Miracle-dz/UniFAR-FTUs huggingface dataset:
Keskusteluaiheita – Discussion papers No . 860

We use plant-level linked employer-employee data from Finland to estimate production functions where also employee characteristics (average age and education, and sex composition) are included. We also estimate similar models for wages to examine whether wages are based on productivity. Our aim is to explain productivity besides manufacturing, also in services. For the service sector plants, no data on capital input, working hours, or value added is available, and productivity has to be measured by sales per employee. We use a stepwise procedure to examine whether the results for manufacturing are affected when less satisfactory data is used. Then we proceed to estimate the final model for manufacturing and services combined. The effect of age on productivity is negative, but wages show strong positive age effects. Higher educational level leads to higher wage, but there is a clear productivity difference between nontechnical and technical education. Some of the productivity effects of technical education are negative. Wage-productivity gaps (relative to the reference group, basic education) are positive for the highest level of technical education, but negative for the highest non-technical education. The share of female workers is negatively related to productivity. Also the wage effect is negative, but smaller in absolute value, leading to a positive female wage-productivity gap. However, the negative productivity effect disappears and the gap is negative if the model is estimated with fixed plant effects.
Dutch Disease Perspective on Vegetable Exports in the Azerbaijan Economy

Agriculture or agrarian sectors together with non-resource manufacturing can be the key drivers of non-mineral development among natural resource-rich countries. However, agricultural development lags behind the extractive industry which puts a big share of the labor force into an uncertain position and creates food security risks. In Azerbaijan, which is an oil-rich post-soviet country, details focus on individual exports like vegetable exports that have not been carried out against specific economic indicators such as the Extractives Dependence Index (EDI), the Real Effective Exchange Rate (REER), etc. This paper is based on one-way variance analysis (ANOVA) and Tukey’s honest significance test (Tukey’s HSD test), as well as the Granger causality test. Our analysis shows that Azerbaijan’s dependency on natural resources (measured by the EDI) has a significant effect on the value of vegetable exports. Moreover, the Granger causality test revealed a one-side causal relationship from the REER and production costs to the vegetable exports, at a 10% significance level. Similarly, a unidirectional Granger causal relationship from crude oil prices to the REER, at a 1% significance level was found. Thus, our findings indicate that overall Dutch disease affects the Azerbaijan economy towards vegetable exports.
Working Paper # 003 / 2019 Does Internal Capital Market Membership Matter for Capital Allocation ? Theory and Evidence from the Euro Area ∗

This paper investigates the capital allocative behavior of firms’ integrating active internal capital markets (ICM). Specifically, examines the investment-cash flow sensitivity and its relationship with factors, such as, financial flexibility, suboptimality of investment expenditure, and crosssubsidization, using a matched sample design of two comparable panel data sets of 636 subsidiaries and stand-alone firms of the euro area, over the 2004–2013 sampling period. Results from panel data regression document that ICM firms exhibit lower sensitivity to the availability of internal funding than pure-play stand-alone firms, and that for stand-alone firms the effect of financial flexibility on investment-cash flow sensitivity is larger than for ICM cohorts. Findings also document that, on average, subsidiaries experience lower levels of investment suboptimality, and that subsidiaries with poor growth opportunities, ceteris paribus, invest less than pure-play stand-alone firms, consistent with lower cross-subsidization problems within ICMs. These findings are consistent with the propositions that centralized capital budgeting systems can potentially mitigate informational and incentive problems associated with investment behavior, and that subsidiary firms may use internal capital markets as a substitute for financial slack.
Quantum chemical modeling of uranyl adsorption on mineral surfaces

Abstract We overview quantum mechanical simulations that model the adsorption of actinide ions at solvated mineral surfaces. Pertinent examples illustrate the status of this emerging field of computational chemistry. In particular, we describe our own studies on uranyl adsorption on kaolinite. Already the few available results, from applications of density functional methods to cluster models or periodic slab models, show that such calculations are a useful complement to experimental investigations. Detailed information at the atomic level from accurate electronic structure calculations on well defined model systems helps to refine current interpretations of the chemical nature of uranyl adsorption species and to discover new features of these interface systems. Results from quantum mechanical simulations also provide a valuable reference for future experimental investigations.
Necessary and sufficient conditions for complete monotonicity and monotonicity of two functions defined by two derivatives of a function involving trigamma function

In the paper, by virtue of convolution theorem for the Laplace transforms, Bernstein's theorem for completely monotonic functions, some properties of a function involving exponential function, and other analytic techniques, the author finds necessary and sufficient conditions for two functions defined by two derivatives of a function involving trigamma function to be completely monotonic or monotonic. These results generalize corresponding known ones.
SOCIOECONOMIC STATUS - EFFECTS AND IMPLICATIONS FOR SPECIAL EDUCATION PLACEMENT

________Brandner Kristine K. ___ (Last Name) (First Name) (Initial) __________ Socioeconomic Status – Effects and Implications for ____________ (Title) _____ ____________Special Eduation Placement____ _________ ___ __Education________Dr. Edwin Biggerstaff__March, 2004 _________47_____ (Graduate Major) (Research Advisor) (Month/Year) (No. of Pages) ______________American Psychological Association, 5 edition _______________ (Name of Style Manual Used in this Study) The purpose of this study was to determine if socioeconomic status played a role in special education referrals and placements. This study included a comprehensive review and critical analysis of research and literature concerning special education, the referral process, and socioeconomic status to determine if there was a relationship between socioeconomic status and placement of students in special education. Conclusions were drawn and recommendations were given for parents, educators, and administrators as well as school districts. Research has suggested that the steps are in place to intervene in struggling student’s education in some school districts. Programs were set up during the school
Video Encoder-Based Compression for Convolutional Neural Network

—Lightweight Convolutional Neural Network (CNN) for mobile devices has been researched in many ways. Much research have achieved great space-saving and reduced computational complexity, maintaining the accuracy. These methods have re-training or ﬁne-tuning step to recover accuracy. In real situation, the re-training steps have some difﬁculties with computing resource or data access. On these scores, we propose the CNN compression method without ﬁne-tuning step for mobile devices. As most mobile devices includes hardware for video coding, proposing method can be used in mobile devices. In this study, we evaluate our method with different datasets and compare with other methods.
Evaluation of Nonlinear Dynamic Response of Rigid and Semi-Rigid Steel Frames under Far-Field Earthquake Records

The purpose of this research was to evaluate the nonlinear dynamic response of rigid and semi-rigid steel frames under FarFault Earthquake Records. Accordingly, the fragility curve of the moment frames with rigid and semi-rigid connections was determined. Considering the analytical knowledge of structures in the past, the analysis and design of steel frames based on the assumptions of rigid or joint connections. While laboratory studies show that most connections are semi-rigid and due to the importance of connections in the structures, it is very important to recognize and accurately study their behavior, especially during an earthquake, and their design must be under their real structural behavior. For this purpose, three twodimensional steel moment frame structures with 6, 12, and 18 stories were used, which represent short, medium, and high structures. Considering the rigid and semi-rigid connections, their seismic performance was investigated using the nonlinear dynamic incremental analysis (IDA). Three cases of connections have been selected corresponding to 50, 60, and 70% rigidity. Finally, the collapse fragility curve parameters obtained and compared. According to the obtained results, decreasing the rigidity of the beam-to-column connections increases the dispersion of the collapse fragility curve. Besides, it was observed that considering the semi-rigid connections leads to a reduction of the median of the collapse fragility curve. The result shows that the mentioned difference cannot be neglected.
Stem cell metabolism: from embryonic development to stem cell differentiation

Transitions through pluripotent stem cell states, differentiation, and reprogramming, involve substantial metabolic remodeling. These metabolic transitions are only just beginning to be understood, often relying on transcriptional data to infer metabolism, rather than actual metabolic outputs. Here, we consider the metabolism of the early embryo through development, and look at the nutrient milieu within the developing stem cell niche. We discuss what is known about the distinct metabolic states captured in vitro by the 2-cell-like, naïve, blastocyst-like, formative, and primed states of pluripotency. We explore the recently described metabolic surge event that occurs as pluripotency is lost and stem cells commit to differentiate. Finally, we explore the most recent understanding of germ layer-specific metabolic remodeling. To establish protocols for the safe and efficient differentiation of healthy cells for therapies, we must develop a better understanding of the dynamic continuum of metabolic states that span pluripotency and differentiation, and how to influence them.
Executive Stock Option and Blockholder Ownership as Governance Mechanisms on Firm Performance

Separation of ownership and control led to agency conflicts between the majority and minority shareholders in South East Asian Corporations. Using panel data pooled GLS estimations, this study investigates the effects of Executive Stock Option (ESO) granting and blockholder ownership on firm performance of Malaysian non-financial listed companies. A positive significant increased relationship between ESO granting and firm performance is found which conform incentive alignment hypothesis, coupled with the modest effect of blockholder ownership while considering both market and accounting based performance measurements. These explanatory variables are in tandem with the enhancement of future revenues by alleviating the conflicts between shareholders and managers of Malaysian firms. The low positive relationship is indicating the blockholder ownership as a monitoring device that has modest power. Additionally, industry effects on firm performance also been observed.
Advances in Neural Rendering

Synthesizing photo‐realistic images and videos is at the heart of computer graphics and has been the focus of decades of research. Traditionally, synthetic images of a scene are generated using rendering algorithms such as rasterization or ray tracing, which take specifically defined representations of geometry and material properties as input. Collectively, these inputs define the actual scene and what is rendered, and are referred to as the scene representation (where a scene consists of one or more objects). Example scene representations are triangle meshes with accompanied textures (e.g., created by an artist), point clouds (e.g., from a depth sensor), volumetric grids (e.g., from a CT scan), or implicit surface functions (e.g., truncated signed distance fields). The reconstruction of such a scene representation from observations using differentiable rendering losses is known as inverse graphics or inverse rendering. Neural rendering is closely related, and combines ideas from classical computer graphics and machine learning to create algorithms for synthesizing images from real‐world observations. Neural rendering is a leap forward towards the goal of synthesizing photo‐realistic image and video content. In recent years, we have seen immense progress in this field through hundreds of publications that show different ways to inject learnable components into the rendering pipeline. This state‐of‐the‐art report on advances in neural rendering focuses on methods that combine classical rendering principles with learned 3D scene representations, often now referred to as neural scene representations. A key advantage of these methods is that they are 3D‐consistent by design, enabling applications such as novel viewpoint synthesis of a captured scene. In addition to methods that handle static scenes, we cover neural scene representations for modeling non‐rigidly deforming objects and scene editing and composition. While most of these approaches are scene‐specific, we also discuss techniques that generalize across object classes and can be used for generative tasks. In addition to reviewing these state‐of‐the‐art methods, we provide an overview of fundamental concepts and definitions used in the current literature. We conclude with a discussion on open challenges and social implications.
Automatically Detecting Exception Handling Defects in Android Applications

Developers often neglect to handle exceptions, which leads to exception handling defects that affect the robustness of applications or even cause crashes. To improve the robustness of android applications while reducing the development burden of developers, we present Fixeh and Automatic Detection Tool, as an approach that can automatically detect exception handling defects related to external resources. By implanting exception control codes into the input application, Fixeh helps applications throw exceptions at the specified call position while running the UI test. During running the UI test, Automatic Detection Tool generates a limited number of exception trigger patterns by using suspicious call filtering algorithm and traversal algorithm. After collecting and analyzing the running results under these patterns, the exception handling defects will be detected. We evaluate our approach by applying it to detect anomalies in 6 different types of applications with stable operation. We conducted 1422 rounds of experiments under different exception triggering patterns, and we observed abnormalities in 517 rounds. A comparison with other related work shows that our approach can detect defects more effectively. Through the analysis of our experiments, we confirmed 39 exception handling defects related to external resources. Finally, we summarized three common types of defects from them.
What Makes Open Source Software Projects Impactful: A Data-Driven Approach

With the wide adoption and acceptance of open source version control and hosting systems, more and more companies, including Google, Microsoft, Apple and Facebook, are putting their projects on such platforms, e.g., GitHub. It is very important for open source projects to be impactful, i.e., to attract attentions from the open source development community, so as to gain support on development, testing as well as maintenance from the community. However, the question of what factors affect open source project impact, remains largely open. Given the numerous confounding factors and the complex correlations among the factors, it is a challenge to answer the question. In this study, we gather a large dataset from GitHub and provide empirical insights on this question base on a data-driven approach. We randomly collect 146,286 projects from GitHub and then adopt data analysis techniques to automatically analyze the correlations of different features with the software project impact. We also provide suggestions on how to potentially make open source projects impactful base on our analysis results.
Dynamic Time Window based Reward for Reinforcement Learning in Continuous Integration Testing

Continuous Integration (CI) testing is an expensive, time-consuming, and resource-intensive process. Test case prioritization (TCP) can effectively reduce the workload of regression testing in the CI environment, where Reinforcement Learning (RL) is adopted to prioritize test cases, since the TCP in CI testing can be formulated as a sequential decision-making problem, which can be solved by RL effectively. A useful reward function is a crucial component in the construction of the CI system and a critical factor in determining RL’s learning performance in CI testing. This paper focused on the validity of the execution history information of the test cases on the TCP performance in the existing CI testing optimization methods based on RL, and a Dynamic Time Window based reward function are proposed by using partial information dynamically for fast feedback and cost reduction. Experimental studies are carried out on six industrial datasets. The experimental results showed that using dynamic time window based reward function can significantly improve the learning efficiency of RL and the fault detection ability when comparing with the reward function based on fixed time window.
Immunological Microenvironment Predicts the Survival of the Patients with Hepatocellular Carcinoma Treated with Anti-PD-1 Antibody

Introduction: Although immune checkpoint inhibitors (ICIs) have been considered as promising agents for the treatment of advanced hepatocellular carcinoma (HCC), previous clinical trials revealed that the response to anti-programmed cell death protein 1 (anti-PD-1) monotherapy was as low as 20%. Identifying subgroups that respond well to ICIs is clinically important. Here, we studied the prognostic factors for anti-PD-1 antibody treatment based on the molecular and immunological features of HCC. Methods: Patients who were administered anti-PD1 antibody for advanced HCC at Kindai University Hospital were included. Clinicopathological backgrounds and antitumor responses were examined in 34 cases where tumor tissues before treatment were available. Transcriptome analysis was performed using 40 HCC samples obtained from surgical resection, and immune status was compared between 20 HCCs with activating mutations in β-catenin and those without the mutations using transcriptome-based immunogram. Results: Univariate analysis showed that the disease control rate was significantly better in patients with α-fetoprotein < 400 ng/mL, negative for β-catenin/glutamate synthetase (GS) staining, high combined positive score (CPS) of programmed death-ligand 1 (PD-L1), and increased infiltration of CD8+ cells in tumor tissues. Among them, negative staining of β-catenin/GS, CPS of PD-L1 ≥ 1, and high degree of CD8+ tumor-infiltrating lymphocytes (TILs) were significantly associated with longer survival in both progression-free survival (PFS) and overall survival (OS). The combination of these factors well stratified the survival of the patients on anti-PD-1 antibody in both PFS and OS (p < 0.0001 and p = 0.0048 for PFS and OS, respectively). In addition, the immunogram revealed that tumor-carrying mutations in β-catenin showed downregulation of immune-related genes, especially in those related to priming and activation by dendritic cells, interferon-γ response, inhibitory molecules, and regulatory T cells. Discussion/Conclusion: The combined score including Wnt/β-catenin activation, CPS of PD-L1, and degree of CD8+ TILs in HCC is informative for predicting the response to ICI in HCC cases. Constitutive activation of β-catenin can induce an immune cold phenotype with downregulation of immune-related genes, and immunohistochemistry-based evaluation is beneficial for identifying the subgroup that shows a good response to ICI.
Real-Life Clinical Data of Cabozantinib for Unresectable Hepatocellular Carcinoma

Introduction: Cabozantinib has been approved by the European Medicine Agency (EMA) for hepatocellular carcinoma (HCC) previously treated with sorafenib. Cabozantinib is also being tested in combination with immune checkpoint inhibitors in the frontline setting. Real-life clinical data of cabozantinib for HCC are still lacking. Moreover, the prognostic factors for HCC treated with cabozantinib have not been investigated. Methods: We evaluated clinical data and outcome of HCC patients who received cabozantinib in the legal context of named patient use in Italy. Results: Ninety-six patients from 15 centres received cabozantinib. All patients had preserved liver function (Child-Pugh A), mostly with an advanced HCC (77.1%) in a third-line setting (75.0%). The prevalence of performance status (PS) > 0, macrovascular invasion (MVI), extrahepatic spread, and alpha-fetoprotein (AFP) >400 ng/mL was 50.0, 30.2, 67.7, and 44.8%, respectively. Median overall survival (OS) and progression-free survival were 12.1 (95% confidence interval 9.4–14.8) and 5.1 (3.3–6.9) months, respectively. Most common treatment-related adverse events (AEs) were fatigue (67.7%), diarrhoea (54.2%), anorexia (45.8%), HFSR (43.8%), weight loss (24.0%), and hypertension (24.0%). Most common treatment-related Grade 3–4 AEs were fatigue (6.3%), HFSR (6.3%), and increased aminotransferases (6.3%). MVI, ECOG-PS > 0, and AFP >400 ng/mL predicted a worse OS. Discontinuation for intolerance and no new extrahepatic lesions at the progression were associated with better outcomes. Conclusions: In a real-life Western scenario (mostly in a third-line setting), cabozantinib efficacy and safety data were comparable with those reported in its registration trial. Data regarding the prognostic factors might help in patient selection and design of clinical trials.
Impaired Response to Immunotherapy in Non-Alcoholic Steatohepatitis-Related Hepatocellular Carcinoma?

An article entitled “NASH Limits Antitumour Surveillance in Immunotherapy-Treated HCC” was recently published in Nature [1]. This article presented shocking evidence that immune checkpoint inhibitors are ineffective in non-alcoholic steatohepatitis (NASH)-related hepatocellular carcinoma (HCC) [1]. When antitumor immunity functions normally, CD8+ T cells are activated and become cytotoxic T lymphocytes (CTLs) upon recognition of antigens presented by major histocompatibility complex (MHC) class I molecules. Those CTLs recognize cancer antigens on the surface of cancer cells through T cell receptors and attack the cancer (Fig. 1). The study in Nature showed that mice fed a choline-deficient highfat diet or Western-style diet with trans-fat to induce NASH (NASH mice) accumulated a higher number of CD8+ T cells (particularly activated CD8+ T cells) over time than control mice fed a normal diet. In addition, although treatment with anti-PD-1 antibody caused a greater increase in these CD8+ T cells, particularly activated CD8+ T cells (CD8+PD-1+ T cells), than in untreated controls, the treatment did not reduce the number or size of tumors in NASH-related HCC [1].