Miracle-dz/UniFAR-FTUs huggingface dataset:
The Impact of ICT and Robots on Labour Market Outcomes of Demographic Groups in Europe

IZA DP No. 15752 NOVEMBER 2022 The Impact of ICT and Robots on Labour Market Outcomes of Demographic Groups in Europe* We study the ageand gender-specific labour market effects of two key modern technologies, Information and Communication Technologies (ICT) and robots, in 14 European countries between 2010 and 2018. To identify the causal effects of technology adoption, we utilise the variation in technology adoption between industries and apply the instrumental variables strategy proposed by Acemoglu and Restrepo (2020). We find that the exposure to ICT and robots increased the shares of young and prime-aged women in employment and the wage bills of particular sectors, but reduced the shares of older women and prime-aged men. The adverse effects were particularly pronounced for older women in cognitive occupations, who had relatively low ICT-related skills; and for young men in routine manual occupations, who experienced substitutions by robots. Between 2010 and 2018, the growth in ICT capital played a much larger role than robot adoption in the changes in the labour market outcomes of demographic groups. JEL Classification: J24, O33, J23
Fueling opposition? Yellow vests, urban elites, and fuel taxation

ABSTRACT The yellow vest movement in France was triggered by a fuel tax increase. The increase was designed to reduce petrol consumption and hence emissions. However, the costs of this policy were unequally distributed among citizens. The yellow vests illustrate that abstract support for public action against climate change is not enough to secure support for concrete policies. These policies run the risk of being opposed by citizens when their costs are unevenly spread across society. Through a survey experiment on Norwegian citizens, we analyse how different policy characteristics generate ‘support gaps’ within society. Particularly, we contrast two stylized profiles: ‘urban élites’ (high-educated urbanites) and ‘yellow vests’ (low-educated ruralites). We find that opposition rises with the individual cost of the policy but in a non-linear way. Environmental earmarking and invoking personal responsibility widen the gap between yellow vests, urban élites, and the rest of society. Redistribution to low-income households and invoking international commitments help to bridge such gaps. We argue that, instead of focusing on aggregate levels of support, both policymakers and academics should rather pay attention to the polarizing effects of certain policy attributes.
Radio Continuum Measurements of Southern Early-Type Stars. II. A Distance-limited Sample of Wolf-Rayet Stars

A distance-limited sample of southern Wolf-Rayet stars within 3 kpc of the Sun has been observed with the Australia Telescope Compact Array at 8.64 and 4.80 GHz. Radio continuum flux densities at one or both frequencies were obtained for 10 sources and upper limits for 20; four sources are found to be thermal emitters on the basis of the observed spectral index. Five sources are classified as nonthermal. One source could not be classified. We derive mass-loss rates for the thermal sources. After combining them with all existing radio mass-loss rates of Wolf-Rayet stars in the northern and southern hemisphere, we perform a comparison with mass-loss rates derived from optical emission lines. The two methods lead to consistent results, which suggests either that the assumption of a spherically symmetric, stationary, homogeneous stellar wind is correct or that deviations from this assumption affect both methods in the same way. Wolf-Rayet mass-loss rates are surprisingly uniform across spectral type. We find an average mass-loss rate of 4 × 10-5 M☉ yr-1 for all types observed, except for WC9 stars, which have rates that are lower by at least a factor of 2. An alternative explanation could be partial recombination of helium from He+ to He0 in the radio region, which would lead to a reduced number of free electrons, and therefore reduced radio flux for WC9 stars. Mass-loss rates of 8 × 10-5 M☉ yr-1 for late WN stars favored in recent stellar evolution models disagree with the observations of these subtypes. The results of this survey suggest that ~40% of all Wolf-Rayet stars with measured spectral index are nonthermal emitters at centimeter wavelengths. This percentage is nearly twice as high as that of nonthermal emitters among OB stars and is higher than that previously estimated for WR stars. The nature of the nonthermal emission is still not fully understood. Possible causes of nonthermal emission are discussed. In particular, we speculate that nonthermal emission may arise from an interaction between a thermal WR wind and surrounding material owing to a shell ejected during a previous evolutionary stage or owing the wind of a companion star.
Zero‐knowledge‐based distributed auditing protocol

Blockchain‐based data outsourcing has attracted a huge deal of attention in recent years. However, key management and reliance on pre‐defined or randomly‐selected third‐party auditors (TPAs) are still challenging owing to refusing to collaborate or break auditing policies. Additionally, it is impossible to store secrets in smart contracts (SCs) for signing or auditing. Thus, in the present study, a zero‐knowledge (ZK)‐based distributed auditing protocol (DAP) is provided. In this protocol, a user‐based key generation mechanism offers users security against curious authorities based on no TPA causing them to reveal no knowledge about under‐auditing data. Based on Pointcheval's and Sanders's signature scheme, as a ZK‐based randomizable signature applied in an SC to handle the auditing process, the proposed DAP provides confidential transactions and user accountability. Evaluation indicates that the proposed ZK‐based DAP is efficient for the user side and it is the fastest DAP in the blockchain.
Two-Stage Intelligent DarkNet-SqueezeNet Architecture-Based Framework for Multiclass Rice Grain Variety Identification

Image processing is an important domain for identifying various crop varieties. Due to the large amount of rice and its varieties, manually detecting its qualities is a very tedious and time-consuming task. In this work, we propose a two-stage deep learning framework for detecting and classifying multiclass rice grain varieties. A series of steps is included in the proposed framework. The first step is to perform preprocessing on the selected dataset. The second step involves selecting and fine-tuning pretrained deep models from Darknet19 and SqueezeNet. Transfer learning is used to train the fine-tuned models on the selected dataset. The 50% sample images are employed for the training and rest 50% are used for the testing. Features are extracted and fused using a maximum correlation-based approach. This approach improved the classification performance; however, redundant information has also been included. An improved butterfly optimization algorithm (BOA) is proposed, in the next step, for the selection of the best features that are finally classified using several machine learning classifiers. The experimental process was conducted on selected rice datasets that include five types of rice varieties and achieves a maximum accuracy of 100% that was improved than the recent method. The average accuracy of the proposed method is obtained at 99.2%, through confidence interval-based analysis that shows the significance of this work.
Molecular Outflows in Powerful OH Megamasers

High signal-to-noise ratio OH and H I data are presented for five powerful OH megamasers. The OH profiles of the main OH lines of III Zw 35, IR 12112+0305, and IC 4553 show extended blueshifted wings. Two newly detected 1720 MHz OH lines in III Zw 35 and IR 17208-0014 are found to be aligned in velocity with the strongest peak in the main lines. Strong blueshifted wings on the OH and H I lines are direct evidence for molecular outflows from the nuclear regions of active galaxies. These high-velocity regions are consistent with the starburst-driven superwinds observed in some active galaxies. It is found that the velocity extremes of the outflowing OH are consistent with an L(IR) exp 1/2 dependence. A similar dependence is also derived from the H I absorption lines. The accelerated molecular material may be as close as 10 pc from the sites of activity, which is well within the narrow line region of active galactic nuclei. Almost all strong OH megamasers exhibit a two-pronged profile in the 1667 MHz line, due to the excitation of the molecular gas in the nucleus. 57 refs.
Essential Amino Acids as Immunonutrition in Critical Illness: Time for Trials?

The derangement of both innate and adaptive immune responses of patients in the intensive care unit (ICU) led to the use of Immuno Nutrition Formula (INF) to reduce the risk of infection complications. While the observed findings might appear beneficial to high-risk surgical patients, they do not support the routine use of INF in medical ICU patients. In our opinion the inconsistent results from clinical trials might be due to the lack of Amino Acids (AA), in particular the Essential Amino Acids (EAAs), that patients receive either from a general nutrition support and from INF formula which does not contain EAAs. To
Energy‐efficient animal tracking with multi‐unmanned aerial vehicle path planning using reinforcement learning and wireless sensor networks

In recent years, the integration of wireless sensor networks (WSNs) and unmanned aerial vehicles (UAVs) has been a popular research domain in animal tracking due to animal habitats in harsh environments. A well‐designed WSN network provides a robust mechanism to detect the animal appearances which can be then collected by UAVs. In this paper, we first design a WSN‐based network model that eliminates the deficiencies of traditional WSNs by intelligently building a WSN topology. Second, we propose a multi‐agent (UAVs) Q‐learning‐based trajectory planning algorithm, which enables UAVs to acquire the detection information of the wild animal on time. Q‐learning algorithm coordinates the UAVs to visit WSN nodes containing fresh animal detection data in a timely manner according to past experience. The experimental results denotes that the proposed animal tracking system delivers significantly higher timely animal detection messages of 45% than the existing algorithms and the single agent Q‐learning approaches. The results also show that since the Zebras' movement contains some randomness, relatively high epsilon value (0.2) in the epsilon‐greedy mechanism of the Q‐learning provides highest rewards (timely delivered messages) for agents (UAVs). In the light of the results, it is clearly seen that intelligently designed WSN and UAV swarm combination could enable tracking of the wild animal in near real time.
Regularization of the deflectometry problem using shading data

Reconstructing a specular surface from observation of structured illumination is mathematically a severely illposed problem. This contribution discusses the close relationship of Shape-from-Shading and the deflectometry problem. Consequently, a novel regularization approach for partially diffuse objects is proposed in this paper. By considering different characteristic curves on the unknown surface, we estimate a set of points that the reconstruction must embed. A solution satisfying the reflection conditions is afterwards fitted to the obtained points with the help of a level set iteration.
The lymphatic system: a therapeutic target for central nervous system disorders

The lymphatic vasculature forms an organized network that covers the whole body and is involved in fluid homeostasis, metabolite clearance, and immune surveillance. The recent identification of functional lymphatic vessels in the meninges of the brain and the spinal cord has provided novel insights into neurophysiology. They emerge as major pathways for fluid exchange. The abundance of immune cells in lymphatic vessels and meninges also suggests that lymphatic vessels are actively involved in neuroimmunity. The lymphatic system, through its role in the clearance of neurotoxic proteins, autoimmune cell infiltration, and the transmission of pro-inflammatory signals, participates in the pathogenesis of a variety of neurological disorders, including neurodegenerative and neuroinflammatory diseases and traumatic injury. Vascular endothelial growth factor C is the master regulator of lymphangiogenesis, a process that is critical for the maintenance of central nervous system homeostasis. In this review, we summarize current knowledge and recent advances relating to the anatomical features and immunological functions of the lymphatic system of the central nervous system and highlight its potential as a therapeutic target for neurological disorders and central nervous system repair.
Study of prognostic factors in gastric cancer: Application of a cox model and logistic regression

Introduction: Gastric cancer has a poor prognosis. It is the fifth most common cancer in terms of incidence and the fourth most common cancer in terms of mortality world wide. The aim of our study is to identify the clinical and pathological factors associated with survival and predictive of death. Method: Our study included 262 patients over a 13-year periodfrom 2007 to 2020 at Aristide Le Dantec Hospital in Senegal and Conakry Hospital in Guinea. The survival period was established from one month after treatment to the date of death or last news. We first used the Cox proportional hazard model to identify independent factors associated with survival. Then we applied logistic regression to these factors to develop the prognostic equation. Results: The overall survival at 6 months, 1 year and 5 years after treatment was respectively 74%, 57%, 38%. The probability of occurrence of death after 5 years can be estimated with 93\% accuracy, by: log ( π i / (1 - π i )) = -19,983 + 2,119* Métastases + 1,268* Ulcère gastrique + 1,100* Tabac + 37,646* Epigastralgie + 37,563* Cardiopathie + 37,220*Mucineux. Conclusion: Our approach contributes to determine the impact of clinical and pathological factors on the survival of patients and the eventual occurrence of death related to stomach cancer.
Fostering the Entrepreneurial Mindset of Students Through Pioneering Teaching Pedagogies: An Empirical Study on a B-School

Recent studies have shown the importance of entrepreneurship on the economy of a country. Universities and Educational institutions play a vital role in nurturing students. The study focuses on the impact of innovative teaching pedagogies such as TAP (Teaching, Application and Practice) on the entrepreneurial mindset of students. The mindset of the students was measured using the “Theory of Planned Behavior” by Dr. Azjen and “Entrepreneurial Potential Theory” and extension of this model by Quixing Yang et. al (2021) in two stages via an experimental design method over a longitudinal period of two years. An instrument has been designed and administered on a sample of 570 respondents from university for pre and post testing in order to understand the entrepreneurial mindset using simple random sampling. An attempt has been made to understand the relationship among determinants of entrepreneurial intention using Structural equation modelling analysis. The result shows that the proposed model in the present study explains 54% of the variance, explaining the existence of entrepreneurial intention among students. The purpose of the research is to inspire additional research on measuring the entrepreneurial mindset of students utilizing other innovative training pedagogies, identifying a suitable pedagogy to foster the entrepreneurial mindset of students, and creating an appropriate eco-system to develop educational policies at the national level.
RAPID GRANULAR FLOWS

▪ Abstract The recent avalanche of research activity in the field of granular matter has yielded much progress. The use of state-of-the-art (and other) computational and experimental methods has led to the discovery of new states and patterns and enabled detailed tests of theories and models. The application of statistical mechanical methods and phenomenology has contributed to the understanding of the microscopic a nd macroscopic properties of granular systems. Some previously open problems seem to be solved. Fluidized granular systems (rapid granular flows), recently referred to as granular gases, are often modeled by hydrodynamic equations of motion, some of which are based on systematic expansions applied to the pertinent Boltzmann equation. The undeniable success of granular hydrodynamics is somewhat surprising in view of the lack of scale separation in these systems and the neglect of certain correlations in most derivations of the hydrodynamic equations. Microstructures have been recognized as key .
Decoding degeneration: the implementation of machine learning for clinical detection of neurodegenerative disorders

Machine learning represents a growing subfield of artificial intelligence with much promise in the diagnosis, treatment, and tracking of complex conditions, including neurodegenerative disorders such as Alzheimer’s and Parkinson’s diseases. While no definitive methods of diagnosis or treatment exist for either disease, researchers have implemented machine learning algorithms with neuroimaging and motion-tracking technology to analyze pathologically relevant symptoms and biomarkers. Deep learning algorithms such as neural networks and complex combined architectures have proven capable of tracking disease-linked changes in brain structure and physiology as well as patient motor and cognitive symptoms and responses to treatment. However, such techniques require further development aimed at improving transparency, adaptability, and reproducibility. In this review, we provide an overview of existing neuroimaging technologies and supervised and unsupervised machine learning techniques with their current applications in the context of Alzheimer’s and Parkinson’s diseases.
Control of the hot electrons produced by laser interaction with nanolayered target

Hot electrons generated by short-pulse-laser interaction with nanolayered target (NT) are investigated using two-dimensional particle-in-cell simulation. Compared to the planar target, the NT leads to more efficient conversion of laser energy to the kinetic energy of the accelerated electrons. However, the energy absorption by the NT decreases at both too-low and too-high laser intensities. At lower laser intensities it is because of the weaker electric and magnetic fields generated by the hot-electron jets and smaller relativistic skin depth. At higher laser intensities it is because of the damage or destruction of the layered structure by the laser field. On the other hand, the dependence of the conversion efficiency and hot-electron number on the duration of the (short) laser pulse and the nanolayer length is weak. Control of the hot-electron characteristics by tailoring the parameters of the laser and the NT is discussed.
Energy costs and leg muscle activities in ascending stairs

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Strain relaxation by alloying effects in Ge islands grown on Si(001)

Transmission electron microscopy is used to study the morphology and the composition profile of "pure'' Ge islands grown at high temperature on Si(001) by molecular beam epitaxy. An alloying process, involving mass transport from the substrate to the islands during the island growth, was identified. It was found that, as a result of Si mass transport to the Ge islands, the island/substrate interface moves towards the substrate, and trenches form on the substrate surface around the islands; Reduction of the misfit strain at the island/substrate interface is the driving force for this process. [S0163-1829(99)00738-1].
Effect of an electron scattering cloud on X-ray oscillations produced by beaming

The effect of a scattering cloud on the amplitude of oscillations produced by a rotating beam of X-rays is investigated using analytical and Monte Carlo methods. The scattering cloud was modeled as a uniform density sphere, and the source was represented as an anistropic distribution of radiation emerging from a point at the center of the scattering cloud. The intensity distribution produced by the source beam is examined as a function of optical depth. The relation between electron scattering optical depth and the forward-backward ratio is studied. It is observed that the scattering in a central corona of various optical depths reduces the amplitude of the oscillation. The data suggest that the quasi-periodic oscillations observed in the X-ray intensities of some luminous low-mass X-ray binaries are caused by oscillations in the luminosity of the X-ray star. 29 references.
1/f noise in bipolar transistors

Measurements have been performed on the low-frequency, excess, noise in silicon, bipolar, npn transistors at frequencies between 10-2 Hz and 25 kHz, at temperatures between 77K and 375K and over a wide range of bias. The DC characteristics have also been studied in detail. The excess noise can be represented completely by a single current noise source between the base and emitter with intensity in2=K'2IB'2 Delta f/Afgamma where I'B is the non-ideal base current, gamma is an exponent near unity which varies only slightly with temperature, A is the base-emitter contact area and K' is a constant for each device which is independent of temperature and other bias quantities. Discussion is presented of the connection between the excess noise and the non-ideal, recombination current and of the relationship between these results and the various noise models.
Autoregressive frequency estimation

SUMMARY Presume that an autoregressive model of given order is fitted to data obtained from a realization of a sinusoidal signal embedded in white noise. This paper investigates the statistical properties of the estimate of the frequency of the signal obtained by minimizing the transfer function of the autoregression. Strong consistency and convergence in distribution of the estimate are established when the order of the autoregression is allowed to increase with sample size at an appropriate rate. It is also shown that the operational characteristics of commonly-used order determination procedures are such as to produce values of the selected order compatible with the application of the asymptotic theory. The outcome of some simulation experiments and an empirical example illustrating the practical impact of the results obtained are also presented.