventing obesity in children and adults, respectively. Programmes based on the reduction of sedentary behaviour were effective in the treatment of obese children. For the treatment of obese adults, behavioural, diet, exercise and drug therapies can be effective when used in combination. Surgery is effective in morbidly obese patients. Weight regain is common following many types of weight loss interventions, and maintenance programmes based on continued contact may be useful. Conclusions: This review has identified some potentially effective interventions for the management of obesity. However, results should be interpreted with caution due to problems with the methodological quality of primary studies.
Spherical robot: A novel robot for exploration in harsh unknown environments
Authors: Ren Wei , Wang You , Liu Haoxiang , Jin Song , Wang Yixu , Liu Yifan , Zhang Ziang , Hu Tao , Li Guang 
Published: October 2023

AbstractThe authors propose a complete software and hardware framework for a novel spherical robot to cope with exploration in harsh and unknown environments. The proposed robot is driven by a heavy pendulum covered by a fully enclosed spherical shell, which is strongly protected, amphibious, anti‐overturn and has a long‐battery‐life. Algorithms for location and perception, planning and motion control are comprehensively designed. On the one hand, the authors fully consider the kinematic model of a spherical robot, propose a positioning algorithm that fuses data from inertial measurement units, motor encoder and Global Navigation Satellite System, improve global path planning algorithm based on Hybrid A* and design an instruction planning controller based on model predictive control (MPC). On the other hand, the dynamic model is built, linear MPC and robust servo linear quadratic regulator algorithm is improved, and a speed controller and a direction controller are designed. In addition, based on the pose and motion characteristics of a spherical robot, a visual obstacle perception algorithm and an electronic image stabilisation algorithm are designed. Finally, the authors build physical systems to verify the effectiveness of the above algorithms through experiments.
StableNet: Distinguishing the hard samples to overcome language priors in visual question answering
Authors: Yu Zhengtao , Zhao Jia , Guo Chenliang , Yang Ying 
Published: October 2023

AbstractWith the booming fields of computer vision and natural language processing, cross‐modal intersections such as visual question answering (VQA) have become very popular. However, several studies have shown that many VQA models suffer from severe language prior problems. After a series of experiments, the authors found that previous VQA models are in an unstable state, that is, when training is repeated several times on the same dataset, there are significant differences between the distributions of the predicted answers given by the models each time, and these models also perform unsatisfactorily in terms of accuracy. The reason for model instability is that some of the difficult samples bring serious interference to model training, so we design a method to measure model stability quantitatively and further propose a method that can alleviate both model imbalance and instability phenomena. Precisely, the question types are classified into simple and difficult ones different weighting measures are applied. By imposing constraints on the training process for both types of questions, the stability and accuracy of the model improve. Experimental results demonstrate the effectiveness of our method, which achieves 63.11% on VQA‐CP v2 and 75.49% with the addition of the pre‐trained model.
Learning to code: interplay of attitude, emotions, and fun
Authors: Tisza Gabriella , Markopoulos Panos , Bekker Tilde 
Published: October 2023

AbstractThere is a worldwide pursuit to increase children’s interest in STEM (Science, Technology, Engineering, Mathematics) especially in computer science through extra-curricular activities such as coding workshops, hackathons, and FabLab initiatives. However, the underlying reasons for children’s willingness for participation in such activities, and the effect of participation on children’s topic-related knowledge are still not well understood. In order to understand the factors influencing children’s attitude about programming and investigate what effects children’s learning during such activities, we designed a workshop for introducing primary school children to programming, and implemented it for a Dutch primary school class (n = 23) as an exploratory case study. We recorded their attitudes towards programming, their state-level emotions, the fun they experienced, and the initial- and final knowledge on the topic and their gender for comparative purposes. Our findings indicate that the coding workshop had a positive effect on children’s state-level emotions, as children felt significantly happier, more excited and more in control at the end of the workshop than at the beginning of it. We also found that children’s attitude toward programming changed significantly and positively during the workshop, and that children’s attitude about programming is influenced by the experienced fun while learning to code regardless their gender. Additionally, we found that the workshop was successful in terms of knowledge acquisition: both the measured and the reported learning indicate that children learned during the activity. Our findings also indicate that children’s reported learning has a positive association with their state-level emotion feeling in control and that the measured learning is negatively influenced by high levels of stress. Accordingly, our results draw attention to the downshifting effect of high arousal emotions on the measured learning. Throughout the paper we discuss gender differences along the study findings and elaborate on further practical implications.
Government regulatory policies for digital transformation in small and medium-sized manufacturing enterprises: an evolutionary game analysis
Authors: Zhu Jianhua , Baker Julien S. , Song Zhiting , Yue Xiao-Guang , Li Wenqi 
Published: October 2023

AbstractIn recent years, digital transformation (DT) has become an inevitable choice for manufacturing enterprises to achieve sustainable development. As a large number of enterprise groups, small and medium-sized manufacturing enterprises (SMMEs) play an important role in the industrial development of China. However, due to insufficient resource investment, high transformation costs, lack of talents, and unclear transformation pathways, how the government can help SMMEs carry out DT has become an important research topic. Based on this background, this study considers the strategies of government, third-party demonstration enterprises (TDEs) and SMMEs, develops and builds a three-party evolutionary game model, and puts forward a governance mechanism for effective DT strategies (TDEs guide DT and SMMEs conduct DT). This study has drawn many interesting conclusions. (1) If the government chooses not to regulate, when SMMEs are risk-neutral, the government only needs to increase the rewards for SMMEs to effectively promote DT. When SMMEs are risk-averse, the government needs to increase the penalties for SMMEs and increase the rewards for TDEs to effectively promote DT. (2) If the government chooses to regulate, when SMMEs are risk-neutral, the government needs to increase the penalties for both TDEs and SMMEs to effectively promote DT. When SMMEs are risk-averse, the government only needs to increase penalties on SMMEs or TDEs to effectively promote DT. (3) When SMMEs are risk-averse, the government’s best choice is regulation. Because when the government does not regulate, DT may fail even if the government increases the penalties for SMMEs and increases the incentives for TDEs.
Do ESG controversies moderate the relationship between CSR and corporate financial performance in oil and gas firms?
Authors: García-Amate Antonio , Ramírez-Orellana Alicia , Rojo-Ramírez Alfonso A. , Casado-Belmonte M. Pilar 
Published: October 2023

AbstractThe oil and gas industry is enmeshed in a continuous debate regarding the negative impact that its activity has on the sustainability of the environment. Increasingly, the market and stakeholders are positively evaluating those firms which are socially responsible and penalizing those that are not. Literature has analyzed the market view through the Environmental, Social and Governance (ESG) controversies and their relationship with Corporate Financial Performance (CFP), as well as with Corporate Social Responsibility (CSR) strategy. This study analyzes the influence of ESG controversies as a moderating variable on the relationship between Environmental, Social, and Governance factors and Corporate Financial Performance from a market valuation perspective. To perform this analysis, PLS-SEM structural equations have been applied to a sample of 264 oil and gas firms globally. The results confirm the moderating influence of ESG controversies on the relationship between E, S, and G factors and Corporate Financial Performance.
ChatGPT-3.5 as writing assistance in students’ essays
Authors: Bašić Željana , Banovac Ana , Kružić Ivana , Jerković Ivan 
Published: October 2023

AbstractChatGPT-3.5, an AI language model capable of text generation, translation, summarization, and question-answering, has recently been released for public use. Studies have shown it can generate abstracts, research papers, and dissertations, and create quality essays on different topics. This led to ethical issues in using ChatGPT in academic writing, AI authorship, and evaluating students’ essays. However, it is still unknown how ChatGPT performs in students’ environments as a writing assistant tool and if it enhances students’ essay-writing performance. In the present study, we examined students’ essay-writing performances with or without ChatGPT as an essay-writing assistance tool. The average essay grade was C for both control (traditional essay-writing, n = 9) and experimental (ChatGPT-assisted essay-writing, n = 9) groups. None of the predictors affected essay scores: group, writing duration, study module, and GPA. The text unauthenticity was slightly higher in the experimental group, but the similarity among essays was generally low in the overall sample. In the experimental group, the AI classifier recognized more potential AI-generated texts. Our results demonstrate that the ChatGPT group did not perform better in either of the indicators; the students did not deliver higher quality content, did not write faster, nor had a higher degree of authentic text. We anticipate that these results can relieve some concerns about this tool’s usage in academic writing. ChatGPT-assisted writing could depend on the previous knowledge and skills of the user, which might, in certain instances, lead to confusion in inexperienced users and result in poorer essay writing performance.
Long-term trajectories of frailty phenotype in older cancer survivors: a nationally representative longitudinal cohort study
Authors: Pu Junlan , Zhou Weijiao , Zeng Wen , Shang Shaomei 
Published: October 2023

Abstract

Background
Frailty is a dynamic process associated with adverse health outcomes. However, little is known about the long-term trajectories of frailty in older cancer survivors.

Objectives
To describe the trajectories of frailty phenotype over time amongst older cancer survivors and examine the socio-demographic and health-related predictors of different trajectories.

Design
Population-based longitudinal cohort study.

Setting
Community-dwelling older adults in the United States.

Subjects
1,763 older adults who were diagnosed with cancer from the National Health and Ageing Trends Study.

Methods
Frailty was assessed by the Fried Frailty Phenotype. The group-based trajectory model was used to identify the trajectories of frailty. Multinomial logistic regression analyses were used to examine the socio-demographic and health-related predictors of different trajectories.

Results
Three frailty trajectories were identified; 52.8% of older cancer survivors had a sustained low risk of frailty over time, 25.0% had a low frailty risk at baseline but the risk increased steadily, and 22.3% had a high frailty risk with a slight change in the observed period. Older cancer survivors were at a high-risk frailty trajectory if they were older, female, African American, had lower education status, had lower annual income, were underweight or obese, self-rated poorer health, had more chronic conditions and difficulties with activities of daily living (ADL), and had worse cognitive functions (P &lt; 0.05).

Conclusions
Long-term frailty trajectories in older cancer survivors are heterogeneous. This study helps identify patients at high risk of sustained or deteriorating frailty and has the potential to inform targeted frailty management strategies addressing modifiable factors identified (e.g. body mass index, ADL).
168 Cases of aneurysmal dermatofibroma and 29 cases of hemosiderotic dermatofibroma: A clinicopathologic study
Authors: Nishimoto Akana , Ito Keigo , Usami Satoshi , Ogawa Rei , Akaishi Satoshi , Ansai Shin-ichi 
Published: October 2023

Abstract

Objectives
Aneurysmal dermatofibroma (ADF) and hemosiderotic dermatofibroma (HDF) are rare variants of dermatofibroma (DF) characterized by distinct histologic features. While HDF is traditionally considered a precursor to ADF, supporting evidence is limited, and the etiology remains unclear. A retrospective analysis of 2128 DF cases (2016-2019) was conducted to investigate the clinicopathologic characteristics of ADF, HDF, and other DFs.

Methods
Histopathologically diagnosed DF cases were examined for ADF and HDF. Univariate analyses were performed to compare clinicopathologic features.

Results
Among the cases, 168 (7.9%) were ADF and 29 (1.4%) were HDF. Aneurysmal dermatofibroma and HDF shared several common characteristics, including lower occurrence in females, larger size, and increased cellularity (all P &lt; .0001). Notably, 29% of ADFs lacked hemosiderin deposition. Aneurysmal dermatofibroma primarily manifested on exposed areas (face and forearm, both P &lt; .001). In contrast, 41% of HDFs occurred on the lower leg (P = .018), and all lower leg HDFs exhibited signs of venous stasis, distinguishing them from other HDFs (P &lt; .0001).

Conclusions
Our findings indicate a potential close relationship between ADF and HDF. Contrary to conventional beliefs, we also presented the possibility of ADF progressing into HDFs. Physical trauma may induce ADF, and HDFs may emerge from ADFs in conjunction with venous stasis in the lower extremities.
Epiphytic CAM bromeliads indicate vulnerability of tropical forest communities to climate change
Authors: Males Jamie , Baksh-Comeau Yasmin , Jaggernauth Dan , Ballah Shane , Paltoo Shahada , Griffiths Howard 
Published: October 2023

Abstract

Background and Scope
Vascular epiphytes have a variety of mechanisms to trap and retain water, including crassulacean acid metabolism (CAM). Niche segregation was investigated for epiphytic bromeliads on the tropical Caribbean island of Trinidad, where habitats range from lowland deciduous forests to high-rainfall montane tropical forests, ~1000 m in elevation.

Methods
Four tank-impounding bromeliad epiphytes in the genus Aechmea (Ae. aquilega, Ae. fendleri, Ae. nudicaulis and Ae. dichlamydea) with CAM were mapped across their distinct geographical and elevational zonations in northern Trinidad and Tobago. Species distribution modelling was used to determine environmental limitations for each species. Anatomical and physiological measurements included leaf succulence traits, gas exchange and CAM activity; hydraulic conductance and vulnerability; stomatal sensitivity and quantum yield responses to nocturnal temperature and long-term water deficits.

Key Results
A total of 2876 field observations identified the transitions between the lowland Ae. aquilega and montane Ae. fendleri, occurring &gt;500 m a.s.l. at the drier western end of the Northern Mountain Range and at progressively lower elevations towards the wetter, eastern region. Anatomical and physiological sensitivities of gas exchange, CAM activity and water use, and responses to elevated nocturnal temperatures and drought, were markedly different for Ae. fendleri compared with Ae. aquilega or the ubiquitous Ae. nudicaulis.

Conclusions
The species distribution model highlighted the susceptibility of Ae. fendleri to a changing climate. For each species, physiological and anatomical traits were tailored to environmental tolerances, consistent with specialist or generalist niche preferences. Using Intergovernmental Panel on Climate Change scenarios, we predict that rapid rainfall and temperature changes will lead to the loss of Ae. fendleri and associated lower (and upper) montane forest communities from Trinidad, seriously impacting both biodiversity and critical ecosystem functions here and in other tropical island habitats. Epiphytic bromeliads act as markers for threatened communities, and their physiological tolerances represent key indicators of climate change impacts.