bluuebunny/crossref_metadata_2025_split huggingface dataset:
Short-term mortality and palliative care use after delayed hospital discharge: a population-based retrospective cohort study
Authors: Jones Aaron , Lapointe-Shaw Lauren , Brown Kevin , Babe Glenda , Hillmer Michael , Costa Andrew , Stall Nathan , Quinn Kieran 
Published: January 2024

ObjectivesIn Canada, patients whose acute medical issues have been resolved but are awaiting discharge from hospital are designated as alternate level of care (ALC). We investigated short-term mortality and palliative care use following ALC designation in Ontario, Canada.MethodsWe conducted a population-based retrospective cohort study of adult, acute care hospital admissions in Ontario with an ALC designation between January and December 2021. Our follow-up window was until 90 days post-ALC designation or death. Setting of discharge and death was determined using admission and discharge dates from multiple databases. We measured palliative care using physician billings, inpatient palliative care records and palliative home care records. We compared the characteristics of ALC patients by 90-day survival status and compared palliative care use across settings of discharge and death.ResultsWe included 54 839 ALC patients with a median age of 80 years. Nearly one-fifth (18.4%) of patients died within 90 days. Patients who died were older, had more comorbid conditions and were more likely to be male. Among those who died, 35.1% were never discharged from hospital and 20.3% were discharged but ultimately died in the hospital. The majority of people who died received palliative care following their ALC designation (68.1%).ConclusionsA significant proportion of patients experiencing delayed discharge die within 3 months, with the majority dying in hospitals despite being identified as ready to be discharged. Future research should examine the adequacy of palliative care provision for this population.
Computational social science with confidence
Authors: Mattsson Carolina E. S. 
Published: January 2024

AbstractThere is an ongoing shift in computational social science towards validating our methodologies and improving the reliability of our findings. This is tremendously exciting in that we are moving beyond exploration, towards a fuller integration with theory in social science. We stand poised to advance also new, better theory. But, as we look towards this future we must also work to update our conventions around training, hiring, and funding to suit our maturing field.
On the duration of face-to-face contacts
Authors: Plaszczynski Stéphane , Nakamura Gilberto , Grammaticos Basile , Badoual Mathilde 
Published: January 2024

AbstractThe analysis of social networks, in particular those describing face-to-face interactions between individuals, is complex due to the intertwining of the topological and temporal aspects. We revisit here both, using public data recorded by the sociopatterns wearable sensors in some very different sociological environments, putting particular emphasis on the contact duration timelines. As well known, the distribution of the contact duration for all the interactions within a group is broad, with tails that resemble each other, but not precisely, in different contexts. By separating each interacting pair, we find that the fluctuations of the contact duration around the mean-interaction time follow however a very similar pattern. This common robust behavior is observed on 7 different datasets. It suggests that, although the set of persons we interact with and the mean-time spent together, depend strongly on the environment, our tendency to allocate more or less time than usual with a given individual is invariant, i.e. governed by some rules that lie outside the social context. Additional data reveal the same fluctuations in a baboon population. This new metric, which we call the relation “contrast”, can be used to build and test agent-based models, or as an input for describing long duration contacts in epidemiological studies.
Predicting Group Choices from Group Profiles
Authors: Emamgholizadeh Hanif , Delić Amra , Ricci Francesco 
Published: January 2024

Group recommender systems (GRSs) identify items to recommend to a group of people by aggregating group members’ individual preferences into a group profile and selecting the items that have the largest score in the group profile. The GRS predicts that these recommendations would be chosen by the group by assuming that the group is applying the same preference aggregation strategy as the one adopted by the GRS. However, predicting the choice of a group is more complex since the GRS is not aware of the exact preference aggregation strategy that is going to be used by the group.To this end, the aim of this article is to validate the research hypothesis that, by using a machine learning approach and a dataset of observed group choices, it is possible to predict a group’s final choice better than by using a standard preference aggregation strategy. Inspired by the Decision Scheme theory, which first tried to address the group choice prediction problem, we search for a group profile definition that, in conjunction with a machine learning model, can be used to accurately predict a group choice. Moreover, to cope with the data scarcity problem, we propose two data augmentation methods, which add synthetic group profiles to the training data, and we hypothesize that they can further improve the choice prediction accuracy.We validate our research hypotheses by using a dataset containing 282 participants organized in 79 groups. The experiments indicate that the proposed method outperforms baseline aggregation strategies when used for group choice prediction. The method we propose is robust with the presence of missing preference data and achieves a performance superior to what humans can achieve on the group choice prediction task. Finally, the proposed data augmentation method can also improve the prediction accuracy. Our approach can be exploited in novel GRSs to identify the items that the group is likely to choose and to help groups to make even better and fairer choices.
Modality-collaborative Transformer with Hybrid Feature Reconstruction for Robust Emotion Recognition
Authors: Chen Chengxin , Zhang Pengyuan 
Published: January 2024

As a vital aspect of affective computing, Multimodal Emotion Recognition has been an active research area in the multimedia community. Despite recent progress, this field still confronts two major challenges in real-world applications: (1) improving the efficiency of constructing joint representations from unaligned multimodal features and (2) relieving the performance decline caused by random modality feature missing. In this article, we propose a unified framework, Modality-Collaborative Transformer with Hybrid Feature Reconstruction (MCT-HFR), to address these issues. The crucial component of MCT is a novel attention-based encoder that concurrently extracts and dynamically balances the intra- and inter-modality relations for all associated modalities. With additional modality-wise parameter sharing, a more compact representation can be encoded with less time and space complexity. To improve the robustness of MCT, we further introduce HFR, which consists of two modules: Local Feature Imagination (LFI) and Global Feature Alignment (GFA). During model training, LFI leverages complete features as supervisory signals to recover local missing features, while GFA is designed to reduce the global semantic gap between pairwise-complete and -incomplete representations. Experimental evaluations on two popular benchmark datasets demonstrate that our proposed method consistently outperforms advanced baselines in both complete and incomplete data scenarios.
Higher Noncalcified Plaque Volume Is Associated With Increased Plaque Vulnerability and Vascular Inflammation
Authors: Suzuki Keishi , Kinoshita Daisuke , Yuki Haruhito , Niida Takayuki , Sugiyama Tomoyo , Yonetsu Taishi , Araki Makoto , Nakajima Akihiro , Seegers Lena Marie , Dey Damini , Lee Hang , McNulty Iris , Takano Masamichi , Kakuta Tsunekazu , Mizuno Kyoichi , Jang Ik-Kyung 
Published: January 2024

BACKGROUND:
Recently, it was reported that noncalcified plaque (NCP) volume was an independent predictor for cardiac events. Pericoronary adipose tissue (PCAT) attenuation is a marker of vascular inflammation and has been associated with increased cardiac mortality. The aim of this study was to evaluate the relationships between NCP volume, plaque vulnerability, and PCAT attenuation.

METHODS:
Patients who underwent preintervention coronary computed tomography angiography and optical coherence tomography were enrolled. Plaque volume was measured by computed tomography angiography, plaque vulnerability by optical coherence tomography, and the level of coronary inflammation by PCAT attenuation. The plaques were divided into 2 groups of high or low NCP volume based on the median NCP volume.

RESULTS:

Among 704 plaques in 454 patients, the group with high NCP volume had a higher prevalence of lipid-rich plaque (87.2% versus 75.9%;
P
<0.001), thin-cap fibroatheroma (38.1% versus 20.7%;
P
<0.001), macrophage (77.8% versus 63.4%;
P
<0.001), microvessel (58.2% versus 42.9%;
P
<0.001), and cholesterol crystal (42.0% versus 26.7%;
P
<0.001) than the group with low NCP plaque volume. The group with high NCP volume also had higher PCAT attenuation than the group with low NCP volume (−69.6±10.0 versus −73.5±10.6 Hounsfield unit;
P
<0.001). In multivariable analysis, NCP volume was significantly associated with thin-cap fibroatheroma and high PCAT attenuation. In the analysis of the combination of PCAT attenuation and NCP volume, the prevalence of thin-cap fibroatheroma was the highest in the high PCAT attenuation and high NCP volume group and the lowest in the low PCAT attenuation and low NCP volume group.

CONCLUSIONS:
Higher NCP volume was associated with higher plaque vulnerability and vascular inflammation. The combination of PCAT attenuation and NCP volume may help identify plaque vulnerability noninvasively.

REGISTRATION:

URL:
https://www.clinicaltrials.gov
; Unique identifier: NCT04523194.
Intermittent theta burst stimulation with synchronised transcranial alternating current stimulation leads to enhanced frontal theta oscillations and a positive shift in emotional bias
Authors: Briley Paul M , Boutry Clement , Webster Lucy , Veniero Domenica , Harvey-Seutcheu Catherine , Jung JeYoung , Liddle Peter F , Morriss Richard 
Published: January 2024

AbstractRepetitive transcranial magnetic stimulation (rTMS), delivered to left dorsolateral prefrontal cortex, is an FDA-approved, and NICE-recommended, neuromodulation therapy for major depressive disorder (MDD). However, there is considerable inter-individual variability in rate and extent of clinical response, leading to a focus on approaches for optimising its effectiveness. We present findings from a non-patient study evaluating an approach that combines an efficient type of rTMS—“intermittent theta burst stimulation” (iTBS)—with a second neuromodulation technique—“transcranial alternating current stimulation” (tACS). tACS is delivered in synchrony with the iTBS with the intent of optimising the brain state during stimulation. In four separate sessions, we delivered 3 minutes of iTBS+tACS, iTBS+sham, sham+tACS, or double sham. We measured changes from pre- to post-stimulation in brain theta (4–8 Hz) oscillatory activity using electroencephalography, and we measured emotional bias post-stimulation using a well-studied emotion identification task. Theta activity has previously shown relationships with response to rTMS, and emotional bias has been proposed as a marker of potential antidepressant efficacy. We found that frontal theta power was enhanced following the dual therapy, building up over the 15-minute post-stimulation period to exceed that following either stimulation technique alone or double sham. Emotional bias, measured 20 minutes post-stimulation, was also significantly more positive following dual therapy. These findings indicate that tACS-synchronised iTBS (tsiTBS) holds promise as an augmentation approach for rTMS, which awaits validation in multi-session patient studies.
Meta-modeling the effects of anodal left prefrontal transcranial direct current stimulation on working memory performance
Authors: Wischnewski Miles , Berger Taylor A. , Opitz Alexander 
Published: January 2024

Abstract
Numerous studies have demonstrated the beneficial effects of anodal prefrontal transcranial direct current stimulation (tDCS) on working memory. However, a large variability exists in the applied tDCS parameters and working memory outcome measures. Using a meta-modeling approach, we investigated the relationship between tDCS electric fields in the left prefrontal cortex and improvements in working memory performance. Using this approach, a vector of outcome measures is correlated with the tDCS-related electric fields across several studies. These performance-electric field correlations (PEC) are calculated for each spatial location of the grey matter. Extracting 354 data points from 67 studies, we compared the spatial maps of tDCS effects on I) working memory accuracy and speed (regardless of working memory type and time of assessment), II) verbal and visuospatial working memory (regardless of performance measurement and time of assessment), and III) performance during and after stimulation (regardless of performance measurement and working memory type). We found that accuracy improves when anodal tDCS is applied to inferior frontal regions (Brodmann area 47) while working memory speed benefits from stimulation to dorsolateral and anterior prefrontal areas (Brodmann areas 9/10). Furthermore, the beneficial effects of left prefrontal tDCS are exclusive to verbal working memory, with no improvements in visuospatial working memory. We also observed region-specific effects only for task performance during, but not after, stimulation. The results of this study elucidate the causal involvement of prefrontal regions in working memory and can help guide tDCS placement for therapeutic application in disorders that involve working memory deficits.
Rohdea gymnogyna (Asparagaceae), a new species from southern Gansu, China
Authors: FENG HUI ZHE , XU TING , BI MING HUI , ZHAO YAN YING , CHANG CE , WANG YOU JUN 
Published: January 2024

Rohdea gymnogyna, a new species from southern Gansu Provinces in northwestern China, is described and illustrated. It is apparently most closely related to R. rotiformis described from Sichuan, southwestern China. These two species share a smooth annular ledge appendage at the throat of the perianth tube. It is, however, readily distinguishable mainly by the lanceolate perianth lobes which strongly curved into a "W" shape in longitudinal section, the very short and bowl-shaped perianth tube, the ovary extends beyond the perianth tube. The taxonomic relationships of the new species to R. urotepala and R. lichuanensis also with an annular ledge appendage were also briefly discussed.
Ice Crystal Alignment: A Concept for High-Temporal-Resolution Monitoring Using Polarimetric Phased Array Radar
Authors: Weber Mark , Zrnic Dusan , Zhang Pengfei , Mansell Edward 
Published: January 2024

Abstract
This article describes a concept whereby future operational polarimetric phased array radars (PPAR) routinely monitor ice crystal alignment regions caused by thundercloud electric fields with volume scan updates (∼12 min−1) sufficient to resolve the temporal variation due to lightning and subsequent rapid electric field regeneration in nonsevere thunderstorms. Routine observations of crystal alignment regions may enhance thunderstorm nowcasting through comparison of their temporal and spatial structure with other polarimetric signatures, integration with lightning detection data, and assimilation into convection resolving numerical weather prediction models. If crystal alignment observations indicate strong electrification well in advance of the first lightning strike and likewise reliably indicate the decay of strong electric fields at the end of a storm, this capability may improve warning for lightning-sensitive activities such as airport ramp operations and space launch. Experimental observations of crystal alignment volumes in central Oklahoma severe storms and their relation to those storms’ structures are presented and used to motivate discussion of possible PPAR architectures. In one case—a tornadic supercell—these observations illustrate an important limitation. Even the hypothesized 12 min−1 volume scan update rate would not resolve the temporal variation of the crystal alignment regions in such storms, suggesting that special, adaptive scanning methods may be appropriate for such storms. We describe how future operational phased array radars could support a crystal alignment measurement mode via parallel, time-multiplexed processing and discuss potential impacts on the radar’s primary weather observation mission. We conclude by discussing research needed to better understand technical challenges and operational benefits.
European Summer Wet-Bulb Temperature: Spatiotemporal Variations and Potential Drivers
Authors: Ma Qiyun , Chen Yumeng , Ionita Monica 
Published: January 2024

Abstract
Heat stress is projected to intensify with global warming, causing significant socioeconomic impacts and threatening human health. Wet-bulb temperature (WBT), which combines temperature and humidity effects, is a useful indicator for assessing regional and global heat stress variability and trends. However, the variations of European WBT and their underlying mechanisms remain unclear. Using observations and reanalysis datasets, we demonstrate a remarkable warming of summer WBT during the period 1958–2021 over Europe. Specifically, the European summer WBT has increased by over 1.0°C in the past 64 years. We find that the increase in European summer WBT is driven by both near-surface warming temperatures and increasing atmospheric moisture content. We identify four dominant modes of European summer WBT variability and investigate their linkage with the large-scale atmospheric circulation and sea surface temperature anomalies. The first two leading modes of the European WBT variability exhibit prominent interdecadal to long-term variations, mainly driven by a circumglobal wave train and concurrent sea surface temperature variations. The last two leading modes of European WBT variability mainly show interannual variations, indicating a direct and rapid response to large-scale atmospheric dynamics and nearby sea surface temperature variations. Further analysis shows the role of global warming and changes in midlatitude circulations in the variations of summer WBT. Our findings can enhance the understanding of plausible drivers of heat stress in Europe and provide valuable insights for regional decision-makers and climate adaptation planning.

Significance Statement
Wet-bulb temperature, which takes into account the combined effect of temperature and humidity, is a good indicator for assessing heat stress. In the context of global warming, heat stress is anticipated to escalate, posing significant risks to human health and causing socioeconomic losses. However, variations in wet-bulb temperature and the associated physical mechanisms have received limited attention. This study aims to improve our understanding of the temporal and spatial variations and the potential driving mechanisms of summer wet-bulb temperature across Europe in recent decades. We have observed a noteworthy increase in summer wet-bulb temperature, indicating a regional intensification of heat stress, particularly within the last 10 years. We further investigate the connections between variations in summer wet-bulb temperature, large-scale atmospheric circulation, and sea surface temperature. Additionally, we explore their associations with global warming and changes in midlatitude atmospheric circulation. The outcomes of this study not only contribute to establishing a scientific basis for evaluating heat-related risks in Europe but also facilitate preparedness for future climate adaptation and mitigation at both regional and local scales.
Multiple-Time-Scale Variations of the Record-Breaking Pre-Summer Rainfall over South China in 2022
Authors: Li Xiuzhen , Wang Donghai , Zhou Wen 
Published: January 2024

Abstract
South China encountered an exceptionally heavy pre-summer rainy season in 2022 with the regional precipitation ranking first in the past 44 years. This study aims to analyze the multiple-time-scale variations of precipitation in this pre-summer rainy season to shed light on the complex dynamics influencing pre-summer precipitation over South China. The findings reveal that the variation of precipitation was dominated by the 10–20-day oscillation during April–May, while interannual variation and trend during May–June. The 10–20-day oscillation of precipitation in pre-summer rainy season in South China demonstrates a strong association with cold-air activity, which can be traced back to the propagation of disturbances along a teleconnection, which represents the dominant mode of intraseasonal atmospheric circulation over Eurasia in high latitudes during April–May. This teleconnection plays a crucial role in facilitating cold-air invasion and triggering precipitation over East China and South China. The interannual component of abnormal precipitation is strong during May–June of 2022. It is primarily attributed to the abnormal highs in the lower troposphere over the subtropical western North Pacific and Japan. These abnormal highs are likely stimulated by the combined influences of Eurasian teleconnection propagation and cooling sea surface temperature anomalies (SSTAs) over the tropical central and eastern Pacific in the third year of a consecutive La Niña event. However, the universality of the impact of Eurasian teleconnection propagation on the abnormal high over Japan on interannual scale necessitates further investigation. Furthermore, there is a significant upward trend in pre-summer rainfall over South China, accounting for 38% of the total anomaly observed in 2022.
Tidal Intrusion Fronts, Surface Convergence, and Mixing in an Estuary with Complex Topography
Authors: Bo Tong , Ralston David K. , Garcia Adrian Mikhail P. , Geyer W. Rockwell 
Published: January 2024

Abstract
Observations from a tidal estuary show that tidal intrusion fronts occur regularly during flood tides near topographic features including constrictions and bends. A realistic model is used to study the generation of these fronts and their influence on stratification and mixing in the estuary. At the constriction, flow separation occurs on both sides of the jet flow downstream of the narrow opening, leading to sharp lateral salinity gradients and baroclinic secondary circulation. A tidal intrusion front, with a V-shaped convergence zone on the surface, is generated by the interaction between secondary circulation and the jet flow. Stratification is created at the front due to the straining of lateral salinity gradients by secondary circulation. Though stratification is expected to suppress turbulence, strong turbulent mixing is found near the surface front. The intense mixing is attributed to enhanced vertical shear due to both frontal baroclinicity and the twisting of lateral shear by secondary circulation. In the bend, flow separation occurs along the inner bank, resulting in lateral salinity gradients, secondary circulation, frontogenesis, and enhanced mixing near the front. In contrast to the V-shaped front at the constriction, an oblique linear surface convergence front occurs in the bend, which resembles a one-sided tidal intrusion front. Moreover, in addition to baroclinicity, channel curvature also affects secondary circulation, frontogenesis, and mixing in the bend. Overall in the estuary, the near-surface mixing associated with tidal intrusion fronts during flood tides is similar in magnitude to bottom boundary layer mixing that occurs primarily during ebbs.