bluuebunny/crossref_metadata_2025_split huggingface dataset:
Towards efficient video-based action recognition: context-aware memory attention network
Authors: Koh Thean Chun , Yeo Chai Kiat , Jing Xuan , Sivadas Sunil 
Published: November 2023

Abstract
Given the prevalence of surveillance cameras in our daily lives, human action recognition from videos holds significant practical applications. A persistent challenge in this field is to develop more efficient models capable of real-time recognition with high accuracy for widespread implementation. In this research paper, we introduce a novel human action recognition model named Context-Aware Memory Attention Network (CAMA-Net), which eliminates the need for optical flow extraction and 3D convolution which are computationally intensive. By removing these components, CAMA-Net achieves superior efficiency compared to many existing approaches in terms of computation efficiency. A pivotal component of CAMA-Net is the Context-Aware Memory Attention Module, an attention module that computes the relevance score between key-value pairs obtained from the 2D ResNet backbone. This process establishes correspondences between video frames. To validate our method, we conduct experiments on four well-known action recognition datasets: ActivityNet, Diving48, HMDB51 and UCF101. The experimental results convincingly demonstrate the effectiveness of our proposed model, surpassing the performance of existing 2D-CNN based baseline models.

Article Highlights

Recent human action recognition models are not yet ready for practical applications due to high computation needs.

We propose a 2D CNN-based human action recognition method to reduce the computation load.

The proposed method achieves competitive performance compared to most SOTA 2D CNN-based methods on public datasets.
AI and the quest for diversity and inclusion: a systematic literature review
Authors: Shams Rifat Ara , Zowghi Didar , Bano Muneera 
Published: November 2023

Abstract
The pervasive presence and wide-ranging variety of artificial intelligence (AI) systems underscore the necessity for inclusivity and diversity in their design and implementation, to effectively address critical issues of fairness, trust, bias, and transparency. However, diversity and inclusion (D&I) considerations are significantly neglected in AI systems design, development, and deployment. Ignoring D&I in AI systems can cause digital redlining, discrimination, and algorithmic oppression, leading to AI systems being perceived as untrustworthy and unfair. Therefore, we conducted a systematic literature review (SLR) to identify the challenges and their corresponding solutions (guidelines/ strategies/ approaches/ practices) about D&I in AI and about the applications of AI for D&I practices. Through a rigorous search and selection, 48 relevant academic papers published from 2017 to 2022 were identified. By applying open coding on the extracted data from the selected papers, we identified 55 unique challenges and 33 unique solutions in addressing D&I in AI. We also identified 24 unique challenges and 23 unique solutions for enhancing D&I practices by AI. The result of our analysis and synthesis of the selected studies contributes to a deeper understanding of diversity and inclusion issues and considerations in the design, development and deployment of the AI ecosystem. The findings would play an important role in enhancing awareness and attracting the attention of researchers and practitioners in their quest to embed D&I principles and practices in future AI systems. This study also identifies important gaps in the research literature that will inspire future direction for researchers.
Long-term outcomes of COVID-19 survivors and an exploratory analysis of factors associated with sequela-free survival of patients treated at Leishenshan Hospital in Wuhan, China
Authors: Huang Dan , Chen Caiyang , Xuan Wei , Pan Shuting , Fu Zhiwei , Chen Jian , Li Wenhui , Jiang Xin , Zhao Hongpan , Zhou Xun , Zhang Liyang , Chen Sihan , Feng Zhaoyan , Jiang Xuliang , Huang Lili , Zhang Xiao , Zhu Hui , Zhang Song , Yu Weifeng , Su Diansan 
Published: November 2023

Abstract
Purpose
While coronavirus disease 2019 (COVID-19) has emerged as a global pandemic, millions of patients with COVID-19 have recovered and returned to their families and work, although the key factors of sequela-free survival remain unknown. Here we determine key factors associated with sequela-free survival of patients with COVID-19.

Methods
Sequela-free survival is defined as having none of the long-term sequelae measured with the Activity of Daily Living (ADL) Scale, modified Medical Research Council (mMRC) Dyspnoea Scale, New York Heart Association (NYHA) classification, Self-rating Depression Scale (SDS), Carcinologic Handicap Index (CHI) and Modified Telephone Interview for Cognitive Status (TICS-M). Multivariable logistic regression was used to examine the key factors of sequela-free survival.

Results
The follow-up period for the 464 patients was 10 August to 30 September 2020. Of these, 424 patients completed the assessment of all scales. 30.2% (128 of 424) were categorised as sequela-free at follow-up. The most common sequelae were psychosocial problems (254 [57.7%]), respiratory function abnormality (149 [32.6%]) and cardiac function abnormality (98 [21.5%]). Risk factors associated with COVID-19 sequelae were anaemia on admission, longer duration from the onset of symptoms to admission and increasing of age, whereas anaemia treatment was a protective factor against sequelae. A haemoglobin level of < 113 g/L for female patients or < 92 g/L for male patients at admission discriminated a likely higher risk of any COVID-19 sequelae.

Conclusions
Only one third COVID-19 survivors were sequela-free. Anaemia on admission, longer duration from the onset of symptoms to admission and increasing of age were the risk factors of any long-term sequela. Anaemia treatment was associated with beneficial outcomes in COVID-19 survivors.
Klimasensible Gesundheitsberatung
Authors: Herrmann Alina , Mews Claudia , Hansen Heike , Lenzer Benedikt , Schwienhorst-Stich Eva-Maria , Quitmann Claudia 
Published: November 2023

ZusammenfassungDie negativen Auswirkungen des Klimawandels auf die Gesundheit werden zunehmend spürbar. Zudem liegt im Klimaschutz großes Potenzial für die Gesundheitsförderung. Im Praxisalltag können Themen zu Klimawandel und Gesundheit in die Beratung von Patient:innen integriert werden. Ziele sind der Schutz und die Förderung der individuellen und öffentlichen Gesundheit sowie weitere klima- und gesundheitsrelevante Aspekte. Inhalte einer solchen „klimasensiblen Gesundheitsberatung“ (KSGB) können Informationen über gesundheitliche Auswirkungen des Klimawandels und entsprechende Schutzmaßnahmen, Aufklärung zu gesunden und klimafreundlichen Lebensstilen oder seltener auch gesellschaftliche Aspekte sein. Bei der Integration von KSGB in Sprechstunde und Praxisabläufe finden bekannte Strategien aus der Gesundheits- und Klimawandelkommunikation Anwendung, v. a. patient:innenzentrierte Kommunikation, motivierende Gesprächsführung oder der differenzierte und offene Umgang mit klimabezogenen Gefühlen.
Real-world data to evaluate effects of a multi-level dissemination strategy on access, outcomes, and equity of monoclonal antibodies for COVID-19
Authors: Hamer Mika K. , Sobczak Chelsea , Whittington Lindsey , Bowyer Rachel L. , Koren Ramona , Begay Joel A. , Lum Hillary D. , Ginde Adit A. , Wynia Matthew K. , Kwan Bethany M. 
Published: November 2023

Abstract

Introduction:
Multi-level dissemination strategies are needed to increase equitable access to effective treatment for high-risk outpatients with COVID-19, particularly among patients from disproportionately affected communities. Yet assessing population-level impact of such strategies can be challenging.

Methods:
In collaboration with key contributors in Colorado, we conducted a retrospective cohort study to evaluate a multi-level dissemination strategy for neutralizing monoclonal antibody (mAb) treatment. Real-world data included county-level, de-identified output from a statewide mAb referral registry linked with publicly available epidemiological data. Outcomes included weekly number of mAb referrals, unique referring clinicians, and COVID-19 hospitalization rates. We assessed weekly changes in outcomes after dissemination strategies launched in July 2021.

Results:
Overall, mAb referrals increased from a weekly average of 3.0 to 15.5, with an increase of 1.3 to 42.1 additional referrals per county in each post-period week (p < .05). Number of referring clinicians increased from a weekly average of 2.2 to 9.7, with an additional 1.5 to 22.2 unique referring clinicians observed per county per week beginning 5 weeks post-launch (p < .001). Larger effects were observed in communities specifically prioritized by the dissemination strategies. There were no observed differences in COVID-19 hospitalization rates between counties with and without mAb treatment sites.

Conclusion:
Real-world data can be used to estimate population impact of multi-level dissemination strategies. The launch of these strategies corresponded with increases in mAb referrals, but no apparent population-level effects on hospitalization outcomes. Strengths of this analytic approach include pragmatism and efficiency, whereas limitations include inability to control for other contemporaneous trends.
Much Ado About Nothing? Reflections on the European Commission’s Proposal for an Inter-institutional Ethics Body
Authors: Petropoulou Ionescu Danai , Năstase Andreea 
Published: November 2023

AbstractOn 8 June 2023, the European Commission published a long-awaited proposal for the establishment of an interinstitutional ethics body, meant to restore the public’s faith in the European Union’s administration following the Qatargate corruption scandal. Alas, the Commission’s proposal outlines a body that lacks investigative and sanctioning powers, has minimal administrative capacity and for the most part relies on the institution’s own policing. Put simply, it falls short of the promises made by the Commission’s President in her 2019 political guidelines, and much shorter of what was expected as a remedy to the European Union’s recent ethics-related scandals. In this short piece, we reflect on the Commission’s proposal for an inter-institutional ethics body in light of the overall ethics framework in the Union and provide a brief analysis of the Commission’s missed opportunity and of what could have been.
On the settling of aligned spherical particles in various quiescent media
Authors: Kang Soohyeon , Hong Liu , Cheng Shyuan , Best James L. , Chamorro Leonardo P. 
Published: November 2023

We investigated experimentally the settling behaviour of vertically aligned spherical particles within various quiescent media at different release frequencies. The particles had a diameter of

$d = 4$

mm and density of

$\rho _s = 2200$

kg m

$^{-3}$

, and were released near the free surface of water, ethanol, a G60 water–glycerine mixture (60 % glycerine by weight) and oil media at frequencies of

$f_P = 4$

, 6 and 8 Hz, thereby allowing study of Galileo numbers,

$Ga \in [16, 976]$

. Particle tracking velocimetry quantified the motion of nearly 800 particles in a 600 mm high tank, and particle image velocimetry examined flow patterns around the particles. Results revealed that the centre of mass of the particle trajectories exhibited preferential in-plane motions, with significant lateral dispersion and large

$Ga$

in water and ethanol, and nearly vertical paths with low

$Ga$

in the G60 mixture and oil media. Varying degrees of particle separation resulted in higher terminal velocities than for a single particle. Hence, particle drag decreased in all cases, with the oil medium showing the highest drag reduction under the closest particle separation, reaching up to nearly 70 % of that for the single particle. The vertical and lateral pair dispersions,

$R^2_z$

and

$R^2_L$

, exhibited ballistic scaling, with dependences on the initial separation,

$r_0$

, and the type of medium. With large

$Ga$

,

$R^2_z$

displayed a ballistic regime followed by a slower rate, whereas with small

$Ga$

,

$R^2_z$

maintained a consistent ballistic regime throughout settling. Finally, normalized

$R^2_z$

demonstrated distinct scaling (exponent 2/3 and 1) dependent on the normalized initial separation and

$Ga$

.
Population monitoring of a Critically Endangered antelope, the mountain bongo, using camera traps and a novel identification scheme
Authors: Sandri Tommy , Prettejohn Mike , Omengo Fred , Cain Bradley , Jones Martin , Harris W. Edwin 
Published: November 2023

AbstractConservation monitoring is paramount for the gathering of information on species and populations in need of conservation actions. However, monitoring of the mountain bongo Tragelaphus eurycerus isaaci, a Critically Endangered antelope endemic to Kenya, has hitherto been limited to surveillance (i.e. focused on persistence of the species in particular areas), thus limiting the information that could be retrieved on the status and trends of these populations. Using a newly developed identification system, we implemented robust design mark–recapture using existing camera-trap records of four wild subpopulations of the bongo. We provide data on sex and age structure and the first estimates of population size in the wild. Males and calves seem to be suffering higher mortality than females, and only two of the four monitored populations include adults of both sexes and calves. The combined size of these two breeding populations is estimated to be 29–50. Our findings confirm the critical situation of the mountain bongo in the wild and highlight the need for conservation actions to reinforce the wild populations for the long-term conservation of this antelope.
White Coats with Blue Collars: Doctors’ Labor Protests and the Struggle for Democracy in Brazil, 1978–1982
Authors: Weinberg Eyal 
Published: November 2023

AbstractThis article explores the labor struggles of doctors in late 1970s and early 1980s Brazil, the final years of the nation's dictatorship. Health workers' protests for better salaries and working conditions were extensive and reflected a dramatic change in the way medical practitioners in Brazil perceived their professional and political identities. Fusing together histories of medicine and labor, the article shows how physicians not only led strikes and unionized by their tens of thousands but also collaborated with blue-collar sectors in a larger struggle for working rights, access to healthcare, and structural reforms. Dictatorship officials, the article reveals, were significantly concerned by hospital strikes and particularly by the emerging cross-sector alliance. In this sense, the doctors' movement played a significant role in challenging Brazil's military rule and advancing the nation's transition to democracy.
International memories in global politics: Making the case for or against UN intervention in Libya and Syria
Authors: Bachleitner Kathrin 
Published: November 2023

AbstractThis paper is interested in the role and function of memories in United Nations Security Council debates about humanitarian intervention. It posits that historical experiences and their lessons serve as interpretative devices for the abstract international norms and principles under discussion. The paper speaks of ‘international memories’ where the meaning and lessons derived from the past coalesce among a group of states. Empirically, its case study explores how the memories of totalitarianism/fascism and colonialism were employed in United Nations (UN) representatives’ verbal pleas to intervene in Libya and Syria after the Arab Spring. It finds that those who supported or opposed humanitarian intervention held different interpretations of these memories and their lessons. In each case, however, memories provided essential normative guidance to states when it came to implementing the abstract international principles, norms, and rights that underlie humanitarian intervention.
Learner engagement regulation of dual-user training based on deep reinforcement learning
Authors: Yang Yang , Liu Xing , Liu Zhengxiong , Huang Panfeng 
Published: November 2023

AbstractThe dual-user training system is essential for fostering motor skill learning, particularly in complex operations. However, the challenge lies in the optimal tradeoff between trainee ability and engagement level. To address this problem, we propose an intelligent agent that coordinates trainees’ control authority during real task engagement to ensure task safety during training. Our approach avoids the need for manually set control authority by expert supervision. At the same time, it does not rely on pre-modeling the trainee’s skill development. The intelligent agent uses a deep reinforcement learning (DRL) algorithm based on trainee performance to adjust adaptive engagement during the training process. Our investigation aims to provide reasonable engagement for trainees to improve their skills while ensuring task safety. Our results demonstrate that this system can seek the policy to maximize trainee participation while guaranteeing task safety.
Multi-modal interaction with transformers: bridging robots and human with natural language
Authors: Wang Shaochen , Zhou Zhangli , Li Bin , Li Zhijun , Kan Zhen 
Published: November 2023

AbstractThe language-guided visual robotic grasping task focuses on enabling robots to grasp objects based on human language instructions. However, real-world human-robot collaboration tasks often involve situations with ambiguous language instructions and complex scenarios. These challenges arise in the understanding of linguistic queries, discrimination of key concepts in visual and language information, and generation of executable grasping configurations for the robot’s end-effector. To overcome these challenges, we propose a novel multi-modal transformer-based framework in this study, which assists robots in localizing spatial interactions of objects using text queries and visual sensing. This framework facilitates object grasping in accordance with human instructions. Our developed framework consists of two main components. First, a visual-linguistic transformer encoder is employed to model multi-modal interactions for objects referred to in the text. Second, the framework performs joint spatial localization and grasping. Extensive ablation studies have been conducted on multiple datasets to evaluate the advantages of each component in our model. Additionally, physical experiments have been performed with natural language-driven human-robot interactions on a physical robot to validate the practicality of our approach.
Association between face mask use and risk of SARS-CoV-2 infection: Cross-sectional study
Authors: Elgersma Ingeborg Hess , Fretheim Atle , Elstrøm Petter , Aavitsland Preben 
Published: November 2023

Abstract
We examined the association between face masks and risk of infection with SARS-CoV-2 using cross-sectional data from 3,209 participants in a randomized trial exploring the effectiveness of glasses in reducing the risk of SARS-CoV-2 infection. Face mask use was based on participants’ response to the end-of-follow-up survey. We found that the incidence of self-reported COVID-19 was 33% (aRR 1.33; 95% CI 1.03–1.72) higher in those wearing face masks often or sometimes, and 40% (aRR 1.40; 95% CI 1.08–1.82) higher in those wearing face masks almost always or always, compared to participants who reported wearing face masks never or almost never. We believe the observed increase in the incidence of infection associated with wearing a face mask is likely due to unobservable and hence nonadjustable differences between those wearing and not wearing a mask. Observational studies reporting on the relationship between face mask use and risk of respiratory infections should be interpreted cautiously, and more randomized trials are needed.
In vitro maturation in synthetic oviductal fluid increases gene expression associated with quality and lipid metabolism in bovine oocytes
Authors: Mendes Adriano Felipe , Puelker Raquel Zaneti , Souza Lilian Francisco Arantes de , Jacintho Andréa Renesto Coimbra , dos Santos Priscila Helena , Giometti Ines Cristina , Firetti Sheila Merlo , Castilho Anthony César de Souza , Zundt Marilice , Membrive Claudia Maria Bertan , Castilho Caliê 
Published: November 2023

SummaryTraditionally, in vitro oocyte and embryo culture progresses through a series of varying culture medium. To investigate simplifying the in vitro production of bovine cumulus–oocyte complexes (COCs), this study used synthetic oviductal fluid (SOF) supplemented with conjugated linoleic acid (CLA). Special interest was placed on gene expression linked to lipid metabolism and oocyte maturation. COCs were matured in different media: Medium 199 (M199 group), M199 with 100 μM CLA (M199 + CLA group), SOF (SOF group), and SOF with 100 μM CLA (SOF + CLA group). COCs matured with SOF showed a higher relative abundance of mRNA of quality indicators gremlin 1 (GREM1) and prostaglandin-endoperoxide synthase 2 (PTGS2) in oocytes, and GREM1 in cumulus cells compared with in the M199 group. SOF medium COCs had a higher relative abundance of fatty acid desaturase 2 (FADS2) compared with the M199 group, which is essential for lipid metabolism in oocytes. Furthermore, the abundance of stearoyl-coenzyme A desaturase 1 (SCD1) in oocytes matured with SOF was not influenced by the addition of CLA, whereas the relative abundance of SCD1 was reduced in M199 medium with CLA. We concluded that maturation in SOF medium results in a greater abundance of genes linked to quality and lipidic metabolism in oocytes, regardless of the addition of CLA.
Calibration of transition risk for corporate bonds
Authors: Sharpe J. , Ginghina F , Mehta G. , Smith A.D. 
Published: November 2023

Abstract
Under the European Union’s Solvency II regulations, insurance firms are required to use a one-year VaR (Value at Risk) approach. This involves a one-year projection of the balance sheet and requires sufficient capital to be solvent in 99.5% of outcomes. The Solvency II Internal Model risk calibrations require annual changes in market indices/term structure/transitions for the estimation of the risk distribution for each of the Internal Model risk drivers.
Transition and default risk are typically modelled using transition matrices. To model this risk requires a model of transition matrices and how these can change from year to year. In this paper, four such models have been investigated and compared to the raw data they are calibrated to. The models investigated are:

A bootstrapping approach – sampling from an historical data set with replacement.

The Vašíček model was calibrated using the Belkin approach.

The K-means model – a new non-parametric model produced using the K-means clustering algorithm.

A two-factor model – a new parametric model, using two factors (instead of a single factor with the Vašíček) to represent each matrix.

The models are compared in several ways:

1.
A principal components analysis (PCA) approach that compares how closely the models move compared to the raw data.

2.
A backtesting approach that compares how each model’s extreme percentile compares to regulatory backtesting requirements.

3.
A commentary on the amount of expert judgement in each model.

4.
Model simplicity and breadth of uses are also commented on.