Miracle-dz/UniFAR-FTUs huggingface dataset:
THE THEORY OF FINANCE

Experimental findings and in particular Prospect Theory and Cumulative Prospect Theory contradict Expected Utility Theory, which in turn may have a direct implication to theoretical models in finance and economics. We show growing evidence against Cumulative Prospect Theory. Moreover, even if one accepts the experimental results of Cumulative Prospect Theory, we show that most theoretical models in finance are robust. In particular, the CAPM is intact even if investors make decisions based on change of wealth, employ decision weights, and are risk-seeking in the negative domain.
Work-Life Balance and Socio-economic Status as Predictors of Psychological Wellbeing among Civil Servants in Makurdi Metropolis

The study examined work-life balance and socio-economic status as predictors of psychological wellbeing among civil servants in Makurdi metropolis. A total of 215 civil servants were randomly drawn in Makurdi metropolis. The findings revealed that 151 (70.2%) were males and 59 (27.4) were females. Three research objectives, questions, and hypotheses were generated to guide the study. The study was a cross-sectional survey design. The study used two standardized instruments which include: Work life Balance scale developed by Brett and Stroh’s (2003), and Psychological Well-Being (PWBS) developed by Ryff’ in (1995). Data analysis was done using Simple Linear and Multiple Regression Analysis via the Statistical Package for Social Science (SPSS). The hypotheses were tested at 0.05 level of significance. Findings showed that there is a significant influence of work-life balance on psychological wellbeing among civil servants [F (1,212) = 12.023, P>. 05]. Results further showed that socioeconomic status significantly influences psychological wellbeing among civil servants [F (1,210) = 6.514, P>. 05]. Finally, there is a significant joint influence of work-life balance and socio-economic status on psychological wellbeing among civil servants [F (2,210) = 18.109, P>. 05]. Based on the findings of the study, it was recommended that management should establish a cohesive relationship with the employees to achieve trust from them in order to enhance their psychological well-being.
Wage Adjustment and Productivity Shocks

We study how workers’ wages respond to TFP-driven innovations in firms’ labor productivity. Using unique data with highly reliable firm-level output prices and quantities in the manufacturing sector in Sweden, we are able to derive measures of physical (as opposed to revenue) TFP to instrument labor productivity in the wage equations. We find that the reaction of wages to sectoral labor productivity is almost three times larger than the response to pure idiosyncratic (firm-level) shocks, a result which crucially hinges on the use of physical TFP as an instrument. These results are all robust to a number of empirical specifications, including models accounting for selection on both the demand and supply side through worker-firm (match) fixed effects. Further results suggest that technological progress at the firm level has negligible effects on the firm-level composition of employees. ∗We thank John Abowd, Per-Anders Edin, Peter Fredriksson, John Haltiwanger, Marcel Jansen, Francis Kramarz, Rafael Lalive, Nuria Rodríguez-Planas and seminar participants at SciencePo, the Helsinki Center of Economic Research (HECER), the Euro-System WDN network, the 6th ECB/CEPR Labor Market Workshop, IFAU, the “Labor Market and the Macroeconomy” conference at Sveriges Riksbank, the LMDG workshop on “Matched Employer-Employee Data: Developments since AKM”, the UCLS Industrial Relations workshop, and the 2010 EEA, EALE/SOLE and LACEA meetings for useful comments. The views expressed in this paper are solely the responsibility of the authors and should not be interpreted as reflecting the views of the Executive Board of Sveriges Riksbank or the World Bank. †Research Department, Sveriges Riksbank E-mail: mikael.carlsson@riksbank.se. ‡Office of the Chief Economist for Latin America and the Caribbean, World Bank. E-mail: jmessina@worldbank.org §Institute for Labour Market Policy Evaluation (IFAU), UCLS, and IZA. E-mail: oskar. nordstrom_skans@ifau.uu. se.
Prediction by financial and economic analysis in the conditions of forest enterprises

Individual companies need to know their financial condition. They have a wide range of methods and procedures to create a system of the financial and economic analysis of a company. The analysis is focused on the evaluation of a specific group of methods for predicting the financial health of a business entity. Evaluations of the financial situation of a company are divided into point methods, mathematical and statistical methods and neural networks. The individual methods differ from each other in difficulty, in the extent of the analyzed areas and possibilities of application. The aim of this work is to assess the possibilities of using selected methods of comprehensive evaluation of companies as a tool for an analysis of the position of each company in the branch. The suitability and feasibility of each method are tested on a selected group of companies. Quick Test, Tamari Model, Beaver Model are included in this work. Based on the results, improvements and recommendations for the practical use were suggested. The results showed that the best predictive methods are Quick Test and Tamari Model, because they are quick and unequivocal when assessing the analyzed companies. An inappropriate prediction method is the Beaver model, which uses only two financial indicators to evaluate companies.
SPANISH VERSION OF THE SHORT DEPRESSION-HAPPINESS SCALE (SDHS): A RELIABILND VALIDITY STUDY IN A SAMPLE OF SPANISH ELDERLY PEOPLE ADAPTACIÓN ESPAÑOLA DE LA ESCALA BREVE DE DEPRESIÓN-FELICIDAD: UN ESTUDIO DE VALIDACIÓN Y FIABILIDAD EN UNA MUESTRA DE PERSONAS MAYORES

The psychometric properties of the Short DepressionHappiness Scale (SDHS) were analyzed in a sample of 216 Spanish elderly people with an average age of 73.89 (SD = 6.49). An exploratory factor analysis and confirmatory factor analysis were developed in order to identify the factorial solution and the best model fit. Just on factor was identified. Regarding reliability and validity, internal consistency index was . 757 and the correlation between the Short Depression-Happiness Scale (SDHS) and measures of others construct, General Health Questionnaire (GHQ) and Center for Epidemiological Studies Depression Scale (CESD) (CESD), were significance. The practical implications of the scale and the index values obtained are discussed.
Running Head: SELF-REGARD: SOCIOMETER OR HIEROMETER? 1 In press, Journal of Personality and Social Psychology

What adaptive function does self-regard serve? Sociometer theory predicts that it positively tracks social inclusion. A new theory, hierometer theory, predicts that it positively tracks social status. We tested both predictions with respect to two types of self-regard: selfesteem and narcissism. Study 1 (N = 940), featuring a cross-sectional design, found that both status and inclusion covaried positively with self-esteem, but that status alone covaried positively with narcissism. These links held independently of gender, age, and the Big Five personality traits. Study 2 (N = 627), a pre-registered cross-sectional study, obtained similar results with alternative measures of self-esteem and narcissism. Studies 3–4 featured experimental designs in which status and inclusion were orthogonally manipulated. Study 3 (N = 104) found that both higher status and higher inclusion promoted higher self-esteem, whereas only higher status promoted higher narcissism. Study 4 (N = 259) obtained similar results with alternative measures of self-esteem and narcissism. The findings suggest that self-esteem operates as both sociometer and hierometer, positively tracking both status and inclusion, whereas narcissism operates primarily as a hierometer, positively tracking status.
GP130 Cytokines in Breast Cancer and Bone

Breast cancer cells have a high predilection for skeletal homing, where they may either induce osteolytic bone destruction or enter a latency period in which they remain quiescent. Breast cancer cells produce and encounter autocrine and paracrine cytokine signals in the bone microenvironment, which can influence their behavior in multiple ways. For example, these signals can promote the survival and dormancy of bone-disseminated cancer cells or stimulate proliferation. The interleukin-6 (IL-6) cytokine family, defined by its use of the glycoprotein 130 (gp130) co-receptor, includes interleukin-11 (IL-11), leukemia inhibitory factor (LIF), oncostatin M (OSM), ciliary neurotrophic factor (CNTF), and cardiotrophin-1 (CT-1), among others. These cytokines are known to have overlapping pleiotropic functions in different cell types and are important for cross-talk between bone-resident cells. IL-6 cytokines have also been implicated in the progression and metastasis of breast, prostate, lung, and cervical cancer, highlighting the importance of these cytokines in the tumor–bone microenvironment. This review will describe the role of these cytokines in skeletal remodeling and cancer progression both within and outside of the bone microenvironment.
A 3D LiDAR Dataset of ITU Heterogeneous Robot Team

This paper describes a data set collected with a heterogeneous team of robots consisting of an unmanned ground and aerial vehicles driven in small area inside Maslak Campus of Istanbul Technical University. It is a valuable data set for testing SLAM, Loop Closure and Map Merging techniques. While UGV platform has IMU, GPS, Odometry and Light Detection and Ranging (LiDAR) sensors, UAV platform has IMU, GPS and LiDAR sensors. In UAV dataset, having multiple traversals of the same path can be useful to test loop closure techniques. The dataset is available for download at robotics.itu. edu.tr/ITU_Dataset.
Is Rank Aggregation Effective in Recommender Systems? An Experimental Analysis

Recommender Systems are tools designed to help users find relevant information from the myriad of content available online. They work by actively suggesting items that are relevant to users according to their historical preferences or observed actions. Among recommender systems, top-N recommenders work by suggesting a ranking of N items that can be of interest to a user. Although a significant number of top-N recommenders have been proposed in the literature, they often disagree in their returned rankings, offering an opportunity for improving the final recommendation ranking by aggregating the outputs of different algorithms. Rank aggregation was successfully used in a significant number of areas, but only a few rank aggregation methods have been proposed in the recommender systems literature. Furthermore, there is a lack of studies regarding rankings’ characteristics and their possible impacts on the improvements achieved through rank aggregation. This work presents an extensive two-phase experimental analysis of rank aggregation in recommender systems. In the first phase, we investigate the characteristics of rankings recommended by 15 different top-N recommender algorithms regarding agreement and diversity. In the second phase, we look at the results of 19 rank aggregation methods and identify different scenarios where they perform best or worst according to the input rankings’ characteristics. Our results show that supervised rank aggregation methods provide improvements in the results of the recommended rankings in six out of seven datasets. These methods provide robustness even in the presence of a big set of weak recommendation rankings. However, in cases where there was a set of non-diverse high-quality input rankings, supervised and unsupervised algorithms produced similar results. In these cases, we can avoid the cost of the former in favor of the latter.
How Enterprises Adopt Agile Forms of Organizational Design: A Multiple-Case Study

The question of how to increase speed and flexibility in times of digital disruption is essential to almost any company. While previous research mainly addresses agility in the context of information systems development, as form for organizing startups or "born digital" companies, little knowledge exists about the adoption of agile practices and structures at established enterprises. With an exploratory study of fifteen global cases, we aim at examining how established enterprises adopt and scale agile forms of organizational design. We found that (1) agile forms of organizational design are currently adopted by enterprises at large scale, (2) agile forms of organizational design are adopted not only by IT, but successively also by business units and in contexts outside information systems development, and (3) while Spotify's organization serves as a widespread template for a fully agile unit, enterprises adapt and fine-tune this template according to their needs and scale. We identified three additional models for fully agile forms of organizational design where a fully agile unit with cross-product support is the most frequently observed model.
Analysis of the Method for Determining Changes in the Airways from the Spirometric Curve Evolution

The severity of chronic respiratory diseases is evaluated performing spirometry, and particularly the forced expiration maneuvers before and after bronchodilation or challenge tests. However, no method has yet been proposed for the quantitative assessment of changes in airway mechanics following such tests. Just recently, a reduced model for forced expiration with 6 free parameters was derived and used to estimate the parameters by fitting it to a spirometric curve. The aim of this work was to perform comprehensive research on the method for quantifying the changes in airway mechanics by fitting the above model to two spirometric curves, representing the states of the respiratory system before and after bronchodilation or bronchoconstriction. To this end, a set of pairs of spirometric curves were generated from randomly drawn parameters, and 2,400 of them were used for testing purposes. The proposed method for spirometric data analysis consisted of two stages: the estimation of 6 parameters from the pre-test data using the inverse neural network and the Levenberg-Marquardt (LM) algorithm, and then the estimation of 2 parameters describing airway properties from the post-test curve with the LM procedure. The results show that this approach allows the quantification of changes in the airway mechanics with the accuracy of about 6-7 % of the parameter ranges. These outcomes encourage further analysis of the method using more reliable spirometric data.
AromaCue - A Scent Toolkit To Cope with Stress using the 4-7-8 Breathing Method

In this paper, we present AromaCue, an initial design for a scent-based toolkit to cope with stressful situations using scent conditioning. The AromaCue toolkit consists of two parts: a breath training device using multiple stimuli and a wearable scent-emitting device (with a stress ball as an activator). Scent can trigger emotional memories. In the initial design, we utilized the properties of various scents as retrieval cues for consciousness breathing. In a comparative experiment, eight participants showed a significant heart rate decrease several minutes after a stressor (the Stroop test) when a scent cue was present, but not without it. One week of user study revealed significant improvement on Depression Anxiety and Stress Scale (DASS-21) scores. Therefore, AromaCue can help users to cope with stress.
How Privacy Concerns, Trust and Risk Beliefs, and Privacy Literacy Influence Users' Intentions to Use Privacy-Enhancing Technologies: The Case of Tor

Due to an increasing collection of personal data by internet companies and several data breaches, research related to privacy gained importance in the last years in the information systems domain. Privacy concerns can strongly influence users' decision to use a service. The Internet Users Information Privacy Concerns (IUIPC) construct is one operationalization to measure the impact of privacy concerns on the use of technologies. However, when applied to a privacy enhancing technology (PET) such as an anonymization service, the original rationales do not hold anymore. In particular, an inverted impact of trusting and risk beliefs on behavioral intentions can be expected. We show that the IUIPC model needs to be adapted for the case of PETs. In addition, we extend the original causal model by including trusting beliefs in the anonymization service itself as well as a measure for privacy literacy. A survey among 124 users of the anonymization service Tor shows that trust in Tor has a statistically significant effect on the actual use behavior of the PET. In addition, the results indicate that privacy literacy has a negative impact on trusting beliefs in general and a positive effect on trust in Tor.
The Effects of Isoflurane on Desensitized Wild-Type and &agr;1(S270H) γ-Aminobutyric Acid Type A Receptors

γ-aminobutyric acid type A receptors (GABAA-R) mediate synaptic inhibition and meet many pharmacological criteria required of important general anesthetic targets. During synaptic transmission GABA release is sufficient to saturate, maximally activate, and transiently desensitize postsynaptic GABAA-Rs. The resulting inhibitory postsynaptic currents (IPSCs) are prolonged by volatile anesthetics like isoflurane. We investigated the effects of isoflurane on maximally activated and desensitized GABAA-R currents expressed in Xenopus oocytes. Wild-type &agr;1β2 and &agr;1β2γ2s receptors were exposed to 600 μM GABA until currents reached a steady-state desensitized level. At clinical concentrations (0.02–0.3 mM), isoflurane produced a dose-dependent enhancement of steady-state desensitized current in &agr;1β2 receptors, an effect that was less apparent in receptors including a γ2s-subunit. When serine at position 270 is mutated to histidine (&agr;1(S270H)) in the second transmembrane segment of the &agr;1-subunit, the currents evoked by sub- saturating concentrations of GABA became less sensitive to isoflurane enhancement. In addition, isoflurane enhancements of desensitized currents were greatly attenuated by this mutation and were undetectable in &agr;1(S270H)β2γ2s receptors. In conclusion, isoflurane enhancement of GABAA-R currents evoked by saturating concentrations of agonist is subunit-dependent. The effects of isoflurane on desensitized receptors may be partly responsible for the prolongation of IPSCs during anesthesia.
The Impact of the SET Awards on Return on Equity of Listed Companies in the Stock Exchange of Thailand

This study aims to investigate the impact of the SET awards on Return on Equity (ROE) of 107 listed companies in the Stock Exchange of Thailand from 2009 to 2017. The study applies quantile regression analysis to estimate the relationship between ROE ratio and five influencing factors, which are the Best Company Performance Award, the Best CEO Award, the Best Investor Relations Award, the Best Corporate Social Responsibility Award, and the Best Innovative Company Award. The findings indicate that the Best Company Performance Award has a positive relationship with the Return on Equity. However, the effect of the Best CEO Award, the Investor Relations Award, the Best Corporate Social Responsibility Award, and the Best Innovative Company on the Return on Equity does not exist.
Model agnostic interpretability of rankers via intent modelling

A key problem in information retrieval is understanding the latent intention of a user's under-specified query. Retrieval models that are able to correctly uncover the query intent often perform well on the document ranking task. In this paper we study the problem of interpretability for text based ranking models by trying to unearth the query intent as understood by complex retrieval models. We propose a model-agnostic approach that attempts to locally approximate a complex ranker by using a simple ranking model in the term space. Given a query and a blackbox ranking model, we propose an approach that systematically exploits preference pairs extracted from the target ranking and document perturbations to identify a set of intent terms and a simple term based ranker that can faithfully and accurately mimic the complex blackbox ranker in that locality. Our results indicate that we can indeed interpret more complex models with high fidelity. We also present a case study on how our approach can be used to interpret recently proposed neural rankers.
Transferring scents over a communication network

In our work on scent technology, we have come across technology that can be used, in a limited way, to achieve scent transfer. In this paper, we document the scent transfer demonstration that we constructed for a science fair in 2018. Scent transfer requires a means to measure, transmit, classify, and reproduce scents. First, an ion-mobility spectrometer was used to measure scents. This data was sent to a server on the Internet. From the server, the measurement data was downloaded, baseline-corrected, and classified with an algorithm based on weighted K nearest neighbors and time series measurements. The classification result was used to instruct an olfactory display prototype to reproduce the scent for humans to sense. Our demonstration included two scents. Many more could be included, but a general-purpose scent reproduction is beyond our, and as far as we know, beyond anybody's current capabilities. Image and audio transmission technology are mature, but in the chemical senses such as olfaction and taste, significant challenges remain before they can be routinely included in multimodal interfaces.
A Methodology for Comparing the Reliability of GPU-Based and CPU-Based HPCs

Today, GPUs are widely used as coprocessors/accelerators in High-Performance Heterogeneous Computing due to their many advantages. However, many researches emphasize that GPUs are not as reliable as desired yet. Despite the fact that GPUs are more vulnerable to hardware errors than CPUs, the use of GPUs in HPCs is increasing more and more. Moreover, due to native reliability problems of GPUs, combining a great number of GPUs with CPUs can significantly increase HPCs’ failure rates. For this reason, analyzing the reliability characteristics of GPU-based HPCs has become a very important issue. Therefore, in this study we evaluate the reliability of GPU-based HPCs. For this purpose, we first examined field data analysis studies for GPU-based and CPU-based HPCs and identified factors that could increase systems failure/error rates. We then compared GPU-based HPCs with CPU-based HPCs in terms of reliability with the help of these factors in order to point out reliability challenges of GPU-based HPCs. Our primary goal is to present a study that can guide the researchers in this field by indicating the current state of GPU-based heterogeneous HPCs and requirements for the future, in terms of reliability. Our second goal is to offer a methodology to compare the reliability of GPU-based HPCs and CPU-based HPCs. To the best of our knowledge, this is the first survey study to compare the reliability of GPU-based and CPU-based HPCs in a systematic manner.
SoC implementation of depthwise separable convolution for object detection

Depthwise separable convolution has been used in CNN to reduce operations and parameters with only limited loss in accuracy. However, the state-of-the-art CNNs that adopt depthwise separable convolution still require a powerful computing platform such as a Graphics Processing Unit (GPU). In this paper: firstly, we design three kinds of work models for process element(PE) based on FPGA: standard convolution model, depthwise convolution model and pointwise convolution model; then we implement MobileNet-SSD on SoC for object detection, and our method requires only limited resources; besides, we propose a method to transform float-point data into fixed-point data, making computation more convenient. And the results show that our work can detect object at 13 fps.