bluuebunny/crossref_metadata_2025_split huggingface dataset:
A detailed library perspective on nearly unsupervised information extraction workflows in digital libraries
Authors: Kroll Hermann , Pirklbauer Jan , Plötzky Florian , Balke Wolf-Tilo 
Published: June 2023

AbstractInformation extraction can support novel and effective access paths for digital libraries. Nevertheless, designing reliable extraction workflows can be cost-intensive in practice. On the one hand, suitable extraction methods rely on domain-specific training data. On the other hand, unsupervised and open extraction methods usually produce not-canonicalized extraction results. This paper is an extension of our original work and tackles the question of how digital libraries can handle such extractions and whether their quality is sufficient in practice. We focus on unsupervised extraction workflows by analyzing them in case studies in the domains of encyclopedias (Wikipedia), Pharmacy, and Political Sciences. As an extension, we analyze the extractions in more detail, verify our findings on a second extraction method, discuss another canonicalizing method, and give an outlook on how non-English texts can be handled. Therefore, we report on opportunities and limitations. Finally, we discuss best practices for unsupervised extraction workflows.
MVDet: multi-view multi-class object detection without ground plane assumption
Authors: Park Sola , Yang Seungjin , Lee Hyuk-Jae 
Published: June 2023

AbstractAlthough many state-of-the-art methods of object detection in a single image have achieved great success in the last few years, they still suffer from the false positives in crowd scenes of the real-world applications like automatic checkout. In order to address the limitations of single-view object detection in complex scenes, we propose MVDet, an end-to-end learnable approach that can detect and re-identify multi-class objects in multiple images captured by multiple cameras (multi-view). Our approach is based on the premise that incorrect detection results in a specific view can be eliminated using precise cues from other views, given the availability of multi-view images. Unlike most existing multi-view detection algorithms, which assume that objects belong to a single class on the ground plane, our approach can classify multi-class objects without such assumptions and is thus more practical. To classify multi-class objects, we propose an integrated architecture for region proposal, re-identification, and classification. Additionally, we utilize the epipolar geometry constraint to devise a novel re-identification algorithm that does not require assumptions about ground plane assumption. Our model demonstrates competitive performance compared to several baselines on the challenging MessyTable dataset.
Artificial intelligence-based solutions for climate change: a review
Authors: Chen Lin , Chen Zhonghao , Zhang Yubing , Liu Yunfei , Osman Ahmed I. , Farghali Mohamed , Hua Jianmin , Al-Fatesh Ahmed , Ihara Ikko , Rooney David W. , Yap Pow-Seng 
Published: June 2023

AbstractClimate change is a major threat already causing system damage to urban and natural systems, and inducing global economic losses of over $500 billion. These issues may be partly solved by artificial intelligence because artificial intelligence integrates internet resources to make prompt suggestions based on accurate climate change predictions. Here we review recent research and applications of artificial intelligence in mitigating the adverse effects of climate change, with a focus on energy efficiency, carbon sequestration and storage, weather and renewable energy forecasting, grid management, building design, transportation, precision agriculture, industrial processes, reducing deforestation, and resilient cities. We found that enhancing energy efficiency can significantly contribute to reducing the impact of climate change. Smart manufacturing can reduce energy consumption, waste, and carbon emissions by 30–50% and, in particular, can reduce energy consumption in buildings by 30–50%. About 70% of the global natural gas industry utilizes artificial intelligence technologies to enhance the accuracy and reliability of weather forecasts. Combining smart grids with artificial intelligence can optimize the efficiency of power systems, thereby reducing electricity bills by 10–20%. Intelligent transportation systems can reduce carbon dioxide emissions by approximately 60%. Moreover, the management of natural resources and the design of resilient cities through the application of artificial intelligence can further promote sustainability.
Supervisory knowing in practice across medical specialities
Authors: Noble Christy , Hilder Joanne , Billett Stephen , Teodorczuk Andrew , Ajjawi Rola 
Published: June 2023

AbstractClinical supervisors play key roles in facilitating trainee learning. Yet combining that role with patient care complicates both roles. So, we need to know how both roles can effectively co-occur. When facilitating their trainees’ learning through practice, supervisors draw on their skills - clinical and supervisory - and available opportunities in their practice. This process can be conceptualised as supervisory knowing in practice (or contextual knowing) and offers ways to elaborate on how facilitating trainees’ learning can be optimised. The practice-based study presented and discussed here examined clinical supervisors’ knowing in practice related to facilitating trainee learning, across three medical specialities. Nineteen clinical supervisors from emergency medicine, internal medicine and surgery, were interviewed about their roles and engagement with trainees. Interview transcripts were analysed in two stages. Firstly, a framework analysis, informed by interdependent learning theory was conducted, focussing on affordances and individual engagement. Secondly, drawing on practice theory, a further layer of analysis was undertaken interrogating supervisors’ knowing in practice. We identified two common domains of supervisor practice used to facilitate trainee learning: (1) orientating and assessing trainees’ readiness (or capabilities), (2) sequencing and enriching pedagogic practices. Yet across the speciality groups the supervisors’ knowing in practice differed and were shaped by a trio of: (i) disciplinary practices, (ii) situational requirements and (iii) clinician preference. Overall, we offer a new reading of clinical supervision as practice differences generated distinct supervisory knowing in practice. These findings emphasise clinical supervision as fundamentally entwined in the speciality’s practice; and reinforce alignments with patient care.
Flame Dynamics Modelling Using Artificially Thickened Models
Authors: Rathore Omer , Navarro-Martinez Salvador 
Published: June 2023

AbstractThickened flame models are prolific in the literature and offer an effective method of resolving flame dynamics on coarse LES meshes. The current state of the art relies heavily on the use of efficiency functions to compensate for impaired wrinkling of the thickened flame. However in practice these functions can involve parameters that are difficult to determine, perform poorly outside of certain ranges or require a posteriori analysis to evaluate performance. An alternative based on a generalised thickening is evaluated across a range of canonical configurations. The approach is demonstrated to perform well across a large range of thickening factors in capturing phenomena such as localised quenching and pinch off as well as generation of flame surface. Including good performance even in the case of large flame dynamics under acoustic forcing where the model has a clear advantage over DNS in achieving grid independence. Finally the approach is unified into an Large Eddy Simulation/Adaptive Mesh Refinement framework and applied to a turbulent Bunsen flame. The results show that even if the internal flame structure is poorly resolved on the original mesh, the global system behaviour is well predicted and compares favourably with other approaches.
Biocontrol of clubroot disease: how successful are endophytic fungi and bacteria?
Authors: Auer Susann , Ludwig-Müller Jutta 
Published: June 2023

AbstractThe commercial aspect of growing Brassica crops has always been influenced by the worldwide occurrence of the clubroot pathogen, Plasmodiophora brassicae. Clubroot symptoms reduce crop yield dramatically and the resilient protist is hard to eradicate from infested soils. Chemical treatments are not so efficient and their use is allowed only in a few areas of the world, none of them in the EU. The majority of clubroot control is mediated by using resistant crops, but not all species have good or durable resistance sources available, and these can be overcome by evolving or new Plasmodiophora pathotypes. Some commercially available biocontrol agents have been tested and found to reduce clubroot on crops such as rapeseed, cauliflower and Chinese cabbage to some extent. More biocontrol organisms have been isolated and described in recent decades but for many commercial application is still a long way off. In this review we summarize trends for bacterial and fungal endophytes for clubroot biocontrol as well as mechanisms behind the effects reported, such as antibiosis, defense induction or competition for space and nutrients. There are indeed plenty of studies on biocontrol of clubroot but not many have reached a point where the biocontrol agents are ready to be applied at field scale. The potential of endophytic microbes in pest management against clubroot disease is huge.
Loneliness and Mood
Authors: Spiegel Thomas J. 
Published: June 2023

AbstractLoneliness is commonly conceived of as a topic under the purview of psychology. Empirical research on loneliness utilizes a definition of psychology as essentially subjective, i.e. as a first-personal mental property an individual can have. As a first-personal mental property, subjects have, as it were, privileged access to their state of being lonely. Rehearsing some well-known arguments from later Wittgenstein, I argue that loneliness – contrary to an unargued assumption present in several academic engagements – is not subjective in the sense that whether or not a person is lonely does not in all cases hinge on that person’s subjective mental states. This becomes apparent when considering cases of alienation from self-knowledge (Moran 2001). Using Heidegger’s notion of being-in-the-world and being-with I argue that such cases from alienation point towards the notion that loneliness is not merely a subjective feeling, but a categorically different privation of the fundamental mode of being with others.
Heating or ginger extract reduces the content of Pinellia ternata lectin in the raphides of Pinellia tuber
Authors: Liu Yan , Nose Itsuki , Terasaka Kazuyoshi , Fueki Tsukasa , Makino Toshiaki 
Published: June 2023

AbstractPinellia tuber, the dried tuber of Pinellia ternata, causes a very strong acridity sensation in the oral and laryngopharynx mucosa when taken orally in its unprocessed form. In traditional Chinese medicine (TCM), this sensation has been called "toxicity", and Pinellia tuber must be processed using ginger extract, licorice, or alum. In Japanese traditional Kampo medicine, since “toxicity” can be eliminated by decocting, it should not be processed. However, little is known about the mechanism underlying the "detoxification" of Pinellia tubers. In this study, we produced murine antiserum using recombinant P. ternata lectin (PTL), developed an immuno-fluorescence staining method for PTL in the needle-shaped crystals (raphides) that were prepared by petroleum ether extraction (PEX) from Pinellia tuber, and elucidated the mechanism of the processing of Pinellia tuber using heat or ginger extract. After heating the raphides in water, the amount of PTL contained in the raphides was significantly reduced by the immunostaining, although the shape of the raphides was not changed. Incubating raphides with dried ginger extract also significantly reduced the amount of PTL in the raphides in a concentration-dependent manner. By the activity-guided fractionation of ginger extract, the active ingredients in the ginger extract were oxalic acid, tartaric acid, malic acid, and citric acid. Among these four organic acids, oxalic acid mainly contributed to the effect of dried ginger extract by its content in ginger extract and its activity. These results exhibit scientific evidences for the traditional theories of processing to "detoxify" Pinellia tuber in TCM and Kampo medicine.
Graphical abstract
Real-time integration between Microsoft HoloLens 2 and 3D Slicer with demonstration in pedicle screw placement planning
Authors: Pose-Díez-de-la-Lastra Alicia , Ungi Tamas , Morton David , Fichtinger Gabor , Pascau Javier 
Published: June 2023

Abstract
Purpose
Up to date, there has been a lack of software infrastructure to connect 3D Slicer to any augmented reality (AR) device. This work describes a novel connection approach using Microsoft HoloLens 2 and OpenIGTLink, with a demonstration in pedicle screw placement planning.

Methods
We developed an AR application in Unity that is wirelessly rendered onto Microsoft HoloLens 2 using Holographic Remoting. Simultaneously, Unity connects to 3D Slicer using the OpenIGTLink communication protocol. Geometrical transform and image messages are transferred between both platforms in real time. Through the AR glasses, a user visualizes a patient’s computed tomography overlaid onto virtual 3D models showing anatomical structures. We technically evaluated the system by measuring message transference latency between the platforms. Its functionality was assessed in pedicle screw placement planning. Six volunteers planned pedicle screws' position and orientation with the AR system and on a 2D desktop planner. We compared the placement accuracy of each screw with both methods. Finally, we administered a questionnaire to all participants to assess their experience with the AR system.

Results
The latency in message exchange is sufficiently low to enable real-time communication between the platforms. The AR method was non-inferior to the 2D desktop planner, with a mean error of 2.1 ± 1.4 mm. Moreover, 98% of the screw placements performed with the AR system were successful, according to the Gertzbein–Robbins scale. The average questionnaire outcomes were 4.5/5.

Conclusions
Real-time communication between Microsoft HoloLens 2 and 3D Slicer is feasible and supports accurate planning for pedicle screw placement.
Two-dimensional carbon material incorporated and PDMS-coated conductive textile yarns for strain sensing
Authors: Islam G. M. Nazmul , Collie Stewart , Gould Maree , Ali M. Azam 
Published: June 2023

AbstractIn recent years, innovative technology based upon conductive textile yarns has undergone rapid growth. Nanocomposite-based wearable strain sensors hold great promise for a variety of applications, but specifically for human body motion detection. However, improving the sensitivity of these strain sensors while maintaining their durability remains a challenge in this arena. In the present investigation, polydopamine-treated and two-dimensional nanostructured material, e.g., reduced graphene oxide (rGO)-coated conductive cotton and polyester yarns, was encapsulated using polydimethylsiloxane (PDMS) to develop robustly wash durable and mechanically stable conductive textile yarns. Flexibility and extensibility of all textile yarns of every stage were analyzed using texture analysis. The chemical interactions essential for measuring coating performance among all components were confirmed by Fourier transform infrared and scanning electron microscopy. The rGO-coated cotton and polyester yarns exhibited an extensibility of 11.77 and 73.59%, respectively. PDMS-coated conductive cotton and polyester yarns also showed an electrical resistance of 12.22 and 20.33 kΩ, respectively, after 10 washing cycles. The PDMS coating layer acted as a physical barrier against impairment of conductivity during washing. Finally, the mechanically stable and flexible conductive textile yarns were integrated into a knitted cotton glove and armband to create a highly stretchable and flexible textile-based strain sensor for measuring finger and elbow movement. Truly wearable garments able to record proprioceptive maps are critical for further developing this field of application.
Emerging roles of the long non-coding RNA NEAT1 in gynecologic cancers
Authors: Farzaneh Maryam , Abouali Gale Dari Mahrokh , Anbiyaiee Amir , Najafi Sajad , Dayer Dian , Mousavi Salehi Abdolah , Keivan Mona , Ghafourian Mehri , Uddin Shahab , Azizidoost Shirin 
Published: June 2023

AbstractGynecologic cancers are a worldwide problem among women. Recently, molecular targeted therapy opened up an avenue for cancer diagnosis and treatment. Long non-coding RNAs (lncRNAs) are RNA molecules (> 200 nt) that are not translated into protein, and interact with DNA, RNA, and proteins. LncRNAs were found to play pivotal roles in cancer tumorigenesis and progression. Nuclear paraspeckle assembly transcript 1 (NEAT1) is a lncRNA that mediates cell proliferation, migration, and EMT in gynecologic cancers by targeting several miRNAs/mRNA axes. Therefore, NEAT1 may function as a potent biomarker for the prediction and treatment of breast, ovarian, cervical, and endometrial cancers. In this narrative review, we summarized various NEAT1-related signaling pathways that are critical in gynecologic cancers.
Graphical abstract
Does threat trigger prosociality? The relation between basic individual values, threat appraisals, and prosocial helping intentions during the COVID-19 pandemic
Authors: Politi Emanuele , Van Assche Jasper , Lüders Adrian , Sankaran Sindhuja , Anderson Joel , Green Eva G.T. 
Published: June 2023

AbstractProsociality is often considered as quintessential in coping with the threats of health emergencies. As previous research has suggested, prosocial behaviors are shaped by both dispositional factors and situational cues about the helping situation. In the present research, we investigated whether “bonding” types of prosociality, helping directed towards close others within one’s social network, and “bridging” types of prosociality, helping directed towards vulnerable people across group boundaries, are predicted by basic individual values and threat appraisals concerning COVID-19. During the pandemic, we conducted a cross-sectional study in the US and India (Ntotal = 954), using the Schwartz value inventory and a multifaceted measure of threat assessment to predict prosocial helping intentions. After controlling for other value and threat facets, self-transcendence values and threat for vulnerable groups uniquely predicted both bonding and bridging types of prosociality. Furthermore, threat for vulnerable groups partially mediated the effect of self-transcendence on prosocial helping intentions: People who endorsed self-transcendent values were particularly concerned by the effect of the pandemic on vulnerable groups, and thus willing to engage in prosocial behaviours to help those in need. Our findings support the idea that prosociality is stimulated by empathic concerns towards others in need and underline the importance for future research to consider the broad spectrum of threats appraised by people during health emergencies.
The effect of childhood adversity on mental health in young adults: a longitudinal study
Authors: Villanueva Lidón , Adrián Juan Emilio , Gomis-Pomares Aitana 
Published: June 2023

AbstractChildhood adversity has been consistently linked to negative outcomes in children’s mental health. Nonetheless, little is known about the lifelong effects of these experiences during a stage of development with high rates of both internalising and externalising problems: emerging adulthood. Therefore, the present study analyses the relation between self-reported exposure to a wide range of adversities in a community sample of young adults and externalising (deviant behaviour) and internalising (stress, anxiety and depression) outcomes. In this two-time prospective study, 490 young adults (62.4% females) with ages ranging from 18 to 20 years (M = 18.90) were interviewed in person first and then over an online questionnaire one year later (N = 84). Linear regressions were performed for each mental health outcome controlling for demographic variables. Physical abuse emerged as the best predictor of deviant behaviour in both time periods in a univocal relation, whereas internalising outcomes seemed to have a broader multifactorial association with distinct types of adversities only in Time 1. These findings, along with the results of the stability externalising consequences derived from physical abuse, emphasise the importance of prevention and intervention strategies to diminish the transmission of these maladaptive strategies in later periods of life.
Ethanol and Methane Production from the Organic Fraction of Municipal Solid Waste in a Two-Stage Process
Authors: Mosquera-Toscano Hamilton Guillermo , González-Barceló Oscar , Valdez-Vazquez Idania , Durán-Moreno Alfonso 
Published: June 2023

AbstractIn the present study, the OFMSW was utilized for ethanol and methane production in a two-stage process. First, the OFMSW was fermented by adjusting different levels of total solids (10%, 20%, and 29%) and a yeast dose (6, 12, and 24 g/kgOFMSW) for bioaugmentation with Saccharomyces cerevisiae. A control treatment without bioaugmentation was used for benchmarking. In the self-fermentation of the OFMSW with its indigenous microbiota, lactic acid was mainly produced, followed by ethanol and acetic acid, where a maximum ethanol production of 113 ± 2 gCOD/kgTS, corresponding to 10.8 ± 0.4 g/L, at 20% of total solids was observed. The results showed that in all treatments with bioaugmentation, regardless of the content of total solids, the main metabolites were ethanol, lactic acid, and acetic acid, which represented more than 95% of the total metabolites. The ethanol concentration was increased by increasing the total solids and the yeast dose. The highest ethanol production was 407 ± 3 gCOD/kgTS with the bioaugmentation of 24 g/kgOFMSW and 20% of total solids, whereas the maximum ethanol concentration of 43.4 ± 0.1 g/L was obtained with bioaugmentation of 12 g/kgOFMSW and 29%. The methane potential of the raw OFMSW was 329 ± 5 NL-CH4/kgVS, whereas the solid digestates resulting from the fermentation exhibited similar or even higher methane yields than raw OFMSW. A maximum methane potential of 464 ± 2 NL-CH4/kgVS from the solid digestate obtained after fermentation of the OFMSW with bioaugmentation of 6 g/kgOFMSW of yeast and 10% of total solids was achieved. Thus, large amounts of ethanol and methane were achieved without the application of pretreatment and/or enzymatic hydrolysis, which implies a low-cost alternative for the production of biofuels.