Miracle-dz/UniFAR-FTUs huggingface dataset:
Aseismic deformations perturb the stress state and trigger induced seismicity during injection experiments

Fluid injections can trigger seismicity even on faults that are not optimally oriented for reactivation, suggesting either sufficiently large fluid pressure or local stress perturbations. Understanding how stress field may be perturbed during fluid injections is crucial in assessing the risk of induced seismicity and the efficiency of deep fluid stimulation projects. Here, we focus on a series of in situ decametric experiments of fluid-induced seismicity, performed at 280 m depth in an underground gallery, while synchronously monitoring the fluid pressure and the activated fractures movements. During the injections, seismicity occurred on existing natural fractures and bedding planes that are misoriented to slip relative to the background stress state, which was determined from the joint inversion of downhole fluid pressure and mechanical displacements measured at the injection. We then compare this background stress with the one estimated from the inversion of earthquake focal mechanisms. We find significant differences in the orientation of the stress tensor components, thus highlighting local perturbations. After discussing the influence of the gallery, the pore pressure variation and the geology, we show that the significant stress perturbations induced by the aseismic deformation (which represents more than 96 per cent of the total deformation) trigger the seismic reactivation of fractures with different orientations.
Teachers’ conceptions and uses of student collaboration in the classroom

ABSTRACT Background The ability to collaborate is a central competence that students need to be taught in school, in order to prepare them for the social and work realities that they will face in the 21st century. Research shows that students often study in educational settings that do not promote collaboration with peers. Based on a renewed focus on the ability to collaborate as an educational outcome in itself, this paper explores how teachers think about and use student collaboration in the classroom. Purpose This study, conducted in Norway, aimed to better understand teachers’ pedagogical reasons for using collaboration. Such insight can offer valuable knowledge about how collaboration is understood and might influence classroom practice. Methods A small scale, detailed qualitative study was undertaken. The participants comprised a teacher team of four lower secondary school teachers, and data were collected through individual, semi-structured interviews. Data were analysed in depth, using content analysis methods. Findings Five main themes were identified that illuminated the teachers’ conceptions of collaboration: (1) collaborative activities as a valued ingredient in teaching, (2) collaboration as organising, (3) collaboration as a tool, (4) collaboration as demanding and (5) collaboration skills ‘taken for granted’. The findings indicated that collaboration was regarded as a valued ingredient in teaching practice, despite sometimes being challenging to use. Further, it appeared that that the dual potential that lies in using collaborative activities – i.e. as a way to work with, and develop, the ability to collaborate – can be overshadowed by an academic focus. Interestingly, learning how to collaborate was rarely regarded as being an educational outcome in itself. Conclusion This paper highlights the need to accentuate the social pedagogy of collaborative activities, in order to prepare students for the social and work realities that lie before them. Opportunities for teachers to develop their understanding of student collaboration and learn about how best to structure teaching and learning to capture the dual potential that lies within should be embedded in teacher education and on-going professional learning.
User motivation in fake news sharing during the COVID-19 pandemic: an application of the uses and gratification theory

Purpose This study developed a predictive model that established the user motivational factors that predict COVID-19 fake news sharing on social media Design/methodology/approach The partial least squares structural equation modelling (PLS-SEM) was used for the analysis Data were drawn from 152 Facebook and WhatsApp users in Nigeria to examine the research model formulated using the uses and gratification theory (UGT) Findings We found that altruism, instant news sharing, socialisation and self-promotion predicted fake news sharing related to COVID-19 pandemic among social media users in Nigeria Specifically, altruism was the strongest predictor to fake news sharing behaviour related to COVID-19, followed by instant news sharing and socialisation On the contrary, entertainment had no association with fake news sharing on COVID-19 Practical implications We suggest intervention strategies which nudge people to be sceptical of the information they come across on social media We also recommend healthcare providers and the Nigerian government to provide relevant information on this current pandemic That is, correct information should be shared widely to the public domain through various conventional and online media This will lessen the spread of fake news on the concocted cure and prevention tips found online Originality/value The salient contributions of this study are as follows: First, it brings to the fore that the desire for self-promotion is associated with fake news sharing on social media;second, it shifts the focus of studies on fake news from detection methods to sharing behaviour, which fuels the uncontrollable spread of falsehood;third, it expands the existing literature on misinformation sharing by demonstrating the user motivation that leads to fake news sharing using the UGT
Responsible Investing: A Study on Non-Economic Goals and Investors’ Characteristics

The notion of rational investment is not attuned with the idea of socially responsible investment. Incongruence with conventional investments, the SRI/sustainable investment/ethical investment is pertained to ethical, environmental and social criteria (Eccles and Viviers,2011). All investors are not single-minded for an objective of wealth creation. The welfare of society and the environment are among the other drivers of investment. In certain cases, investors do prefer sustainable development to personal financial aspects (Beal et al., 2005). The present study has primarily focused on assessing the relationship between individual investors’ attributes and their noneconomic goal in order to comprehend their socially responsible investment behaviour specifically in Indian scenario. The findings of study are useful for fund managers, regulators and researchers as study has provided useful insights regarding behaviour of Indian investors for responsible investments.
Performance of Cholesterol Oxidase Sequestered within Reverse Micelles Formed in Supercritical Carbon Dioxide

The authors report the first results on an enzyme-induced reaction within the water core of reverse micelles that have been formed in supercritical CO{sub 2} (scCO{sub 2}). By using a perfluoropolyether ammonium carboxylate (PFPE) surfactant, the authors form reverse micelles in scCO{sub 2} with water cores and the authors show that the oxidation of cholesterol by cholesterol oxidase (ChOx) obeys Michaelis-Menten kinetics. The results of their experiments also show that (1) the optimum ChOx activity occurs when the molar ratio of H{sub 2}O-to-PFPE (R) exceeds {approximately}12, (2) the rate constant describing the conversion of the ChOx-cholesterol complex to product ({kappa}{sub cat,app}) is similar to values reported using reverse micelle systems formed in liquid alkanes, (3) the equilibrium constant that describes the ChOx-cholesterol complex dissociation (K{sub m,app}) is optimal at high R values, (4) the best-case K{sub m,app} is {approximately}2-fold better than the value reported using reverse micelles formed in liquid alkanes, (5) there is little change in the ChOx {kappa}{sub cat,app} and K{sub m,app} as the authors adjust the CO{sub 2} pressure between 100 and 260 bar, and (6) the ChOx was active within the PFPE water pool for at least 5 h; however, after 8 or more hours withinmore » the PFPE water pool, ChOx became temporarily inactive. « less
New Acentric Core Structure for Organic Electrooptic Crystals Optimal for Efficient Optical‐to‐THz Conversion

polar molecules are required to align perfectly parallel to produce a highly polar crystal. [ 13 ] However, in most cases polar push–pull π-conjugated molecules possessing a large dipole moment (usually over 10 D) result in an antiparallel alignment in the crystalline state due to strong dipole–dipole antiparallel aggregations. [ 13 ] Up to now, only few classes of organic crystals exhibiting a large electrooptic coeffi cient of over 50 pm V −1 in the (nonresonant) IR region have been developed. [ 8,9 ]
Detection and Identification of Bogus Profiles in online Social Network using Machine Learning Methods

: Here current creation online social networks (OSNs) become more and more common and the social life of people has become more linked to these pages. They use OSNs to remain in finger with everyone else, distribute news, prepare dealings and still run their personal e. Out of control of the OSN's evolution and the huge extent of their supporters 'individual developments, they have been attackers and impostors who take individual information, share fake news and disseminate vindictive exercises. Researchers in various fields began inspecting environmentally friendly techniques in order to perform abnormal activity and counterfeit money that is based on accounting and classification algorithms [1]. However, the use of stand-alone classification algorithms no longer yields a straightforward outcome, some of the factors that are manipulated by the account have a low influence or have no impact in the closing results. The paper proposes to use the SVM-NN as a modern algorithm to effectively identify suspected Twitter accounts and bots, to add four choices and to restrict measurements. Three laptop classification mastering algorithms were used to determine the actual or false identity of target accounts. They included the SVM, the Neural Network and our recently urbanized SVM-NN method that utilizes far less hardware but is still able to correctly identify about 98% of the money due to the training data set.
Numerical Study Of Natural Convection In Square Cavity Using Lattice Boltzmann Method: Obstacles Effect

In this work, the natural convection is studied in a closed square cavity differentially heated, using the Lattice Boltzmann numerical Method. Completely filled with a newtonian fluid, the cavity is managed by two rigid walls in right and left sides, and is provided with two rectangular adiabatic obstacles interposed on the mid-horizontal walls. The height of the two obstacles is varied from 10% to 40% of the side (L). The calculation code was performed for a laminar flow and an incompressible fluid with a Prandtl number Pr = 0.71 (the case of air). The computation code thus developed was used to analyse the effect of the length of obstacles in the mid-square cavity. The obtained results were validated by comparing with those of a previously published works. It has been deduced that the addition of the obstacles influences the thermal and hydrodynamic profiles of the flow inside the cavity and its thermal performances.
Minimal entropy production rate of interacting systems

Many systems are composed of multiple, interacting subsystems, where the dynamics of each subsystem only depends on the states of a subset of the other subsystems, rather than on all of them. I analyze how such constraints on the dependencies of each subsystem’s dynamics affects the thermodynamics of the overall, composite system. Specifically, I derive a strictly nonzero lower bound on the minimal achievable entropy production rate of the overall system in terms of these constraints. The bound is based on constructing counterfactual rate matrices, in which some subsystems are held fixed while the others are allowed to evolve. This bound is related to the ‘learning rate’ of stationary bipartite systems, and more generally to the ‘information flow’ in bipartite systems. It can be viewed as a strengthened form of the second law, applicable whenever there are constraints on which subsystem within an overall system can directly affect which other subsystem.
Social and environmental factors influencing dietary choices among Dawenkou culture sites, Late Neolithic China

Archaeological cultures are commonly defined by typologies established from ceramic assemblages at sites dated to a relatively restricted timeframe and located in specific geographic regions. It is often assumed that cultural traditions, social organizations, and other aspects of lifeways were similar throughout the established cultural areas. However, variations in pottery assemblages, burial practices, house construction techniques, and subsistence strategies are observed among late Neolithic Dawenkou culture sites in China. This study uses stable isotopic, archaeobotanical, and archaeozoological analysis to investigate variation in diet at middle and late Dawenkou sites. We provide new isotopic data for two sites and a comparison of results for all studies to date for the Dawenkou culture area. There is significant synchronic and diachronic variation, both among and within sites, during the middle and late Dawenkou period. There are multiple potential explanations for this variability including constraints from environmental factors such as temperature, precipitation, local geomorphology, and social factors such as gender, social status, and ethnicity. This study demonstrates that closer examination of Dawenkou culture sites using multiple approaches provides a more nuanced understanding of variation in communities that deserve further analysis.
Data-driven network loading

ABSTRACT Dynamic Network Loading (DNL) models are typically formulated as a system of differential equations where travel times, densities or any other variable that indicates congestion is endogenous. However, such endogeneities increase the complexity of the Dynamic Traffic Assignment (DTA) problem due to the interdependence of DNL, route choice and demand. In this paper, attempting to exploit the growing accessibility of traffic-related data, we suggest that congestion can be instead captured by exogenous variables, such as travel time observations. We propagate the traffic flow based on an exogenous travel time function, which has a piece-wise linear form. Given piece-wise stationary route flows, the piece-wise linear form of the travel time function allows us to use an efficient event-based modelling structure. Our Data-Driven Network Loading (DDNL) approach is developed in accordance with the theoretical DNL framework ensuring vehicle conservation and FIFO. The first simulation experiment-based results are encouraging, indicating that the DDNL can contribute to improving the efficiency of applications where the monitoring of historical network-wide flows is required. Abbreviations: DDNL – Data Driven Network Loading; DNL – Dynamic Network Loading; DTA – Dynamic Traffic Assignment; ITS – Intelligent Transportation Systems; OD – Origin Destination; TTF – Travel Time Function; LTT – Linear Travel Time; DL – Demand level
Moral Force: Leaders' Actions and Social Distancing

In the context of the COVID-19 pandemic, leaders' actions can influence whether individuals stay at home or ignore social distancing orders. Mexican president Lopez Obrador held public events in different states of the country during the health emergency. This paper studies whether his example of contravening social distancing recommendations affects mobility rates in municipalities that support him. We use mobility data from UNDP-GRANDATA and electoral data from the 2018 presidential election. Using a multiple difference-in-differences model, we find that after president Lopez Obrador holds public events outside of his office, mobility rates increase where his political support is high. The effect is higher during the period of social distancing implemented by the health authorities: the overall effect of his public appearances is an increase of more than 0.13 standard deviations on mobility rates of municipalities that support him. These results suggest that leaders' actions are relevant to influence decisions when individuals have limited information.
Preparation and Release Behavior of Polyelectrolyte Microcapsules

Hybrid calcium carbonate (CaCO3)/poly(styrene sulfonate) (PSS) particle, as a template, was synthesized using colloidal crystallization with the presence of nitrate tetrahydrate (Ca(NO3)2•4H2O), sodium carbonate (Na2CO3) and PSS. Microcapsule was prepared by template-assisted layer-by-layer (LbL) technology in solutions of two oppositely charged polyelectrolytes, poly(styrenesulfonate) (PSS) and poly(allylamine hydrochloride) (PAH) alternately, followed by dissolving the template with disodium ethylenediaminetetraacetate (EDTA). The release behavior of rhodamine B (RhB) from the microcapsules was examined and the rates of release at different pH were studied.
UWB Transmission through Human Thorax: An Index of Cardiac Health

There are many applications which require remote and non-invasive measurement of heartbeat of a human being using an ultra-wideband (UWB) radar. Sophisticated models and their analysis need to be referred before the design of a practical radar prototype. In this paper, i) a UWB wave propagation model of human thorax and ii) the power transmission coefficients estimated from the simulations of the model in the range 1-10 GHz using MATLAB are presented. The study reveals that there is a periodic variation of the transmission coefficients in correlation with the instantaneous physical dimensions of an active heart.
Temperature Measurement of Modern Cutting Tools During Turning

The study presents the influence of the anti-wear coatings and the type of material from which the cutting tools are made of on the cutting temperature occurring on the tool. The cutting tools made of boron nitride and tungsten carbide composite were investigated. The methodology of measuring the cutting temperature using the thermoelement and thermovision techniques was presented. The results of the temperature measurements occurring on the cutting tool in the cutting zone were compared. The paper also presents a method of determining the effective emissivity of the tested tools, necessary for the correct temperature measurement using the non-contact method. The obtained data were interpreted and the relationships described, and then the results obtained were discussed.
Predicted success of prophylactic antiviral therapy to block or delay SARS-CoV-2 infection depends on the targeted mechanism

Repurposed drugs that are immediately available and have a good safety profile constitute a first line of defense against new viral infections. Despite a limited antiviral activity against SARS-CoV-2, several drugs serve as candidates for application, not only in infected individuals but also as prophylaxis to prevent infection establishment. Here we use a stochastic model to describe the early phase of a viral infection. We find that the critical efficacy needed to block viral establishment is typically above 80%. This value can be improved by combination therapy. Below the critical efficacy, establishment can still sometimes be prevented; for that purpose, drugs blocking viral entry into target cells (or equivalently enhancing viral clearance) are more effective than drugs reducing viral production or enhancing infected cell death. When a viral infection cannot be prevented because of high exposure or low drug efficacy, antivirals can still delay the time to reach detectable viral loads from 4 days when untreated to up to 30 days. This delay flattens the within-host epidemic curve, and possibly reduces transmission and symptom severity. These results suggest that antiviral prophylaxis, even with reduced efficacy, could be efficiently used to prevent or alleviate infection in people at high risk. It could thus be an important component of the strategy to combat the SARS-CoV-2 pandemic in the months or years to come.
Correlation between alterations of gut microbiota and miR-122-5p expression in patients with type 2 diabetes mellitus

Background To investigate the correlation between gut microbiota and circulating microRNAs (miRNAs) in patients with primary diagnosis of type 2 diabetes mellitus (T2DM) and to explore the possible mechanisms of miRNA-gut microbiota crosstalke network in the regulation of the insulin signaling pathway and glucose homeostasis in T2DM. Methods T2DM patients and normal controls were recruited. Fasting plasma and fecal samples were collected from the subjects, and their biochemical indexes including fasting blood glucose (FBG), glycated hemoglobin (HbAlc), cholesterol (TC), total triglycerides (TG), high-density lipoprotein (HDL), low-density lipoprotein (LDL), and insulin were recorded. The variations in intestinal microbiota in the two groups were analyzed using 16S rRNA third-generation sequencing technology, and the differential expression of miRNAs between the groups was screened using miRNA high-throughput sequencing. The correlation and association between specifically changed intestinal microbiota and miRNA expressions were analyzed using a combination of bioinformatics analysis and statistical methods. Finally, 16S functional gene prediction analysis and target gene enrichment pathway analysis were carried out to predict relevant gut microbiota and miRNAs. Results Compared with normal controls, the biochemical indexes of HAlbc, FBG, TG, TC, LDL, HDL, and insulin were significantly different in T2DM patients (P<0.001, P<0.001, P=0.0125, P=0.98, P<0.001 P=0.022, and P=0.0013, respectively). The two groups also showed significantly different intestinal microbiota distribution and miRNA expression characteristics, including in the counts of Bacteriodes. uniformis and Phascolarctobacterium. Faecium (P=0.023, 0.031), which were negatively correlated (P=0.014, FC = -2.36) with the expression levels of serum miR-122-5p (r=−0.68, −0.60, P=0.01, 0.01). Conclusions This study discovered specific gut microbiota and miRNA characteristics in patients with a primary diagnosis of T2DM. A negative correlation between miR-122-5p and the intestinal bacteria Bacteriodes. uniformis and Phascolarctobacterium. Faecium was also revealed, suggesting that the crosstalke between miRNA and gut microbiota may regulate the insulin secretion and signal transduction by controling key genes of glucose metabolism during the development of T2DM.