Miracle-dz/UniFAR-FTUs huggingface dataset:
Coexisting spin resonance and long-range magnetic order of Eu in 
EuRbFe4As4

Magnetic excitations and magnetic structure of EuRbFe$_4$As$_4$ were investigated by inelastic neutron scattering (INS), neutron diffraction, and random phase approximation (RPA) calculations. Below the superconducting transition temperature $T_\text{c}=36.5$~K, the INS spectra exhibit the neutron spin resonances at $Q_\text{res}=1.27(2)$~$\text{\AA}^{-1}$ and $1.79(3)$~$\text{\AA}^{-1}$. They correspond to the $\mathbf{Q}=(0.5,0.5,1)$ and $(0.5,0.5,3)$ nesting wave vectors, showing three dimensional nature of the band structure. The characteristic energy of the neutron spin resonance is $E_\text{res}=17.7(3)$~meV corresponding to $5.7(1)k_\text{B}T_\text{c}$. Observation of the neutron spin resonance mode and our RPA calculations in conjunction with the recent optical conductivity measurements are indicative of the $s_\pm$ superconducting pairing symmetry in EuRbFe$_4$As$_4$. In addition to the neutron spin resonance mode, upon decreasing temperature below the magnetic transition temperature $T_\text{N}=15$~K, the spin wave excitation originating in the long-range magnetic order of the Eu sublattice was observed in the low-energy inelastic channel. Single-crystal neutron diffraction measurements demonstrate that the magnetic propagation vector of the Eu sublattice is $\mathbf{k}=(0, 0, 0.25)$, representing the three-dimensional antiferromagnetic order. Linear spin wave calculations assuming the obtained magnetic structure with the intra- and inter-plane nearest neighbor exchange couplings of $J_1/k_\text{B}=-1.31$~K and $J_c/k_\text{B}=0.08$~K can reproduce quantitatively the observed spin wave excitation. Our results show that superconductivity and long-range magnetic order of Eu coexist in EuRbFe$_4$As$_4$ whereas the coupling between them is rather weak.
Multiple gaps revealed by low temperature specific heat in the 1111-type CaFe0.88Co0.12AsF single crystals

Low-temperature specific heat (SH) is measured on the 1111-type CaFe0.88 Co0.12AsF single crystals under different magnetic fields. A clear SH jump with the height mJ mol−1 K−2 is observed at the superconducting transition temperature Tc. The electronic SH coefficient increases linearly with the field below 5 T and a kink is observed around 5 T, indicating a multi-gap feature in the present system. Such a sign is also reflected in the Tc − B data. A detailed analysis shows that this behavior can be interpreted in terms of a two-gap scenario with the ratio –4.5.
24 rational curves on K3 surfaces

Given [Formula: see text], we prove that all smooth K3 surfaces (over any field of characteristic [Formula: see text]) of degree greater than [Formula: see text] contain at most 24 rational curves of degree at most [Formula: see text]. In the exceptional characteristics, the same bounds hold for non-unirational K3 surfaces, and we develop analogous results in the unirational case. For [Formula: see text], we also construct K3 surfaces of any degree greater than [Formula: see text] with 24 rational curves of degree exactly [Formula: see text], thus attaining the above bounds.
Impact of HFOSS on Education on Instructors

Student involvement in Humanitarian Free and Open Source Software (HFOSS) increases student self-reported learning while providing the motivation of "doing good" [11]. Supporting this type of student participation also impacts the instructors. This effect includes modifying one's teaching approach, providing a different perspective on the subject matter, and changing how instructors perceive their roles. This paper explores the impact on instructors that result from supporting student participation in HFOSS, including consideration of pedagogical practices, self-perceptions of teaching, and exposure to open source culture and technologies. The paper also examines resources that instructors consider important for HFOSS education. The analysis presented here is based upon a qualitative analysis of semi-structured interviews with 24 faculty members. Results indicate that exploring HFOSS education changes instructors' pedagogical approaches, broadens instructors' perspectives on the connections between academic content and professional practice, and has impact on instructors' attitudes and motivations when teaching.
Evaluating Instructors' Classification of Programming Exercises Using the Revised Bloom's Taxonomy

It is a well-known fact that different instructors understand Bloom's taxonomy differently, thus they classify given test exercises into different levels of the taxonomy. The article reports on the impact of training instructors on the use of the taxonomy for programming courses with two innovations: encouraging instructors to classify each exercise into several cognitive processes necessary to solve it, and providing them with a wide range of examples of classified programming exercises. We evaluated the impact of these innovations in two training sessions. In the first session, the revised Bloom's taxonomy was introduced to the participants, and in the second session, the innovations were presented. In both sessions, participants were asked to classify ten exercises. The results show that classification into several cognitive processes was natural to instructors. However, other results were mixed. On the one hand, accuracy was increased, and confidence was increased for experienced participants. On the other hand, variation was increased, and confidence was decreased for non-experienced participants. Results show that our approach assists instructors in classifying exercises, but higher increases of expert instructors suggest that longer training is necessary for non-expert instructors.
Text-based Programming in Elementary School: A Comparative Study of Programming Abilities in Children with and without Block-based Experience

This paper describes an elementary school intervention to teach a text-based programming language to 10-11 year old students. We compare students with no previous programming experience with students with 3 semesters of experience with a block-based programming language. We analyze students' performance and learning based on detailed logs in an online programming platform and on multiple choice tests. Although both groups have a similar percentage of syntactical errors, the experienced group showed a better performance on exam scores and a lower number of test case errors. These findings suggest that, 10-11 year old students benefit from block-based experience when learning a new text-based programming language.
The Impact of Adding Textual Explanations to Next-step Hints in a Novice Programming Environment

Automated hints, a powerful feature of many programming environments, have been shown to improve students' performance and learning. New methods for generating these hints use historical data, allowing them to scale easily to new classrooms and contexts. These scalable methods often generate next-step, code hints that suggest a single edit for the student to make to their code. However, while these code hints tell the student what to do, they do not explain why, which can make these hints hard to interpret and decrease students' trust in their helpfulness. In this work, we augmented code hints by adding adaptive, textual explanations in a block-based, novice programming environment. We evaluated their impact in two controlled studies with novice learners to investigate how our results generalize to different populations. We measured the impact of textual explanations on novices' programming performance. We also used quantitative analysis of log data, self-explanation prompts, and frequent feedback surveys to evaluate novices' understanding and perception of the hints throughout the learning process. Our results showed that novices perceived hints with explanations as significantly more relevant and interpretable than those without explanations, and were also better able to connect these hints to their code and the assignment. However, we found little difference in novices' performance. Our results suggest that explanations have the potential to make code hints more useful, but it is unclear whether this translates into better overall performance and learning.
Art by Computing Machinery

When does a machine-created work becomes art? What is art? Can machine artworks fit in to the historical and present discourse? Do machine artworks demonstrate creativity, or are they a type of new media from which artists extend their creativity with? Will solely machine-created artworks be acceptable by our artworlds? This article probes these questions by first identifying the frameworks for defining and explaining art and evaluating its suitability for explaining machine artworks. It then explores how artworks have a necessary relationship with their human artists and the wider context of history, institutions, styles, and approaches and with audiences and artworlds. The article then questions whether machines have such a relational context and whether machines will ever live up to our standard of what constitutes an artwork as defined by us or whether machines are good only for assisting creativity. The question of intellectual property, rights, and ownership are also discussed for human--machine artworks and purely machine-produced works of art. The article critically assesses the viability of machines as artists as the central question in the historical discourse, extended through art and the artworld and evaluates machine-produced work from such a basis.
Laughter over Dread: Early Collaborative Problem Solving through an Extended Induction using Robots

Software development companies want new hires with strong interpersonal and problem solving skills. To ensure the development of such skills, they must be embedded throughout the curriculum. However, many students struggle to collaborate with peers and in self-regulated practice during the early stages of their course. Explicit scaffolding can, however, motivate such engagement. This tips and techniques session shows how an ice-breaker using LEGO EV3 robots at two UK institutions enhanced peer interaction and increased self-regulated practice over the first four weeks of 2016-17 and 2017-18.
Modeling the Propagation of Soft Errors in Programs

Due to the continuous growth of transistors in processors, the cloud computing paradigm and increasingly complex environment, soft errors, which are a category of typical transient errors, have become an urgent challenge in ground-level systems. To handle these errors, making clear the error propagation is the key step. As programs become large, we cannot employ traditional fault injection campaigns to monitor every possible error. This paper proposes a method to study and model the propagation of soft errors within a program. Based on dynamic instructions traced in an error-free program execution, the ACE analysis classifies soft errors in architectural registers into benign ones and non-benign ones. The benign errors are considered to be derated in the propagation. Then we build a crash model and an improved DDG to analyze the propagation of each non-benign error and to predict its consequence (crash or silent data corruption). If the error is considered to cause a crash, the crash latency and the propagation path are also predicted. The method can be used to predict outcomes of programs under soft errors as well as occurrence of correct outputs, silent data corruptions or crashes. Extensive fault-injection experiments are provided to validate the proposed method from multiple perspectives.
Are There Differences in Learning Gains When Programming a Tangible Object or a Simulation?

Physical computing is about programming and interacting with a tangible object to learn fundamental concepts of Computer Science (CS). This approach presents several benefits regarding motivation, creativity, and learning gains. Yet, these learning gains hardly are compared with those resulting from the programming of a simulation of a tangible object. In this article we present the results of a comparative study that has been conducted to explore this issue. With this study, we aimed to determine whether the programming of a tangible object or its digital simulation yields significantly different learning gains. In the experiment we conducted, participants (aged 14-17 with little or no prior programming knowledge) were divided into two groups: one programmed a tangible electronic board (the BBC micro:bit) while the other programmed a simulation of it. The results of this experiment suggest that, while each group significantly improved their understandings of fundamental CS concepts (i.e., variables, conditions, and loops), no significant difference was found when comparing the learning gains between the two groups.
A New Complex Network Robustness Attack Algorithm

Complex networks have been widely used in many systems of bank, social networks and smart grid, etc. A vital quantitative criteria for complex networks is to measure the robust performance in those systems. It observes the response of the networks when nodes or links are removed from potential threats. Most of the existing works focus on the enhancement of the robustness itself, but not considering the completeness of the possible removal attacks from the viewpoint of adversary. In this paper, we first propose a new RL-based critical edge removal attack (RCERA) algorithm, and prove that the damage of the robustness using the proposed algorithm is worse than that using the existing degree product attack and random edge attack. In order to solve the uncertainty of the network robustness evaluation algorithm proposed before, we propose a new complex network robustness evaluation algorithm. Finally we apply our attack algorithm to a Bitcoin OTC network. The result shows that our algorithm is better than the other two algorithm.
Adoption of Information Technology in Public Accounting Firm

The purpose of this study was to determine the auditor's acceptance of the use of audit technology in the process of financial audit work. This research is a quantitative research that uses primary data in the form of questionnaires distributed to research objects, namely auditors who work in public accountant offices. This research instrument refers to previous research developed by [1] and used by [2] which refers to Technical Organizational Environmental (TOE). This study examines hypotheses between variables using path analysis, while the independent variables in this study are Technical Context, Organizational Context and Environmental Context while the Firm Size moderating variable and the dependent variable are Adoption of Audit Technology. The results of this study are to knowing the adoption of auditors in information technology in their work processes. It is expected that it will provide an overview of the auditor's expectations on the use of information technology, so that it can improve the quality of work to be more effective and efficient, especially in terms of time and energy. The results of this study are expected to provide an overview of the adoption of audit technology by auditors in the financial audit process.
Breaking ALASKA: Color Separation for Steganalysis in JPEG Domain

This paper describes the architecture and training of detectors developed for the ALASKA steganalysis challenge. For each quality factor in the range 60-98, several multi-class tile detectors implemented as SRNets were trained on various combinations of three input channels: luminance and two chrominance channels. To accept images of arbitrary size, the detector for each quality factor was a multi-class multi-layered perceptron trained on features extracted by the tile detectors. For quality 99 and 100, a new "reverse JPEG compatibility attack" was developed and also implemented using the SRNet via the tile detector. Throughout the paper, we explain various improvements we discovered during the course of the competition and discuss the challenges we encountered and trade offs that had to be adopted in order to build a detector capable of detecting steganographic content in a stego source of great diversity.
Exploiting Adversarial Embeddings for Better Steganography

This work proposes a protocol to iteratively build a distortion function for adaptive steganography while increasing its practical security after each iteration. It relies on prior art on targeted attacks and iterative design of steganalysis schemes. It combines targeted attacks on a given detector with a \min\max strategy, which dynamically selects the most difficult stego content associated with the best classifier at each iteration. We theoretically prove the convergence, which is confirmed by the practical results. Applied on J-Uniward this new protocol increases \perr from 7% to 20% estimated by Xu-Net, and from 10% to 23% for a non-targeted steganalysis by a linear classifier with GFR features.
Elevated blood pressure variability is associated with incidence of sepsis-associated encephalopathy

Background: Cerebral microcirculation disorder is associated with the pathophysiology of sepsis-associated encephalopathy (SAE). Blood pressure variability could be involved in the altered cerebral microcirculation due to dysfunctional cerebral autoregulation in septic patients. Methods: In this prospective study, blood pressure was monitored to analyze its variability in septic patients. The cognitive ability of these patients was assessed daily using the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU) test. Survivors were followed-up for a 12-month period. Results: Forty percent of sepsis patients (n = 45) presented with delirium. The cut-off value (8.94 mmHg) of BP variability was detected by ROC curve analysis. Patients with high BP variability (> 8.94 mmHg) presented with a greater degree of delirium (60.7% vs. 19.6%, P < 0.001) with higher Sequential Organ Failure Assessment (SOFA) scores (10.29 ± 4.82 vs. 7.7 ± 3.48, P = 0.014) and mortality (41.1% vs. 23.2%, P < 0.05). Multivariate logistic regression analysis showed that BP variability was related to delirium (OR: 1.17, 95% CI: 1.021.33, P = 0.02), and death following within 28 days (OR: 1.17, 95% CI: 1.00-1.37, P < 0.05), independent of mean BP and vasoactive drug usage. Conclusions: Elevated BP variability is positively related to clinical signs of SAE and mortality in septic patients.
Toward An Integrated Car-following and Lane-changing Model by A Neural Fuzzy Approach

Objectives In the past decades, car following and lane changin g behaviours, the soul of microscopic traffic simulation, have been intensively studied and diffe rent forms of models have been proposed and implemented. Most of the models use mathematical fo rmulas and conventional logic rules to represent the driver knowledge and the models are c librated by measured data on variables predetermined by the expert knowledge. However, hum an drivers have the characteristics of making decision based on the imprecise perceptions of the surrounding environments and they also behave in an integrated way, which means that they are taking care of lane changing and car following at the same time. In this research, a fuzzy inference system is proposed to represent the human driving knowledge including both car foll owing and lane changing behaviour. Neural network is used to calibrate and tune the structure and parameters of the fuzzy inference system.
What Kind of Results Do Effective Management Teams Achieve?

Most organizations use management teams at different levels in the hierarchy to oversee and coordinate their businesses. Such teams typically make decisions, solve problems, coordinate tasks, and keep one another informed, and they can strongly influence the performance of an organization. Hence it is vital to identify factors that are associated with effective management-team performance. Based on a review of international research on management and decision-making teams from the early 1980s through today, we have identified a number of variables that seem to be important for the effectiveness of management teams. The variables are organized into 4 different categories: (a) input factors, which are relatively stable characteristics of the team and its environment (team purpose, team tasks, team size, team composition, and reward systems); (b) process factors, which refer to how the team works (meeting goals, focused communication, handling of task and relationship conflict, dialogical communication, political behavior, behavioral integration, external relationships, team learning behavior, and team leadership); (c) emergent states, which are cognitive, motivational, and affective states that emerge from the team members’ interaction (team psychological safety, team cohesion, and functional team norms); and (d) output factors, which describe the different kinds of outcomes achieved by the team (task performance and individual well-being and growth). In this paper, we discuss the empirical research behind each of the variables and how the variables are associated with management-team effectiveness.
Ageing is a contributing factor to excess weight in adult First Nations living on the reserves of British Columbia, Canada

Background: Excess weight (EW) a public health problem in First Nations living on the reserves of British Columbia (BC). EW is a multifactorial condition involving biological, genetic, cultural and environmental and sociodemographic and lifestyle factors. We hypothesize that age is a risk factor of excess weight in that population. The objective of this study was to determine whether age is an important factor to be considered in interventions aiming to prevent or manage excess weight, specifically obesity. Method: A cross-sectional study on data collected in 2008 and 2009 through a research study named “First Nations Food, Nutrition and Environment Study” (FNFNES), aiming to document the nutritional status and exposure to contaminants in Canadian First Nations communities living south of the 60th parallel. Three level’s random sampling: province, communities and households. 493 women and 356 men aged 19 years and over were randomly selected from households in 20 communities. The statistical analysis software (SAS 9.1) was used to carry out univariate, bivariate and multivariate analysis. Results: Association between excess weight and age was observed only in women. As compared to reference age group (19 – 30years), obesity was increased 2.2 times in the 31 to 50 years age category and 4.2 times in the 50 to 70 years category. Similar trend was observed for overweight which augmented 1.06 and 1.28 times respectively in the 31 to 50 years and 51 to 70 years categories. No association was observed in men. Conclusions: EW was associated to age in the FN women. In men, although no significant association was seen between the two variables, the prevalence of EW increased with age in bivariate analysis. Policies aiming reduction of excess weight should be implemented in early life, in childhood, for a healthier and safer adulthood.
MMP-9 expression levels and the pathological differentiation of oral squamous cell carcinoma ( OSCC ) : a meta-analysis

The purpose of this study is to evaluate the association of MMP-9 expression levels with the pathological parameters in the differentiation of oral squamous cell carcinoma (OSCC). Literature retrieval, selection and assessment, data extraction, and meta-analyses were performed according to the RevMan 5.3 guidelines. We used odds ratios (ORs) and 95% confidence intervals (CIs) to assess the association of MMP-9 expression levels with the differentiation degree of OSCC based on the results of a heterogeneity test. Nine eligible studies including 468 OSCC patients were analyzed. Statistically significant positive associations were found between high MMP-9 expression levels and poorer OSCC differentiation degrees (OR=2.15, 95% CI: 1.40-3.29; P=0.0005). Our meta-analysis shows that a high level of MMP-9 expression is an important sensitive coincident indicator for the poorer differentiation degree of OSCC.