bluuebunny/crossref_metadata_2025_split huggingface dataset:
A cross-domain fruit classification method based on lightweight attention networks and unsupervised domain adaptation
Authors: Wang Jin , Zhang Cheng , Yan Ting , Yang Jingru , Lu Xiaohui , Lu Guodong , Huang Bincheng 
Published: December 2022

AbstractImage-based fruit classification offers many useful applications in industrial production and daily life, such as self-checkout in the supermarket, automatic fruit sorting and dietary guidance. However, fruit classification task will have different data distributions due to different application scenarios. One feasible solution to solve this problem is to use domain adaptation that adapts knowledge from the original training data (source domain) to the new testing data (target domain). In this paper, we propose a novel deep learning-based unsupervised domain adaptation method for cross-domain fruit classification. A hybrid attention module is proposed and added to MobileNet V3 to construct the HAM-MobileNet that can suppress the impact of complex backgrounds and extract more discriminative features. A hybrid loss function combining subdomain alignment and implicit distribution metrics is used to reduce domain discrepancy during model training and improve model classification performance. Two fruit classification datasets covering several domains are established to simulate common industrial and daily life application scenarios. We validate the proposed method on our constructed grape classification dataset and general fruit classification dataset. The experimental results show that the proposed method achieves an average accuracy of 95.0% and 93.2% on the two datasets, respectively. The classification model after domain adaptation can well overcome the domain discrepancy brought by different fruit classification scenarios. Meanwhile, the proposed datasets and method can serve as a benchmark for future cross-domain fruit classification research.
Conceptualisations of curriculum co-creation: ‘it’s not them and us, it’s just us’
Authors: Lubicz-Nawrocka Tanya 
Published: December 2022

AbstractBuilding on the growing field of curriculum co-creation in higher education, this research analyses current conceptualisations of this concept based on the perceptions of student and staff co-creation practitioners. It draws on a rigorous review of international curriculum co-creation literature and describes in-depth research on experiences and conceptualisations of fifteen curriculum co-creation initiatives across eight subject areas at five universities in Scotland. Following an inductive analysis, the findings highlight conceptualisations of curriculum co-creation that focus on (A) developing shared values, (B) enhancing creativity through collaboration and (C) negotiating power for mutual benefit. These findings are discussed with respect to how they contribute to a new definition: curriculum co-creation is a relational way of working underpinned by shared responsibility, reciprocity in learning from each other, mutual respect, care, trust and empathy. This values-based, creative process helps staff and students work together to share and negotiate decision-making about aspects of curricula, which often leads to mutual benefits for learners and teachers. This new definition encompasses current conceptualisations of curriculum co-creation in the rapidly-changing higher education sector, with implications for fostering resilient, authentic and meaningful pedagogies that are relevant to today’s challenges in higher education and beyond.
Domain adversarial training for classification of cracking in images of concrete surfaces
Authors: Oliveira Santos Bruno , Valença Jónatas , Costeira João P. , Julio Eduardo 
Published: December 2022

AbstractThe development of automatic methods to recognize cracks in surfaces of concrete has been under focus in recent years, firstly through computer vision methods and more recently focusing on convolutional neural networks that are delivering promising results. Challenges are still persisting in crack recognition, namely due to the confusion added by the myriad of elements commonly found on concrete surfaces. The robustness of these methods would deal with these elements if access to correspondingly heterogeneous datasets was possible. Even so, this would be a cumbersome methodology, since training would be needed for each particular case and models would be case dependent. Thus, efforts from the scientific community are focusing on generalizing neural network models to achieve high performance in images from different domains, slightly different from those in which they were effectively trained. The generalization of networks can be achieved by domain adaptation techniques at the training stage. Domain adaptation enables finding a feature space in which features from both domains are invariant, and thus, classes become separable. The work presented here proposes the DA-Crack method, which is a domain adversarial training method, to generalize a neural network for recognizing cracks in images of concrete surfaces. The domain adversarial method uses a convolutional extractor followed by a classifier and a discriminator, and relies on two datasets: a source labeled dataset and a target unlabeled small dataset. The classifier is responsible for the classification of images randomly chosen, while the discriminator is dedicated to uncovering to which dataset each image belongs. Backpropagation from the discriminator reverses the gradient used to update the extractor. This enables fighting the convergence promoted by the updating backpropagated from the classifier, and thus generalizing the extractor enabling it for crack recognition of images from both source and target datasets. Results show that the DA-Crack training method improved accuracy in crack classification of images from the target dataset in 54 percentage points, while accuracy on the source dataset remains unaffected.
Les personnes âgées immigrantes et leurs proches à Montréal : des vies oubliées durant la pandémie
Authors: Brotman Shari , Simard Julien , Hanley Jill , Raymond Émilie , Delgado Pascual 
Published: December 2022

RésuméMalgré l’attention renouvelée de plusieurs médias sur la question des risques liés à la COVID-19 au sein de diverses communautés marginalisées au Québec, nous entendons encore très peu parler des personnes âgées immigrantes et de leurs proches. Dans cette note sur les politiques et pratiques, nous aborderons l’expérience du contexte pandémique chez les personnes âgées immigrantes montréalaises et leurs réseaux. Nous présenterons d’abord quelques données sociodémographiques sur les immigrants âgés montréalais. Nous exposerons ensuite nos constats sur les impacts de la COVID-19 sur les personnes âgées immigrantes, en particulier en ce qui concerne l’accès aux soins de la santé et aux services sociaux, la proche-aidance, l’emploi et le logement, à partir de nos travaux et de la littérature en gérontologie sociale. Nous terminerons en proposant quelques recommandations qui permettraient d’améliorer l’inclusion sociale des personnes âgées immigrantes et de leurs proches, autant en matière de politiques publiques que de pratiques sur le terrain.
The association between language exposure and nonword repetition performance in bilingual children: A systematic review and meta-analysis
Authors: Farabolini Gianmatteo , Taboh Analí R. , Ceravolo Maria Gabriella , Guerra Federico 
Published: December 2022

AbstractWe conducted a systematic review and meta-analysis on the association between nonword repetition (NWR) and language exposure in bilingual children and explored whether the association is influenced by other variables. We performed a blind literature review on ERIC and Google Scholar, a random-effects model meta-analysis and subgroup analyses to test potential moderators. Out of 822 screened articles, we identified 24 works including 1399 children. Significant associations were found using either cumulative or current exposure, language-like nonwords, phoneme NWR scoring, in children with typical language development. Nonsignificant associations were found in studies either using age of first exposure, on children older than six, with less than 50 participants, using NWR lists containing 16-24 nonwords or with participants having different native languages. Weak associations were found when considering whole-word scoring or gray literature. We highlight the contributions of different variables to NWR, and evidence to optimally design NWR for bilingual language assessment.
Stochastic Volatility Modeling of Daily Streamflow Time Series
Authors: Wang Huimin , Song Songbai , Zhang Gengxi , Ayantobo Olusola O. , Guo Tianli 
Published: December 2022

AbstractUnder the changing climate, the natural characteristics of hydrological processes are assumed to have been intensified, and the volatility of these processes to have increased significantly. However, the applicability of traditional time series analysis methods and the commonly used Gaussian GARCH (Generalized AutoRegressive Conditional Heteroskedasticity) to streamflow modeling has been limited. Although SV‐type (stochastic volatility) models have appeared as competitive alternatives to GARCH‐type models owing to their flexibility in modeling volatilities, they have not been applied in hydrological studies. Therefore, this study assesses the applicability of SV models to streamflow modeling using daily streamflow series from 21 hydrological stations in the Yellow River basin. Considering the influence of different types of GARCH and residual distributions, 7 hybrid models with variance fluctuation (fractional autoregressive integrated moving average‐GARCH) based on 9 distributions are compared to determine the optimal model for each station. Then 4 SV‐type models are introduced and compared with the results of the optimal GARCH‐type model to verify their applicability. The results show that: (a) the Gaussian distribution is not applicable in both GARCH‐type and SV‐type models for modeling daily streamflow; (b) although the GARCH‐type models are shown to describe the volatility of streamflow processes and improve the modeling performance, large residuals have been observed in the results of the analysis during the peak flow period; and (c) SV‐type models can better describe the streamflow series with time‐varying variance and accurately capture the occurrence of peak streamflow. The findings of this study offer practical and promising time series analysis methods for daily streamflow modeling.
Real‐Time Seismogeodetic Earthquake Magnitude Estimates for Local Tsunami Warnings
Authors: Golriz Dorian , Hirshorn Barry , Bock Yehuda , Weinstein Stuart , Weiss Jonathan R. 
Published: December 2022

AbstractWe estimate a seismogeodetic earthquake moment magnitude using unclipped, broadband velocity and displacement waveforms from collocated Global Navigation Satellite Systems and seismic stations located within 800 km epicentral distance for nine 7.2 < < 9.1 earthquakes. We consider the vertical component of seismogeodetic displacement as an approximate source time function and integrate the associated time series to obtain the seismic moment. By continuing to integrate vertical displacement beyond the initial P‐waves, we obtain rapid estimates of that are within 0.2 magnitude units for 8 thrust faulting events and within 0.3 units for the single normal faulting event. Because our estimates of the seismic moment are based on the maximum value of integrated displacement, no regression against other source parameters, or distance, is necessary. Our new method shows promise for integration into earthquake and local tsunami early warning systems, including tsunami earthquakes characterized by relatively slow moment release over a longer rupture time, and earthquakes with complex source time functions.
Flume Investigation Into Mechanisms Responsible for Particle Sorting in Gravel‐Bed Meandering Channels
Authors: White Daniel C. , Nelson Peter A. 
Published: December 2022

AbstractMeandering gravel‐bed rivers tend to exhibit bed surface sorting patterns with coarse particles located in pools and fine particles on bar tops. The mechanism by which these patterns emerge has been explored in sand‐bed reaches; however, for gravel‐bed meandering channels it remains poorly understood. Here we present results from a flume experiment in which bed morphology, velocity, sediment sorting patterns, and bed load transport were intensively documented. The experimental channel is 1.35 m wide, 15.2 m long, and its centerline follows a sine‐generated curve with a crossing angle of 20°. Water and sediment input were held constant throughout the experiment and measurements were collected under quasi‐equilibrium conditions. Boundary shear stress calculated from near‐bed velocity measurements indicates that in a channel with mild sinuosity, deposition of fine particles on bars is a result of divergent shear stress at the inside bend of the channel, downstream of the apex. Boundary shear stress in the upstream half of the pool was below critical for coarse particles (>8 mm), leading to an armored pool. Inward directed selective transport was responsible for winnowing of fine particles in the pool. Fine and coarse sediment followed similar trajectories through the meander bend, which contrasts earlier studies of sand‐bedded meanders where the loci of fine and coarse particles cross paths. This suggests a different sorting mechanism for gravel bends. This experiment shows that a complex interaction of quasi‐equilibrium bed topography, selective sediment transport, and secondary currents are responsible for the sorting patterns seen in gravel‐bed, meandering channels.
Peripheral blood cellular immunophenotype in depression: a systematic review and meta-analysis
Authors: Foley Éimear M. , Parkinson Joel T. , Mitchell Ruth E. , Turner Lorinda , Khandaker Golam M. 
Published: December 2022

Abstract
Introduction
Meta-analyses implicate immune dysfunction in depression confirming increased levels of circulating immune proteins (e.g., cytokines) in depression cases compared to controls. White blood cells (WBC) both produce and are influenced by cytokines, and play key roles in orchestrating innate and adaptive immune responses, but their role in depression remains unclear. Therefore, a systematic review of studies of various WBC subsets in depression is required for a greater understanding of the nature of immune dysfunction in this illness.

Methods
We searched PubMed and PsycINFO databases (inception to 5th April 2022) and conducted a systematic review and meta-analysis of identified studies comparing absolute count and/or relative percentage of flow cytometry-derived WBC subsets between depression cases and controls. Selected studies were quality assessed. Random-effect meta-analysis was performed.

Results
Thirty-three studies were included and 27 studies (n = 2277) were meta-analysed. We report an increase in mean absolute counts of WBC (seven studies; standardised mean difference [SMD] = 1.07; 95% CI, 0.61–1.53; P < 0.01; I2 = 64%), granulocytes (two studies; SMD = 2.07; 95% CI, 1.45–2.68; P < 0.01; I2 = 0%), neutrophils (four studies; SMD = 0.91; 95% CI, 0.23–1.58; P < 0.01; I2 = 82%), monocytes (seven studies; SMD = 0.60; 95% CI, 0.19–1.01; P < 0.01; I2 = 66%), CD4+ helper T cells (11 studies; SMD = 0.30; 95% CI, 0.15–0.45; P < 0.01; I2 = 0%), natural killer cells (11 studies; SMD = 1.23; 95% CI, 0.38–2.08; P < 0.01; I2 = 95%), B cells (10 studies; SMD = 0.30; 95% CI, 0.03–0.57; P = 0.03; I2 = 56%), and activated T cells (eight studies; SMD = 0.45; 95% CI, 0.24–0.66; P < 0.01; I2 = 0%) in depression, compared to controls. Fewer studies reported relative percentage, indicating increased neutrophils and decreased total lymphocytes, Th1, and Th2 cells in depression.

Conclusions
Depression is characterised by widespread alterations in circulating myeloid and lymphoid cells, consistent with dysfunction in both innate and adaptive immunity. Immune cells could be useful biomarkers for illness subtyping and patient stratification in future immunotherapy trials of depression, along with cytokines, other biomarkers, and clinical measures.
Good practice recommendations to better coordinate the management of oncological pain: a Delphi survey
Authors: Escobar Yolanda , Margarit César , Pérez-Hernández Concepción , Quintanar Teresa , Virizuela Juan A. 
Published: December 2022

AbstractTreatment of oncological pain is complex and requires a multidisciplinary management approach between oncology services and pain units. Although significant improvements have been achieved in the treatment and overall survival of cancer patients, the management of oncological pain has not followed the same directions. Many patients are not referred to pain units even though they could benefit from it. The purpose of this Delphi survey was to map the current situation in the management of cancer pain, identify barriers and propose recommendations to improve its management by emphasizing the importance of collaboration and coordination between oncology services and pain units. A survey among members with recognized experience in the management of oncology patients and oncological pain was held based on the Delphi method principles. The experts were asked to vote preselected statements on cancer pain management in two rounds and conclusions and recommendations were formulated based on the consensus reached for each statement. Barriers and areas for improvement were identified: need of multidisciplinary management approach, effective communication between oncology services and pain units, timely referral of cancer patients to pain units, training of health care professionals dealing with cancer aspects and identification of those patients that could benefit from a multidisciplinary management of their oncological disease. The experts issued recommendations targeting the identified barriers and areas for improvement by defining the service requirements of hospital and units treating cancer pain patients, establishing referral pathways necessities and adopted measures to improve the care of cancer patients.
A two-mediator serial mediation chain of the association between social isolation and impaired sleep in old age
Authors: Gyasi Razak M. , Abass Kabila , Segbefia Alexander Yao , Afriyie Kwadwo , Asamoah Edward , Boampong Mary Sefa , Adam Anokye M. , Owusu-Dabo Ellis 
Published: December 2022

AbstractPoor sleep is a long-term public health issue that has become increasingly prevalent among socially isolated older adults. However, research on the mechanisms explaining the link between social isolation and impaired sleep (IS) remains limited, particularly in low- and middle-income countries. This study explored the serial mediating effects of loneliness and mental distress on the association of social isolation with IS among Ghanaian older adults. We analyzed data from 1201 adults aged ≥ 50 from Ghana's AgeHeaPsyWel–HeaSeeB study (mean age = 66.14, SD = 11.85, age range = 50–111; women = 63.28%). Measures included the UCLA 3-item Loneliness Scale, modified Berkman–Syme Social Network Index, Sleep Quality Scale, and Mental Distress Questionnaire. We used bootstrapping techniques from Hayes’ PROCESS macro program to estimate the hypothesized serial mediation. Social isolation was significantly associated with IS (β = 0.242, p < 0.001). Crucially, social isolation indirectly predicted IS via three significant mediating pathways. Loneliness accounted for 17.6% (β = 0.054, CI = 0.096, 0.016), mental distress accounted for 6.5% (β = 0.020, 95% CI = 0.004, 0.040), and loneliness and mental distress accounted for 32.2% (β = 0.099, 95% CI = 0.065, 0.138) of the overall effect. The total mediating effect was 56.4%. These findings suggest that the social isolation-sleep link is respectively and serially explained by loneliness and mental distress. Social integrative interventions for sleep quality in old age should target mental and emotional well-being.
Multi-omics investigation reveals functional specialization of transcriptional cyclin dependent kinases in cancer biology
Authors: Donovan Micah G. , Galbraith Matthew D. , Espinosa Joaquin M. 
Published: December 2022

AbstractTranscriptional addiction is recognized as a valid therapeutic target in cancer, whereby the dependency of cancer cells on oncogenic transcriptional regulators may be pharmacologically exploited. However, a comprehensive understanding of the key factors within the transcriptional machinery that might afford a useful therapeutic window remains elusive. Herein, we present a cross-omics investigation into the functional specialization of the transcriptional cyclin dependent kinases (tCDKs) through analysis of high-content genetic dependency, gene expression, patient survival, and drug response datasets. This analysis revealed specialization among tCDKs in terms of contributions to cancer cell fitness, clinical prognosis, and interaction with oncogenic signaling pathways. CDK7 and CDK9 stand out as the most relevant targets, albeit through distinct mechanisms of oncogenicity and context-dependent contributions to cancer survival and drug sensitivity. Genetic ablation of CDK9, but not CDK7, mimics the effect on cell viability the loss of key components of the transcriptional machinery. Pathway analysis of genetic co-dependency and drug sensitivity data show CDK7 and CDK9 have distinct relationships with major oncogenic signatures, including MYC and E2F targets, oxidative phosphorylation, and the unfolded protein response. Altogether, these results inform the improved design of therapeutic strategies targeting tCDKs in cancer.
Synthesis, characterization and potential sensing application of carbon dots synthesized via the hydrothermal treatment of cow milk
Authors: Kumar Avinash , Kumar Ishant , Gathania Arvind K. 
Published: December 2022

AbstractCarbon quantum dots (CQDs) were synthesized in this study by hydrothermally treating cow milk. The procedure is simple, non-hazardous to the environment, and does not necessitate the use of any special instruments or chemicals. CQDs were practically almost circular when they were manufactured and had an average size of 7 nm. Carbon (67.36%), oxygen (22.73%), and nitrogen (9.91%) comprised the majority of their composition. They feature broad excitation-emission spectra, excitation-dependent emission, and temperature-dependent photoluminescence. They remained quite stable in the presence of a lot of salt, UV radiation, and storage time. Because luminescence quenching mechanisms are sensitive to and selective for Sn2+, they can be employed to create a nanosensor for detecting Sn2+.