Miracle-dz/UniFAR-FTUs huggingface dataset:
Legal Systems, Capital Structure, and Debt Maturity in Developing Countries

Manuscript type. Empirical. Research Question/Issue. This paper analyzes the importance of two aspects of the legal system in shaping firm leverage and debt maturity structure across developing countries. Research Findings/Insights. Using a larger number of developing countries compared to prior research, four main findings are obtained. First, whereas corruption increases firm debt financing, its effect is moderated when considering the impact of stronger laws. Second, the common versus civil law distinction does matter for firm financing in developing countries, but in the opposite direction documented for developed countries. Third, less corruption combined with stronger laws increases reliance on long‐term debt. Finally, by listing on a developed exchange abroad, firms in developing countries are able to raise equity and extend the maturity of their debt.Theoretical/Academic Implications. The findings on the relative importance of the legal system for firm financing decisions in developing countries do not necessarily agree with prior findings for developed countries. Future research focusing exclusively on developing countries may be warranted to better understand the drivers of private sector‐led growth in these economies. Practitioner/Policy Implications. This study reinforces the importance of strengthening public governance and laws as well as deepening capital markets in developing countries to improve financing conditions.
Development of the DLR TAU code for modelling of control surfaces

The simulation of movable control surfaces is of interest for many applications in aerospace engineering, but it is challenging to perform high-fidelity computations considering them. Generating a new mesh for each deflection angle is computationally expensive, so alternative approaches that allow using only one mesh have been developed in the recent years. This work gives an overview of the available methods for modelling of control surfaces, with special focus on the ones that consider the spanwise gaps between the wing and the control surface. This includes the usage of the Chimera technique combined with mesh deformation as well as a sliding interfaces boundary condition. Their performance has been tested with the DLR MULDICON configuration.
Semantics-Driven Aspect-Based Sentiment Analysis

markdownabstractPeople using the Web are constantly invited to share their opinions and preferences with the rest of the world, which has led to an explosion of opinionated blogs, reviews of products and services, and comments on virtually everything. This type of web-based content is increasingly recognized as a source of data that has added value for multiple application domains. While the large number of available reviews almost ensures that all relevant parts of the entity under review are properly covered, manually reading each and every review is not feasible. Aspect-based sentiment analysis aims to solve this issue, as it is concerned with the development of algorithms that can automatically extract fine-grained sentiment information from a set of reviews, computing a separate sentiment value for the various aspects of the product or service being reviewed. This dissertation focuses on which discriminants are useful when performing aspect-based sentiment analysis. What signals for sentiment can be extracted from the text itself and what is the effect of using extra-textual discriminants? We find that using semantic lexicons or ontologies, can greatly improve the quality of aspect-based sentiment analysis, especially with limited training data. Additionally, due to semantics driving the analysis, the algorithm is less of a black box and results are easier to explain.
Implementing and evaluating a Self-Stabilizing Software Defined Network Control Plane

Software Defined Networking (SDN) provides an attractive alternative to traditional, manual, error prone networks. SDN provides the opportunity to add programmability to networks, and decouple the control plane from the data plane. By doing so, a network administrator may control an entire network from a single SDN controller. While the work in this field is extensive, the question of how to maintain the connection between the control plane and the data plane has not received much attention. There is an algorithm called Renaissance that approaches the problem by utilizing self-stabilization, which is a strong notion of fault-tolerance for distributed systems. However, only a proof-of-concept implementation has been created for Renaissance this far. This report presents a prototype of the self-stabilizing SDN control plane algorithm that is implemented using the Floodlight controller. In addition we present an evaluation of the prototype. The evaluation shows that the prototype is fault-tolerant and able to recover from transient faults, which means that it is self-stabilizing. The stabilization time is shown to depend mostly on the degree of a network, but also on the number of nodes. Lastly, we present a proof-of-concept implementation using the ONOS controller.
Efficient Synchronization for GPGPU

High-performance General Purpose Graphics processing units (GPGPUs) have exposed bottlenecks in synchronizations of threads and cores. The massively parallel computing cores and complex hierarchies of threads present new challenges for synchronizations at different granularities. Performance of GPU is hindered by inefficient global and local synchronizations. I propose hardware-software cooperative frameworks for efficient synchronization of GPGPU to address the following issues. To provide efficient global synchronization (Gsync), an API with direct hardware support is proposed. The GPU cores are synchronized by an on-chip Gsync controller. Partial context switch is employed to guarantee deadlock-free execution. The proposed Gsync avoids expensive API calls and alleviates data thrashing. Prioritized warp scheduling is used to increase the overlap of context switch with kernel execution. To efficiently exploit the inherent parallelism of producer-consumer problems, a flexible wait-signal scheme is proposed at thread-block level. I propose dedicated APIs to express fine-grained static and dynamic dependencies with hardware support. The proposed scheme can accelerate wavefront, graph and machine learning applications. The architectural design of on-chip wait-signal controller eliminates busy wait loop and long-latency memory operations. I also propose thread block dispatch scheduling to address the problem of load imbalance and large context switch overhead. To reduce stall due to synchronizations, a synchronization-aware warp scheduling is proposed to coordinate multiple warp schedulers upon synchronization events. Both performance and hardware utilization are improved by resolving the barrier sooner.
Researches on Risk Evaluation Green Agro-products Closed Supply Chain

Based on the research results of the current literatures on supply chain risk and agro-product supply chain,related subjects of the agro-product closed supply chain involving production,management and consumption are studied and analyzed and the primary risking factors in the supply chain system are classified into environmental risk,system risk,information risk,management risk and quality risk.Risk of agro-product closed supply chain is evaluated by using the method of fuzzy comprehensive evaluation and the values are acquired.The result shows that risk of agro-product closed supply chain is moderate with relatively high risk,which basically accords with the present actual situations.It can be seen from the index weights of various levels that the key first-level indices influencing the risks are system risk,information risk,quality and safety risk and the key second-level are the coordinating and controlling ability of core enterprises,the implement of information traceability and the construction of quality safety system.Therefore,risk of agro-product closed supply chain should be reduced by taking prevention and controlling measures mainly from these aspects.
Understanding the Effect of Task Complexity and Problem-Solving Skills on the Design Performance of Agents in Systems Engineering

Systems engineering processes coordinate the efforts of many individuals to design a complex system. However, the goals of the involved individuals do not necessarily align with the system-level goals. Everyone, including managers, systems engineers, subsystem engineers, component designers, and contractors, is self-interested. It is not currently understood how this discrepancy between organizational and personal goals affects the outcome of complex systems engineering processes. To answer this question, we need a systems engineering theory that accounts for human behavior. Such a theory can be ideally expressed as a dynamic hierarchical network game of incomplete information. The nodes of this network represent individual agents and the edges the transfer of information and incentives. All agents decide independently on how much effort they should devote to a delegated task by maximizing their expected utility; the expectation is over their beliefs about the actions of all other individuals and the moves of nature. An essential component of such a model is the quality function, defined as the map between an agent’s effort and the quality of their job outcome. In the economics literature, the quality function is assumed to be a linear function of effort with additive Gaussian noise. This simplistic assumption ignores two critical factors relevant to systems engineering: (1) the complexity of the design task, and (2) the problem-solving skills of the agent. Systems engineers establish their beliefs about these two factors through years of job experience. In this paper, we encode these beliefs in clear mathematical statements about the form of the quality function. Our approach proceeds in two steps: (1) we construct a generative stochastic model of the delegated task, and (2) we develop a reduced order representation suitable for use in a more extensive game-theoretic model of a systems engineering process. Focusing on the early design stages of a systems engineering process, we model the design task as a function maximization problem and, thus, we associate the systems engineer’s beliefs about the complexity of the task with their beliefs about the complexity of the function being maximized. Furthermore, we associate an agent’s problem solving-skills with the strategy they use to solve the underlying function maximization problem. We identify two agent types: “naïve” (follows a random search strategy) and “skillful” (follows a Bayesian global optimization strategy). Through an extensive simulation study, we show that the assumption of the linear quality function is only valid for small effort levels. In general, the quality function is an increasing, concave function with derivative and curvature that depend on the problem complexity and agent’s skills.
SVEUČILIŠTE U ZAGREBU FAKULTET PROMETNIH ZNANOSTI

The transportation system is an important economic factor in every country. Today is very important to have well developed transportation system because the place of sales is further from place of manufacture what is increasing transportation costs. There is a solution seen in the form of intermodal transportation because of its economic and environmental benefits but also because of "door to door" service. The needs for the development of intermodal transport are aware of in the European Union and therefore carry out transportation policy, which allows the development of intermodal transport. Although, most of the intermodal transport is done by sea and rail, road transport still takes a large part of traffic and because of that EU implements a variety of measures to shift traffic to other branches. In Croatia, most of the traffic is conducted by road,although in recent years intermodal transportation started to develop which is clearly emerging as a better and cheaper solution than conventional modes of transportation. KEWORDS: intermodal transportation, transportation policy, transport shifting
METHOD OF THE MULTITONAL SIGNAL CONSTRUCTION IN DECISION SUPPORT SYSTEMS ACS

Subject: The article deals with the issues of creation of a psychoacoustic model of perception of sound quality of sound signals, the development on its basis of the method of creating a multi-tonal signal, which provides a high correlation with subjective evaluation. Purpose: to develop a multitoon signal creation method. Objective: To analyze the distortion of the sound signals that arise during reproducing them on the sound reproduction devices. Classify these distortions and assess the extent of their impact on subjective assessment. Allocate the most significant of them in terms of impact on the quality of sound. Investigate modern methods for assessing the quality of reproduction of sound signals, standards and recommendations devoted to this task; to evaluate the effectiveness of modeling the human auditory system used in the development of these methods; formulate the scientific and applied requirements for developing objective quality assessment method. Conclusions: The application of the developed method will allow obtain results that coincide with the data of subjective and statistical examinations (SSE) with the accuracy required for practice.
Model reduction of network systems with structure preservation : Graph clustering and balanced truncation

A framework of complex networks can adequately describe a wide class of complex systems composing of many interacting subsystems. A large number of subsystems and their high-dimensional dynamics often result in the high complexity of a network system, which poses intense challenges to system management and operation. The main motivation of this research is to establish suitable model reduction techniques that generate simplified models to capture the essential features of the complex network systems. Two approaches are developed in this thesis to reduce the complexity of a network system with structure preservation. The first one is based on graph clustering, which aims to partition a network into several nonoverlapping clusters and merges all the vertices in each cluster into a single vertex. A reduced-order model is then formulated via the framework of the Petrov-Galerkin projection. This thesis discusses the applications of the clustering-based model reduction methods for second-order networks, controlled power networks, multi-agent systems and directed networks in Part I. The second approach in Part II extends the balanced truncation method for control systems to the simplification of dynamical networks. For networked linear passive systems, the proposed method reduces interconnection structures of a network and the dynamics of each subsystem via a unified framework. Additionally, an approach is developed for the reduction of nonlinear Lur’e networks, showing that the dimension of each nonlinear subsystem can be reduced while preserving the robust synchronization property of the overall network.
Telecom Customer Churn Prediction Model Based on Improved SVM

With development of reform and fiercer competition in telecom industry,the customer churn rate is increasing now.How to predict and reduce customer churn effectively influences the existence and development of telecom corporations directly.Churning customers only absorb the small portion of the total customers.Thus,obvious unbalanced data problem exists in the data set of telecom customer.But,traditional customers churn prediction model dealt churn prediction as a common pattern recognition problem,and built the prediction model based on pervasive machine learning.It is of vital importance when the misclassification costs of two errors are great deal of difference.This paper brings forward the cost-sensitive learning theory,and builds a telecom customer churn prediction model based on cost-sensitive SVM.It brings different misclassification costs into modeling process and improves the prediction performance effectively.
Competition and Quality Choice in Hospital Markets

While hospital quality is typically measured using clinical outcomes, patients are likely to also value non-clinical attributes such as hospital amenities. As a result, using clinical outcome measures to evaluate whether competition policy effectively encourages higher hospital quality will not provide a complete picture if hospitals compete along non-clinical dimensions. We examine the causal impact of competition on both a hospital’s level of demand-shifting quality and clinical quality. We find that demand-shifting quality is increased for all patients when competing for managed care patients while the impact of competition for Medicare patients is mixed. Clinical quality also improves with competition for managed care patients but declines with competition for Medicare patients. Competition appears to affect clinical quality through the selective networking practices of managed care while direct competition for patients largely affects other non-clinical quality attributes.
Planning the nation's health workforce: let the market in.

For most of this century, public policymakers have been concerned over the supply of health workers? notably over the supply of physi? cians and nurses. At virtually every turn, ei? ther the prevailing or the projected workforce was thought to deviate from the "proper" supply.1 Prior to World War II, for example, policy? makers fretted over an imagined surplus of physicians. In the early post-war years, until about the mid-1970s, commission after com? mission projected an impending shortage of physicians. The response of public policy at both the federal and state levels was to double the capacity of American medical schools and to open the gates wide for foreign-trained phy? sicians. There has been similar concern over
UK Mutual Fund Performance Persistence with Active Peer Benchmarks

We assess UK mutual fund performance from a perspective of a peer-group, applying a novel approach suggested in Hunter et al. (2014). Our sample comprises of 817 UK long-only active equity mutual funds allocated to nine Morningstar style category peer-groups in the period 1992-2016. Overall, we find that those funds with most significant positive peer-group adjusted alphas continue to perform well one-year-ahead, using both parametric and non-parametric measures of persistence in performance. Further, a small increase in significance of peer-group adjusted alphas significantly improves the probability that a fund will be placed in the top quartile in the following period. Finally, we document that persistence in performance is driven by both winner and loser funds. The results within each peer group by and large conform to these findings.
An Empirically Derived Conceptual Framework to Assess Dis-Adoption of Conservation Agriculture: Multiple Drivers and Institutional Deficiencies

Efforts of national governments and international agencies aimed at alleviating hunger and poverty are often undermined by lack of long-term adoption of agricultural innovations. Studies commonly explain farmers’ adoption decisions using household general determinants, yet decision-making, particularly for under-resourced smallholder farmers in sub-Saharan Africa, is a complex process. Using the case of conservation agriculture [CA], this article analyses dis-adoption of agricultural technologies by examining multiple domains of Malawi’s CA innovation system and how these influence farmer decision-making. It analyses institutional arrangements of CA promoters, national policies and farmers’ experiences. From this, we empirically derive a multifaceted dis-adoption drivers’ framework to explain CA dis-adoption in smallholder farming systems. Our findings reveal that adverse features in national policies, institutional arrangements, technological attributes and social cultural dimensions all lead to unfavourable experiences of CA for smallholder farmers, which can culminate in dis-adoption. The CA dis-adoption drivers’ framework we develop in this study provides a useful troubleshooting tool. It can be used to guide improvements in the design and implementation of project-based interventions seeking long-term adoption of agricultural innovations across sub-Saharan Africa.
The Moderating Role of External Environment on the Relationship Between Resource Isolating Mechanism and Sustainable Competitive Advantage

Dynamic changes in the firm’s external environment influence the future direction of the firm. The operations of the firm are affected by the striking advances in globalization such as shifts in technology, stiff competition among business entities and new entrances within an industry. The firms including commercial banks in Kenya should therefore, have the ability to predict future trends in the external environment for survival. The main purpose of this study was to establish the moderating role of external environment on the relationship between resource isolating mechanism and sustain competitive advantage among commercial banks in Kenya. Descriptive and explanatory research design was employed in the study. The research targeted all the commercial banks in Kenya. Purposive sampling was used to select a sample of 160 respondents from the key departments of Finance, Sales and Marketing, Strategy and Operations of all the forty (40) commercial banks’ headquarters in Nairobi, Kenya. The data collection instrument used was semi-structured questionnaire. The variable characteristics were summarized using descriptive statistics. Agreement to the most frequent responses to the statements on the study variables ranged between moderate and high extent. Based on results of hypotheses testing, external environment have no moderating effect on the relationship between resource isolating mechanism and sustainable competitive advantage.
The influence of a human resource strategy to the function of human resource processes in small and medium-sized enterprises (SMEs)

The human resources management strategy is currently considered one of the most important elements of a corporate strategy, mainly because its main goal is to work with people as the most important capital of each organization. Without people, the organization is unable to meet its goals. A well-prepared HR strategy and an action plan for its implementation enables an organization to effectively plan and manage individual processes to support the organization's goals and to respond flexibly to any change. The paper deals with a sub-research of the management of small and medium-sized enterprises in the Czech Republic. It is focused on the use of HR strategy in SMEs management and the assessment of the significance of HR process. Data were gathered as questionnaires and interviews from 290 enterprises operating in the Czech Republic. The research was done in 2016. Unfortunately, the HR strategy is defined by 2/5 of small and medium-sized enterprises in the Czech Republic. Based on statistics analysis, the authors proved a weak relation between HR strategy and the function of human
Towards paradigm shift in public sector innovation

Societal challenges, together with decreasing public finance, require a new approach to public administration practices. This study is focused on citizen co-creation in the context of public sector innovation. The aim of the study is to find out how could citizens be bettter engaged in designing of public services and what does that require from the public sector innovation process. The paper argues that service design and current public sector innovation have a similar ethos. Service design approach can be utilised to include citizens in public sector innovation process. This makes service design as a practical tool in public sector innovation process. The research data was collected during the three case studies of the WeLive project that applied service design involving the citizens in the development of digital public services. The findings indicate that service design can contribute to the empowerment and sustainable development of the citizendriven service innovation in public sector.