bluuebunny/crossref_metadata_2025_split huggingface dataset:
The market as a process for the discovery of whom not to trust
Authors: Choi Ginny Seung , Storr Virgil Henry 
Published: May 2021

Abstract
Trust is an important component of all successful commercial exchanges. Indeed, there is now a considerable literature on the economic importance of trust as well as the relationship between trust and institutions. Although there is now a sizeable literature on the economic importance of trust, and on the institutions that are associated with higher levels of trust, this literature remains relatively silent on the potential of markets to generate trust and, more specifically, how market actors discover whom to trust and, perhaps more importantly, whom not to trust. In this paper, we build on research by market process theorists that understands the market as a discovery process. We argue that the market is also a discovery process through which market participants acquire knowledge about their trading partners' dispositions, moral priorities, and personalities. Specifically, we argue that the market facilitates the identification of trustworthy and untrustworthy individuals and is, thus, a process for the discovery of whom to trust and whom not to trust. Additionally, we report experimental evidence that suggests that although market participants are trusting of strangers (at least in our experimental setting), they are less trusting of trading partners who have proven to be untrustworthy in past dealings.
Description and Demonstration of the Coupled Community Earth System Model v2 – Community Ice Sheet Model v2 (CESM2‐CISM2)
Authors: Muntjewerf Laura , Sacks William J. , Lofverstrom Marcus , Fyke Jeremy , Lipscomb William H. , Ernani da Silva Carolina , Vizcaino Miren , Thayer‐Calder Katherine , Lenaerts Jan T. M. , Sellevold Raymond 
Published: May 2021

AbstractEarth system/ice‐sheet coupling is an area of recent, major Earth System Model (ESM) development. This work occurs at the intersection of glaciology and climate science and is motivated by a need for robust projections of sea‐level rise. The Community Ice Sheet Model version 2 (CISM2) is the newest component model of the Community Earth System Model version 2 (CESM2). This study describes the coupling and novel capabilities of the model, including: (1) an advanced energy‐balance‐based surface mass balance calculation in the land component with downscaling via elevation classes; (2) a closed freshwater budget from ice sheet to the ocean from surface runoff, basal melting, and ice discharge; (3) dynamic land surface types; and (4) dynamic atmospheric topography. The Earth system/ice‐sheet coupling is demonstrated in a simulation with an evolving Greenland Ice Sheet (GrIS) under an idealized high CO2 scenario. The model simulates a large expansion of ablation areas (where surface ablation exceeds snow accumulation) and a large increase in surface runoff. This results in an elevated freshwater flux to the ocean, as well as thinning of the ice sheet and area retreat. These GrIS changes result in reduced Greenland surface albedo, changes in the sign and magnitude of sensible and latent heat fluxes, and modified surface roughness and overall ice sheet topography. Representation of these couplings between climate and ice sheets is key for the simulation of ice and climate interactions.
A Changing Hydrological Regime: Trends in Magnitude and Timing of Glacier Ice Melt and Glacier Runoff in a High Latitude Coastal Watershed
Authors: Young Joanna C. , Pettit Erin , Arendt Anthony , Hood Eran , Liston Glen E. , Beamer Jordan 
Published: May 2021

AbstractWith a unique biogeophysical signature relative to other freshwater sources, meltwater from glaciers plays a crucial role in the hydrological and ecological regime of high latitude coastal areas. Today, as glaciers worldwide exhibit persistent negative mass balance, glacier runoff is changing in both magnitude and timing, with potential downstream impacts on infrastructure, ecosystems, and ecosystem resources. However, runoff trends may be difficult to detect in coastal systems with large precipitation variability. Here, we use the coupled energy balance and water routing model SnowModel‐HydroFlow to examine changes in timing and magnitude of runoff from the western Juneau Icefield in Southeast Alaska between 1980 and 2016. We find that under sustained glacier mass loss (−0.57 ± 0.12 m w. e. a−1), several hydrological variables related to runoff show increasing trends. This includes annual and spring glacier ice melt volumes (+10% and +16% decade−1) which, because of higher proportions of precipitation, translate to smaller increases in glacier runoff (+3% and +7% decade−1) and total watershed runoff (+1.4% and +3% decade−1). These results suggest that the western Juneau Icefield watersheds are still in an increasing glacier runoff period prior to reaching “peak water.” In terms of timing, we find that maximum glacier ice melt is occurring earlier (2.5 days decade−1), indicating a change in the source and quality of freshwater being delivered downstream in the early summer. Our findings highlight that even in maritime climates with large precipitation variability, high latitude coastal watersheds are experiencing hydrological regime change driven by ongoing glacier mass loss.
Predictors of trajectories of obsessive-compulsive symptoms during the COVID-19 pandemic in the general population in Germany
Authors: Jelinek Lena , Göritz Anja S. , Miegel Franziska , Moritz Steffen , Kriston Levente 
Published: May 2021

AbstractThe COVID-19 pandemic has been associated with an increase in obsessive-compulsive disorder/symptoms (OCD/OCS). However, knowledge is limited regarding the trajectories of OCS during the pandemic, as well as their predictors and mechanisms (e.g., experiential avoidance, EA). The aim of this study was to describe the trajectories of OCS and the identification of associated factors. We assessed 1207 participants of the general population in March 2020 (t1) and June 2020 (t2). Pre-pandemic data was available from March 2014 for a subsample (n = 519). To define trajectories, we determined OCS status (OCS+/−). We performed a hierarchical multinomial logistic regression to investigate predictors of trajectories. Between t1 and t2, 66% of participants had an asymptomatic trajectory (OCS−/OCS−); 18% had a continuously symptomatic trajectory (OCS+/OCS+). Ten percent had a delayed-onset trajectory (OCS−/OCS+), and the recovery trajectory group (OCS+/OCS−) was the smallest group (6%). Higher education reduced the odds of an OCS+/OCS− trajectory. OCS in 2014 was associated with increased odds of showing an OCS+/OCS+ or OCS−/OCS+ trajectory. When EA at t1 and change in EA from t1 to t2 were added to the model, higher EA at t1 was associated with increased odds of scoring above the cut score on one or more of the assessments. A higher decrease in EA from t1 to t2 reduced the probability of showing an OCS+/OCS+ and an OCS−/OCS+ trajectory. While the current data supports a slight increase in OCS during the pandemic, trajectories differed, and EA seems to represent an important predictor for an unfavorable development.
A diet high in sugar and fat influences neurotransmitter metabolism and then affects brain function by altering the gut microbiota
Authors: Guo Yinrui , Zhu Xiangxiang , Zeng Miao , Qi Longkai , Tang Xiaocui , Wang Dongdong , Zhang Mei , Xie Yizhen , Li Hongye , Yang Xin , Chen Diling 
Published: May 2021

AbstractGut microbiota (GM) metabolites can modulate the physiology of the host brain through the gut–brain axis. We wished to discover connections between the GM, neurotransmitters, and brain function using direct and indirect methods. A diet with increased amounts of sugar and fat (high-sugar and high-fat (HSHF) diet) was employed to disturb the host GM. Then, we monitored the effect on pathology, neurotransmitter metabolism, transcription, and brain circularRNAs (circRNAs) profiles in mice. Administration of a HSHF diet-induced dysbacteriosis, damaged the intestinal tract, changed the neurotransmitter metabolism in the intestine and brain, and then caused changes in brain function and circRNA profiles. The GM byproduct trimethylamine-n-oxide could degrade some circRNAs. The basal level of the GM decided the conversion rate of choline to trimethylamine-n-oxide. A change in the abundance of a single bacterial strain could influence neurotransmitter secretion. These findings suggest that a new link between metabolism, brain circRNAs, and GM. Our data could enlarge the “microbiome–transcriptome” linkage library and provide more information on the gut–brain axis. Hence, our findings could provide more information on the interplay between the gut and brain to aid the identification of potential therapeutic markers and mechanistic solutions to complex problems encountered in studies of pathology, toxicology, diet, and nutrition development.
Understanding the impact of removable partial dentures on patients' lives and their attitudes to oral care
Authors: Shaha Mita , Varghese Roshan , Atassi Mounir 
Published: May 2021

AbstractIntroduction Due to a rising prevalence of removable partial denture (RPD) use, there is an unmet need to explore the psychological impact on patient wellbeing.Aim To assess the psychological effects of consumers losing teeth and receiving partial dentures to better manage their needs.Design Four market research surveys, undertaken on behalf of GlaxoSmithKline Consumer Healthcare, are described.Setting Surveys were conducted across the US, Japan, Malaysia, Colombia, Brazil, Poland and Italy.Materials and methods Quantitative/qualitative methods were used to gain knowledge regarding patients' experiences living with partial dentures.Results In a global market research survey involving 3,952 RPD wearers (RPDWs), 54% said that losing teeth was difficult to accept, 40% were concerned about their appearance, 32% were embarrassed about wearing dentures and 62% wished that more oral care education was available when they were younger. In another survey of >1,000 RPDWs, self-esteem was negatively impacted in 51% of respondents and 57% reported anxiety around dental visits.Conclusions Global market research confirmed that RPDWs can have emotional and practical needs that are not well understood/documented by dental healthcare professionals (HCPs). Consumer research can enhance understanding of patients' needs by dental HCPs and provide suggestions about how they may address them.
Sulfamic acid pyromellitic diamide-functionalized MCM-41 as a multifunctional hybrid catalyst for melting-assisted solvent-free synthesis of bioactive 3,4-dihydropyrimidin-2-(1H)-ones
Authors: Valiey Ehsan , Dekamin Mohammad G. , Alirezvani Zahra 
Published: May 2021

AbstractThis study introduces a practical approach to fabricate a novel hybrid acidic catalyst, namely sulfamic acid pyromellitic diamide-functionalized MCM-41 (MCM-41-APS-PMDA-NHSO3H). Various techniques such as FTIR, TGA, XRD, BET, FESEM, and EDX were used to confirm its structural characteristics. The efficiency of the new MCM-41-APS-PMDA-NHSO3H organosilica nanomaterials, as a heterogenous nanocatalyst, was examined in the synthesis of biologically active 3,4-dihydropyrimidin-2-(1H)-one derivatives under solvent-free conditions. It was found that the nanoporous MCM-41-APS-PMDA-NHSO3H, demonstrating acidic nature and high surface area, can activate all the Biginelli reaction components to afford desired 3,4-dihydropyrimidin-2-(1H)-ones under solvent-free conditions in short reaction time. Furthermore, easy and quick isolation of the new introduced hybrid organosilica from the reaction mixture as well as its reusability with negligible loss of activity in at least five consecutive runs are another advantages of this green protocol.
Simultaneous corn and soybean yield prediction from remote sensing data using deep transfer learning
Authors: Khaki Saeed , Pham Hieu , Wang Lizhi 
Published: May 2021

AbstractLarge-scale crop yield estimation is, in part, made possible due to the availability of remote sensing data allowing for the continuous monitoring of crops throughout their growth cycle. Having this information allows stakeholders the ability to make real-time decisions to maximize yield potential. Although various models exist that predict yield from remote sensing data, there currently does not exist an approach that can estimate yield for multiple crops simultaneously, and thus leads to more accurate predictions. A model that predicts the yield of multiple crops and concurrently considers the interaction between multiple crop yields. We propose a new convolutional neural network model called YieldNet which utilizes a novel deep learning framework that uses transfer learning between corn and soybean yield predictions by sharing the weights of the backbone feature extractor. Additionally, to consider the multi-target response variable, we propose a new loss function. We conduct our experiment using data from 1132 counties for corn and 1076 counties for soybean across the United States. Numerical results demonstrate that our proposed method accurately predicts corn and soybean yield from one to four months before the harvest with an MAE being 8.74% and 8.70% of the average yield, respectively, and is competitive to other state-of-the-art approaches.
Humidity sensor based on Gallium Nitride for real time monitoring applications
Authors: Furqan Chaudhry Muhammad , Khan Muhammad Umair , Awais Muhammad , Jiang Fulong , Bae Jinho , Hassan Arshad , Kwok Hoi-Sing 
Published: May 2021

AbstractGallium Nitride (GaN) remarkably shows high electron mobility, wide energy band gap, biocompatibility, and chemical stability. Wurtzite structure makes topmost Gallium atoms electropositive, hence high ligand binding ability especially to anions, making it usable as humidity sensor due to water self-ionization phenomenon. In this work, thin-film GaN based humidity sensor is fabricated through pulse modulated DC magnetron sputtering. Interdigitated electrodes (IDEs) with 100 μm width and spacing were inkjet printed on top of GaN sensing layer to further enhance sensor sensitivity. Impedance, capacitance, and current response were recorded for humidity and bio-sensing applications. The sensor shows approximate linear impedance response between 0 and 100% humidity range, the sensitivity of 8.53 nF/RH% and 79 kΩ/RH% for capacitance and impedance, and fast response (Tres) and recovery (Trec) time of 3.5 s and 9 s, respectively. The sensor shows little hysteresis of < 3.53% with stable and wide variations for accurate measurements. Especially, it demonstrates temperature invariance for thermal stability. Experimental results demonstrate fabricated sensor effectively evaluates plant transpiration cycle through water level monitoring by direct attachment onto leaves without causing any damage as well as freshness level of meat loaf. These properties of the proposed sensor make it a suitable candidate for future electronics providing a low-cost platform for real time monitoring applications.
Subgap dynamics of double quantum dot coupled between superconducting and normal leads
Authors: Baran B. , Taranko R. , Domański T. 
Published: May 2021

AbstractDynamical processes induced by the external time-dependent fields can provide valuable insight into the characteristic energy scales of a given physical system. We investigate them here in a nanoscopic heterostructure, consisting of the double quantum dot coupled in series to the superconducting and the metallic reservoirs, analyzing its response to (i) abrupt bias voltage applied across the junction, (ii) sudden change of the energy levels, and imposed by (iii) their periodic driving. We explore subgap properties of this setup which are strictly related to the in-gap quasiparticles and discuss their signatures manifested in the time-dependent charge currents. The characteristic multi-mode oscillations, their beating patters and photon-assisted harmonics reveal a rich spectrum of dynamical features that might be important for designing the superconducting qubits.
Transcriptomic analysis of atopic dermatitis in African Americans is characterized by Th2/Th17-centered cutaneous immune activation
Authors: Wongvibulsin Shannon , Sutaria Nishadh , Kannan Suraj , Alphonse Martin Prince , Belzberg Micah , Williams Kyle A. , Brown Isabelle D. , Choi Justin , Roh Youkyung Sophie , Pritchard Thomas , Khanna Raveena , Eseonu Amarachi C. , Jedrych Jaroslaw , Dillen Carly , Kwatra Madan M. , Chien Anna L. , Archer Nathan , Garza Luis A. , Dong Xinzhong , Kang Sewon , Kwatra Shawn G. 
Published: May 2021

AbstractAtopic dermatitis (AD) often presents more severely in African Americans (AAs) and with greater involvement of extensor areas. To investigate immune signatures of AD in AAs with moderate to severe pruritus, lesional and non-lesional punch biopsies were taken from AA patients along with age-, race-, and sex-matched controls. Histology of lesional skin showed psoriasiform dermatitis and spongiotic dermatitis, suggesting both Th2 and Th17 activity. Gene Set Variation Analysis showed upregulation of Th2 and Th17 pathways in both lesional versus non-lesional and lesional versus control (p < 0.01), while Th1 and Th22 upregulation were observed in lesional versus control (p < 0.05). Evidence for a broad immune signature also was supported by upregulated Th1 and Th22 pathways, and clinically may represent greater severity of AD in AA. Furthermore, population-level analysis of data from TriNetX, a global federated health research network, revealed that AA AD patients had higher values for CRP, ferritin, and blood eosinophils compared to age-, sex-, and race-matched controls as well as white AD patients, suggesting broad systemic inflammation. Therefore, AA AD patients may feature broader immune activation than previously thought and may derive benefit from systemic immunomodulating therapies that modulate key drivers of multiple immune pathways.
NLR and BRCA mutational status in patients with high grade serous advanced ovarian cancer
Authors: Marchetti Claudia , D’Indinosante Marco , Bottoni Carolina , Di Ilio Chiara , Di Berardino Stefano , Costantini Barbara , Minucci Angelo , Vertechy Laura , Scambia Giovanni , Fagotti Anna 
Published: May 2021

AbstractLaboratory-markers of the systemic inflammatory-response, such as neutrophil/lymphocyte-ratio (NLR) have been studied as prognostic factors in several tumors but in OC-patients their role is still controversial and no data about the possible correlation with the BRCA-status has been ever reported. We consecutively enrolled a series of 397 newly diagnosed high-grade serous-advanced OC-patients. All patients were tested for BRCA-mutational-status and blood-parameters have been collected 48 h before staging-surgery. A significant correlation of NLR with disease distribution (p < 0.005) was found and patients with NLR < 4 underwent primary-debulking-surgery more frequently (p-value 0.001), with a lower surgical-complexity-score (p-value 0.002). Regarding survival-data, patients with NLR < 4 had a significant 7-month increase in mPFS (26 vs 19 months, p = 0.009); focusing on the BRCA-status, among both BRCA-mutated and BRCA-wild type patients, those with lower NLR had a significantly prolonged mPFS compared to patients with NLR > 4 (BRCA-mutated: 35 vs 23 months, p = 0.03; BRCA-wt: 19 vs 16 months, p = 0.05). At multivariate-analysis, independent factors of prolonged PFS were BRCA mutational status, having received complete cytoreduction and NLR < 4. Also, the strongest predictors of longer OS were BRCA-mutational status, having received complete cytoreductive surgery, NLR < 4 and age. NLR is confirmed to be a prognostic marker in OC-patients and it seems unrelated with BRCA-mutational status.
Predicting youth diabetes risk using NHANES data and machine learning
Authors: Vangeepuram Nita , Liu Bian , Chiu Po-hsiang , Wang Linhua , Pandey Gaurav 
Published: May 2021

AbstractPrediabetes and diabetes mellitus (preDM/DM) have become alarmingly prevalent among youth in recent years. However, simple questionnaire-based screening tools to reliably assess diabetes risk are only available for adults, not youth. As a first step in developing such a tool, we used a large-scale dataset from the National Health and Nutritional Examination Survey (NHANES) to examine the performance of a published pediatric clinical screening guideline in identifying youth with preDM/DM based on American Diabetes Association diagnostic biomarkers. We assessed the agreement between the clinical guideline and biomarker criteria using established evaluation measures (sensitivity, specificity, positive/negative predictive value, F-measure for the positive/negative preDM/DM classes, and Kappa). We also compared the performance of the guideline to those of machine learning (ML) based preDM/DM classifiers derived from the NHANES dataset. Approximately 29% of the 2858 youth in our study population had preDM/DM based on biomarker criteria. The clinical guideline had a sensitivity of 43.1% and specificity of 67.6%, positive/negative predictive values of 35.2%/74.5%, positive/negative F-measures of 38.8%/70.9%, and Kappa of 0.1 (95%CI: 0.06–0.14). The performance of the guideline varied across demographic subgroups. Some ML-based classifiers performed comparably to or better than the screening guideline, especially in identifying preDM/DM youth (p = 5.23 × 10−5).We demonstrated that a recommended pediatric clinical screening guideline did not perform well in identifying preDM/DM status among youth. Additional work is needed to develop a simple yet accurate screener for youth diabetes risk, potentially by using advanced ML methods and a wider range of clinical and behavioral health data.
Space-time characterization of community noise and sound sources in Accra, Ghana
Authors: Clark Sierra N. , Alli Abosede S. , Nathvani Ricky , Hughes Allison , Ezzati Majid , Brauer Michael , Toledano Mireille B. , Baumgartner Jill , Bennett James E. , Nimo James , Bedford Moses Josephine , Baah Solomon , Agyei-Mensah Samuel , Owusu George , Croft Briony , Arku Raphael E. 
Published: May 2021

AbstractUrban noise pollution is an emerging public health concern in growing cities in sub-Saharan Africa (SSA), but the sound environment in SSA cities is understudied. We leveraged a large-scale measurement campaign to characterize the spatial and temporal patterns of measured sound levels and sound sources in Accra, Ghana. We measured sound levels and recorded audio clips at 146 representative locations, involving 7-days (136 locations) and 1-year measurements between 2019 and 2020. We calculated metrics of noise levels and intermittency and analyzed audio recordings using a pre-trained neural network to identify sources. Commercial, business, and industrial areas and areas near major roads had the highest median daily sound levels (LAeq24hr: 69 dBA and 72 dBA) and the lowest percentage of intermittent sound; the vice-versa was found for peri urban areas. Road-transport sounds dominated the overall sound environment but mixtures of other sound sources, including animals, human speech, and outdoor music, dominated in various locations and at different times. Environmental noise levels in Accra exceeded both international and national health-based guidelines. Detailed information on the acoustical environmental quality (including sound levels and types) in Accra may guide environmental policy formulation and evaluation to improve the health of urban residents.