bluuebunny/crossref_metadata_2025_split huggingface dataset:
Interpersonal relation recognition: a survey
Authors: Guerdelli Hajer , Ferrari Claudio , Berretti Stefano 
Published: September 2022

AbstractPeople spend a considerable amount of their time in social activities, where person-to-person relations are of main relevance. Recently, there has been an increasing research interest in automatically analyzing interpersonal relations, for the social and behavioral implications, and the many practical applications it may have. However, to the best of our knowledge, there is not a systematic study providing a harmonized view of the literature in the field. On this ground, we summarize in our work interpersonal relation recognition datasets and methods aiming to help researchers to have a better understanding of the characteristics of the state-of-the-art. In the proposed study, we distinguish between methods that address objective relations that do not depend on behavior or emotional state, and methods that consider subjective ones that depend on emotions. It turns out quite evidently that aiming at the latter recognition task is more challenging, with the existing methods that provide convincing results only on limited and very specific cases. For both the broad categories, we discuss datasets and methods according to the different behavioural and psychological models used to annotate and classify the data. We conclude our review work, by providing a comprehensive discussion pointing out current limitations and future research perspectives.
Visual Processing During the Interictal Period Between Migraines: A Meta-Analysis
Authors: Sezai Timucin , Murphy Melanie J. , Riddell Nina , Nguyen Vinh , Crewther Sheila G. 
Published: September 2022

AbstractMigraine is a poorly understood neurological disorder and a leading cause of disability in young adults, particularly women. Migraines are characterized by recurring episodes of severe pulsating unilateral headache and usually visual symptoms. Currently there is some disagreement in the electrophysiological literature regarding the universality of all migraineurs exhibiting physiological visual impairments also during interictal periods (i.e., the symptom free period between migraines). Thus, this meta-analysis investigated the evidence for altered visual function as measured electrophysiologically via pattern-reversal visual evoked potential (VEP) amplitudes and habituation in adult migraineurs with or without visual aura and controls in the interictal period. Twenty-three studies were selected for random effects meta-analysis which demonstrated slightly diminished VEP amplitudes in the early fast conducting P100 component but not in N135, and substantially reduced habituation in the P100 and the N135 in migraineurs with and without visual aura symptoms compared to controls. No statistical differences were found between migraineurs with and without aura, possibly due to inadequate studies. Overall, insufficient published data and substantial heterogeneity between studies was observed for all latency components of pattern-reversal VEP, highlighting the need for further electrophysiological experimentation and more targeted temporal analysis of visual function, in episodic migraineurs.
RiskScape: a flexible multi-hazard risk modelling engine
Authors: Paulik Ryan , Horspool Nick , Woods Richard , Griffiths Nick , Beale Tim , Magill Christina , Wild Alec , Popovich Benjamin , Walbran Glenn , Garlick Russel 
Published: September 2022

AbstractThis paper presents the architecture and features of RiskScape software. RiskScape is an open-source software with a flexible modelling engine for multi-hazard risk analysis. The RiskScape engine implements modeller-defined risk quantification workflows as ‘model pipelines’. Model pipeline steps and functions analyse hazard, exposure, and vulnerability data across different spatio-temporal domains using geoprocessing and spatial sampling operations. The RiskScape engine supports deterministic and probabilistic risk quantification, with several probabilistic-based modes described in this paper. RiskScape advances modelling software for multi-hazard risk analysis through several implementation features. The RiskScape engine operates model pipelines independent of system prescribed model input data classifications or standards. Multiple hazard types, metric intensities, and temporal occurrence information is geometry processed and sampled to create coverage data of simultaneous or sequenced multi-hazard events at object-exposure locations. Escalating multi-hazard event impacts are then determined for object-exposures using scripted conditional or nested statements that apply vulnerability functions in a logical sequence of temporal hazard and impact occurrence. These model features, supported by open geospatial consortium standard geospatial data files and operations, expedite RiskScape for modelling multi-hazard risk at any geographical location or scale.
An evaluation of vegetation loss due to the super typhoon Sarika in Hainan Island of China
Authors: Fengjin Xiao , Qiufeng Liu 
Published: September 2022

AbstractWith the continued strengthening of global climate change, various extreme climate events have become increasingly prominent. Typhoons are the most disastrous weather event that cause severe losses to the economy, agriculture, transportation, communication, and ecosystem in coastal regions. The super typhoon Sarika that hit Hainan Island on October 18, 2016, lasted for 15 h, and it was the most severe typhoon that hit this island in October since 1970. The coastal land of Hainan Island experienced gales with an average speed of 35 m/s. In this study, we evaluated the impact of the super typhoon Sarika on vegetation by performing normalized difference vegetative index (NDVI) difference analysis using MODIS multi-temporal images acquired before and after the typhoon. The assessment of typhoons depends on the land-use types and landscape topography of slope, aspect, and altitude. The results indicated that the super typhoon Sarika seriously hit forestry, agriculture, shrubs, plantations, and orchards on Hainan Island. Overall, 79% of vegetation exhibited a negative change, whereas only 21% of vegetation exhibited a positive change in NDVI after the super typhoon Sarika. Agriculture was most severely impacted by the typhoon, where more than 81% of areas exhibited a decrease in NDVI, followed by plantations and orchards, where 77% of areas exhibited a decrease in NDVI. Additionally, the impact of the typhoon on vegetation was affected by the degree of NDVI decrease with the altitude, slope, and aspect. In conclusion, vegetation damage is associated with land cover types, altitude, aspect, and slope. NDVI decreased more in low-altitude plain and coastal areas than in higher altitude montane forest areas.
Decoherence and classicalization of continuous-time quantum walks on graphs
Authors: Bressanini Gabriele , Benedetti Claudia , Paris Matteo G. A. 
Published: September 2022

AbstractWe address decoherence and classicalization of continuous-time quantum walks (CTQWs) on graphs. In particular, we investigate three different models of decoherence and employ the quantum-classical (QC) dynamical distance as a figure of merit to assess whether, and to which extent, decoherence classicalizes the CTQW, i.e. turns it into the analogue classical process. We show that the dynamics arising from intrinsic decoherence, i.e. dephasing in the energy basis, do not fully classicalize the walker and partially preserves quantum features. On the other hand, dephasing in the position basis, as described by the Haken–Strobl master equation or by the quantum stochastic walk (QSW) model, asymptotically destroys the quantumness of the walker, making it equivalent to a classical random walk. We also investigate how fast is the classicalization process and observe a larger rate of convergence of the QC-distance to its asymptotic value for intrinsic decoherence and the QSW models, whereas in the Haken–Strobl scenario, larger values of the decoherence rate induce localization of the walker.
What drives the valuation of entrepreneurial ventures? A map to navigate the literature and research directions
Authors: Colombo Massimo G. , Montanaro Benedetta , Vismara Silvio 
Published: September 2022

AbstractThe drivers of the valuations of entrepreneurial ventures are an important issue in entrepreneurial finance, but related research is fragmented. The theoretical perspectives and the drivers highlighted by previous studies differ based on the financial milestones during a venture’s lifecycle in which the valuation is performed (e.g., venture capital investments, initial public offerings, acquisitions). The introduction of new digital financing channels (e.g., crowdfunding, initial coin offerings) that allow retail investors to directly invest in entrepreneurial ventures challenge our understanding of the drivers of valuation. This change has also increased the diversity in the sequence of financial milestones that ventures go through, with important implications for valuation. We conduct a systematic literature review and develop a map highlighting how and why the drivers of venture valuations and their underlying theoretical lenses vary across the different milestones that ventures go through. The map allows us to outline new promising avenues for future research.
Patterns of white-tailed deer movements in suburban Maryland: implications for zoonotic disease mitigation
Authors: Roden-Reynolds P. , Kent C. M. , Li A. Y. , Mullinax J. M. 
Published: September 2022

AbstractUnderstanding the ecology of the often dense white-tailed deer populations in urban and suburban landscapes is important for mitigating a variety of conflicts that arise with dense human populations, such as issues surrounding zoonotic disease mitigation. We collared white-tailed deer in highly suburban areas of Howard County, Maryland with high-resolution GPS collars. Then, we created autocorrelated kernel density home ranges for broader land use analyses and concurrently used general additive models to characterize fine-scale hourly measures of speed, activity, and proximity to residential buildings. Suburban deer home ranges encompassed approximately 35% direct residential land, and an average of 71 and 129 residential properties were found within female and male core ranges, respectively. Sex, time of day, and day of year all influenced fine-scale speeds, activity levels, and proximity to residential property buildings. Deer moved into residential areas nightly, especially in winter, and exhibited bouts of increased speed and activity shortly after sunrise and sunset, with distinctive seasonal changes. We discuss how variation in home ranges and movements may influence population management success and explore year-round periods of increased risk of deer transporting ticks to residential areas. These findings focus our broad understanding of deer movements in suburban and urban landscapes to improve deer population management and to mitigate the spread of ticks into residential areas.
OASIS: Only Adversarial Supervision for Semantic Image Synthesis
Authors: Sushko Vadim , Schönfeld Edgar , Zhang Dan , Gall Juergen , Schiele Bernt , Khoreva Anna 
Published: September 2022

AbstractDespite their recent successes, generative adversarial networks (GANs) for semantic image synthesis still suffer from poor image quality when trained with only adversarial supervision. Previously, additionally employing the VGG-based perceptual loss has helped to overcome this issue, significantly improving the synthesis quality, but at the same time limited the progress of GAN models for semantic image synthesis. In this work, we propose a novel, simplified GAN model, which needs only adversarial supervision to achieve high quality results. We re-design the discriminator as a semantic segmentation network, directly using the given semantic label maps as the ground truth for training. By providing stronger supervision to the discriminator as well as to the generator through spatially- and semantically-aware discriminator feedback, we are able to synthesize images of higher fidelity and with a better alignment to their input label maps, making the use of the perceptual loss superfluous. Furthermore, we enable high-quality multi-modal image synthesis through global and local sampling of a 3D noise tensor injected into the generator, which allows complete or partial image editing. We show that images synthesized by our model are more diverse and follow the color and texture distributions of real images more closely. We achieve a strong improvement in image synthesis quality over prior state-of-the-art models across the commonly used ADE20K, Cityscapes, and COCO-Stuff datasets using only adversarial supervision. In addition, we investigate semantic image synthesis under severe class imbalance and sparse annotations, which are common aspects in practical applications but were overlooked in prior works. To this end, we evaluate our model on LVIS, a dataset originally introduced for long-tailed object recognition. We thereby demonstrate high performance of our model in the sparse and unbalanced data regimes, achieved by means of the proposed 3D noise and the ability of our discriminator to balance class contributions directly in the loss function. Our code and pretrained models are available at https://github.com/boschresearch/OASIS.
An intelligent access algorithm for large scale multihop wireless networks based on mean field game
Authors: Wang Yu , Ni Qinyin , Yu Junjiang , Jia Enfu , Zhu Xiaorong 
Published: September 2022

AbstractIn a distributed wireless network with a large number of nodes, competitive access of nodes may result in the deterioration of throughput and energy. Therefore, in this paper we propose an intelligent access algorithm based on the mean field game (MFG). First, we formulate the competitive access process between nodes as a game Query ID="Q1" Text="Please check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary." process by a stochastic differential game model, which maximizes the energy efficiency of nodes and obtain the optimal behavior strategy while meeting the requirements of channel access. However, as the number of nodes increases, the dimension of the matrix used to characterize the interaction between nodes becomes too large, which increases the complexity of the solution procedure. Therefore, we introduce the MFG and the interaction between nodes can be approximately transformed into the interaction between nodes and the mean field, which not only reduces the complexity, but also reduces the computational overhead. In addition, the HJB-FPK equation is solved to obtain the Nash equilibrium of the MFG. Finally, a backoff strategy based on the Markov model is proposed, and the node obtains the corresponding backoff strategy according to the network situation and its own state. Simulation results show that the proposed algorithm has good performances on optimizing network throughput and energy efficiency for a large scale multi-hop wireless network.
Andrographolide ameliorates hepatic steatosis by suppressing FATP2-mediated fatty acid uptake in mice with nonalcoholic fatty liver disease
Authors: Ran Li-Sha , Wu Ya-Zeng , Gan Yi-Wen , Wang Hong-Lian , Wu Li-Juan , Zheng Chun-Mei , Ming Yao , Xiong Ran , Li Yong-Lin , Lei Shi-Hang , Wang Xue , Lao Xiao-Qing , Zhang Hong-Min , Wang Li , Chen Chen , Zhao Chang-Ying 
Published: September 2022

Abstract
Excessive intrahepatocellular lipid accumulation or steatosis is caused by abnormal lipid metabolism and a common character of nonalcoholic fatty liver disease (NAFLD), which may progress into cirrhosis and hepatocellular cancer. Andrographolide (Andro) is the primary active ingredient extracted from Andrographis paniculata, showing a protective role against dietary steatosis with the mechanism not fully understood. In this study, we showed that administration of Andro (50, 100, and 200 mg/kg/day for 8 weeks, respectively) attenuated obesity and metabolic syndrome in high-fat diet (HFD)-fed mice with improved glucose tolerance, insulin sensitivity, and reduced hyperinsulinemia, hyperglycemia, and hyperlipidemia. HFD-fed mice presented hepatic steatosis, which was significantly prevented by Andro. In vitro, Andro decreased the intracellular lipid droplets in oleic acid-treated LO2 cells. The selected RT-PCR array revealed a robust expression suppression of the fatty acid transport proteins (FATPs) by Andro treatment. Most importantly, we found that Andro consistently reduced the expression of FATP2 in both the oleic acid-treated LO2 cells and liver tissues of HFD-fed mice. Overexpression of FATP2 abolished the lipid-lowering effect of Andro in oleic acid-treated LO2 cells. Andro treatment also reduced the fatty acid uptake in oleic acid-treated LO2 cells, which was blunted by FATP2 overexpression. Collectively, our findings reveal a novel mechanism underlying the anti-steatosis effect of Andro by suppressing FATP2-mediated fatty acid uptake, suggesting the potential therapeutic application of Andro in the treatment of NAFLD.

Graphical abstract
An ecosystem service approach to the study of vineyard landscapes in the context of climate change: a review
Authors: Candiago Sebastian , Winkler Klara Johanna , Giombini Valentina , Giupponi Carlo , Egarter Vigl Lukas 
Published: September 2022

AbstractVineyard landscapes significantly contribute to the economy, identity, culture, and biodiversity of many regions worldwide. Climate change, however, is increasingly threatening the resilience of vineyard landscapes and of their ecological conditions, undermining the provision of multiple ecosystem services. Previous research has often focused on climate change impacts, ecosystem conditions and ecosystem services without systematically reviewing how they have been studied in the literature on viticulture. Here, we systematically review the literature on vineyard landscapes to identify how ecosystem conditions and services have been investigated, and whether an integrative approach to investigate the effects of climate change was adopted. Our results indicate that there are still very few studies that explicitly address multiple ecosystem conditions and services together. Only 28 and 18% of the reviewed studies considered more than two ecosystem conditions or services, respectively. Moreover, while more than 97% of the relationships between ecosystem conditions and services studied were addressing provisioning and regulating services, only 3% examined cultural services. Finally, this review found that there is a lack of integrative studies that address simultaneously the relationships between ecosystem condition, ecosystem services and climate change (only 15 out of 112 studies). To overcome these gaps and to better understand the functioning of vineyard socio-ecological systems under climate change, multidisciplinary, integrative, and comprehensive approaches should be adopted by future studies. A holistic understanding of vineyard landscapes will indeed be crucial to support researchers and decision makers in developing sustainable adaptation strategies that enhance the ecological condition of vineyards and ensure the provision of multiple ecosystem services under future climate scenarios.
Demographic reporting across a decade of neuroimaging: a systematic review
Authors: Sterling Elijah , Pearl Hannah , Liu Zexuan , Allen Jason W. , Fleischer Candace C. 
Published: September 2022

AbstractDiversity of participants in biomedical research with respect to race, ethnicity, and biological sex is crucial, particularly given differences in disease prevalence, recovery, and survival rates between demographic groups. The objective of this systematic review was to report on the demographics of neuroimaging studies using magnetic resonance imaging (MRI). The Web of Science database was used and data collection was performed between June 2021 to November 2021; all articles were reviewed independently by at least two researchers. Articles utilizing MR data acquired in the United States, with n ≥ 10 human subjects, and published between 2010–2020 were included. Non-primary research articles and those published in journals that did not meet a quality control check were excluded. Of the 408 studies meeting inclusion criteria, approximately 77% report sex, 10% report race, and 4% report ethnicity. Demographic reporting also varied as function of disease studied, participant age range, funding, and publisher. We anticipate quantitative data on the extent, or lack, of reporting will be necessary to ensure inclusion of diverse populations in biomedical research.
Overcoming Vaccine Hesitancy for Future COVID-19 and HIV Vaccines: Lessons from Measles and HPV Vaccines
Authors: Aguolu Obianuju G. , Malik Amyn A. , Ahmed Noureen , Omer Saad B. 
Published: September 2022

Abstract
Background
The discovery of vaccines significantly reduced morbidity and mortality of infectious diseases and led to the elimination and eradication of some. Development of safe and effective vaccines is a critical step to the control of infectious diseases; however, there is the need to address vaccine hesitancy because of its potential impact on vaccine uptake.

Methods
We conducted a narrative review of studies on interventions to address measles and human papillomavirus vaccine hesitancy. We discussed how lessons learned from these studies could be applied towards COVID-19 and future human immunodeficiency virus vaccines.

Results
We found that there are several successful approaches to improving vaccine acceptance. Interventions should be context specific and build on the challenges highlighted in various settings.

Conclusion
Strategies could be used alone or in combination with others. The most successful interventions directly targeted the population for vaccination. Use of financial incentives could be a potential tool to improve vaccine uptake.
Physiological linkage of thyroid and pituitary sensitivities
Authors: Fitzgerald Stephen Paul , Bean Nigel G. , Falhammar Henrik , Hoermann Rudolf 
Published: September 2022

Abstract
Objectives
The sensitivities of the pituitary to thyroxine feedback, and the thyroid to thyrotropin stimulation determine the free thyroxine /thyrotropin feedback loop and can be described mathematically by two curves. It is not well understood how the two curves combine in a healthy population with normal thyroid function to express the individual balance points that are observed. This study was directed at this issue testing the possibilities of random combination and directed linkage between the two curves.

Methods
We reverse-engineered two sets of population data, on the assumption of independent combinations of thyroid and pituitary sensitivities, to obtain estimates of the curve describing thyroid sensitivity. Sensitivity studies were performed.

Results
No analysis resulted in a physiologically feasible estimate of the curve describing thyroid sensitivity. There was evidence of linkage of the two curves in terms of their combination throughout the normal range. Thyroid response curves reflecting a low free thyroxine response to thyrotropin tended to be combined in individuals with thyrotropin curves reflecting a high thyrotropin response to free thyroxine, and vice versa.

Conclusions
Thyroid and pituitary sensitivities are linked, being combined in individuals in a non-random directed pattern. Direct mutual interaction may contribute to this linkage. This linkage precludes the derivation of the curves describing these sensitivities from population data of the free thyroxine and thyrotropin relationship and complicates their derivation by physiological experimentation. This linkage and probable interaction may also bestow evolutionary advantage by minimising inter-individual variation in free thyroxine levels and by augmenting homeostasis.