bluuebunny/crossref_metadata_2025 huggingface dataset:
Analyzing neural network behavior through deep statistical model checking
Authors: Gros Timo P. , Hermanns Holger , Hoffmann Jörg , Klauck Michaela , Steinmetz Marcel
Published: December 2022

Neural networks (NN) are taking over ever more decisions thus far taken by humans, even though verifiable system-level guarantees are far out of reach. Neither is the verification technology available, nor is it even understood what a formal, meaningful, extensible, and scalable testbed might look like for such a technology. The present paper is an attempt to improve on both the above aspects. We present a family of formal models that contain basic features of automated decision-making contexts and which can be extended with further orthogonal features, ultimately encompassing the scope of autonomous driving. Due to the possibility to model random noise in the decision actuation, each model instance induces a Markov decision process (MDP) as verification object. The NN in this context has the duty to actuate (near-optimal) decisions. From the verification perspective, the externally learnt NN serves as a determinizer of the MDP, the result being a Markov chain which as such is amenable to statistical model checking. The combination of an MDP and an NN encoding the action policy is central to what we call “deep statistical model checking” (DSMC). While being a straightforward extension of statistical model checking, it enables to gain deep insight into questions like “how high is the NN-induced safety risk?”, “how good is the NN compared to the optimal policy?” (obtained by model checking the MDP), or “does further training improve the NN?”. We report on an implementation of DSMC inside the ModestToolset in combination with externally learnt NNs, demonstrating the potential of DSMC on various instances of the model family, and illustrating its scalability as a function of instance size as well as other factors like the degree of NN training.
Exploring the benefits and dis-benefits of climate migration as an adaptive strategy along the rural-peri-urban continuum in Namibia
Authors: Thorn Jessica P. R. , Nangolo Penelao , Biancardi Rebeca Aleu , Shackleton Sheona , Marchant Robert A. , Ajala Olayinka , Delgado Guillermo , Mfune John K. E. , Cinderby Steve , Hejnowicz Adam P.
Published: December 2022

The scale of climate migration across the Global South is expected to increase during this century. By 2050, millions of Africans are likely to consider, or be pushed into, migration because of climate hazards contributing to agricultural disruption, water and food scarcity, desertification, flooding, drought, coastal erosion, and heat waves. However, the migration-climate nexus is complex, as is the question of whether migration can be considered a climate change adaptation strategy across both the rural and urban space. Combining data from household surveys, key informant interviews, and secondary sources related to regional disaster, demographic, resource, and economic trends between 1990 and 2020 from north central and central dryland Namibia, we investigate (i) human migration flows and the influence of climate hazards on these flows and (ii) the benefits and dis-benefits of migration in supporting climate change adaptation, from the perspective of migrants (personal factors and intervening obstacles), areas of origin, and areas of destination. Our analysis suggests an increase in climate-related push factors that could be driving rural out-migration from the north central region to peri-urban settlements in the central region of the country. While push factors play a role in rural-urban migration, there are also several pull factors (many of which have been long-term drivers of urban migration) such as perceived higher wages, diversity of livelihoods, water, health and energy provisioning, remittances, better education opportunities, and the exchange of non-marketed products. Migration to peri-urban settlements can reduce some risks (e.g. loss of crops and income due to climate extremes) but amplify others (e.g. heat stress and insecure land tenure). Adaptation at both ends of the rural–urban continuum is supported by deeply embedded linkages in a model of circular rural–urban-rural migration and interdependencies. Results empirically inform current and future policy debates around climate mobilities in Namibia, with wider implications across Africa.

Graphical abstract
Coarse Mesh Superconvergence in Isogeometric Frequency Analysis of Mindlin–Reissner Plates with Reduced Integration and Quadratic Splines
Authors: Xu Xiaolan , Lin Zhiwei , Hou Songyang , Wang Dongdong
Published: December 2022

A frequency accuracy study is presented for the isogeometric free vibration analysis of Mindlin–Reissner plates using reduced integration and quadratic splines, which reveals an interesting coarse mesh superconvergence. Firstly, the frequency error estimates for isogeometric discretization of Mindlin–Reissner plates with quadratic splines are rationally derived, where the degeneration to Timoshenko beams is discussed as well. Subsequently, in accordance with these frequency error measures, the shear locking issue corresponding to the full integration isogeometric formulation is elaborated with respect to the frequency accuracy deterioration. On the other hand, the locking-free characteristic for the isogeometric formulation with uniform reduced integration is illustrated by its superior frequency accuracy. Meanwhile, it is found that a frequency superconvergence of sixth order accuracy arises for coarse meshes when the reduced integration is employed for the isogeometric free vibration analysis of shear deformable beams and plates, in comparison with the ultimate fourth order accuracy as the meshes are progressively refined. Furthermore, the mesh size threshold for the coarse mesh superconvergence is provided as well. The proposed theoretical results are consistently proved by numerical experiments.
Habits Over Routines: Remarks on Control Room Practices and Control Room Studies
Authors: Silvast Antti , Virtanen Mikko J. , Abram Simone
Published: December 2022

The evolution of computer tools has had profound impacts on many aspects of control rooms and control room studies. In this paper, we discuss some key assumptions underpinning these studies based on a new case of the electricity distribution control rooms, where the reliability of the electricity infrastructure is managed by a combination of planning and real-time maintenance. Some of these practices have changed remarkably little over the past decades – partially because they have been considered to have been ‘digitalized’ since the 1950s and have continued to amass digital solutions from different periods. Hence, the gradual transformation of control room work demands nuanced attention, both conceptual and empirical. To outline a framework for this work, we provide a conceptualization of organizational routines, habits, and reflectivity and synthesize existing CSCW and control room literature. We then present an empirical study that demonstrates our concepts and shows how they can be applied to study cooperative work. By addressing these aims the paper complements, and advances, the important topics recognized in this special theme issue and hence develops new research openings in CSCW. We address the necessity to avoid implicit determinism when analyzing new digital support tools and suggest focusing on how working habits mediate social changes, distribution, and decentralization in representing the power distribution in control rooms.
Unambiguous Identification of Glucose-Induced Glycation in mAbs and other Proteins by NMR Spectroscopy
Authors: Moises Jennifer E. , Regl Christof , Hinterholzer Arthur , Huber Christian G. , Schubert Mario
Published: December 2022

Objective

Glycation is a non-enzymatic and spontaneous post-translational modification (PTM) generated by the reaction between reducing sugars and primary amine groups within proteins. Because glycation can alter the properties of proteins, it is a critical quality attribute of therapeutic monoclonal antibodies (mAbs) and should therefore be carefully monitored. The most abundant product of glycation is formed by glucose and lysine side chains resulting in fructoselysine after Amadori rearrangement. In proteomics, which routinely uses a combination of chromatography and mass spectrometry to analyze PTMs, there is no straight-forward way to distinguish between glycation products of a reducing monosaccharide and an additional hexose within a glycan, since both lead to a mass difference of 162 Da.

Methods

To verify that the observed mass change is indeed a glycation product, we developed an approach based on 2D NMR spectroscopy spectroscopy and full-length protein samples denatured using high concentrations of deuterated urea.

Results

The dominating β-pyranose form of the Amadori product shows a characteristic chemical shift correlation pattern in 1H-13C HSQC spectra suited to identify glucose-induced glycation. The same pattern was observed in spectra of a variety of artificially glycated proteins, including two mAbs, as well as natural proteins.

Conclusion

Based on this unique correlation pattern, 2D NMR spectroscopy can be used to unambiguously identify glucose-induced glycation in any protein of interest. We provide a robust method that is orthogonal to MS-based methods and can also be used for cross-validation.
Three Psychometric-Model-Based Option-Scored Multiple Choice Item Design Principles that Enhance Instruction by Improving Quiz Diagnostic Classification of Knowledge Attributes
Authors: Stout William , Henson Robert , DiBello Lou
Published: December 2022

Three IRT diagnostic-classification-modeling (DCM)-based multiple choice (MC) item design principles are stated that improve classroom quiz student diagnostic classification. Using proven-optimal maximum likelihood-based student classification, example items demonstrate that adherence to these item design principles increases attribute (skills and especially misconceptions) correct classification rates (CCRs). Simple formulas compute these needed item CCRs. By use of these psychometrically driven item design principles, hopefully enough attributes can be accurately diagnosed by necessarily short MC-item-based quizzes to be widely instructionally useful. These results should then stimulate increased use of well-designed MC item quizzes that target accurately diagnosing skills/misconceptions, thereby enhancing classroom learning.
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

The 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

In 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

Currently, 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

This 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

This 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

In 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

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.
Complexity Science
Authors: Jensen Henrik Jeldtoft
Published: December 2022

Ecosystems, the human brain, ant colonies, and economic networks are all complex systems displaying collective behaviour, or emergence, beyond the sum of their parts. Complexity science is the systematic investigation of these emergent phenomena, and stretches across disciplines, from physics and mathematics, to biological and social sciences. This introductory textbook provides detailed coverage of this rapidly growing field, accommodating readers from a variety of backgrounds, and with varying levels of mathematical skill. Part I presents the underlying principles of complexity science, to ensure students have a solid understanding of the conceptual framework. The second part introduces the key mathematical tools central to complexity science, gradually developing the mathematical formalism, with more advanced material provided in boxes. A broad range of end of chapter problems and extended projects offer opportunities for homework assignments and student research projects, with solutions available to instructors online. Key terms are highlighted in bold and listed in a glossary for easy reference, while annotated reading lists offer the option for extended reading and research.
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

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

Himalayan 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

This 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

In 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

Objective

Post-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.

Method

This 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.

Results

A 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.

Conclusion

Further 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.
Localized compressional self-heating in magnetic islands
Authors: Villa Daniele , Dubuit Nicolas , Agullo Olivier , Poyé Alexandre , Garbet Xavier , Smolyakov Andrei
Published: December 2022

A spontaneous heating process is found to arise in a system where a magnetic island is present due to a linearly unstable tearing mode. The parity, the relative phases and the structure of the fields determined linearly by the tearing mode cause the compression of the plasma in the direction parallel to the magnetic field to heat the plasma in the vicinity of the separatrix in the nonlinear phase. Using a six-field electromagnetic fluid model, the process is found to be present in both two-dimensional single-helicity and three-dimensional multi-helicity simulations with both symmetric and asymmetric magnetic equilibrium profiles. A noteworthy feature of the model is that the higher-order compression terms responsible for the heating process are retained in the equations. The process is believed to be linked to experimental observations of localized hot-spots on externally induced magnetic islands.
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

According 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

This 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

Background:

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.
Best Practices for Ethical Conduct of Misinformation	Research
Authors: Greene Ciara M. , de Saint Laurent Constance , Murphy Gillian , Prike Toby , Hegarty Karen , Ecker Ullrich K. H.
Published: December 2022

Abstract: Misinformation can have noxious impacts on cognition, fostering the formation of false beliefs, retroactively distorting memory for events, and influencing reasoning and decision-making even after it has been credibly corrected. Researchers investigating the impacts of real-world misinformation are therefore faced with an ethical issue: they must consider the immediate and long-term consequences of exposing participants to false claims. In this paper, we first present an overview of the ethical risks associated with real-world misinformation. We then report results from a scoping review of ethical practices in misinformation research. We investigated (1) the extent to which researchers report the details of their ethical practices, including issues of informed consent and debriefing, and (2) the specific steps that researchers report taking to protect participants from the consequences of misinformation exposure. We found that fewer than 30% of misinformation papers report any debriefing, and almost no authors assessed the effectiveness of their debriefing procedure. Building on the findings from this review, we evaluate the balance of risk versus reward currently operating in this field and propose a set of guidelines for best practices. Our ultimate goal is to allow researchers the freedom to investigate questions of considerable scientific and societal impact while meeting their ethical obligations to participants.
Mapping and Scaling of In Situ Above Ground Biomass to Regional Extent With SAR in the Great Slave Region
Authors: Kraatz S. , Bourgeau‐Chavez L. , Battaglia M. , Poley A. , Siqueira P.
Published: December 2022

Global forests are increasingly threatened by disturbance events such as wildfire. Spaceborne Synthetic Aperture Radar (SAR) missions at L‐ (or P‐) band, such as the upcoming NASA ISRO SAR (NISAR), have great potential to advance global mapping of above‐ground biomass (AGB). AGB mapping with SAR is challenging due to lack of available L‐ or P‐ band data, and because SAR data are sensitive to confounding factors such as hydrology and terrain. This study uses recently collected AGB validation site data (AGBV) to produce a 1 ha biomass map about the Great Slave Lake in Canada using SAR data, and reports on NISAR's anticipated performance. This study addresses errors inherent to the representativeness of AGBVs with coarser grid/landscape scale processes by evaluating model performance as data are aggregated over increasingly larger areas (AOAs). Air and spaceborne SAR data were found to be interoperable after processing them according to analysis ready data specifications, improving data availability. Owing to poor model performance at two AGBVs, root‐mean‐square errors (RMSEs) were ∼60 Mg/ha, irrespective of AOA. When instead using NISAR's more lenient assessment criteria, RMSEs decreased to 32, 15, and 21 Mg/ha for the small (∼0.1 ha), medium (∼3.5 ha), and large (∼14 ha) AOA. Thus, AGB mapping in this region appears to benefit significantly from coarser data aggregations than to be used by NISAR's. This approach is practical for identifying a suitable scale of correspondence between the AGBV and SAR data and the landscape‐scale processes and can substantially improve AGB mapping accuracy.
Three‐Dimensional Temperature Responses to Northward‐Moving Typhoons in the Shallow Stratified Yellow Sea in Summer
Authors: Liu Xingchuan , Zhai Fangguo , Yan Junjie , Gu Yanzhen , Wang Yucheng , Li Peiliang , Wu Kejian
Published: December 2022

Characterized by a sharp thermocline and large cold‐water mass below, the Yellow Sea (YS) in summer is a shelf sea that is one of the most vulnerable to typhoons in the world. With observations and high‐resolution numerical simulations, we investigated the three‐dimensional temperature changes and underlying dynamics during the passage of Typhoon Bavi in August 2020, which was representative of northward‐moving typhoons in the eastern YS. Bavi's cyclonic strong winds caused intense turbulent mixing and Ekman divergence. The intense vertical mixing generated spatially coherent temperature cooling in the surface layer and partly caused temperature warming in the subsurface layer on both sides of the typhoon track. The largest surface cooling and subsurface warming both occurred on the right side of the typhoon track. Wind‐induced Ekman divergence generated two overturning circulation systems zonally across the YS, consisting of upper layer shoreward currents, coastal downwelling, lower layer seaward currents and upwelling on the typhoon track. Downwelling and seaward currents caused temperature warming below the thermocline, especially in the bottom layer. Upwelling shoaled the thermocline, resulting in subsurface cooling on the typhoon track. Additionally, Ekman divergence produced sea surface height minima on the typhoon track, causing strong southward barotropic currents to the left, which subsequently drove strong temperature cooling above the southern bottom slope of the South YS and fast southward movement of the YS Cold Water Mass. Further numerical experiments indicated that the magnitudes of the above changes increased with increasing maximum wind speeds and/or decreasing moving speeds of typhoons.
Bone morphogenetic protein 4 inhibits rat stem/progenitor Leydig cell development and regeneration via SMAD-dependent and SMAD-independent signaling
Authors: Li Xiaoheng , Fang Yinghui , Chen Lanlan , Quan Hehua , Wang Yiyan , Ge Ren-Shan
Published: December 2022

Bone morphogenetic protein 4 (BMP4) is an important member of the transforming growth factor-β superfamily. BMP4 is expressed in the Leydig cell lineage. We hypothesized that BMP4 might regulate the development of stem/progenitor Leydig cells. The BMP4 receptors, BMPR1A, BMPR1B, and BMPR2 were found to be expressed in progenitor Leydig cells of prepubertal testis and isolated cells. BMP4 at 1 and 10 ng/mL significantly reduced androgen production and down-regulated steroidogenesis-related gene and protein expression possibly by activating the SMAD signaling pathway (increasing SMAD1/5 phosphorylation and SMAD4) at 24 h treatment. BMP4 at 0.1 ng/mL and higher concentrations markedly reduced the EdU labeling index of CD90+stem Leydig cells after 24 h treatment and significantly reduced the number of EdU+stem Leydig cells on the surface of seminiferous tubules after 7 days of culture. BMP4 at 0.01 ng/mL and higher concentrations significantly blocked the differentiation of stem Leydig cells into adult cells, as shown by the reduction of testosterone secretion and the downregulation ofLhcgr, Scarb1, Cyp11a1, Hsd11b1, andInsl3and their function after 3D seminiferous tubule culture for 3 weeks, and this effect was reversed by co-treatment with the BMP4 antagonists noggin and doxomorphine. In addition, BMP4 also blocked stem Leydig cell differentiation through SMAD-independent signaling pathways (ERK1/2 and AMPK). Ethanedimethane sulfonate (EDS) single injection can result in reduction of testosterone, restoration can happen post treatment. In an in vivo model of Leydig cell regeneration following EDS treatment, intratesticular injection of BMP4 from day 14 to day 28 post-elimination significantly reduced serum testosterone levels and down-regulated the expression ofScarb1, Star, Hsd11b1,andInsl3and its proteins, possibly through SMAD-dependent and SMAD-independent (ERK1/2 and AMPK) signaling pathways. In conclusion, BMP4 is expressed in cells of the Leydig cell lineage and blocks entry of stem/progenitor Leydig cells into adult Leydig cells through SMAD-dependent and SMAD-independent signaling pathways.
Epigenetic priming of immune/inflammatory pathways activation and abnormal activity of cell cycle pathway in a perinatal model of white matter injury
Authors: Schang Anne-Laure , Van Steenwinckel Juliette , Ioannidou Zoi S. , Lipecki Julia , Rich-Griffin Charlotte , Woolley-Allen Kate , Dyer Nigel , Le Charpentier Tifenn , Schäfer Patrick , Fleiss Bobbi , Ott Sascha , Sabéran-Djoneidi Délara , Mezger Valérie , Gressens Pierre
Published: December 2022

Prenatal inflammatory insults accompany prematurity and provoke diffuse white matter injury (DWMI), which is associated with increased risk of neurodevelopmental pathologies, including autism spectrum disorders. DWMI results from maturation arrest of oligodendrocyte precursor cells (OPCs), a process that is poorly understood. Here, by using a validated mouse model of OPC maturation blockade, we provide the genome-wide ID card of the effects of neuroinflammation on OPCs that reveals the architecture of global cell fate issues underlining their maturation blockade. First, we find that, in OPCs, neuroinflammation takes advantage of a primed epigenomic landscape and induces abnormal overexpression of genes of the immune/inflammatory pathways: these genes strikingly exhibit accessible chromatin conformation in uninflamed OPCs, which correlates with their developmental, stage-dependent expression, along their normal maturation trajectory, as well as their abnormal upregulation upon neuroinflammation. Consistently, we observe the positioning on DNA of key transcription factors of the immune/inflammatory pathways (IRFs, NFkB), in both unstressed and inflamed OPCs. Second, we show that, in addition to the general perturbation of the myelination program, neuroinflammation counteracts the physiological downregulation of the cell cycle pathway in maturing OPCs. Neuroinflammation therefore perturbs cell identity in maturing OPCs, in a global manner. Moreover, based on our unraveling of the activity of genes of the immune/inflammatory pathways in prenatal uninflamed OPCs, the mere suppression of these proinflammatory mediators, as currently proposed in the field, may not be considered as a valid neurotherapeutic strategy.
Green synthesis of propylene oxide directly from propane
Authors: Kube Pierre , Dong Jinhu , Bastardo Nuria Sánchez , Ruland Holger , Schlögl Robert , Margraf Johannes T. , Reuter Karsten , Trunschke Annette
Published: December 2022

The chemical industry faces the challenge of bringing emissions of climate-damaging CO2 to zero. However, the synthesis of important intermediates, such as olefins or epoxides, is still associated with the release of large amounts of greenhouse gases. This is due to both a high energy input for many process steps and insufficient selectivity of the underlying catalyzed reactions. Surprisingly, we find that in the oxidation of propane at elevated temperature over apparently inert materials such as boron nitride and silicon dioxide not only propylene but also significant amounts of propylene oxide are formed, with unexpectedly small amounts of CO2. Process simulations reveal that the combined synthesis of these two important chemical building blocks is technologically feasible. Our discovery leads the ways towards an environmentally friendly production of propylene oxide and propylene in one step. We demonstrate that complex catalyst development is not necessary for this reaction.