Miracle-dz/UniFAR-FTUs huggingface dataset:
Research Area : Labour Market and Employment Forschungsschwerpunkt : Arbeitsmarkt und Beschäftigung Research Unit : Labour Market Policy and Employment Abteilung : Arbeitsmarktpolitik und Beschäftigung

The international literature on active labour market programmes has generated inconsistent and confusing, but generally pessimistic, conclusions regarding their impact on the employment prospects of participants. This paper argues that much of this confusion is due to a general lack of attention to qualitative differences between programmes. The paper develops a typology of active labour market programmes, differentiating between training and employment measures on the basis of their orientation to the labour market and argues that programmes with a strong orientation to the market are more likely to improve the job prospects of participants than those characterised by weak market linkages. That hypothesis is tested using the results of a survey of young participants in labour market programmes in Ireland. The analysis shows that programmes with strong linkages to the labour market both enhance the employment prospects of their participants and increase their earnings, even when we take account of relevant individual characteristics such as education and previous labour market experience.
Strategic and operational remanufacturing mental models

Remanufacturing is the only end-of-life (EOL) treatment process that results in as-new functional and aesthetic quality and warranty. However, applying mental model theory, the purpose of this paper is to argue that the conception of remanufacturing as an EOL process activates an operational mental model (OMM) that connects to resource reuse, environmental concern and cost savings and is thus opposed to a strategic mental model (SMM) that associates remanufacturing with quality improvements and potential price increases. ,The authors support the argument by empirically assessing consumers’ multi-attribute decision process for cars with remanufactured or new engines among 202 car buyers in China. The authors conduct a conjoint analysis and use the results as input to simulate market shares for various markets on which these cars compete. ,The results suggest that consumers on average attribute reduced utility to remanufactured engines, thus in line with the OMM. However, the authors identify a segment accounting for about 30 per cent of the market with preference for remanufactured engines. The fact that this segment has reduced environmental concern supports the SMM idea that remanufactured products can be bought for their quality. ,A single-country (China) single-brand (Volkswagen) study is used to support the conceptualised mental models. While this strengthens the internal validity of the results, future research could improve the external validity by using more representative sampling in a wider array of empirical contexts. Moreover, future work could test the theory more explicitly. ,By selling cars with remanufactured engines to customers with a SMM that values the at least equal performance of remanufactured products, firms can enhance their profit from remanufactured products. In addition, promoting SMM enables sustainable business models for the sharing economy. ,As a community, the authors need to more effectively reflect on shaping mental models that disconnect remanufacturing from analogies that convey inferior quality and performance associations. Firms can overcome reduced utility perceptions not only by providing discounts, i.e. sharing the economic benefits of remanufacturing, but even more by increasing the warranty, thus sharing remanufacturing’s performance benefit and reducing consumers’ risk, a mechanism widely acknowledged in product diffusion but neglected in remanufacturing so far.
Autophagy Deficiency Leads to Impaired Antioxidant Defense via p62-FOXO1/3 Axis

Autophagy, an intracellular degradation mechanism eliminating unused or damaged cytoplasmic components for recycling, is often activated in response to diverse types of stress, profoundly influencing cellular physiology or pathophysiology. Upon encountering oxidative stress, autophagy acts rapidly and effectively to remove oxidized proteins or organelles, including damaged mitochondria that generate more ROS, thereby indirectly contributing to the maintenance of redox homeostasis. Emerging studies are shedding light on the crosstalks among autophagy, mitochondria, and oxidative stress; however, whether and how autophagy could directly modulate antioxidant defense and redox homeostasis remains unaddressed. Here, we showed mitochondrial dysfunction, elevated ROS level, impaired antioxidant enzymes, and loss of FOXO1/3 in autophagy deficiency cellular models established by either chemical inhibitors or knocking down/out key molecules implementing autophagy, and overexpression of FOXO1/3 restored antioxidant enzymes hence suppressed elevated ROS; knockdown of p62 increased protein level of FOXO1/3 and recovered FOXO1 in Atg5-knockdown cells. Our data demonstrates that the loss of FOXO1/3 is responsible for the impairment of antioxidant enzymes and the consequent elevation of ROS, and accumulation of p62 under condition of autophagy deficiency might be mediating the loss of FOXO1/3. Furthermore, we found in an animal model that the p62-FOXO1/3 axis could be dominant in aging liver but not in type 2 diabetic liver. Together, these evidences uncover the p62-FOXO1/3 axis as the molecular cue that underlies the impairment of antioxidant defense in autophagy deficiency and suggest its potential involvement in aging, substantiating the impact of inadequate autophagy on mitochondria and redox homeostasis.
EFL University Instructors’ Employment Status and Their Perception of Professional Commitment

Instructors play an important role in educating the future members of society through their work in universities and quality education cannot be achieved without the supreme efforts of dedicated and committed university teachers. Hence, there is a call for more research concerning the notion of teacher commitment, its dimensions and the factors that influence it. The current study first aimed to set priority among the dimensions of EFL instructors’ professional commitment through Partial Least Squares Structural Equation Modeling and then investigate the effect of EFL instructors’ employment status as full time or part time on their professional commitment through two-tailed t-test. A previously validated EFL Teachers’ Professional Commitment Questionnaire was employed to collect data from 420 EFL male and female university instructors. The results exhibited a significant difference between these two variables in total. One of the important implications of this research is that EFL instructors inspire to evaluate their commitment regarding the priority of dimensions and their underlying components meticulously to find out what they should work on more to improve students’ achievements in the EFL learning context of Iran.
Psychotherapy trainees’ epistemological assumptions influencing research-practice integration

Over the last few decades a growing number of psychotherapy scholars as well as psychotherapy researchers have joined a paradigm shift, moving from a reductionist to a complexity-oriented epistemology. Many authors recognize that when human subjectivity is the object of intervention and study, it is appropriate to resist simplification and to assume a more complex approach. While this paradigm shift is taking place not only in psychology but also in other disciplines, many psychotherapists still share the assumption that psychotherapy practice and psychotherapy research have opposite values; hence, they are worlds that cannot be reconciled. Considering this as one of the main reasons preventing a useful integration of evidence-based practice and clinical training in psychotherapy, we conducted an online survey of 126 Italian trainees from three differently-oriented psychotherapy institutes (cognitive-behavioral, relational-psychoanalytic and relational-systemic) to explore the epistemology underling the clinical and research practices. After presenting a clinical vignette, we asked questions about diagnostic considerations, case formulations, and treatment plans; we also asked questions about participants’ involvement in research projects or in research methodology courses and about willingness to be involved in future research studies in their clinical practice. We found some significant differences among trainees with different orientations, but in general most of the responses reflected a positivistic epistemology underlying both clinical and research activities. These findings suggest that a deeper awareness of one’s own epistemological assumptions could help trainees foster a more theory-coherent and research-informed clinical practice.
Comparison of the Accuracy of Black Hole Algorithms and Gravitational Research and the Hybrid Method in Portfolio Optimization

The main purpose of this research is portfolio optimization in Tehran securities exchange using the black hole algorithm and the Gravitational Research algorithm. We also propose an algorithm named Hybrid Algorithm which combines the two algorithms above to cover the weaknesses of these two algorithms. Finally we compare the results with the Markowitz model and choose the optimal algorithm. In order to analyze the data that is the same information extracted from the TSE Client software and RahAvard Novin Software, MATLAB software version of 2016and GAMS and SPSS have been used. This research is fulfilled in the period from 2011 to 2016. The method used in this study is based on the purpose of the applied research and based on the way of data collection as a descriptive research and correlation type, which is noticed with the retrospective and post-event approach and through the analysis of the observed information, attempts to optimize the portfolio using a black hole algorithm. In all the years of research, the hybrid method introduced in this research has obtained the nearest solution to the exact solution, which is the same Markowitz. In order to optimize the portfolio, black hole meta-heuristic algorithms, Gravitational Research and hybrid algorithm (hybrid) can be used instead of the Markowitz algorithm with higher accuracy and speed. The results of the present case study and other studies show that black hole algorithms, Gravitational Research, and hybrid algorithms are very quick in solving portfolio optimization problems
From ‘Wanting’ to ‘Liking’: Listeners’ Emotional Responses to Musical Cadences as Revealed by Skin Conductance Responses

Research on the emotional responses and brain activations evoked by music has been a topic of great academic and public interest. A recent brain-imaging study by Salimpoor et al. (2011) suggests the involvement of mechanisms for ‘wanting’ and ‘liking’ when subjects listened to intensely pleasurable music. Their paper elaborates the roles of the reward system in music listening, and its correlates to musical emotions. It is widely reported that music influences listeners’ emotional state. An emotional response can be related to an isolated musical event and/or the temporal structure of a music piece. In the past decades, physiological measures have been used to investigate the relationship between musical structures and listeners’ emotional reactions. Skin conductance is one of the most commonly used response systems. There is a high correlation between bursts of sympathetic nerve activity and skin conductance responses (SCRs). An SCR is characterized by an abrupt increase of skin conductance and should be interpreted as arousal elevation. Music-induced chills are often accompanied by SCRs (Grewe et al., 2007; Guhn et al., 2007; Salimpoor et al., 2009). An alternative method of quantifying SCRs focuses on their instantaneous slope (Blain et al., 2008). Since a positive SCR slope reflects activity of sweat glands, the SCR slope may serve as an indicator of arousal. Aims
Static Analysis for Malware Detection

Malware detection becomes a necessity with the rising amount and power of cyber attacks. Nowadays, Windows operating system is the most widely used system, and for that reason, it is targeted the most by malware authors. We focus on malware detection in Portable Executable files since it is the most common file format used for spreading malware in Windows OS. The amount of malware is too large, so it is not possible to analyze all the samples by hand, even only running them would cost too much time and resources. Therefore, it is necessary to analyze binaries without actually executing them, i.e., perform static analysis. Many methods of static analysis have been proposed, but they lack comparison on the same real-world data. In this thesis, we provide a comparison of features extracted from raw byte code, PE header, and assembly code. We evaluate gain of each feature separately, and then select the best performing set of features and use them to train Gradient Boosting Tree. We tested our approach on a dataset of almost 900,000 binaries collected in the wild between November 2017 and January 2018. Our dataset is much larger than those usually used for research and contains a wide range of malware variants. We show that proposed approach provides sufficient results for deployment in real applications. Besides, we provide a thorough analysis of obtained results to understand where and why the classifier makes mistakes.
Macroeconomic factors in asset pricing : an analysis of out-of-sample robustness

Cramer, Max; Ribeiro, Ruy Monteiro (Advisor). Macroeconomic factors in asset pricing: an analysis of out-of-sample robustness. Rio de Janeiro, 2018. 41p. Dissertação de Mestrado – Departamento de Economia, Pontifícia Universidade Católica do Rio de Janeiro. This study aims to identify the macroeconomic factors constituting the systematic risk for US asset prices and mutual fund returns using the Arbitrage Pricing Theory in the spirit of Chen, Roll and Ross (1986). We find that the model does not explain the cross-section of stock returns well in the most recent sample and that risk premia estimates are not stable.
Wood Species Identification using Convolutional Neural Network (CNN) Architectures on Macroscopic Images

Indonesia is a country that is very rich in tree species that grow in forests. Wood growth in Indonesia consists of around 4000 species that have different names and characteristics. These differences can determine the quality and exact use of each type of wood. The procedure of standard identification is currently still carried out through visual observation by the wood anatomist. The wood identification process is very in need of the availability of wood anatomists, with a limited amount of wood anatomist will affect the result and the length of time to make an identification. This thesis uses an identification system that can classify wood based on species names with a macroscopic image of wood and the implementation of the Convolutional Neural Network (CNN) method as a classification algorithm. Supporting architecture used is AlexNet, ResNet, and GoogLeNet. Architecture is then compared to a simple CNN architecture that is made namely Kayu30Net. Kayu30Net architecture has a precision performance value reaching 84.6%, recall 83.9%, F1 score 83.1% and an accuracy of 71.6%. In the wood species classification system using CNN, it is obtained that AlexNet as the best architecture that refers to a precision value of 98.4%, recall 98.4%, F1 score 98.3% and an accuracy of 96.7%.
Incidental Learning of Modal Features of North Indian Music

Musical knowledge is largely implicit; it is acquired without awareness of its complex rules, through interaction with a large number of samples during musical enculturation. Whereas several studies explored implicit learning of features of Western music, very little work has been done with respect to non-Western music, and synthetic rather than ecologically valid stimuli have been predominantly used. The present study investigated implicit learning of modal melodic features in traditional North Indian music in a realistic and ecologically valid way. It employed a cross-grammar design, using melodic materials from two ragas that use the same scale, Toṛī and Multānī. Participants were trained on the ālāp section of either rāga and tested on novel excerpts from joṛ sections of both ragas featuring 5 distinct melodic features and using binary familiarity and 6-point confidence judgments. Three of the five features were melodically distinctive of either rāga, whereas two were only distinctive based on other than mere pitch sequence features (for instance, emphasis). Findings indicated that Western participants in both groups incidentally learned to recognise some, but not all, of the five features above chance level, and that the melodically distinctive features were better recognised than the non-distinctive ones. Confidence ratings suggest that participants’ performance was consistently correlated with confidence, indicating that they became aware of whether they were right in their responses, i.e. they possessed explicit judgment knowledge. Altogether participants began to incidentally acquire familiarity with a musical style from beyond their cultural background during only a very short exposure.
www.econstor.eu Agency and Communication in IMF Conditional Lending: Theory and Empirical Evidence

We focus on the role that the transmission of information between a multilateral (the IMF) and a country has for the optimal design of conditional reforms. Our model predicts that when agency problems are especially severe, and/or IMF information is valuable, a centralized control is indeed optimal. To the contrary, when local knowledge is more important than the agency bias we expect delegation to dominate. Controlling for economic and political factors, our empirical tests show that the number of IMF conditions is lower in countries with a greater social complexity, while it increases with the bias of the countries’ authorities, openness, and transparency, consistently with the theory. JEL Code: C23, D82, F33, N2.
A 1-V 10-bit 16.83-fJ/Conversion-step Mixed Current Mode SAR ADC for WSN

This paper proposes a 10-bit mixed current mode low power SAR ADC for sensor node application. The different entities of a successive approximation register (SAR) analog-to-digital converter (ADC) circuit has a hybrid or mixed mode approach i.e.,voltage mode regenerative comparator; mixed SAR logic; and current mode digital-to-analog converter (DAC). The performance limitation of speed and the kick-back noise of a dynamic comparator is resolved using duty cycle controlled regenerative comparator. A mixed mode logic of a SAR is partitioning the design into synchronous ring counter and asynchronous output register. The data shifting of a ring counter is with the common clock tick while the output register exchanged it asynchronously using handshake signals, resulting in a low power SAR. The current mode switching function in a DAC to reduce asynchronous switching effect resulting in a low energy conversion per step. In overall, the proposed mixed SAR ADC consumes a 41.6 W  power and achieves an SFDR 69.3 dB at 10 MS/sec and 1 V supply voltage. It is designed and simulated in the 0.18  m TSMC CMOS process.
Interactive comment on “ Revisiting the relationship between soil moisture and N 2 O production pathways by measuring 15 N 2 O isotopomers

Understanding the production pathways of potent greenhouse gases, such as nitrous oxide (N2O), is essential for accurate flux prediction and for developing effective adaptation and mitigation strategies in response to climate change. Yet, there remain surprising gaps in our understanding and precise quantification of the underlying production 10 pathways – such as the relationship between soil moisture and N2O production pathways. A powerful, but arguably underutilized, approach for quantifying the relative contribution of nitrification and denitrification to N2O production involves determining 15N2O isotopomers and 15N site preference (SP) via spectroscopic techniques. Using one such technique, we conducted a short-term incubation where N2O production and 15N2O isotopomers were measured 24-h after soil moisture treatments of 40 to 105% water-filled pore space (WFPS) were established – for each of three soils 15 that differed in nutrient levels, organic matter and texture. Relatively low N2O fluxes and high SP values indicted nitrification during dry soil conditions, whereas at higher soil moisture, peak N2O emissions coincided with a sharp decline in SP indicating denitrification. This pattern supports the classic N2O production curves from nitrification and denitrification as inferred by earlier research; however, our isotopomer data enabled the quantification of source partitioning for either pathway. At soil moisture levels < 53% WFPS, the fraction of N2O attributed to nitrification 20 (FN) predominated but thereafter decreased rapidly with increasing soil moisture (x), according to: F" = 3.19 − 0.041x, until a WFPS of 78% was reached. Simultaneously, from WFPS of 53 to 78%, the fraction of N2O that was attributed to denitrification (FD) was modelled as: F, = −2.19 + 0.041x; at moisture levels of > 78%, denitrification completely dominated. Clearly, the soil moisture level during transition is a key regulator of N2O production pathways. The presented equations may be helpful for other researchers to estimate N2O source partitioning when soil moisture 25 falls within the transition from nitrification to denitrification.
New interdisciplinary research on Neolithic-Eneolithic sites in the Low Volga River region

The Neolithic and Eneolithic sites in the Low Volga River region have been poorly investigated in comparison with other territories due to a small number of excavated sites. On the Algay site and the Oroshaemoe I settlement there is evidence of the earliest appearance of Neolithic pottery and the first sign of domestication in the Eneolithic period within the Volgo-Ural territory. Archaeological, lithological, grain-size analyses, mineralogical-geochemical methods and radiocarbon dating of cultural deposits have been applied to reconstruct the palaeoenvironment in the Holocene in this area. The results show that the landscape-climatic conditions in the steppe area of the Lower Volga basin strongly affected the development and adaptation of ancient societies.
Augmented Intention Model for Next-Location Prediction from Graphical Trajectory Context

Human trajectory prediction is an essential task for various applications such as travel recommendation, location-sensitive advertisement, and traffic planning. Most existing approaches are sequential-model based and produce a prediction by mining behavior patterns. However, the effectiveness of pattern-based methods is not as good as expected in real-life conditions, such as data sparse or data missing. Moreover, due to the technical limitations of sensors or the traffic situation at the given time, people going to the same place may produce different trajectories. Even for people traveling along the same route, the observed transit records are not exactly the same. Therefore trajectories are always diverse, and extracting user intention from trajectories is difficult. In this paper, we propose an augmented-intention recurrent neural network (AI-RNN) model to predict locations in diverse trajectories. We first propose three strategies to generate graph structures to demonstrate travel context and then leverage graph convolutional networks to augment user travel intentions under graph view. Finally, we use gated recurrent units with augmented node vectors to predict human trajectories. We experiment with two representative real-life datasets and evaluate the performance of the proposed model by comparing its results with those of other state-of-the-art models. The results demonstrate that the AI-RNN model outperforms other methods in terms of top-k accuracy, especially in scenarios with low similarity.