bluuebunny/crossref_metadata_2025_split huggingface dataset:
A review of ICT-enabled learning for schoolgirls in Asia and its impacts on education equity
Authors: Liang Min , Lim Cher Ping , Park Jonghwi , Mendoza Norman B. 
Published: December 2022

AbstractThe education pathways and opportunities of schoolgirls in Asia are facing different challenges. The empirical studies have implemented Information and Communication Technology-enabled learning to expand such pathways and opportunities and promote education inclusiveness and equity. Through the Gender Analysis Framework, this review paper focuses on exploring and discussing how ICT-enabled learning may expand schoolgirls’ education pathways and opportunities in Asia for inclusive and equitable education. This review covers 30 studies that adopted ICT-enabled learning, synthesizes, and presents four key ICT-enabled learning approaches: Emerging technologies-enabled learning, Digital game-based learning, Mobile-enabled learning, and Computer-assisted learning. Our result discusses about how different approaches in this review (in)directly impact on schoolgirls’ access to assets, their practice and participation in learning activities, belief and perception of their own and other stakeholders’, and how policies accommodate these approaches. The review further suggests several guidelines to develop an inclusive learning environment enabled by ICT to education pathways and opportunities of schoolgirls, thereby enhancing education inclusiveness and equity.
Creation and validation of systems for product and process configuration based on data analysis
Authors: Frey Alex Maximilian , May Marvin Carl , Lanza Gisela 
Published: December 2022

AbstractIn the course of increasing individualization of customer demand, configurable products are gaining importance. Nowadays, variant-specific bills of materials and routings for configurable products are created with the help of rule-based configuration systems, so-called low-level configuration systems. The rules and generic structures on which such configuration systems are based are created manually today. This is challenging because it can be difficult and sometimes impossible to directly transfer expert knowledge into those systems. Furthermore documents that have already been created by experts in the past such as bills of material and routings contain relevant information as well which may be exploited to compose configuration systems. However, in the literature, there are no approaches yet to systematically transfer expert knowledge into configuration systems or to consider existing documents. In addition, the creation of such configuration systems is prone to error due to their complexity. Although there are already numerous approaches to the formal testing of configuration systems, approaches based on data analysis to support the validation of such systems have not yet been considered. Therefore, in this paper an approach is presented to automatically create low-level configuration systems by means of exemplary variant-specific bill of materials and routings using machine learning. The super bill of materials and the super routing as well as the dependencies between the product characteristics and the components respectively the operations are learned. Furthermore, it is shown how errors in the input data as well as errors in the resulting low-level configuration system can be detected by means of anomaly detection.
An innovative structural health assessment tool for existing precast concrete buildings using deep learning methods and thermal infrared satellite imagery
Authors: Kargin Madi , Lukpanov Rauan , Serenkov Andrey , Shaymagambetov Yerkin , Kargin Jumat , Garcia Reyes , Laory Irwanda 
Published: December 2022

AbstractCurrently, there is a limited number of tools that can be used to assess progressive damage of buildings in large-scale study areas. The effectiveness of such tools is also constrained by a lack of sufficient and reliable data from the buildings and the area itself. This research article presents an innovative framework for damage detection and classification of precast concrete (PC) buildings based on satellite infrared (IR) imagery. The framework uses heat leakage changes over time to assess the progressive damage of buildings. Multispectral satellite images are used for a spatial scanning and large-scale assessment of a study area. A deep learning object detection algorithm coupled with two pixel intensities classification approaches are utilized in the framework. The proposed framework is demonstrated on two case study areas (parts of Karaganda and Almaty cities) in Kazakhstan using a set of multitemporal satellite images. Overall, the proposed framework, in combination with a YOLOv3 algorithm, successfully detects 85% of the PC buildings in the study areas. The use of a peak heat leakage classification approach (in comparison to mean heat leakage classification) over the 4 years showed a good agreement with the proposed framework. On-site visual inspections confirmed that PC buildings that were classified as having “High damage probability” have indeed evident signs of deterioration, as well as a more heat leakage than the rest of the buildings in the study areas. Whilst the framework has some limitations such as its applicability to extreme continental climate and its low sensitivity to detect minor damage, the proposed innovative framework showed very promising results at detecting progressive damage in PC buildings. This article contributes towards developing more efficient long-term damage assessment tools for existing buildings in large urban areas.
Extended non-destructive testing for inline quality control of cleaning and pre-treatment processes in adhesive bonding of polymer blends
Authors: Geurts K. J. , Creemers F. , Campestrini P. , Van de Weyenberg I. , Noeske M. , Ihde J. , Pauly G. , Peschka M. , Vallée T. , Tornow C. , Brune K. 
Published: December 2022

AbstractThis investigation aims to demonstrate relevant pitfalls of exemplary surface contaminations on polymer blends with respect to quality assurance (QA) of adhesive joints, and highlights approaches of Extended Non-Destructive Testing (ENDT) for tackling the challenges inline during manufacture or repair processes. Greasy fingerprints were intentionally applied on surfaces of different acrylonitrile butadiene styrene (ABS) substrates before joining them with a two component (2C) polyurethane (PU) adhesive. Even when a required cleaning process was omitted before performing a pre-treatment with atmospheric-pressure plasma (APP), measured initial strengths of unaged joints did not reveal significant differences, if compared to joints produced following the qualified bonding process, which comprises a wipe-off wet cleaning before the pre-treatment step. However, after accelerated ageing mimicking the application conditions for joints, resulting strengths were more than 30% lower than for joints produced with the qualified bonding process. Thus, applying post-process random inspection of as-manufactured joints based on destructive testing, and merely evaluating initial joint strengths is not sufficient for assuring the reliability of such manufactured joints. Rather, it is recommended to encompass the intended or specified use within the formulation of the quality requirements. Introducing in-process ENDT procedures, and exemplarily monitoring the substrate surfaces with an Aerosol Wetting Test (AWT), is shown to identify latent fingerprints and to ensure a rapid and documented way to validate adherend surface quality before the application of the adhesive.Article Highlights

Surface quality assurance leads the way for process management decisions to safeguard relevant adherend properties before applying adhesive.

Using an Aerosol Wetting Test for plastic adherends allows for identifying latent fingerprints that would impair joint strength.

Extended Non-Destructive Testing facilitates embracing potential in-process contaminations when scheduling cleaning processes for adherends.
Measurement of body temperature in the oral cavity with a temperature sensor integrated with a powered toothbrush
Authors: Flyborg Johan , Renvert Stefan , Anderberg Peter , Isaksson Ulrika , Berglund Johan Sanmartin 
Published: December 2022

AbstractThis paper presents a method for collecting core body temperature data via a temperature sensor integrated into a powered toothbrush. The purpose is to facilitate the collection of temperature data without any extended effort from the user. Twelve participants use a powered toothbrush with a temperature sensor mounted on the brush head twice daily for two months. The obtained values are compared with those from a conventional fever thermometer approved for intraoral use. The results show that the temperature sensor–integrated powered toothbrush can measure the core body temperature and provide values comparable to those provided by a traditional oral thermometer. The use of the device can facilitate disease monitoring, fertility control, and security solutions for the elderly.
Developing a smart tool for integrated climate action planning (ICLAP 2050) in Asia-Pacific Cities
Authors: Sethi Mahendra , Mittal Shilpi 
Published: December 2022

AbstractIn light of the growing global environmental challenges, smart cities need to serve as testing workshops or labs to smartly tackle complex cross-sectional issues like jobs, seamless mobility, safety and security, sustained growth, while responding to the impending climate change too. This necessitates for developing a smart model or tool that integrates such varied but crucial climate concerns of a city into its direct decision-making and long-term planning. In this research, we conduct a literature review to have an overview of the state-of-the-affairs on urban climate planning in Asia-Pacific Cities covering China, Japan, India, Philippines, Singapore and Thailand. This is followed by an intensive theoretical understanding on the need of having a smart tool in urban climate action planning. This includes the study of recent urban climate metrics and tools, their different typologies based on key purpose, method, sectoral and geographical scope, and challenges and gaps in formulating smart urban climate tools. We then introduce the conceptual framework for integrated climate action planning (ICLAP) tool that transects spatial, statistical and bibliometric methods. We establish applicability of ICLAP in case of Indian cities by discerning climate vulnerabilities, GHG trends and relevant urban climate solutions. The paper eventually culminates with major scientific findings and policy recommendations, essentially underscoring more intensive and wider application of ICLAP like smart urban climate tools in local decision making and national urban policies duly supported by international scientific collaborations.
NetBCE: An Interpretable Deep Neural Network for Accurate Prediction of Linear B-Cell Epitopes
Authors: Xu Haodong , Zhao Zhongming 
Published: December 2022

Abstract
Identification of B-cell epitopes (BCEs) plays an essential role in the development of peptide vaccines and immuno-diagnostic reagents, as well as antibody design and production. In this work, we generated a large benchmark dataset comprising 124,879 experimentally supported linear epitope-containing regions in 3567 protein clusters from over 1.3 million B cell assays. Analysis of this curated dataset showed large pathogen diversity covering 176 different families. The accuracy in linear BCE prediction was found to strongly vary with different features, while all sequence-derived and structural features were informative. To search more efficient and interpretive feature representations, a ten-layer deep learning framework for linear BCE prediction, namely NetBCE, was developed. NetBCE achieved high accuracy and robust performance with the average area under the curve (AUC) value of 0.8455 in five-fold cross-validation through automatically learning the informative classification features. NetBCE substantially outperformed the conventional machine learning algorithms and other tools, with more than 22.06% improvement of AUC value compared to other tools using an independent dataset. Through investigating the output of important network modules in NetBCE, epitopes and non-epitopes tended to be presented in distinct regions with efficient feature representation along the network layer hierarchy. The NetBCE is freely available at https://github.com/bsml320/NetBCE.
A Gaussian process state-space model for sea surface temperature reconstruction from the alkenone paleotemperature proxy
Authors: Lee Taehee , Liu Jun S. , Lawrence Charles E. 
Published: December 2022

Abstract
Reconstructing past climate events relies on the relevant proxies and how they are related. Depending only on such relationships, however, could not be robust because only few proxy observations are usually available at each age. A state-space model employs a prior to make the hidden past climate events correlated with one another so that extreme inferences are precluded. Here, we construct a Gaussian process state-space model for reconstructing past sea surface temperatures from the alkenone paleotemperature proxy and apply the model to nine sediment cores with three different calibration curves and compare the results.
Glacier inventory and glacier changes (1994–2020) in the Upper Alaknanda Basin, Central Himalaya
Authors: Mishra Aditya , Nainwal H. C. , Bolch Tobias , Shah Sunil Singh , Shankar R. 
Published: December 2022

AbstractHimalayan glaciers have been shrinking and losing mass rapidly since 1970s with an enhanced rate after 2000. The shrinkage is, however, quite heterogeneous and it is important to document individual glacier characteristics and their changes at the basin scale. We present an updated glacier inventory of the Upper Alaknanda Basin (UAB), Central Himalaya for the year 2020 and report area, debris cover and length changes for the periods 1994–2006 and 2006–2020 based on remote-sensing data. We identified 198 glaciers, comprising an area of 354.6 ± 8.5 km2, and classified them according to their size and morphology. The glaciers of the basin lost 4.2 ± 2.9% (0.16 ± 0.11% a−1) of their frontal area (from 368.6 ± 9.2 to 353.0 ± 5.3 km2) from 1994 to 2020. The average retreat rate was higher in the period 2006–2020 (13.3 ± 1.8 m a−1) in comparison to 1994–2006 (9.3 ± 1.9 m a−1). However, the area change rate was similar for the two periods (0.14 ± 0.27% a−1 for 1994–2006 and 0.16 ± 0.19% a−1 for 2006–2020). The debris-covered area has increased by 13.4 ± 4.4% from 1994 to 2020. A comparison with previous studies in UAB indicates consistent area loss of ~0.15% a−1 since the 1960s.
New Industry Paradigms May Overwhelm Dynamic Capabilities: Different Competitive Dynamics Around Tesla and Chinese EV Start-Ups
Authors: Jiang Hong , Lu Feng 
Published: December 2022

ABSTRACTThis is a follow-up discussion about the Chinese electric vehicle (EV) sector, in particular the relative prospects of traditional automotive manufacturers and new ‘species’, four years after our last conversation on this topic (Jiang & Lu, 2018). It is also a response to Murmann and Vogt's (2022) latest article, which goes beyond Teece's (2019) focus on dynamic capabilities and constructs a systematic framework of firm capabilities to understand the competitive dynamics during a transformational shift of products.
Expatriates’ Embeddedness and Host Country Withdrawal Intention: A Social Exchange Perspective
Authors: Lehtonen Miikka J. , Koveshnikov Alexei , Wechtler Heidi 
Published: December 2022

ABSTRACTIn this study, we conceptualize the thus far little explored relationship between expatriate and host country as a form of social exchange governed by the norm of reciprocity. Drawing from social exchange theory and our analysis of 451 self-initiated expatriates (SIEs) living and working in the United Arab Emirates, we examine whether the degree of SIEs’ career and community embeddedness explains their host country withdrawal intention via enhanced perceived institutional trust and a more tolerant attitude toward workplace discrimination. Our results provide general support for our theoretical model and most of our hypotheses. In this way, our article makes three contributions. First, it suggests a novel way to conceptualize the relationship between SIEs and host country as a form of social exchange. Second, it differentiates between two dimensions of embeddedness and explicates how the two contribute to SIEs’ intentions to stay in the host country. Finally, the analysis theorizes and empirically tests two previously little explored mechanisms of enhanced institutional trust and a more tolerant attitude toward workplace discrimination through which SIEs’ host country embeddedness influences their host country withdrawal intentions.
Does infection play a role in post-tonsillectomy haemorrhage? A narrative review
Authors: Williamson A , Coleman H , Douglas C 
Published: December 2022

AbstractObjectivePost-tonsillectomy haemorrhage is an increasingly common cause of morbidity following tonsillectomy. Secondary post-tonsillectomy haemorrhage occurring more than 24 hours after an operation has long been attributed to post-operative infection; however, there is little evidence to support this hypothesis and the associated use of antibiotics in the current literature.MethodThis study looked at the aetiology and evidence-based management of post-tonsillectomy haemorrhage, and investigated the impact of bacterial infection and antimicrobials on the pathogenesis and clinical course of this complication.ResultsA number of peri-operative risk factors for post-tonsillectomy haemorrhage exist, and infective pathologies, including recurrent or chronic tonsillitis and group A streptococcus on blood cultures, may predispose to bleeding. Very few studies have shown a link between post-tonsillectomy haemorrhage and objective markers of infection such as pyrexia, raised inflammatory markers or positive microbiology cultures. The role of antibiotics in secondary post-tonsillectomy haemorrhage remains controversial, and numerous randomised, controlled trials of peri-operative antibiotics have shown no significant difference in bleeding rates between antibiotics and controls.ConclusionFurther trials investigating the role of antibiotics and more robust studies investigating the presence of bacterial infection at the time of bleeding may be required to determine the true role of infection in post-tonsillectomy haemorrhage.
Lecidea glacierensis (Lecideaceae), a new lichen species from China revealed by morphology and molecular phylogenetics
Authors: Mamut Reyim , Jiamahat Aerguli , Abbas Abdulla 
Published: December 2022

AbstractAccording to morphological and molecular data, a new species of Lecidea s. str., Lecidea glacierensis, is described from Xinjiang Province, China. It is distinctive due to its well-developed, regularly areolate to bullate thallus, and its habitat on calciferous rocks. This species was collected mostly in the area of Tianshan No.1 Glacier, which is located at an elevation of 3454 m and c. 118 km south-west of Urumqi and is considered to be one of the most important dryland glacier areas in Asia. An illustration and detailed description of the taxon are provided.
Chicago-The City That Works
Authors: Haider Donald 
Published: December 2022

Chicago is Richard J. Daley and Richard J. Daley is Chicago—puckish, often provincial, mostly pragmatic, and above all—fiercely proud. As Len O'Connor observed of the Mayor, “Surely the nation has never seen his like before—nor is it likely to see anyone quite like him again.” The same may be said of Chicago, which Carl Sandburg called, “The City of Big Shoulders.” “Chicago has never been a genteel town,” notes political scientist Milton Rakove, author of the most recent haiography of the city's politics. “It has always been, and still is today, a lusty, brawling, sprawling city.” It is appropriate that political scientists gather in Chicago during our bicentennial celebration. Chicago is not only a significant link to our nation's past, but may well be our window to the future.Where Chicago's toughness, unsophisticated and unreformed demeanor may offend some, the city's abundance of excellent restaurants will quickly disarm even its most vehement critics. The city is unique and perhaps unparalleled among convention cities with respect to culinary offerings—variety, ambiance, price, and accessibility. For those more timid souls whose range of gastronomic inquiry is limited to within eight blocks of thePalmer House, let me suggest three mainstays of downtown dining.Berghoff, 17 W. Adams, is a traditional favorite of convention goers. It is an inexpensive German restaurant and brauhaus which specializes in Hungarian goulash, sauerbraten, and schnitzel.The Blackhawk, 139 N. Wabash, is another favorite of Chicagoans for luncheon and dinner with excellent prime beef and the house specialty, Boston scrod. For greater variety and a touch of French cooking, I suggest you try Binyon's at 327 W. Plymouth Court, located across the street from the Dirksen Federal Office Building.
The sound change of oralization in Mewahang
Authors: Gerber Pascal 
Published: December 2022

AbstractThis paper discusses the sound change of oralization in the Mewahang language (Eastern Kiranti, Trans-Himalayan/Sino-Tibetan) spoken in eastern Nepal. The sound change of oralization turned syllable-final nasals into homorganic oral stops when followed by voiceless obstruents. This sound change constitutes a diagnostic innovation of Mewahang with regard to its closest relatives Lohorung and Yamphu. In this paper, the process of oralization in both compounding as well as derivational and inflectional morphology is described and illustrated with primary data collected in fieldwork. The explanatory potential of the sound change for synchronic peculiarities in the verbal morphology and morphophonology is discussed, and an overview of exceptions to the sound change is provided.
A qualitative process evaluation of social recovery therapy for enhancement of social recovery in first-episode psychosis (SUPEREDEN3)
Authors: Gee Brioney , Berry Clio , Hodgekins Joanne , Greenwood Kathryn , Fitzsimmons Michael , Lavis Anna , Notley Caitlin , Pugh Katherine , Birchwood Max , Fowler David 
Published: December 2022

AbstractBackground:Many individuals with first-episode psychosis experience severe and persistent social disability despite receiving specialist early intervention. The SUPEREDEN3 trial assessed whether augmenting early intervention in psychosis services with Social Recovery Therapy (SRT) would lead to better social recovery.Aims:A qualitative process evaluation was conducted to explore implementation and mechanisms of SRT impact from the perspective of SUPEREDEN3 participants.Method:A subsample of SUPEREDEN3 trial participants (n= 19) took part in semi-structured interviews, which were transcribed verbatim and analysed thematically. Trial participants were early intervention service users aged 16–35 years with severe and persistent social disability. Both SRT plus early intervention and early intervention alone arm participants were interviewed to facilitate better understanding of the context in which SRT was delivered and to aid identification of mechanisms specific to SRT.Results:The six themes identified were used to generate an explanatory model of SRT’s enhancement of social recovery. Participant experiences highlight the importance of the therapist cultivating increased self-understanding and assertively encouraging clients to face feared situations in a way that is perceived as supportive, while managing ongoing symptoms. The sense of achievement generated by reaching targets linked to personally meaningful goals promotes increased self-agency, and generates hope and optimism.Conclusions:The findings suggest potentially important processes through which social recovery was enhanced in this trial, which will be valuable in ensuring the benefits observed can be replicated. Participant accounts provide hope that, with the right support, even clients who have persistent symptoms and the most severe disability can make a good social recovery.