bluuebunny/crossref_metadata_2025_split huggingface dataset:
Designing all-pay auctions using deep learning and multi-agent simulation
Authors: Gemp Ian , Anthony Thomas , Kramar Janos , Eccles Tom , Tacchetti Andrea , Bachrach Yoram 
Published: October 2022

AbstractWe propose a multi-agent learning approach for designing crowdsourcing contests and All-Pay auctions. Prizes in contests incentivise contestants to expend effort on their entries, with different prize allocations resulting in different incentives and bidding behaviors. In contrast to auctions designed manually by economists, our method searches the possible design space using a simulation of the multi-agent learning process, and can thus handle settings where a game-theoretic equilibrium analysis is not tractable. Our method simulates agent learning in contests and evaluates the utility of the resulting outcome for the auctioneer. Given a large contest design space, we assess through simulation many possible contest designs within the space, and fit a neural network to predict outcomes for previously untested contest designs. Finally, we apply mirror ascent to optimize the design so as to achieve more desirable outcomes. Our empirical analysis shows our approach closely matches the optimal outcomes in settings where the equilibrium is known, and can produce high quality designs in settings where the equilibrium strategies are not solvable analytically.
Using intrinsic properties of quantum dots to provide additional security when uniquely identifying devices
Authors: Fong Matthew J. , Woodhead Christopher S. , Abdelazim Nema M. , Abreu Daniel C. , Lamantia Angelo , Ball Elliott M. , Longmate Kieran , Howarth David , Robinson Benjamin J. , Speed Phillip , Young Robert J. 
Published: October 2022

AbstractUnique identification of optical devices is important for anti-counterfeiting. Physical unclonable functions (PUFs), which use random physical characteristics for authentication, are advantageous over existing optical solutions, such as holograms, due to the inherent asymmetry in their fabrication and reproduction complexity. However, whilst unique, PUFs are potentially vulnerable to replication and simulation. Here we introduce an additional benefit of a small modification to an established model of nanoparticle PUFs by using a second measurement parameter to verify their authenticity. A randomly deposited array of quantum dots is encapsulated in a transparent polymer, forming a tag. Photoluminescence is measured as a function of excitation power to assess uniqueness as well as the intrinsic nonlinear response of the quantum material. This captures a fingerprint, which is non-trivial to clone or simulate. To demonstrate this concept practically, we show that these tags can be read using an unmodified smartphone, with its built-in flash for excitation. This development over constellation-style optical PUFs paves the way for more secure, facile authentication of devices without requiring complex fabrication or characterisation techniques.
400 W average power Q-switched Yb:YAG thin-disk-laser
Authors: Radmard Saeid , Moshaii Ahmad , Pasandideh Kaveh 
Published: October 2022

AbstractWe report on producing up to 403 W average power directly from an acousto-optically Q-switched Yb:YAG thin-disk laser (TDL). To achieve this power, it has theoretically and experimentally been shown that the laser stability border could be shifted toward higher repetition rates by engineering of the output coupler transmittance. This allows for stable operation of the laser at higher frequencies and a further increase in the power extraction from the active medium. Using an output coupler with 93% reflectivity, a maximum average power of 403 W at the repetition rate of 12.0 kHz has been recorded under the pump power of 1220 W. Furthermore, the maximum pulse energy of 57 mJ was produced at the repetition rate of 1.00 kHz and the pump power of 520 W. The characteristics of the laser at various Q-switching rates and the pump powers have been investigated. In addition, a numerical study for supporting the experimental results has been proposed here. To the best of our knowledge, the achieved average power and the pulse energy are the highest values reported to date from a Q-switched Yb:YAG TDL. The results pave the way to further power scaling of solid-state Q-switched oscillators.
Safety assessment of charcoal usage and effects of common charcoal ignition aiders on combustion indices
Authors: Ajayeoba A. O. , Fajobi M. O. , Adebiyi K. A. , Raheem W. A. , Oladapo S. O. , Olayinka M. D. 
Published: October 2022

AbstractCharcoal is a popular form of biofuel embraced for domestic and industrial purposes. However, the use of Charcoal has some associated challenges, such as the required charcoal pot and setting it into the fire at first by using Charcoal-Ignition-Aiders (CIA) (e.g. discarded paper, nylon, rubber, plastics, petrol, the residue of processed palm oil, maise cob, wood, and kerosene). Coupled with the chemical properties of Charcoal, the resulting gases from CIA are capable of polluting the environment with perceived Adverse-Health-Implications (AHI) on the ecosystem. Therefore, this study conducted a safety assessment of charcoal biofuel usage and the effects of common CIA on combustion indices. This study followed standard methods and the use of peculiar equipment. This study established that Charcoal is commonly used in the studied area because it is cheap, readily available and requires less technical know-how. Considering the combustion indices, using paper as a CIA generated the lowest carbon monoxide (CO) value, 28.1 ppm, with 3,434.54 ppm volatile organic compound, VOC. Compared with the ACGIH standard permissible exposure level of ≤ 30 ppm, the paper gave a lesser CO value of 28.10 ppm among all the CIA. At the same time, all the CIA recorded higher VOC compared with EPA standard permissible exposure level of ≤ 15 ppm. ANOVA analysis conducted on the socio-demographic profile of the respondents, cooking attributes of the respondents, and use of charcoal pot types by the respondents in Zone 1, Zone 2, and Zone 3 gave p-values of 0.032, 0.028, and 0.039, respectively. These imply significant differences within the zones in each of the indices. The average energy content reported for charcoals sourced from oak trees, afara, obeche, mahogany, and iroko woods is 3,2149 kJ/kg compared to the lower ones. Therefore, this study recommended using these charcoals alongside discarded paper as CIA because they are a better combination to reduce AHI.
Increased risk of open-angle glaucoma in non-smoking women with obstructive pattern of spirometric tests
Authors: Lee Jihei Sara , Kim Yong Joon , Kim Sung Soo , Park Sungeun , Choi Wungrak , Bae Hyoung Won , Kim Chan Yun 
Published: October 2022

AbstractTo investigate differences in the prevalence of open-angle glaucoma (OAG) between different pulmonary function types. A population-based, cross-sectional analysis was conducted using Korean National Health and Nutrition Examination Surveys from 2008 to 2011. A total of 8941 subjects  ≥ 40 years of age were analyzed. Chronic obstructive pulmonary disease (COPD) was defined as the ratio between first second of forced expiration (FEV1) and forced vital capacity (FVC) below 70%. The prevalence of glaucoma, as defined by the International Society of Geographical and Epidemiological Ophthalmology, was the main outcome. OAG was more prevalent in women with COPD (8.0% vs. 4.8% normal, P = 0.001) compared to women with normal pulmonary function. Intraocular pressure (IOP) of women with COPD were 13.3 (0.2) mmHg (13.9 (0.1) mmHg for normal function, P = 0.182). Never-smokers were more prevalent in women with COPD and glaucoma (92.9% vs. 52.4% normal function; P < 0.001). COPD was found to increase the risk of glaucoma in women (OR 2.077, P = 0.017) and even further in non-smoking women (OR 2.711, P = 0.003). Women with COPD showed a higher glaucoma prevalence despite similar IOP in comparison to women with normal pulmonary function. Non-smoking COPD is significantly associated with open-angle glaucoma in women.
Adapting and pretesting the World Health Organization’s Caregiver Skills Training Program for children with autism and developmental disorders or delays in Hong Kong
Authors: Wong Paul Wai-Ching , Lam Yan-Yin , Lau Janet Siu-Ping , Fok Hung-Kit ,   The WHO CST Team, Servili Chiara , Salomone Erica , Pacione Laura , Shire Stephanie , Brown Felicity 
Published: October 2022

AbstractThe World Health Organization Caregiver Skills Training Program (WHO-CST) was developed to strengthen caregivers’ skills in supporting children with developmental delays and the caregivers’ well-being. The WHO-CST Hong Kong (HK) was adapted, and pre-pilot tested to support families with children suspected of having developmental delays and autism spectrum disorder and to empower the caregivers to foster their children’s learning, social communication, and adaptive behavior. A sequential mixed-methods research methodology was undertaken to examine the adaptation process and initial implementation experiences. The acceptability, feasibility, and perceived benefits of the WHO-CST were assessed using stakeholders’ and caregivers’ qualitative and caregivers’ quantitative pre- and post-intervention feedback. The data included materials generated from (1) three consultation meetings with stakeholders; (2) detailed reviews of the translated and adapted WHO-CST materials by master trainees (n = 10) trained by the WHO-CST representatives; (3) needs assessment focus group interviews with caregivers (n = 15) of children with autism spectrum disorder; and (4) pre- and post-CST program qualitative focus group interviews and quantitative evaluation. Consultation with stakeholders suggested that the program was acceptable for the local community, but the home visit and fidelity components were initially considered to be challenges towards the feasibility and sustainability of the program. Caregivers in the needs assessment focus groups gave widely diverse views about the program’s uniqueness, length, delivery mode, and the inclusion of videotaping in-home visits. Post-intervention comments by caregivers about the program were mainly positive, while the MTs were critical of the content and length of the training and fidelity process. As one of the first high-income locations to adopt the WHO-CST, the evaluation findings of the WHO-CST-HK indicate that it is feasible and acceptable to implement the program in a metropolitan area where families have busy work schedules and are very conscious of privacy issues. The study results suggest that the WHO-CST program in HK and other high-income countries require scaling up and further evaluation of its implementation in real community settings. This involves systemic and contextual changes to allow task-sharing between professionals and non-specialists at the macro level. Furthermore, technology should be used to support the supervision of non-specialists. In addition, easier access to the WHO-CST materials at the micro level is required to ensure equity, equality, diversity, and inclusion of diversified families of children with developmental delays.
Improving protein succinylation sites prediction using embeddings from protein language model
Authors: Pokharel Suresh , Pratyush Pawel , Heinzinger Michael , Newman Robert H. , KC Dukka B. 
Published: October 2022

AbstractProtein succinylation is an important post-translational modification (PTM) responsible for many vital metabolic activities in cells, including cellular respiration, regulation, and repair. Here, we present a novel approach that combines features from supervised word embedding with embedding from a protein language model called ProtT5-XL-UniRef50 (hereafter termed, ProtT5) in a deep learning framework to predict protein succinylation sites. To our knowledge, this is one of the first attempts to employ embedding from a pre-trained protein language model to predict protein succinylation sites. The proposed model, dubbed LMSuccSite, achieves state-of-the-art results compared to existing methods, with performance scores of 0.36, 0.79, 0.79 for MCC, sensitivity, and specificity, respectively. LMSuccSite is likely to serve as a valuable resource for exploration of succinylation and its role in cellular physiology and disease.
Deep learning model for analyzing the relationship between mandibular third molar and inferior alveolar nerve in panoramic radiography
Authors: Sukegawa Shintaro , Tanaka Futa , Hara Takeshi , Yoshii Kazumasa , Yamashita Katsusuke , Nakano Keisuke , Takabatake Kiyofumi , Kawai Hotaka , Nagatsuka Hitoshi , Furuki Yoshihiko 
Published: October 2022

AbstractIn this study, the accuracy of the positional relationship of the contact between the inferior alveolar canal and mandibular third molar was evaluated using deep learning. In contact analysis, we investigated the diagnostic performance of the presence or absence of contact between the mandibular third molar and inferior alveolar canal. We also evaluated the diagnostic performance of bone continuity diagnosed based on computed tomography as a continuity analysis. A dataset of 1279 images of mandibular third molars from digital radiographs taken at the Department of Oral and Maxillofacial Surgery at a general hospital (2014–2021) was used for the validation. The deep learning models were ResNet50 and ResNet50v2, with stochastic gradient descent and sharpness-aware minimization (SAM) as optimizers. The performance metrics were accuracy, precision, recall, specificity, F1 score, and area under the receiver operating characteristic curve (AUC). The results indicated that ResNet50v2 using SAM performed excellently in the contact and continuity analyses. The accuracy and AUC were 0.860 and 0.890 for the contact analyses and 0.766 and 0.843 for the continuity analyses. In the contact analysis, SAM and the deep learning model performed effectively. However, in the continuity analysis, none of the deep learning models demonstrated significant classification performance.
A cross-sectional study to validate an administrative back pain severity classification tool based on the graded chronic pain scale
Authors: Hochheim M. , Ramm P. , Wunderlich M. , Amelung V. 
Published: October 2022

AbstractTreatment of chronic lower back pain (CLBP) should be stratified for best medical and economic outcome. To improve the targeting of potential participants for exclusive therapy offers from payers, Freytag et al. developed a tool to classify back pain chronicity classes (CC) based on claim data. The aim of this study was to evaluate the criterion validity of the model. Administrative claim data and self-reported patient information from 3,506 participants (2014–2021) in a private health insurance health management programme in Germany were used to validate the tool. Sensitivity, specificity, and Matthews’ correlation coefficient (MCC) were calculated comparing the prediction with actual grades based on von Korff’s graded chronic pain scale (GCPS). The secondary outcome was an updated view on direct health care costs (€) of patients with back pain (BP) grouped by GCPS. Results showed a fair correlation between predicted CC and actual GCPS grades. A total of 69.7% of all cases were correctly classified. Sensitivity and specificity rates of 54.6 and 76.4% underlined precision. Correlation between CC and GCPS with an MCC of 0.304 also indicated a fair relationship between prediction and observation. Cost data could be clearly grouped by GCPS: the higher the grade, the higher the costs and the use of health care. This was the first study to compare the predicted severity of BP using claim data with the actual severity of BP by GCPS. Based on the results, the usage of CC as a single tool to determine who receives CLBP treatment cannot be recommended. CC is a good tool to segment candidates for specific types of intervention in BP. However, it cannot replace a medical screening at the beginning of an intervention, as the rate of false negatives is too high.
Trial registration The study was conducted using routinely collected data from an intervention, which was previously evaluated and registered retrospectively in the German Registry of Clinical Trials under DRKS00015463 (04/09/2018). Informed consent and the self-reported questionnaire have remained unchanged since the study and, therefore, are still valid according to the ethics proposal.
Lockdown measures during the COVID-19 pandemic strongly impacted the circulation of respiratory pathogens in Southern China
Authors: Wang Heping , Zheng Yuejie , de Jonge Marien I. , Wang Rongjun , Verhagen Lilly M. , Chen Yunsheng , Li Li , Xu Zhi , Wang Wenjian 
Published: October 2022

AbstractA range of public health measures have been implemented to suppress local transmission of coronavirus disease 2019 (COVID-19) in Shenzhen. We examined the effect of these measures on the prevalence of respiratory pathogens in children. Clinical and respiratory pathogen data were collected for routine care from hospitalized children with acute respiratory infections in Shenzhen Children’s Hospital from July 2018 to January 2022. Nasopharyngeal swabs were collected and respiratory pathogens were detected using standardized clinical diagnostics as part of routine care. Data were analyzed to describe the effects of COVID-19 prevention procedures on other common pathogens. A total of 56,325 children under 14 years of age were hospitalized with an acute respiratory infection during the study period, 33,909 were tested from July 2018 to January 2020 (pre-lockdown), 1168 from February 2020 to May 2020 (lockdown) and 21,248 from July 2020 to January 2022 (post-lockdown). We observed a 37.3% decline of routine care in respiratory infection associated hospital admission in the 19 months’ post-lockdown vs. the 19 months’ pre-lockdown. There were 99.4%, 16.0% and 1.26% reductions measured for Mycoplasma pneumoniae, influenza virus A and adenovirus, respectively. However, a 118.7% and 75.8% rise was found for respiratory syncytial virus (RSV) and human para-influenza virus (HPIV) during the 19 months’ post-lockdown in comparison to the pre-pandemic period. The detection of RSV especially increased in toddlers after the lockdown. Lockdown measures during the COVID-19 pandemic led to a significant reduction of Mycoplasma pneumoniae, influenza virus A and adenovirus infection. In contrast, RSV and HPIV infection increased.
Characterization of complex fluvial-deltaic deposits in Northeast India using Poisson impedance inversion and non-parametric statistical technique
Authors: Nagendra Babu M. , Ambati Venkatesh , Nair Rajesh R. 
Published: October 2022

AbstractCharacterizing complex fluvial-deltaic deposits is a challenging task for finding hydrocarbon discoveries. We described a methodology for predicting the hydrocarbon zones from complex well-log and prestack seismic data. In this current study, data analysis involves an integrated framework based on Simultaneous prestack seismic inversion (SPSI), target correlation coefficient analysis (TCCA), Poisson impedance inversion, and non-parametric statistical analysis, and Bayesian classification. First, seismic elastic attributes from prestack seismic data were estimated. They can provide the spatial distribution of petrophysical properties of seismic data. Then target correlation coefficient analysis (TCCA) was estimated roration factor “c” from well-log data. Using the seismic elastic attributes and rotation factor “c”, Poisson impedance inversion was performed to predict the Poisson impedance volume. Finally, Bayesian classification integrated the Poisson impedance volume with non-parametric probabilistic density functions (PDFs) to estimate the spatial distribution of lithofacies. Despite complex characteristics in the elastic properties, the current study successfully delineated the complex fluvial-details deposits. These results were verified with conventional findings through numerical analysis.
Multi-Omic analyses characterize the ceramide/sphingomyelin pathway as a therapeutic target in Alzheimer’s disease
Authors: Baloni Priyanka , Arnold Matthias , Buitrago Luna , Nho Kwangsik , Moreno Herman , Huynh Kevin , Brauner Barbara , Louie Gregory , Kueider-Paisley Alexandra , Suhre Karsten , Saykin Andrew J. , Ekroos Kim , Meikle Peter J. , Hood Leroy , Price Nathan D. ,   The Alzheimer’s Disease Metabolomics Consortium, Arnold Matthias , Blach Colette , Kaddurah-Daouk Rima , Doraiswamy Murali , Mahmoudiandehkordi Siamak , Welsh-Bohmer Kathleen , Plassman Brenda , Krumsiek Jan , Batra Richa , Saykin Andrew , Yan Jingwen , Risacher Shannon L. , Meikle Peter , Wang Tingting , Ikram Arfan , Ahmad Shahzad , Hankemeier Thomas , Hernandez Ivan A. , Heinken Almut , Martinelli Filippo , Thiele Ines , Hertel Johannes , Hensen Tim , Hulshof Tim , Farrer Lindsay A. , Au Rhoda , Qiu Wendy Wei Qiao , Stein Thor , Karu Naama , Borkowski Kamil , Newman John , Jia Wei , Xie Guoxiang , Wang Jingye , Wei Runmin , Rader Dan , Kling Mitchel , Shaw Leslie , Doraiswamy P. Murali , Funk Cory C. , Hernández A. Iván , Kastenmüller Gabi , Baillie Rebecca , Han Xianlin , Kaddurah-Daouk Rima 
Published: October 2022

AbstractDysregulation of sphingomyelin and ceramide metabolism have been implicated in Alzheimer’s disease. Genome-wide and transcriptome-wide association studies have identified various genes and genetic variants in lipid metabolism that are associated with Alzheimer’s disease. However, the molecular mechanisms of sphingomyelin and ceramide disruption remain to be determined. We focus on the sphingolipid pathway and carry out multi-omics analyses to identify central and peripheral metabolic changes in Alzheimer’s patients, correlating them to imaging features. Our multi-omics approach is based on (a) 2114 human post-mortem brain transcriptomics to identify differentially expressed genes; (b) in silico metabolic flux analysis on context-specific metabolic networks identified differential reaction fluxes; (c) multimodal neuroimaging analysis on 1576 participants to associate genetic variants in sphingomyelin pathway with Alzheimer’s disease pathogenesis; (d) plasma metabolomic and lipidomic analysis to identify associations of lipid species with dysregulation in Alzheimer’s; and (e) metabolite genome-wide association studies to define receptors within the pathway as a potential drug target. We validate our hypothesis in amyloidogenic APP/PS1 mice and show prolonged exposure to fingolimod alleviated synaptic plasticity and cognitive impairment in mice. Our integrative multi-omics approach identifies potential targets in the sphingomyelin pathway and suggests modulators of S1P metabolism as possible candidates for Alzheimer’s disease treatment.
Topological soliton metacrystals
Authors: Fan Zhiwei , Puzyrev Danila N. , Skryabin Dmitry V. 
Published: October 2022

AbstractDesigning metamaterials with the required band structure, topology and chirality using nano-fabrication technology revolutionise modern science. The approach of this work to the metamaterial theme is, however, different. We report that a periodic sequence, i.e., metacrystal, of the dissipative optical solitons rotating in a ring microresonator acts as an effective metamaterial in the radio to terahertz frequency range. The metacrystal unit cell consists of the bound pair of solitons, where the inter-soliton distance is used as a control parameter. We investigate the soliton metacrystal band structure and topological properties. The latter is confirmed by the π steps experienced by the crystal phonons’ geometrical (Zak) phase. Furthermore, we found the phononic edge states in the metacrystals with defects made by removing several solitons. Optical frequency combs corresponding to the soliton metacrystals hide the spectral butterfly pattern serving as a signature of the spatio-temporal chirality and bearing a resemblance to the natural occurrences of chirality.