Miracle-dz/UniFAR-FTUs huggingface dataset:
Embedding Visual Software Analytics on the GitHub Platform on the Example of Static Source Code Metrics and Software Maps

Readily available software analytics tools are often operated as external services, where measured software analysis data is kept internal, and no external use of the data is available. We propose an approach for embedded visual software analytics on the GitHub platform by leav-eraging GitHub Actions and the GitHub API. The proposed approach collects static source code metrics for each commit and augments the commit by the resulting software analytics data that is stored as git objects within the same repository. We show that this approach is feasible to be integrated into software projects as it poses only little overhead to CI runtime and storage overhead. The stored software analytics data is externally accessible to allow for external visualization tools, such as software maps. This enables a large amount of projects to have access to software analytics as well as provide means to communicate the current status of a project.
Work in Progress: A Glance at Social Media Self-Censorship in North America

—There is a growing trend of social backlash and ostracism for thoughts and opinions shared online. Coupled with the rise of strict content moderation or digital nudges discouraging unpopular opinions, this trend calls into question whether users feel comfortable expressing their views freely on social media. Self-censorship can be defined as the “act of intentionally and voluntarily withholding information from others in the absence of formal obstacles” [4]. In this work, we sought to understand the self-censorship behavior of Canadian and United States social media users through an online survey. Our analysis suggests that users’ exhibit different degrees of concern when posting controversial content, and that these differences can be explained by demographic, psychometric and political orientation factors. Our results also suggest that there seems to be a consensus on the type of content that is more prone to be self-censored.
Added value of seasonal hindcasts for UK hydrological drought outlook

The UK has experienced recurring periods of hydrological droughts in the past, including the latest drought declared in summer 10 2022. Seasonal hindcasts, consisting of a large sample of plausible weather sequences, can be used to add value to existing approaches to water resources planning. In this study, the drivers of winter rainfall in the Greater Anglia region are investigated using the ECMWF SEAS5 hindcast dataset, which includes 2850 plausible winters across 25 ensemble members and 3 lead times. Four winter clusters were defined using the hindcast winters based on possible combinations of various atmospheric circulation indices (such as North Atlantic Oscillation, East Atlantic Pattern and the El-Niño Southern Oscillation). Using the 15 2022 drought as a case study, we demonstrate how storylines of the event could be created in autumn 2022 to provide an outlook of drought conditions and to explore plausible worst cases over winter 2022/23 and beyond. The winter clusters span a range of temperature and rainfall response in the Anglian region and represent circulation storylines that could have happened over winter 2022/23. Although winter 2022/23 has now passed, we aim to demonstrate the added value of this approach to provide outlooks during an ongoing event with a brief retrospective of how winter 2022/23 transpired. Storylines created from 20 the hindcast winters were simulated using the GR6J catchment hydrological model and the groundwater level model Aquimod at selected catchments and boreholes in the Anglian region. Results show that drier than average winters characterised by predominantly NAO-/EA- and NAO+/EA- circulation patterns would result in the continuation of the drought with a high likelihood of below normal to low river flows across all selected catchments and boreholes by spring and summer 2023. Catchments in Norfolk are particularly vulnerable to a dry summer in 2023
Image Compression Via Sparse Representation

In recent years sparse representation has become a hot topic in the research of image representation model and there has been a growing interest in the study of image compression based on sparse representation. However, when coding different images, we have to train the dictionaries that correspond to these images. In the paper, we use three different kinds of image databases to train a group of bases which respectively reflects the characteristics of the three kinds of image, these bases are formed a big over-complete dictionary. Experimental results show that the proposed dictionary is superior to image compression based on the dictionaries trained by single image database.
Development of a Web-based Population Monitoring Information System

--------------------------------------------------------------------------------------------------------------------- ABSTRACT Nigeria being the most populous country in Africa has been using the manual method in population count. This has its attendant problem of being tedious, time consuming, monotonous as well as repetitive. The need to improve our manual census activities to an online based method was conceived. Hence, the objective of this research is to create a web-based population monitoring information system (web-based-PMIS) that provides inputs and outputs information support to admin/users in order to update their demographic information. In this project, the object oriented analysis and design methodology (OOADM) was adopted. The high level model of the proposed system was also designed and displayed in a format easily understandable to the user. There were two modules in all, each taking care of specific function like: user module and admin module. User module manages individual registration based on user option, search, and complaints while admin module add users and report generation such as updating and deleting report. Consequently, the parallel change over methodology was adopted to enable the comparison of the results of the two systems before implementation. For easy allocation, PHP, Ajax, Jquery and MYSQL were used for this development, which makes this application easily accessible from any part of the world, furthermore, the end result is an electronic identity that is encrypted which makes it very secured. This project is useful in any agency whose primary job is to enumerate human beings of any age bracket and obtain suitable demographic information as well as empower countries to make informed decisions for effective policy, planning and management of their economy.
Self-Regulated Learning Strategies, Academic Motivation, Perception of Technology and Mathematics Performance of the Senior High School STEM Students

: The objective of the study was to identify potential indicators of mathematics performance among students at three senior high schools in the province of Pangasinan. It took into consideration self-regulated learning methodologies, technological perception, and academic motivations. Inferential and descriptive statistics were used to obtain the values necessary for drawing logical conclusions. The research was conducted in three STEM-focused mega schools in the province of Pangasinan. The population of the study consisted of 124 11th graders enrolled during the first semester and continuing through the second semester of the 2020-2021 school year. The most common way for students to self-regulate their learning is to consider time and search for an appropriate learning environment. When students set aside time and cultivate a conducive learning environment, they perceive themselves as more productive. In addition, students felt comfortable learning with their mobile devices in and out of the classroom. Academic motivation (7), self-regulated learning strategies (9) and perception of technology were utilized to predict students' performance in mathematics using hierarchical multiple regression. As identified, identified regulation, motivation, rehearsal, time and study environment, and introjection regulation and rehearsal significantly predict students' mathematical performance. The derived model has a predictive accuracy of approximately 72.3% and was determined to be a good model. It is recommended that additional research be conducted on these factors contributing to the academic performance of students and that effective teaching strategies be developed to maximize the effects of these variables.
A Ramsey Test Analysis of Causation for Causal Models

We aim to devise a Ramsey test analysis of actual causation. Our method is to define a strengthened Ramsey test for causal models. Unlike the accounts of Halpern and Pearl ([2005]) and Halpern ([2015]), the resulting analysis deals satisfactorily with both overdetermination and conjunctive scenarios.
A global function of climatic aridity accounts for soil moisture stress on carbon 1 assimilation 2

18 19 The coupling between carbon uptake and water loss through stomata implies that gross primary 20 production (GPP) can be limited by soil water availability through reduced leaf area and/or 21 reduced stomatal conductance. Vegetation and land-surface models typically assume that GPP 22 is highest under well-watered conditions and apply a stress function to reduce GPP with 23 declining soil moisture below a critical threshold, which may be universal or prescribed by 24 vegetation type. It is unclear how well current schemes represent the water conservation 25 strategies of plants in different climates. Here eddy-covariance flux data are used to investigate 26 empirically how soil moisture influences the light-use efficiency (LUE) of GPP. Well-watered 27 GPP is estimated using the P model, a first-principles LUE model driven by atmospheric data 28 and remotely sensed green vegetation cover. Breakpoint regression is used to relate the daily 29 value of the ratio β(θ) (flux-derived GPP/modelled well-watered GPP) to soil moisture, which 30 is estimated using a generic water-balance model. Maximum LUE, even during wetter periods, 31 is shown to decline with increasing climatic aridity index (AI). The critical soil-moisture 32 threshold also declines with AI. Moreover, for any AI, there is a value of soil moisture at which 33 β(θ) is maximized, and this value declines with increasing AI. Thus, ecosystems adapted to 34 seasonally dry conditions use water more conservatively (relative to well-watered ecosystems) 35 when soil moisture is high, but maintain higher GPP when soil moisture is low. An empirical 36 non-linear function of AI expressing these relationships is derived by non-linear regression, 37 and used to generate a β(θ) function that provides a multiplier for well-watered GPP as 38 simulated by the P model. Substantially improved GPP simulation is shown during both 39 unstressed and water-stressed conditions, compared to the reference model version that ignores 40 soil-moisture stress, and to an earlier formulation in which maximum LUE was not reduced. 41 This scheme may provide a step towards better-founded representations of carbon-water cycle 42 coupling in vegetation and land-surface models.
SUCCESS WILL BE THE BEST REVENGE: REVENGE AS MOTIVATION FOR GOAL PURSUIT

In much of the published literature, revenge and goal achievement are studied as disparate fields. The present study attempts to unify these two fields by investigating whether motivation to get revenge can spur goal achievement. University students ( N = 130) were randomly assigned, in an online-survey format, to play an economic game with a fair or unfair partner. Previous study showed playing with an unfair partner, unlike playing with a fair partner, can lead to revenge motivation. Uniquely, rather than using real currency like most studies with economic games, valueless “virtual units” were used. Next, participants were offered the chance to compete against their economic game partner in completing anagrams, some of which were impossible. Then, revenge motivation, goal complex, and task enjoyment measures were collected. As expected, participants that played with an unfair partner were more likely to harbor feelings of revenge than those who played with a fair partner. However, counter to expectations, motivation to get revenge did not significantly predict perseverance on impossible anagrams. While these findings are unable to establish the hypothesized link between revenge motivation and goal achievement, they do show that virtual currencies can be used in economic games in some circumstances, opening up new avenues for future research.
Running title : Hemodynamic management of septic shock 8 9

36 Although the SSC Guidelines provide a standardized and generalized guidance, they are less 37 individualized. This review focuses on recent updates in the hemodynamic management of septic 38 shock. Monitoring and intervention for septic shock should be personalized according to the phase of 39 shock. In the salvage phase, fluid resuscitation and vasopressors should be given to provide tissue 40 perfusion for life-saving. During the optimization phase, tissue perfusion should be optimized. In the 41 stabilization and de-escalation phases, minimal fluid infusion and safe fluid removal should be 42 performed, respectively, while preserving organ perfusion. There is a controversy on the use of 43 restrictive versus liberal fluid strategies after initial resuscitation. Fluid administration after initial 44 resuscitation should depend on the patient's fluid responsiveness and require individualized 45 management. A number of dynamic tests have been proposed to monitor fluid responsiveness, which 46 help clinicians decide whether to give fluid or not. The optimal timing for the initiation of 47 vasopressors is unknown. Recent data suggest that early vasopressor initiation should be considered. 48 Inotropes can be considered in patients with decreased cardiac contractility associated with impaired 49 tissue perfusion despite adequate volume status and arterial blood pressure. Veno-arterial ECMO 50 should be considered for refractory septic shock with severe cardiac systolic dysfunction. 51 52
potential formation

The authors thank the reviewer for the careful review of our manuscript and helpful comments and suggestions, which significantly improved our manuscript. All the comments (in bold text) are addressed below point by point, with our response following in non-bold text and the corresponding revisions to the manuscript in blue. All updates of the original submission are tracked in the revised version.
Modelling below-cloud scavenging of size resolved particles in GEM-MACHv3.1

Below-cloud scavenging is the process of aerosol removal from the atmosphere between cloud-base and the ground by precipitation (e.g. rain or snow), and affects aerosol number/mass concentrations, lifetime and distributions. An accurate representation of precipitation phases is important in treating below-cloud scavenging as the efficiency of aerosol scavenging differs significantly between liquid and solid precipitation. The impact of 10 different representations of below-cloud scavenging on existing model biases (Makar et al, 2018), was examined through implementing a new aerosol below-cloud scavenging scheme (from Wang et al., 2014) and comparing with the GEM-MACH’s existing scavenging scheme, based on Slinn (1984). Further, the current GEM-MACH employs a single-phase precipitation for below-cloud scavenging: total precipitation is treated as either liquid or solid depending on a fixed environment temperature threshold. Here, we consider co-existing liquid and solid 15 precipitation phases as they are predicted by the GEM microphysics. GEM-MACH simulations are compared with - observed precipitation samples, with a focus on the particulate base cation NH 4+ , acidic anions NO 3- , SO 4= , HSO 3- in precipitation, and ambient particulate sulfate, ammonium and nitrate. Overall, the precipitation-phase partitioning and Wang et al. (2014) scavenging scheme improve GEM-MACH performance relative to earlier approaches. Including multi-phase approach leads to a decrease in SO 42- scavenging 20 and impacts the below-cloud scavenging of SO 2 into the aqueous phase over the domain. Sulphate biases improved from +46% to -5% relative to Alberta Precipitation Quality Monitoring Program wet sulphate observations. At Canadian Air and Precipitation Monitoring Network stations the biases became more negative, from -10% to -30
Electrical Resistivity method applied to the temporal variation of the groundwater level of the Alter do Chão aquifer, in Santarém, Pará.

: Based on the observation of permanent floods near the Federal University of Western Pará, this study aimed to verify the fluctuation of the water table level in the free aquifer of the Alter do Chão Formation and the possible relationship with permanent flooding in the research area. In the study area, the techniques of Vertical Electrical Sounding and Electrical Profiling Technique were applied. The measurements of the vertical electrical soundings made it possible to identify the most superficial layer, associated with the soil, with an average thickness of 1.42 m and apparent resistivity of ≅ 1000Ωm; a 2nd underlying layer, with an average thickness of 10.91 m and a highly resistive anomaly ( ≅ 4600Ωm); and a 3rd layer, at a depth of 12.34 m, in which there is an abrupt drop in resistivity ( ≅ 300Ωm). Vertical Electrical Sounding was carried out 5 times in the same location, from December 2017 to June 2018, allowing the correlation of the water table level variation with rainfall in the same period. Results indicate oscillation in water level of the Alter do Chão Formation unconfined aquifer in 7 m, during the studied period. Electrical Profiling Technique made it possible to associate the highly resistive anomaly of the 2nd layer with the Matura Lateritic Cover, which is the main cause of flooding in the investigated area.
Test Coverage for Network Configurations

We develop NetCov, the first tool to reveal which network configuration lines are being tested by a suite of network tests. It helps network engineers improve test suites and thus increase network reliability. A key challenge in its development is that many network tests test the data plane instead of testing the configurations (control plane) directly. We must be able to efficiently infer which configuration elements contribute to tested data plane elements, even when such contributions are non-local (on remote devices) or non-deterministic. NetCov uses an information flow graph based model that precisely captures various forms of contributions and a scalable method to lazily infer contributions. Using it, we show that an existing test suite for Internet2 (a nation-wide backbone network in the USA) covers only 26% of the configuration lines. The feedback from NetCov makes it easy to define new tests that improve coverage. For Internet2, adding just three such tests covers an additional 17% of the lines.
Investigating the development of clouds within marine cold-air outbreaks

Abstract. Marine cold-air outbreaks are important parts of the high-latitude climate system and are characterised by strong surface fluxes generated by the air–sea temperature gradient. These fluxes promote cloud formation, which can be identified in satellite imagery by the distinct transformation of stratiform cloud “streets” into a broken field of cumuliform clouds downwind of the outbreak. This evolution in cloud morphology changes the radiative properties of the cloud and therefore is of importance to the surface energy budget. While the drivers of stratocumulus-to-cumulus transitions, such as aerosols or the sea surface temperature gradient, have been extensively studied for subtropical clouds, the factors influencing transitions at higher latitudes are relatively poorly understood. This work uses reanalysis data to create a set of composite trajectories of cold-air outbreaks moving off the Arctic ice edge and co-locates these trajectories with satellite data to generate a unique view of liquid-dominated cloud development within cold-air outbreaks. The results of this analysis show that clouds embedded in cold-air outbreaks have distinctive properties relative to clouds following other trajectories in the region. The initial strength of the outbreak shows a lasting effect on cloud properties, with differences between clouds in strong and weak events visible over 30 h after the air has left the ice edge. However, while the strength (measured by the magnitude of the marine cold-air outbreak index) of the outbreak affects the magnitude of cloud properties, it does not affect the timing of the transition to cumuliform clouds or the top-of-atmosphere albedo. In contrast, the initial aerosol conditions do not strongly affect the magnitude of the cloud properties but are correlated to cloud break-up, leading to an enhanced cooling effect in clouds moving through high-aerosol conditions due to delayed break-up. Both the aerosol environment and the strength and frequency of marine cold-air outbreaks are expected to change in the future Arctic, and these results provide insight into how these changes will affect the radiative properties of the clouds. These results also highlight the need for information about present-day aerosol sources at the ice edge to correctly model cloud development.
Impact of the COVID-19 Pandemic on SME Debt in a 1 Sub-Saharan Context: The Case of Cameroon

7 Following the confinement imposed by the Cameroonian authorities after the contamination of 8 some people by the Coronavirus, several companies in general and SMEs in particular have 9 experienced great diﬀiculties due to a partial or total cessation of their activities. The 10 objective of this study is to evaluate the impact of the Covid-19 pandemic on the indebtedness 11 of Cameroonian SMEs. Through statistical and econometric analyses carried out on a sample 12 of 450 Cameroonian SMEs, the results obtained highlight the significant influence of the 13 Covid-19 health crisis on the better development of Cameroonian SMEs’ activities. This 14 suggests that the Cameroonian government and/or financial partners should provide financial 15 assistance to SMEs in order to alleviate the cash flow diﬀiculties caused by the Covid-19 16 pandemic. 17