Miracle-dz/UniFAR-FTUs huggingface dataset:
ColdGuess: A General and Effective Relational Graph Convolutional Network to Tackle Cold Start Cases

Low-quality listings and bad actor behavior in online retail websites threatens e-commerce business as these result in sub-optimal buying experience and erode customer trust. When a new listing is created, how to tell it has good-quality? Is the method effective, fast, and scalable? Previous approaches often have three limitations/challenges: (1) unable to handle cold start problems where new sellers/listings lack sufficient selling histories. (2) inability of scoring hundreds of millions of listings at scale, or compromise performance for scalability. (3) has space challenges from large-scale graph with giant e-commerce business size. To overcome these limitations/challenges, we proposed ColdGuess, an inductive graph-based risk predictor built upon a heterogeneous seller product graph, which effectively identifies risky seller/product/listings at scale. ColdGuess tackles the large-scale graph by consolidated nodes, and addresses the cold start problems using homogeneous influence1. The evaluation on real data demonstrates that ColdGuess has stable performance as the number of unknown features increases. It outperforms the lightgbm2 by up to 34 pcp ROC-AUC in a cold start case when a new seller sells a new product . The resulting system, ColdGuess, is effective, adaptable to changing risky seller behavior, and is already in production
Cost-Aware Multidimensional Auto-Scaling of Service- and Cloud-Based Dynamic Routing to Prevent System Overload

Dynamic reconfiguration is commonly used to accommodate the dynamic behavior of today’s applications. As cloud-based systems become increasingly complex, it is hard and cost-ineffective to manage them manually. Dynamic routers, such as API Gateways or Message Brokers, in combination with auto-scalers can adapt the system to the resource demands, e.g., when a sudden load spike for a specific part of the system is observed. Without taking costs of cloud resources into account, this reconfiguration can lead to significant increase of charges. We propose a self-adaptive and cost-aware dynamic routing architecture called Adaptive Dynamic Routers. The novel architecture performs a multi-criteria optimization analysis to automatically reconfigure the routers and the services of a cloud-based system considering the costs of reconfiguration. This multidimensional auto-scaling of resources takes incoming load as an input, and uses queuing theory to find an optimal reconfiguration solution. We systematically evaluated our architecture with an extensive number of evaluation cases (9600). On average over cases where an overload is predicted, our approach reduces the overload rate by 46.7% and 61.8% for routers and services, respectively.
Robustness of Urban Coastal Rail Network under Projected Future Floods

Recent events suggest weather extremes are becoming more frequent and intense under a changing climate. The floods of the future, in all likelihood, will be more severe, causing substantial damage to human lives and critical lifeline systems such as urban transportation networks. With an aging infrastructure and rising climate risk, a research hypothesis to examine is how much of the increased climate risk will translate to critical lifeline systems downstream, especially in urban areas where exposure is the highest. In this work, we develop a resilience framework blending statistical analysis of weather extremes and network science-based modeling of impacted systems. Two major urban rail networks in the US - Boston and Washington DC - are considered case studies. This study aims to evaluate quantitatively how a future flooding scenario might impact the respective networks in terms of loss of functionality. The insights generated can help stakeholders in data-driven decision-making and adaptation strategies. Furthermore, the framework developed can be generalized to other types of weather extremes and critical networks for similar evaluation studies.
Climate adaptation scenarios for a resilient future at UBC Botanical Garden:

As anthropogenic climate change continues to disrupt forests and species’ ecological niches, there is increasing urgency to create plans surrounding adaptation and mitigation for especially vulnerable species. The University of British Columbia’s Botanical Garden (UBCBG) wants to understand species responses to climate change and whether species within their collection will be able to survive in the Garden, given the effects of climate change. One especially important collection UBCBG curates is maple ( Acer ) trees, currently leading the global consortium of Acer and housing over 50 different species. This study examined the survival probability of four Acer species UBCBG curates including: five-fingered Maple ( Acer pentaphyllum Diels), considered critically endangered; paperbark/bloodbark Maple ( Acer griseum (Franch.) Pax), considered endangered; bigleaf maple ( Acer macrophyllum Pursh), not endangered; and vine maple ( Acer circinatum Pursh), not endangered. Maxent, a popular machine-learning algorithm, was used with open- source WorldClim’s 19 bioclimatic variables and provided presence -only occurrence data to conduct species distribution models for each tree species. Each model was evaluated using area under the curve (AUC). AUC scores were considered ‘good’ for each model; A. griseum - 0.95; A. pentaphyllum - 0.877; A. macrophyllum - 0.986; A. circinatum - 0.976. However, future distribution maps contain questionable results due to insufficient field data to inform the model, such as in-field temperature, moisture, elevation, and surrounding vegetation data. Though results can be interpreted as binary regarding whether or not UBCBG will be suitable for each species, they should be taken as preliminary ideas where management plans for mitigation and adaptation can be developed. This study concludes by detailing the importance of field data collection and provides future directions for research that UBCBG may consider when conducting similar analysis.
Power-of-Collaboration: A Sustainable Resilient Ledger Built Democratically

The recent surge in blockchain applications has accelerated the research in designing efficient decentralized currencies. Building a decentralized economy on the traditional byzantine fault-tolerant ( BFT ) protocols or the Proof-of-Work ( P O W ) consensus protocol is inadequate as the immutability of the ledger created by the former is at the mercy of the long-term safe-keeping of private keys of participants, while the latter yields an extremely inefficient and environmentally unsustainable consensus. To ameliorate this situation, we envision the design of our H YBRID C HAIN architecture, which offers the best of both worlds. Our H YBRID C HAIN design runs a traditional BFT protocol to commit client transactions and employs our novel Power-of-Collaboration ( P O C ) protocol to notarize the BFT chain. Unlike P O W , our P O C protocol advocates for participants to work together collaboratively instead of competing (often selfishly), which results in a safe, high-throughput, and resource-efficient consensus design.
CLEP_A_374788 949..957

1Research, Copenhagen Emergency Medical Services, Copenhagen, Denmark; 2Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; 3Department of Cardiology, Herlev and Gentofte Hospital, Copenhagen, Denmark; 4Emergency Medical Services, The Region of Southern Denmark, Odense, Denmark; 5Department of Regional Health Research, University of Southern Denmark, Odense, Denmark; 6Emergency Medical Services, North Region of Denmark, Aalborg, Denmark; 7Emergency Medical Services, Central Denmark Region, Viborg, Denmark; 8Center for Prehospital and Emergency Research, Aalborg University Hospital and Aalborg University, Aalborg, Denmark; 9Department of Cardiology and Clinical Investigation, Nordsjaellands Hospital, Hillerød, Denmark; 10Department of Cardiology, Aalborg University Hospital, Aalborg, Denmark; 11Emergency Medical Services, Naestved, Region Zealand, Denmark; 12Danish Clinical Quality Program (RKKP) ▪ National Clinical Registries, Copenhagen, Denmark
Quantifying Polarization in Models of Opinion Dynamics

It is widely believed that society is becoming increasingly polarized around important issues, a dynamic that does not align with common mathematical models of opinion formation in social networks. In particular, measures of polarization based on opinion variance always decrease over time in models like the popular DeGroot model. Complementing recent work that seeks to resolve this inconsistency by modifying opinion models, we instead resolve the inconsistency by proposing changes to how polarization is quantified . We present a natural class of group-based polarization measures that capture the extent to which opinions are clustered into distinct groups. Using theoretical and empirical arguments, we show that these group-based measures display interesting, non-monotonic dynamics, even in the simple DeGroot model. In particular, for natural social networks, group-based metrics can increase over time, and thereby correctly capture perceptions of increasing polarization. Our results build on work by DeMarzo et al., who introduced a group-based polarization metric based on ideological alignment. We show that a central tool from that work, a limit analysis of individual opinions under the DeGroot model, can be extended to the dynamics of other group-based polarization measures, including established statistical measures like bimodality. We also consider local measures of polarization that operationalize how polarization is perceived in a network setting. In conjunction with evidence from prior work that group-based measures better align with real-world perceptions of polarization, our work provides formal support for the use of these measures in place of variance-based polarization in future studies of opinion dynamics.
A DAB Converter with Common-Point-Connected Winding Transformers Suitable for a Single-Phase 5-Level SST System

One of the main disadvantages of the multi-level solid-state transformer (SST) system is the voltage imbalance on the output of the rectifier modules. This voltage imbalance can be caused by parameter mismatch of the active and passive components, different loads, and the floating structure of the high voltage DC-links. Some studies have been done to solve this voltage imbalance problem. A common way to avoid this imbalance is to balance the voltage of DC-links at the AC/DC conversion stage and balance the power between the modules at the DC/DC conversion stage. Most of these methods require a complex balancing controller or additional circuits. This paper proposes a novel dual active bridge (DAB) converter specialized in power balancing in a single-phase 5-level SST system. The proposed DAB converter does not require any additional balancing controllers or techniques for power balancing. The performance of the proposed DAB converter was verified by simulation and experiments using a 3 kW 5-level SST prototype system.
Database for Baghdad Soil Using GIS Techniques

teen sites Baghdad are made. The sites are divided into two groups, one in Karkh and the other in Rusafa. Assessing the underground conditions can be occurred by drilling vertical holes called exploratory boring into the ground, obtaining soil (disturbed and undisturbed) samples, and testing these samples in a laboratory (civil engineering laboratory /University of Baghdad). From disturbed, the tests involved the grain size analysis and then classified the soil, Atterberg limit, chemical test (organic content, sulphate content, gypsum content and chloride content). From undisturbed samples, the test involved the consolidation test (from this test, the following parameters can be obtained: initial void ratio eo, compression index cc, swelling index cs , coefficient of consolidation cv , coefficient of volume change mv, maximum preconsolidation stress Pc , Effective overburden pressure Po )and shear test (the following parameters can be obtained: undrained cohesion cu, angle of friction φ. In-situ testing was carried out by the standard penetration test in order to obtain the penetration resistance of the soil strata in a bore hole. Database for Baghdad soils is made using different GIS techniques connecting the spatial locations of those soils with their properties (ِAtterberg Limits, Specific Gravity, Grain size Analysis, Shear Strength parameters, Consolidation parameters), Borehole log, Site profile using the attribute tables, hyperlinks, metadata and SQL (System Query Language), so GIS techniques give the facilities for adding, editing and analyzing the existingdata as well as the any future data of Baghdad soils.
Passive, Consultative, and Coconstructive Methods: A Framework to Facilitate Community Participation in Design for Development

The complexity of design for development (D4D), humanitarian engineering (HE), and similar projects emerges from multiple sources, including the overarching requirement to address complex sociotechnical problems by effectively engaging community members. However, missing from the literature on enacting D4D/HE projects is a clear framework that classifies extant community participation methods based on key characteristics, especially vis-à-vis level of community participation in problem definition and solution processes. To address this lack of a classification framework, we first conducted a systematized literature search to identify methods used in D4D/HE projects. This literature search resulted in 64 identified methods. Following an iterative, inductive, and systematic process to develop classification systems combined with content analysis, a bidimensional framework emerged to classify the methods. The first dimension of the framework organizes methods according to a spectrum of three levels of community engagement: (1) passive, (2) consultative, and (3) coconstructive. The second dimension classifies methods based on the part of the design process in which it is most appropriate to use them. We conclude the paper by discussing considerations engineers should reflect upon when using the framework to inform their projects, as well as opportunities for future research.
Looking for Guidance? Five Principles for Leveraging Tensions in Corporate–Startup Collaboration

Corporate–startup collaboration (CSC) allows the co-development of innovations for pressing societal needs. Paradoxically, CSC is both fueled and challenged by diverging interests and approaches of the unequal actors. We apply a paradox lens to better understand the complex collaborative demands of CSC from the perspective of the corporate actors involved. Over the course of three years, we conducted 52 contextualized semi-structured interviews in a corporate-sponsored accelerator pursuing sustainability improvements. We identify five CSC paradoxes, which we translate into guiding principles for managing such paradoxes with a both/and mindset. Further, we show how these guiding principles help to address interdependencies between the CSC paradoxes. By disentangling the inherently paradoxical nature of the collaborative demands, we contribute to a fuller theoretical understanding of how organizational actors can manage these demands. We encourage companies engaging in CSC to use the guiding principles for empowering organizational actors’ understanding and approaches to CSC paradoxes.
Association between Influenza and COVID-19 Viruses and the Risk of Atherosclerosis: Meta-Analysis Study and Systematic Review

Highlights Atherosclerosis is an important issue in health care systems and one of the main causes of morbidity and mortality in patients. There is evidence of an association between infectious diseases and atherosclerosis. The present study demonstrates that infections with influenza and COVID-19 are risk factors for arthrosclerosis. It seems necessary to consider different strategies for managing and eradicating viral infections. Abstract There is a lot of evidence to suggest that patients infected with the COVID-19 and influenza viruses are at risk of atherosclerosis. Additionally, there are heterogeneous studies on the risk of arthrosclerosis in patients infected with the influenza and COVID-19 viruses. We conducted a case–control and cross-sectional study and examined the association between the risk of atherosclerosis, and influenza virus (IV-A and IV-B) and COVID-19 infections in this study. We searched for keywords such as influenza virus, COVID-19 and atherosclerosis in English and Persian in well-known databases such as PubMed, SID, Magiran and Google Scholar. In this study, we analyzed the information using a meta-analysis, the random effect model, the I2 index and STAT (version 11.2). The results from the analysis of ten studies on influenza virus and nine studies on COVID-19 reviewed individually (totaling 6428 samples for influenza virus infections and 10,785 samples for COVID-19 infections) demonstrated a risk of arthrosclerosis in patients with influenza and COVID-19 infections, with an OR (odds ratio) = 0.45 ((95% CI): 0.25 to 0.64) and an OR (odds ratio) = 1.04 ((95% CI): 0.82 to 1.26), respectively. The present study provides new insights into the risk of atherosclerosis in patients infected with the COVID-19 and influenza viruses. Therefore, it seems necessary to consider different strategies for managing and eradicating viral infections among individuals.
Bibliometric Analysis of Research on the Use of the Nine Hole Peg Test

Manual dexterity is essential for performing daily life tasks, becoming a primary means of interaction with the physical, social, and cultural environment. In this respect, the Nine Hole Peg Test (NHPT) is considered a gold standard for assessing manual dexterity. Bibliometrics is a discipline that focuses on analyzing publications to describe, evaluate, and predict the status and development trends in certain fields of scientific research. We performed a bibliometric analysis to track research results and identify global trends regarding the use of the NHPT. The bibliographic data were retrieved from the Web of Science database and then analyzed using the Bibliometrix R package, resulting in the retrieval of a total of 615 publications from 1988 to 2021. Among the 263 journals investigated, the most prolific were the Multiple Sclerosis Journal, Clinical Rehabilitation, and Multiple Sclerosis and Related Disorders. North America and Europe were the areas with the highest production of publications, with the United States (n = 104) ranking first in terms of the number of publications, followed by the United Kingdom (n = 62) and Italy (n = 62). The analysis of keywords revealed that there were two main lines of research, with one related to the study of recovery and disability of the upper limbs caused by certain diseases and another related to the study of reliability and validity. Structured information can be useful to understand the research trajectory and the uses of this tool.
The influence of bedrock river morphology and alluvial cover on gravel entrainment. Part 2: Modelling critical shear stress

The critical shear stress (τc) at which grains are entrained on a bedrock surface is important for determining how bedrock rivers evolve through changes in sediment cover and bedrock erosion. The difference in τc for grains on bedrock and alluvial surfaces also determines whether a channel may be susceptible to runaway alluviation. Bedrock channel beds can have a wide variety of morphologies, but we do not fully understand how this variation affects τc. Here we address how bedrock morphology alters the grain entrainment parameters of pivoting angle, grain exposure and roughness height z0, and thus τc. In our companion article we used scaled, 3D printed replicas of seven bedrock surfaces to measure grain pivoting angles for four grain sizes. For three surfaces, pivoting angles were also measured with 25–100% sediment cover. In this second article, we combine these pivot angle data with measurements of grain exposure and surface roughness (standard deviation of elevations, σz) to predict τc using a force–balance model. The bedrock topography produces substantial variation in τc; for a given grain diameter (D), a 3.6× range of σz across the surfaces without sediment cover produces up to a 5.1× variation in τc. For comparison, for any single surface, τc varies by up to 2.5× for a fourfold range in grain size. Comparison to previous models with less representation of grain‐scale geometry shows that in our results grains move at lower values of dimensionless critical shear stress (τ*c), and that τ*c decreases more quickly with increasing D/σz. However, direct comparison is difficult because previous relationships are based on a hydraulic roughness length that cannot be easily predicted without hydraulic data. Our results propose a new relationship between D/σz and τ*c, but further development and testing require datasets that combine measurements of flow, τc and grain‐scale geometry.
Impact of Producer Service Agglomeration on Carbon Emission Efficiency and Its Mechanism: A Case Study of Urban Agglomeration in the Yangtze River Delta

As an important part of the economic system of urban agglomeration, the agglomeration of producer services (APS) has become a key contributor to regional low-carbon development. This study analyzes the spatial effect of APS on carbon emission efficiency (CEE) as well as its mechanism and heterogeneity using the panel data of 41 cities in the Yangtze River Delta (YRD) region from 2005 to 2019. First, a U-shaped relationship exists between APS and CEE in both local and neighboring areas. Second, the non-linear relationship between APS and CEE is generated by allocation effects, structural effects and technology effects. Third, the effect of APS on CEE is constrained by the heterogeneity of urban characteristics, in which human capital, fiscal expenditure, and information infrastructure all support and positively moderate the energy-saving and carbon-reduction effect of APS. Fourth, the impact of externalities of APS on CEE varies, both the Marshall–Arrow–Romer (MAR) and Porter externalities having a U-shaped relationship with the CEE of neighboring areas but Jacobs externalities having no significant influence on the CEE of the surrounding areas. The findings of this study indicate that increasing the scale of APS in urban agglomeration, promoting the diversification and division of labor and the cooperation of industries across areas, and promoting the process of city–industry integration are important for achieving the goal of carbon peaking and carbon neutrality in the YRD region.
Mapping the Field of Social Media Engagement: A Literature Review Using Bibliometric Analysis

The aim of this article is to analyse the existing literature on social media engagement using bibliometric techniques to examine its evolution since its introduction in the business, management and accounting domains. This study comprises the following techniques based on a bibliometric analysis of 305 research papers extracted from Elsevier’s Scopus from 2011 to February 2021: citation analysis, co-citation analysis, co-occurrence of author keywords. The analysis highlights the essence of research in the field of social media engagement over the last 10 years. Social media engagement based on content, different platforms and various industries emerges as prominent themes in the extant literature. Further, the analysis identifies the most influential authors and journals, pertaining to the field of social media engagement. Lastly, directions for future research have been explained. Journal of Business Research has been a significant contributor to this concept among various other journals. This research will help practitioners obtain a deep understanding of the concept of social media engagement, which they can then use as a strategy to engage with customers.