Miracle-dz/UniFAR-FTUs huggingface dataset:
Who wants to be a computer scientist? The computing aspirations of students in English secondary schools

ABSTRACT Despite being in a digital age, the diversity of young people choosing to study and work in computing is of ongoing concern, especially low numbers of girls. This paper aims to determine the profile of students who are more likely to aspire to be computer scientists and provide insights into the key factors that shape their aspirations in this area. We draw on questionnaire data from 4,983 secondary school students in England, in schools that have a higher-than-average uptake of GCSE Computer Science (a national exam taken by students at age 16). Amongst students who have chosen to study GCSE Computer Science, girls have a lower odds of aspiring to be a Computer Scientist compared to boys. Amongst younger students yet to pick their GCSE options, there are significantly more girls than boys wanting to work in digital art. Multivariable regression analysis identified 10 factors that were associated with aspirations to become a computer scientist. These include being a boy, being of Asian ethnicity, currently studying GCSE Computer Science, having a parent in computing, as well as having higher ‘coding self-belief’, elevated levels of ‘family support’ and aspiring towards ‘technical jobs’. Implications for practice and curriculum design are discussed.
Simplified 2D CNN Architecture With Channel Selection for Emotion Recognition Using EEG Spectrogram

Emotion Recognition through electroencephalography (EEG) is one of the prevailing emotion recognition techniques achieving higher accuracy rates. Nevertheless, one of the problems is the emotion recognition for inter-subjects where accuracy measures are lower. This happens because the EEG is a non-stationary signal which is resulting a domain shift across recordings of subjects, even under the same emotions, thus making emotional patterns difficult to identify. Another common observation is the emotion recognition of inter-subject and intra-subject by using all channels originating from the standard EEG recording mechanism. This requires higher computational resources and deep networks which are more complex including DenseNet, ResNet, etc. In this paper, we propose a novelty emotion recognition classification model that offers a simplified structure and employs only the selected channels from the 32 recorded channels. Residing on a standard approach of transforming EEG data– Database for Emotion Analysis of Physiological Signals (DEAP)– into 2D images using Short-Time Fourier Transform (STFT) EEG signals for training and analysis. Follows the channel selection approach and makes use of a simplified 2D CNN model. The channel selection adopts a search and retention approach using the selected samples of the data. The experimental results show that the performance of the proposed architecture improves the accuracy of the inter-subject emotion recognition using 32 channels by 9.73% and 11.7% on valence and arousal, respectively. While the use of the proposed selected channel method, with only 10 channels, performance increased by 3.53% and 7.2% on valence and arousal classes, respectively. Thus, by keeping a lower complexity level, the proposed architecture attains higher performance rates.
Exploratory Projection Pursuit: The Multivariate and Discrete Case

Exploratory Projection Pursuit (EPP) is a tool for an exploratory data analysis. The theorem of Cram er-Wold allows us to concentrate on (bivariate) projections of the data. The work of Diaconis & Freedman (1984) emphasizes the search for projections with a non-normal density. Index functions are used to describe the amount of structure of a projection. A (local) maximum of the index function provides interesting 2-dimensional views of the data. A variety of index functions have been developed over the last 20 years and some of these have been implemented in programs like XGobi or XploRe. We discuss the problem of the selection of the smoothing parameter and computational aspects in connection with interactive software for several index functions. An application for the Swiss Banknote data is given. Then extensions are made for the case of multivariate projections and the case of discrete variables. 1 Why EPP ? The analysis of multivariate data is an interesting and diicult problem in statistics. The diiculties are for several reasons: structures which have a dimension larger than 3 can not be easily visualized for human perception. Non-parametric models which do not x the structure like paremetric models suuer from the \curse of dimensionality", which means we need many observations to be sure that the estimate is correct. How can we examine structure (here: the distribution) of the data and describe the data ? 2 Diese Arbeit ist im Sonderforschungsbereich 373 \Quantiikation und Simulation Okonomischer Prozesse" der DFG an der Humboldt-Universitt at zu Berlin entstanden. 3 I would like to thank Claudia Gajewski (SFB 373) and an unknown referee for their comments.
Managing a Household during a Pandemic: Cognitive Labor and Parents’ Psychological Well-being

Rising domestic burdens for mothers fueled concerns that the COVID-19 pandemic exacerbated gender inequalities in well-being. Yet, survey research has not considered whether and how cognitive labor—planning, organizing, and monitoring family needs—contributed to gendered health disparities during the pandemic. Using data from the Study on U.S. Parents’ Divisions of Labor during COVID-19 (SPDLC) and a stress process perspective, we examine the association between cognitive labor and parents’ psychological well-being, and whether this association (1) differs between mothers and fathers and (2) is moderated by employment status and telecommuting. Mothers performed more cognitive labor during the pandemic than fathers, and cognitive labor was negatively associated with mothers’ psychological well-being—particularly for mothers who never or exclusively telecommuted. Mothers’ psychological well-being was higher when fathers did more cognitive labor, especially among mothers who worked outside the home. Overall, cognitive labor appears to be another stressor that contributed to increased gender inequality.
NOTES AND CORRESPONDENCE Determination of the Horizontal Pressure Gradient Force Using Global Positioning System on board an Instrumented Aircraft

The horizontal pressure gradient force is the single most important dynamical term in the equation of motion that governs the forcing of the atmosphere. It is well known that the slope of an isobaric surface is a measure of the horizontal pressure gradient force. Measurement of this force over mesoscale distances using an airborne platform has been attempted for over two decades in order to understand the dynamics of various wind systems. The most common technique has been to use a radar altimeter to measure the absolute height of an isobaric surface above sea level. Typical values of the horizontal pressure gradient force in the atmosphere are quite small, amounting to an isobaric surface slope of 0.0001 for a 10 m s 1 geostrophic wind at middle latitudes. Detecting the horizontal pressure gradient over irregular terrain using an instrumented aircraft has proven to be especially difficult since correction for the underlying terrain features must be made. Use of the global positioning system (GPS) is proposed here as a means to infer the horizontal pressure gradient force without the need for altimetry and terrain registration over irregular surface topography. Differential kinematic processing of data from dual-frequency, carrier phase tracking receivers on research aircraft with similar static base station receivers enables the heights of an isobaric surface to be determined with an accuracy estimated to be a few decimeters. Comparison of results obtained by conventional altimetry-based methods over the ocean and Lake Michigan with GPS reveals the potential of the GPS method at determining the horizontal pressure gradient force, even over complex terrain.
Jet-Flapped Wings in Very Close Proximity to the Ground

The method of matched asymptotic expansions is applied to the problem of jet-flapped wings of finite span in very close proximity to the ground. For the linearization of this problem, the order of small parameters, the angle of attack and jet deflection, are assumed to be smaller than the ratio of the ground clearance to the root chord. This linearized problem is solved as a direct problem represented by a source distribution on the upper surface of the wing and jet sheet with concentrated sources around the leading and side edges plus a separate confined channel flow region under the wing and jet sheet. The two-dimensional, jet-flapped airfoil is examined in detail, and the calculated lift coefficients lie within 5% of corresponding results by Lissaman.1 In the three-dimensional case, a simple analytic solution is obtained for a flat plate semi-elliptic wing with a straight trailing edge, zero angle of attack and uniform momentum distribution of the jet. Spanwise lift distributions and lift coefficients are derived and the distributions of the jet momentum are discussed for minimum induced drag.
Extent of adoption of ANGRAU technologies in Bengal gram crop in YSR district of Andhra Pradesh, India

Bengalgram is the major pulse crop of YSR District grown exclusively during Rabi season covering 1,05,462 hectares. ANGRAU was established during 1964 and developed different agricultural technologies in various crops. But the adoption of those technologies was not documented officially. The present study was conducted during 2019-20 in YSR Kadapa district with 60 number of respondents selected from 12 number of villages and 6 number of mandals from YSR Kadapa district to study the extent of adoption of ANGRAU technologies and the reasons for non adoption of the recommended technologies in Bengalgram crop. The major findings of the study indicate that majority of the farmers (96.67 %) adopted Inter cultivation twice at 20 and 30 DAS, followed by 90.00% adopted Sowing Time-October-November, followed by Fertilisers-20 Kg N, 50Kg P2 O5 , 40 Kg sulphur and 50Kg/ha, Zn as basal dose (86.67%), followed by Curative spray either Monocrotophos @ 1.6 ml or Acephate @ 1.0 g or Quinalphos @ 2.0 ml or Thio dicarb @ 1 g/l (80%). The reasons expressed by the farmers (80.00%) for non adoption of spacing 30x10 cm was due to high seed rate, followed by 75.00 per cent of farmers expressed the reason for non adoption of Neem Seed Kernel Extract 5 % (NSKE 5%) as it is laborious.
On the efficient and reliable numerical solution of rate-and-state friction problems

We present a mathematically consistent numerical algorithm for the simulation of earthquake rupture with rate-and-state friction. Its main features are adaptive time-stepping, a priori mesh-adaptation, and a novel algebraic solution algorithm involving multigrid and a fixed point iteration for the rate-and-state decoupling. The algorithm is applied to a laboratory scale subduction zone which allows us to compare our simulations with experimental results. Using physical parameters from the experiment, we find a good fit of recurrence time of slip events as well as their rupture width and peak slip. Preliminary computations in 3D confirm efficiency and robustness of our algorithm.
Analysis of thick and thin shell structures by curved finite elements

A general formulation for the curved, arbitrary shape of thick shell finite elements is presented in this paper along with a simplified form for axisymmetric situations. A number of examples ranging from thin to thick shell applications are given, which include a cooling tower, water tanks, an idealized arch dam and an actual arch dam with deformable foundation. A new process using curved, thick shell finite elements is developed overcoming the previous approximations to the geometry of the structure and the neglect of shear deformation. A general formulation for a curved, arbitrary shape of shell is developed as well as a simplified form suitable for axisymmetric situations. Several illustrated examples ranging from thin to thick shell applications are given to assess the accuracy of solution attainable. These examples include a cooling tower, tanks, and an idealized dam for which many alternative solutions were used. The usefulness of the development in the context of arch dams, where a ‘thick shell’ situation exists, leads in practice to a fuller discussion of problems of foundation deformation, etc., so that practical application becomes possible and economical.
Robust ℋ∞ filtering for vehicle sideslip angle estimation with sampled-data measurements

In this paper, the problem of vehicle sideslip angle estimation is studied based on a single-track model, and an approach to robust ℋ∞ filter design with sampled-data measurements is proposed. Considering the changes of the vehicle mass, the moment of inertia about the yaw axis and the nonlinear relationships between the road surface and tyres, the vehicle lateral dynamics are characterized by a system with parameter uncertainties, which belong to a given convex polytope. By utilizing an input delay approach, the filtering error system is transformed into a continuous-time system with time delay in the state. By introducing a Lyapunov–Krasovskii functional and a free weighting matrix technique, LMI-based conditions have been formulated for the stability analysis of the filtering error system and the existence of admissible filters, which ensure the filtering error system is asymptotically stable with a prescribed ℋ∞ disturbance attenuation level. Finally, some simulation results are provided to illustrate the effectiveness of the proposed method.
An empirical study of competitiveness and international economic growth: The case study of the EU

The paper's general topic considers national competitiveness, a factor suppressing the competitiveness and economic growth of the EU member states, including the UK. The paper's main objective is to investigate possible causal links between economic growth and competitiveness with an exclusive focus on factors which disadvantage national competitiveness. As a primary source of data, results compiled within the Global competitiveness report (GCR 2017-2018) and provided by the World economic forum (WEF) have been used. The national competitiveness of each member state was expressed by its unique Global competitiveness index (GCI) elaborated according to the GCR methodology. Part of the report was an exclusive business opinion survey about general business and entrepreneurial conditions in each state. Firstly, the probability distribution of each random variable was established. As most problematic factors were highlighted taxes and tax regulations, inefficient state bureaucracy and restrictive labor conditions. Subsequently, the relations between the national competitiveness (GCI), factor score, and economic growth were analyzed. The results point to a relatively weak link between the GCI vs factor score and GCI vs economic growth, which was statistically insignificant. However, there was a moderately strong negative correlation between the factor score and economic growth, suggesting a higher factor score means lower economic growth and vice versa. There is a number of EU member states, including 'old' member states afflicted by slow economic growth. Also, these states have a higher factor score. Conversely, there are states, mostly 'new' ones, which are less developed, however, were able to achieve higher economic growth rates. In turn, their factor score is lower. Based on the results, the possible causal relationship between the economic growth and factors suppressing the business cannot be ruled out. The position of each EU member state is mainly a consequence of its own social-economic policy framework design and implementation.
Synthetic jet application in the wind turbine concentrator design

ABSTRACT Due to population growth and technological advancements, the energy demands of countries are increasing every year. Consequently, research and development (R&D) studies in renewable energy have been on the rise in order to meet the growing energy demands. Wind energy is especially crucial in this regard. Wind turbines are capable of producing energy within the wind speed range of 5 m/s to 25 m/s, with a capacity factor of approximately 30–35%. In areas where wind speeds are insufficient, efforts are being made to improve turbine performance for energy production at low wind speeds. One of these studies involves incorporating the turbine into a concentrator to increase the wind speed and subsequently the capacity factor of the turbine for energy production at low wind speeds. In this study, the concentrator of the wind turbine with the SG 6043 blade section is taken into consideration, and the impact of synthetic jet application in the wind turbine concentrator is investigated. An optimization study is conducted to determine the parameters that will maximize the speed increase in the concentrator. The optimum parameters that lead to the maximum wind speed increase in the concentrator are as follows: the velocity of the synthetic jet is 140 m/s, the frequency of the synthetic jet is 58.89 Hz, the angle of the synthetic jet is 26. 16º, the position of the synthetic jet is 0.675 m, and the angle of attack is 24. 1º at a free wind speed of 5 m/s. The use of synthetic jet application in the wind turbine concentrator results in a 1.33 times increase in free wind speed. Consequently, the concentrator with synthetic jet application can be used in regions with poor wind speed statistics to generate energy from wind and increase the capacity factor of wind turbines.
Pulmonary Telerehabilitation for People With Chronic Obstructive Pulmonary Disease in Brazil: A Mixed-Methods Feasibility Study

This study assessed the feasibility of pulmonary telerehabilitation‧s (PTR) acceptability, implementation, practicality, and adaptation for people with Chronic Obstructive Pulmonary Disease (COPD) in Brazil. It also explored associations with clinical and socioeconomic features of Brazilians with COPD. This mixed-method study included thirty-one participants with COPD (age 62±10 years; FEV1= 72±14% predicted). Most participants (74.2%) reported good PTR session acceptability on the System Usability Scale and scores of 4.6±0.3 and 4.5±0.6 on a 1–5 Likert-type scale of implementation and practicality, respectively. Participants suggested adaptations for better comfort on the exercise bike and varying exercise modalities. PTR acceptability was associated with participants' younger age (rs=−0.57, p<0.01) and higher education (rs=0.51, p<0.01). PTR is feasible for people with COPD in Brazil regarding acceptability, implementation, practicality, and adaptation. Younger age and higher educational level are associated with greater PTR acceptability.
Preoperative neurocognitive function as an independent survival prognostic marker in primary glioblastoma

Abstract Background Aim of the present study is to investigate whether preoperative neurocognitive status is prognostically associated with overall survival (OS) in newly diagnosed glioblastoma (GBM) patients. Methods Ninety patients with dominant-hemisphere IDH-wild-type GBM were assessed by Mini Mental Status Exam (MMSE), Trail Making Test (TMT) A and B parts, and Control Word Association Test (COWAT) phonemic and semantic subtests. Demographics, Karnofsky Performance Scale, tumor parameters, type of surgery, and adjuvant therapy data were available for patients. Results According to Cox proportional hazards model the neurocognitive variables of TMT B (P < .01), COWAT semantic subset (P < .05), and the MMSE (P < .01) were found significantly associated with survival prediction. From all other factors, only tumor volume and operation type (debulking vs biopsy) showed a statistical association (P < .05) with survival prediction. Kaplan Meier Long rank test showed statistical significance (P < .01) between unimpaired and impaired groups for TMT B, with median survival for the unimpaired group 26 months and 10 months for the impaired group, for COWAT semantic (P < .01) with median survival 23 months and 12 months, respectively and for MMSE (P < .01) with medial survival 19 and 12 months respectively. Conclusions Our study demonstrates that neurocognitive status at baseline—prior to treatment—is an independent prognostic factor for OS in wild-type GBM patients, adding another prognostic tool to assist physicians in selecting the best treatment plan.
Uncertainties in Onboard Algorithms for Autonomous Vehicles: Challenges, Mitigation, and Perspectives

Autonomous driving is considered one of the revolutionary technologies shaping humanity’s future mobility and quality of life. However, safety remains a critical hurdle in the way of commercialization and widespread deployment of autonomous vehicles on public roads. Safety concerns require the autonomous driving system to handle uncertainties from multiple sources that are either preexisting, e.g., the stochastic behavior of traffic participants or scenario occlusion, or introduced as a result of processing, e.g., the application of neural networks. Thus, it is crucial to analyze the sources of uncertainties and quantify the risks associated with them, including the propagated risks that accumulate in the decision-making system. In this context, this paper provides an overview of uncertainty challenges and state-of-the-art techniques for mitigating these challenges. We argue that the uncertainties mainly originate from two aspects: 1) the external traffic environment, and 2) the internal autonomous driving system. Specifically, this paper first analyzes the safety challenges caused by the uncertainties and summarizes their sources. In addition, the corresponding techniques that mitigate and quantify the risk of uncertainties are presented. Finally, research perspectives are highlighted to facilitate future studies for guaranteeing the safety of autonomous vehicles.