Miracle-dz/UniFAR-FTUs huggingface dataset:
Risk reporting quality: implications of academic research for financial reporting policy

In this paper, I survey empirical research on the relevance of firms’ financial report information for the evaluation of their risk. I recommend that financial reporting policymakers require or encourage firms to enhance their risk reporting quality in four ways. First, firms should report comprehensive income statements that: (1) use fair value or a similarly information-rich accounting measurement attribute and (2) separate the components of comprehensive income that are primarily driven by variation in cash flows from those that are primarily driven by variation in costs of capital. Such comprehensive income statements would provide users of financial reports with the flexibility to calculate alternative summary accounting numbers and to perform different types of risk assessment analyses. Second, firms should conduct and disclose the results of back-tests of prior significant accrual estimates, indicating any identified trends in and drivers of revisions to those estimates, and describing the effects of those revisions on current or future summary accounting numbers. Third, firms should aggregate and present risk disclosures in tabular or other well-structured formats that promote the usability of the information. Identifying existing best disclosure practices and encouraging new best practices are the most natural way to do this. Fourth, for model-dependent risk disclosures, firms should disclose the primary historical and forward-looking attributes of the models and their implementation in practice, sensitivity of the model outputs, and benchmarking of the models to standard portfolios of exposures.
Estimating the Actual Relocation of Dutch People Based on ‘Wish to Move’ Messages on Twitter

Currently the ‘wish to move’ to another house of the Dutch people is measured through the WoON survey conducted every three years. A more frequent way of measuring is wished for to improve policy making in housing. Nowadays, people express their ‘wish to move’ on social media. In this research, it was found that certain features derived from tweet texts distinguish ‘wish to move’ tweets from others. The best logistic regression classifier developed in this research achieves an F1-score of 0.556 in identifying ‘wish to move’ tweets indicating that it is possible to timely keep track of the proportion of the ‘wish to move’ proportion of the Dutch population active on Twitter. Further, it is found that actual relocation can be identified by following ‘wish to move’ users. By engineering features through aggregating their subsequent tweets, classifiers were established to automatically determine if a ‘wish to move’ user relocated in the follow-up period. The best logistic regression classifier can determine if ‘wish to move’ users relocated in the two subsequent years with an F1-score of 0.701. With it, the proportion of ‘wish to move’ users who actually relocated later can be estimated.
Relationship Between Corporate Governance And Organizational Performance: Nigerian Listed Organizations Experience

This study examined the relationship between three corporate governance mechanisms ( Board independence, board size, and chief executive duality) and two organization performance measures ( earnings per share and return to equity) of Nigerian listed organizations.The data used for this study were derived from the audited finance statements of the firms listed on the Nigerian Stock Exchange (NSE) between 2005 – 2010 which comprises of fifteen (15) manufacturing firms and fifteen (15) financial and service institutions respectively as sample size. Panel data methodology was adopted because it combined time series and cross sectional data. The method of analysis is that of multiple regressions and the method of estimation is Ordinary Least Squares (OLS). The result showed that there is positive significant relationship between board independence and organizational performance while board size and chief executive duality have negative significant relationship with organizational performance. It is recommended that the office of chairman and chief executive officer should be occupied by different person in order to enhance check and balance also Small size boards and board independence should be put in place.
Hydrolyses of meat and soybean proteins using crude bromelain to produce halal peptone as a complex nitrogen source for the growth of lactic acid bacteria

The aim of the present work was to study the effect of temperature and time on the hydrolysis of meat and soybean proteins by crude bromelain to produce halal protein hydrolysates as nitrogen source for the growth of lactic acid bacteria. Crude bromelain was extracted from pineapple without any further purification. The hydrolysis of meat and soybean proteins by crude bromelain were carried out at various incubation temperature (30°C, 40°C, 50°C) and time (1, 2, 3 h). The degree of hydrolysis and soluble nitrogen contents of the protein hydrolysate were then measured. Incubation temperature at 50°C yielded the highest degree of hydrolysis for both protein samples. The degree of meat protein hydrolysis significantly increased to 75.30% during the first hour, and reached to more than 95% after three hours with soluble nitrogen content of 201.32 mg/100 mL. Similar profile was also observed in the soybean protein which yielded 85.14% protein hydrolysate with soluble nitrogen content of 260 mg/100 mL. The meat and soybean protein hydrolysates obtained were used as nitrogen sources in media containing sucrose, young coconut water, mung-bean sprout extract and tomato extract for the growth of Lactobacillus plantarum Dad 13. The performance of these media for cellular growth was almost as good as the performance of commercial MRS growth medium.
MPPT & Solar Photovoltaic (PV) Incremental Conductance Algorithm Maximum Power Point (MPP) Electrical Power Thermal Energy using DSP

A maximum power point tracking (MPPT) scheme is obligatory to ameliorate the efficiency of a solar photovoltaic (PV) panel. This paper proposes an ameliorated incremental conductance algorithm (InC) for tracking the maximum power point (MPP) of a solar PV panel. Solar PV cells have a non-linear V-I characteristic with a distinct MPP which depends on environmental factors such as temperature and irradiation. Solar energy systems have emerged as a viable source of renewable energy over the past two or three decades, and are now widely utilized for a variety of industrial and domestic applications. Such systems are predicated on a solar collector, designed to amass the sun’s energy and to convert it into either electrical power or thermal energy. In general, the puissance developed in such applications depends fundamentally upon the amount of solar energy captured by the collector, and thus the quandary of developing tracking schemes capable of following the trajectory of the sun throughout the course of the day on a year. The obtained simulation results are compared with MPPs achieved utilizing the conventional InC algorithm under sundry atmospheric conditions. The results show that the ameliorated InC algorithm is better than the conventional InC algorithms for tracking MPPs of solar PV panels. Adscititiously, it is simple and can be facilely implemented in digital signal processor (DSP).
Data analysis of (non-)metric (dis-)similarities at linear costs

The analysis of large datasets is often based on domain specific dissimilarity measures. Such measures can be found for example in the life-sciences but also in fields like web mining or social networks. These measures can generate similarities or dissimilarities and may be metric or non-metric, often without an explicite vector space. Metric similarity data are easily processed by kernel methods, whereas for dissimilarity data only few specific methods are available or costly transformations are needed to obtain a valid kernel matrix. If the data additionally are non-euclidean further corrections are needed and it is argued that transformations to a kernel space, are not only costly but further can lead to information loss. We consider the linear processing of metric similarity and dissimilarity data and show procedures to do data analysis with linear costs for both types of data. Machine Learning Reports http://www.techfak. uni-bielefeld.de/∼fschleif/mlr/mlr.html Data analysis of (non-)metric (dis-)similarities at linear costs
Assessing the Potential Impact of a Nationwide Class-Based Affirmative Action System

We examine the possible consequences of a change in law school admissions in the United States from an affirmative action system based on race to one based on socioeconomic class. Using data from the 1991-1996 Law School Admission Council Bar Passage Study, students were reassigned attendance by simulation to law school tiers by transferring the affirmative action advantage for black students to students from low socioeconomic backgrounds. The hypothetical academic outcomes for the students were then multiply-imputed to quantify the uncertainty of the resulting estimates. The analysis predicts dramatic decreases in the numbers of black students in top law school tiers, suggesting that class-based affirmative action is insufficient to maintain racial diversity in prestigious law schools. Furthermore, there appear to be no statistically significant changes in the graduation and bar passage rates of students in any demographic group. The results thus provide evidence that, other than increasing their representation in upper tiers, current affirmative action policies relative to a socioeconomic-based system neither substantially help nor harm minority academic outcomes, contradicting the predictions of the "mismatch" hypothesis, which asserts otherwise.
HIGH ORDER SLIDING MODE AND ITS APPLICATION ON THE TRACKING CONTROL OF PIEZOELECTRIC SYSTEMS

Aiming at a kind of piezoelectric actuator (PEA) with hysteresis nonlinearity, a new high order sliding mode controller (HOSMC) is presented. Firstly, the two-order nonlinear dynamic model of the PEA is introduced and the hysteresis nonlinearity part is analyzed as a kind of bounded disturbance acting on the system. Then, the high order sliding mode control law is designed. Further, the finite-time astringencies of the sliding mode variables and the asymptotic astringency of tracking error variable are proved theoretically. The simulation results show the validity of the HOSMC for this kind of piezoelectric actuators with hysteresis nonlinearity.
Metabolic Explosion in Yeast Glycolysis

To study metabolism in biology, budding yeast (S. cerevisiae) is often chosen as the subject of study. As such a model organism, its metabolic network is known in more detail than any other unicellular eukaryote. Therefore it is possible to model the dynamics of its metabolism rather precisely. A speci c mutant of this species is known in some cases to fail to grow when glucose is abundantly present. Measurements then show that in the cell cytoplasm concentrations of intermediate metabolites, such as fructose-1,6-biphosphate, rise and keep rising beyond healthy levels yielding impeded growth and even death. This is called metabolic explosion. Recently, Hulshof, Planqué, Bruggeman and Teusink [1] introduced a novel opproach to the analysis of a well known simple toy model, `the Old Lady', that allowed to study its bifurcation behaviour in more detail. It is founded on smart monotonicity arguments to derive properties of implicitly de ned functions to get at existence of (non-trivial) steady states. They were able to draw conclusions on the stability of these steady states too. In this thesis a new model is presented for the pathway of glycolysis. It is introduced as an extention of the Old Lady and is meant to bridge the gap in complexity between this toy model, favored in mathematics [1] and a descriptive model favored in biology [2], such that the model is more descriptive than the Old Lady, but the mathematical framework used for the toy model is still applicable. Some general theory of Metabolic Network Analysis is considered. The existence of trivial and non-trivial steady states is described, where the general theory is shown to be applicable. This is then formulated in a general proposition which can help to show existence also in larger models. The mathematical framework to describe metabolic explosion, as introduced in [1], is formulated for the new model. Existence of steady states proves to be a subtle exercise in mathematics as the ve metabolite concentrations that are considered, in steady state, are implicit solutions to non-linear equations. The stability analysis is done only for the trivial steady states as computing eigenvalues of the Jacobian showed no meaningful results for the non-trivial steady states. This work will be continued in a follow up PhD project in the group of Joost Hulshof at the University Amsterdam (VU).
INTER-REGIONAL MIGRATION IN CZ AND SK: THE EMPIRICAL STUDY OF PANEL DATA AT NUTS3 LEVEL

The aim of this paper is to define the relationship between migration, income, and unemployment rates, and therefore estimate these relationships using vector autoregression and the Granger causality test. This study focused on inter-regional migration at NUTS3 level in the Czech and Slovak Republics. The analysed period is from the year 2004 to 2013, and the final panel data is set for one variable, and therefore contains a total of 220 observations. According to the results, the regional migration in the Czech and Slovak Republics was determined by income differences and it is in accordance with the neoclassical theory. The causal relation was not confirmed for differences in unemployment rate. The changes of income and unemployment rates in the Czech Republic and Slovakia were not caused by migration. These results do not support conclusions of the neoclassical model of migration.
Giant reed (Arundo donax L.): A weed plant or a promising energy crop?

Giant reed (Arundo donax) is a perennial rhizomatous grass which is widely diffused in subtropical and warm temperate regions. From its native area, probably Eastern Asia, it has been dispersed all over the world by humans who use it for multiple purposes such as roof thatching, reeds in woodwind instruments, fishing rods, etc. Its spontaneous and rapid growth allows A. donax to be considered as an invasive weed. But more recently, due to its high biomass production and great adaptability to marginal land, it is being seen as one of the most promising energy crops for lignocellulosic bioethanol production. A. donax is a sterile plant because it is a hybrid with uneven ploidy or triploid specie. Therefore, its propagation is strictly agamic by rhizome fragmentation and sprouting from cane nodes. The lack of sexual reproduction is a negative characteristic when we consider A. donax as an energy crop, since it makes genetic improvement difficult, and this is further limited by the absence of genome sequence information and the lack of specific molecular tools. In this review we will summarize and discuss recent data on A. donax, specifically its origins, genetics and possible utilization as a source of biomass. Key words: Arundo donax, vegetative propagation, polyploidy, energy crop, biomass, ethanol fermentation.
A FRAMEWORK FOR PROMOTING DIALOGUE ON PARAMETERIZING A HARVEST CONTROL RULE WITH LIMIT AND TARGET REFERENCE POINTS FOR NORTH ATLANTIC ALBACORE

,SUMMARY A framework for promoting dialogue between SCRS and the Commission is proposed for advancing the application of a Harvest Control Rules consistent with the Commission’s decision making framework for development and application of conservation and management measures. A provisional example is provided for northern Albacore, although the methods could be more broadly applied across the range of stocks for which quantitative stock assessments have been conducted and Kobe 2 Strategy matrices provided. RESUME
Serie speciale in collaborazione con HERMES

The aim of this paper is to account for the impact of statistical noise and exogenous regulatory and environmental factors on the efficiency of public transit systems in a DEA-based framework. To this end, we implement a three-stage DEA-SFA mixed approach based on Fried et al. (2002) using a 1993-1999 panel of 42 Italian public transit companies. This allows us to decompose input-specific DEA inefficiency measures into three components: exogenous effects, pure managerial inefficiency, and statistical noise. First, the initial evaluation of producer performance is carried out using conventional variable returns to scale DEA (Banker et al., 1984). Second, a SFA approach (Battese and Coelli, 1992) is used to regress single input slacks on subsidies regulation (cost-plus versus fixed-price contracts) and a set of environmental variables including network speed and user density. Finally, third stage re-runs DEA on inputs purged of both exogenous effects and statistical noise. Results are such that adjusting for the type of regulatory scheme, environmental conditions, and statistical noise increases average efficiency in the industry and reduces dispersion among firms. Furthermore, the implementation of fixedprice subsidies is found to enhance efficiency in the usage of “drivers” and “materials and services” inputs. Such a result sheds some light on the determinants of input-specific efficiency differentials in the industry, improving the existing evidence on mean overall cost efficiency (e.g. Gagnepain e Ivaldi, 2002; Piacenza, 2006). As a policy implication, it is confirmed the relevance of regula tion aimed at replacing cost-plus subsidization mechanisms with high-powered incentive contracts as well as improving operating conditions of public transport networks.
Model-independent approaches for the XFEM in fracture mechanics

Applications of the XFEM to fracture mechanics involve enriching the regions near the crack-tips. The accuracy of such approximations largely depends upon these crack-tip enrichment functions. Such functions are based on the asymptotic fields in the near-tip region for the fracture model considered. Consequently, for each fracture model, a different set of enrichment functions is required. Herein, two model-independent approaches are presented that can be used independent of the fracture model considered. In the first approach, a set of crack-tip enrichment functions is proposed that is able to capture arbitrary high gradients at the crack-tip. A second approach is based on an adaptive mesh refinement in the near-tip region and the treatment of hanging nodes in combination with the step enrichment is of concern. Examples show the effectiveness of the proposed methods for brittle and cohesive cracks. Copyright c © 2010 John Wiley & Sons, Ltd.
Intestinal Transplantation

Intestinal transplantation (ITx) has evolved in the past few decades moving from an experimental procedure to a life-changing modality for patients suffering from intestinal failure (IF). It is particularly for those with complications as a consequence of parenteral nutrition and/or who have a high risk of dying due to their underlying disease. In addition to this, intestinal transplantation is also increasingly considered for the treatment of conventionally unresectable abdominal tumors. With advancements in immunosuppressive drugs, induction regimens, standardization of surgical techniques and improved postoperative care, survival is increasing. The ultimate goal for intestinal transplantation would be to become as good and safe as total parenteral nutrition (TPN) and as such, it could become a viable first-line option of intestinal failure.
Automatic Detection of Elephant flows through Openflow-based OpenvSwitch

Software Defined Networking (SDN) has proved its importance as it allows users to create a Virtual network with just a few lines of code. It provides a vision of the network with the control plane separated from the data plane and is managed centrally. It also enables easy integration of new functionalities. While SDN is rapidly spreading through the network industry, it still faces issues with managing, monitoring, and controlling the network centrally. One of the major issues faced is the monitoring of the traffic flowing in the network. As there is rapid growth in data, there is an increase in data flow in the network every day. This leads to traffic congestion, and monitoring the traffic is a challenging task. The traffic can be caused due to several reasons, and one of the major reasons is due to large flows. These large flows are known as Elephant flows. This paper proposes an algorithm to detect the elephant flows in an Openflow network automatically. This algorithm sets a predefined bandwidth for the flow, and if the bandwidth exceeds the limit, the flows are automatically captured and presented in the form of a graph. This project involves Open Flow controller, OpenvSwitch and Open Flow protocol. In SDN, Open Flow provides additional features to help in monitoring the traffic. Previously, a lot of efforts have been made in this field to improve the quality of the network. The prime focus in this project is to collect the flow details and detect the elephant flows in the network automatically. The analysis and the enhancements carried out in this project have proved to be a better detector of the elephant flows in the network.
Biogenic methanol and its impacts on tropospheric oxidants

We use a global chemical transport model (MOZART‐2) to estimate the effects of surface emissions of methanol on tropospheric oxidants. The importance of methanol in tropospheric chemistry is two fold. First, methanol has a relatively large surface emission with an estimated global emission of 70 to 350 Tg methanol/year. The estimated methanol flux is comparable to other major hydrocarbon surface emissions such as isoprene and total monoterpenes, but the chemical lifetime of methanol is several days (in the boundary layer) to a few weeks (in the upper troposphere), which is much longer than the chemical lifetime of isoprene or monoterpenes (For example, the chemical lifetime of isoprene is about 2 hours). With a surface emission of 104 to 312 Tg methanol/year (encompasses estimated uncertainty in methanol emissions), the calculation shows that on average, the inclusion of methanol emission produces approximately 1–2% increase in O3, 1–3% decrease in OH, 3–5% increase in HO2, and 3–9% increase in CH2O globally. The maximum perturbation to the oxidants occurs in the tropical upper troposphere. However, the uncertainty associated with current methanol emission estimates produces significantly different model predictions of tropospheric oxidant distributions.