Miracle-dz/UniFAR-FTUs huggingface dataset:
Determinants of Export Behaviour of German Business Services Companies

The determinants of export behaviour at firm level have been widely investigated for manufacturing companies. By contrast, what has remained largely neglected is a detailed investigation in the service sector. As aggregate statistics show, international trade in services has grown significantly over the last few years. However, it is unclear why some companies export and others do not. This paper presents some initial results about the German business services sector at firm level. Using a unique panel dataset of enterprises from the business services sector (transport, storage and communication, real estate, renting and business activities) for the years 2003 to 2005, we analysed the impact of several firm-specific characteristics such as size, productivity, human capital, experience on the national market in Germany, etc. on the firms' export performance. Further, we used the pooled fractional probit estimator, recently introduced by Papke & Wooldridge, an approach that considers both the special nature of the export intensity variable and in addition unobserved time-invariant characteristics. When there is no control for fixed enterprise effects the overall results are in line with previous studies. When there is a control for unobserved heterogeneity, the positive effects of productivity and human capital disappear, indicating that these variables are not per se positively related to export performance, but rather to time-constant characteristics that are unobserved. Size and product diversification still have a positive and significant effect.
Molecular Mechanisms Underlying the Neuroprotective Effect of Hypothermia in Cerebral Ischemia

Cerebral ischemia is a serious dynamic event in the brain involving heterogeneous cell types. Neuroprotective agents represent a potential approach for the treatment of acute stroke. Presently, recombinant tissue plasminogen activator (rtPA) is the only drug that is approved for the management of acute ischaemic stroke, except for the antioxidant Edaravone in Japan (Yoshida et al., 2006). Although stroke patients can receive rtPA therapy within the initial 3 h therapeutic window, there is an increased risk of intracranial haemorrhage, disruption of the blood brain barrier, seizures, or the progression of neuronal damage (Laloux, 2001). Thus, there is a continued need to explore novel neuroprotective strategies for the management of ischemic stroke. A large number of therapeutic agents have been tested, including N-methyl-D-aspartate receptor antagonists, calcium channel blockers, and antioxidants, for the management of stroke, but none has provided significant neuroprotection in clinical trials (Green et al., 2003; Kidwell et al., 2001).
Development of Novel Low-Cost Quaternized Adsorbent from Palm Oil Agriculture Waste for Reactive Dye Removal

An attempt was made to chemically modify palm kernel shell (MPKS) to increase adsorption affinity towards Reactive Black 5 (RB5). Granulated palm kernel shell (PKS) was quaternized successfully by treating with N-(3-chloro-2-hydroxypropyl)trimethylammonium chloride under alkaline conditions and was characterized. Surface characterization by Scanning Electron Microscopy (SEM) and BET analysis confirmed the surface pore enlargement from mesospores to macropores after modification. Fourier Transform-Infrared (FTIR) Spectrometer and CHN analysis revealed that the quaternary ammonia group (NR4+) was successfully reacted on MPKS fiber. pH 4 is the optimum for removal of RB5 on MPKS. Equilibrium isotherms were analyzed by the Langmuir, Freundlich, and Redlich-Peterson models. The Redlich-Peterson model was found to fit well with the data. The maximum adsorption capacity of MPKS was 207.5 mg/g for adsorption of RB5.
IRPORMATION SEARCH AND THE EFFECTS OF FAILUREt A TEST OF COMPLEXITY THEORY 1

The effects of increasing failure and of individual differences in the complexity of conceptual structure on dyad decision-making teaaa were examined. A complex experimental simulation environment was used as the research method. It was found that simple subjects engaged in more delegated Information search them complex subjects, probably due to the influence of social desirability. No differences between simple and complex groups of subjects were found in self-initiated information search. This ' form of search increased with initial increasing (lover) failure levels, and remained fairly constant under higher failure levels. Two measures of integrative Information utilization were employed. The number of information search moves later utilized in integrative (strategic) decision making produced an inverted U-shaped curve with optimal levels under moderate failure conditions. Efficiency of information utilization showed a general decrease as failure increased. Complex groups of subjects exceeded simple groups on both measures of information utilization. The data produced only limited support for complexity theory, and did support, where applicable, the information search theory of Feather.
Modeling effluent heavy metal concentrations in a bioleaching process using an artificial neural network technique

Artifical neural networks practices were used to predict the recovery of heavy metals (Zn, Cu, Ni, Pb, Cd and Cr) from dewatered metal plating sludge (with no sulfide or sulfate compounds) using bioleaching process involving Acidithiobacillus ferrooxidans . The bioleaching process was operated as a completely mixed batch (CMB) reactor. The leaching performance data of the CMB reactor in terms of heavy metals was applied to a multi-layer perceptron (MLP) neural network technique for simulation. The performance of the reactor was evaluated with this robust model using the experimental data obtained under varying heavy metal concentrations in the sludge. Agitation time, pulp density of the sludge, and pH were used as inputs for the model, whereas the heavy metals (Cd, Cr, Cu, Ni, Pb, and Zn) concentrations were the output variables. The results of the models were compared using statistical criteria such as mean square error (MSE), mean absolute error (MAE), mean absolute relative error (MARE), and determination coefficient (R 2 ). The results show that the MLP neural network produced highly accurate estimation of the aforementioned metals with R2 over 97.9%. Key words : Bioleaching, heavy metals removal, artificial neural network, multi-layer perceptron.
Earnings Inequality and Welfare Spending: A Disaggregated Analysis

The welfare state is generally viewed as either providing redistribution from rich to poor or as providing publicly financed insurance. Both views are incomplete. Welfare policies provide both insurance and redistribution in varying amounts, depending on the design of the policy. The authors explore the political consequences of the mix of redistribution and insurance in the context of studying the impact of income inequality on expenditures in different categories of welfare spending in advanced industrial societies from 1980 to 1995. They find that spending on pensions, health care, family benefits, poverty alleviation and housing subsidies is largely uncorrelated with income inequality, but that spending on income replacement programs such as unemployment insurance, sickness pay, occupational illness and disability are significantly higher in countries with more egalitarian income distributions. They show that this pattern is exactly what a theory of political support for redistributive social insurance programs would predict.
Gene modification in mice Introduction

The 2007 Nobel Prize in physiology or medicine is awarded to Drs Mario R. Capecchi, Martin J. Evans and Oliver Smithies for their discoveries of principles for introducing specific gene modifications in mice by the use of embryonic stem cells. Their work has made it possible to modify specific genes in the germline of mammals and to raise offspring that carry and express the modified gene. The toolbox of experimental genetic methods developed by Capecchi, Evans and Smithies, commonly called the knockout technology, has permitted scientists to determine the role of specific genes in development, physiology, and pathology. It has revolutionized life science and plays a key role in the development of medical therapy.
Monogenean infestations of arowana (Osteoglossum bicirrhosum) and cat fish (Hypostomus plecostomus)

Arowana (Osteoglossum bicirrhosum) and cat fish (Hypostomus plecostomus) are two species of ornamental fishes which are mostly imported to Iran. Monogenea are plathyhelminthes which can dominantly infest the fish skin and gills with high host specificity. In this research, 35 O. bicirrhosum and 50 H. plecostomus with clinical signs were collected from different ornamental fish markets in Semnan, Iran and transferred alive to the Lab. Fish skin and gills were examined for monogenean infestations. No monogenea was observed on the skin specimens, but Gonocleithrum cursitans and Unilatus unilatus infested 54.28% and 74% of gills in O. bicirrhosum and H. plecostomus, respectively. This is the first report of both G.cursitans and U. unilatus in Iran.
Modelling the spatial distribution of agricultural land use at the regional scale

Agriculture is the most important land use in Europe in geographic terms and because of this it plays a central role in the quality of the wider environment. Whilst the spatial patterns of agricultural land use have changed considerably in recent times, further changes are likely as a result of the influences of policy reform, socio-economics and climate change. Understanding, therefore, how agricultural land use might respond to global environmental change drivers is a research question of considerable importance. The first step, however, in projecting potential future changes in agricultural land use is to be able to understand and represent in models both the socio-economic and physical processes that control current land use distributions. Thus, this paper presents an approach to modelling the spatial distribution of agricultural land use at the regional scale. The approach is based on the simulation of farm-scale decision making processes (based on optimisation) and the response of crops to their physical environment. Regional scale applications of the model are undertaken through the use of spatially-variable, geographic data sets (soils, climate and topography) combined with economic data. Examples of the application of the model are given for two regions of England: the north-west and east Anglia. These regions were selected to give examples of contrasting land use systems within the context of northern European agriculture. The model results are compared statistically with observed distributions of agricultural land use for the same regions in a quasi-validation exercise. The comparison suggests that the model is very good at representing land use that is aggregated at the regional level, and at representing general spatial trends in land use patterns. Some differences were observed, however, in land use densities between the modelled and observed data. The results suggest that the basic hypothesis of the model: that farmers are risk averse, profit maximisers, is a reasonable assumption for the regions studied. However, further study of decision making processes would be likely to improve our ability to model agricultural land use distributions. This includes, for example, the role of farmer attitudes to risk, differing views on future prices and profitability, and the effect of time lags in the decision process. © 2002 Elsevier Science B.V. All rights reserved.
Impact of non‐stationarity on hybrid ensemble filters: A study with a doubly stochastic advection‐diffusion‐decay model

Effects of non‐stationarity on the performance of hybrid ensemble filters is studied. (By hybrid filters we mean those which blend ensemble covariances with some other regularizing covariances.) To isolate effects of non‐stationarity from effects due to nonlinearity (and the non‐Gaussianity it causes), a new doubly stochastic advection‐diffusion‐decay model (DSADM) is proposed. The model is hierarchical: it is a linear stochastic partial differential equation whose coefficients are random fields defined through their own stochastic partial differential equations. DSADM generates conditionally Gaussian spatiotemporal random fields with a tunable degree of non‐stationarity in space and time. DSADM allows the use of the exact Kalman filter as a baseline benchmark.
Studying Methods of Estimating Heat Generation at Three Different Zones in Metal Cutting: A Review of Analytical models

The temperature rise during machining would severely affects the quality of work as well as tool life, if goes beyond a limit. Prior estimation and control of this temperature rise have always being a thrust area for machinists in adopting the optimum machining parameters. Though the temperature rise can be measured experimentally but reliable and time tested mathematical model(s) will serve the purpose in a better way. Mathematical model(s) is handy and economic as compared to experimental methods for set of machining parameters. A number of mathematical methods are developed, and the results have been compared with reality. In this paper efforts have been made to review and systemize the study of all such major analytical methods developed in past to identify the future scope of research. Further, a Comparative study of merits and demerits of experimental methods for measurement of temperature rise developed, in past is tabulated.
Staphylococcus aureus: resistance pattern and risk factors

Introduction: Methicillin resistant Staphylococcus aureus (MRSA) has emerged as a nosocomial pathogen of major worldwide importance and is an increasingly frequent cause of community-acquired infections. In this study, different risk factors and MRSA resistance pattern were investigated. Methods: In a 24 months period, all of the patients who were confined to bed in the surgery ward were included in the study. Then they were assessed to find out as if they had MRSA infection when hospitalized and once when they were discharged. Almost 48 h after admission, when patients were discharged, social and medical histories were acquired. Acquired samples were examined. Results: During the present study of 475 patients, 108 patients (22.8%) had S. aureus. About frequency of antibiotic resistance among collected S. aureus colonies, erythromycin resistance, was the most frequent antibiotic resistance, also resistance to vancomycin was 0.4% that was the least. Only hospitalization duration had statistically significant correlation with antibiotic resistance, also resistance to erythromycin had statistically significant relation with history of surgery and alcohol consumption. Of all 34 MRSA species, 22 (64.7%) samples were resistant to erythromycin, 17 (50.0%) resistant to cefoxitin, 5 (14.7%) resistant to mupirocin, 1 (2.9%) resistant to vancomycin and 1 (2.9%) resistant to linezolid. Conclusion: The results of the current study show that among hospitalized patients, there is resistance against methicillin. Since based on results of the study there is resistance against oxacillin and erythromycin in most cases, administering appropriate antibiotics have an important role in minimizing the resistance burden among bacterial species.
Effect of Dietary Energy and Protein on Performance, Egg Composition, Egg Solids, Egg Quality and Profits of Hy-Line W-36 Hens During Phase 2

A 4×3 factorial experiment with four added dietary energy (fat) levels (0.00 (0.00), 0.33 (16.7), 0.67 (33.5) and 1.00 (50.4) MJ ME/kg (g fat/kg)) and three protein levels (173.9, 166.5 and 160.7 g protein/kg) was conducted to determine the effect of dietary energy on performance, egg composition, egg solids, egg quality and profits of Hy-line W-36 hens at different protein levels. Hy-line W-36 hens (n = 1080) in Phase II (40 weeks of age) were randomly divided into 12 treatments (6 replicates of 15 birds per treatment) and fed the experimental diets for 12 wks. There was no significant interaction on all parameters between dietary energy and protein. Increasing protein had a significant effect on nutrient intake per g egg, percent albumen and yolk/albumen ratio, but had no effect on performance, egg solids, or egg quality. Hens had the capability to linearly decrease feed intake as dietary energy level increased so that the similar quantities of dietary energy (0.022 to 0.023 MJ/kg) was consumed to produce 1 g egg. Increasing dietary energy by the addition of poultry oil significantly improved nutrient (protein, lysine, or TSAA) utilization. As added dietary energy increased from 0.00 to 0.67 MJ/kg, feed intake linearly decreased and feed conversion linearly improved. However, a further increase of added dietary energy from 0.67 to 1.00 MJ/kg had no additional effect on feed intake and feed conversion. Based on feed intake and feed conversion, increasing 0.67 MJ/kg dietary energy by the addition of 33.5 g poultry oil/kg gave optimal performance in Hy-line W-36 hens from 40 to 51 wk of age. Because feed ingredient prices and egg price vary, there can be no fixed ideal dietary energy level for optimal profits during phase 2 (wk 40 to 51).
resort , Varna , April 2 – 6 , 2007 QUASI-STATIC MOTION OF THE CONTACT LINE IN THE WILHELMY-PLATE GEOMETRY : CONTACT LINE DISSIPATION MODEL

We study numerically the motion of contact lines in the context of a dip coating process: a vertical solid plate is withdrawn at constant velocity from a tank of liquid. We apply the contact line dissipation model to describe the quasi-static motion of the contact line. Our study is based on the approach suggested in de Ruijter et al. [3] which uses the standard mechanical description of dissipative system dynamics and which introduces a phenomenological dissipation term proportional to the contact line length. We obtain numerically the motion of the contact line and the dependence of its dynamics on the solid plate velocity in the case of a homogeneous solid plate. We find that the time dependence of the height of the contact line is well approximated by an exponential decay function. We show how one can obtain estimates for the friction coefficient from the experimental data. The numerically obtained data is compared to the experimental results in Delon G. et al. [8] and a very good agreement is found for velocities below the entrainment transition.
The Influence of Empathy in Mock Jury Criminal Cases: Adding to the Affect Control Model

Affect control theory proposes a relationship among emotion display, identity, and behavior. This study adds another variable to affect control theory by incorporating empathy into the affect control model. The inclusion of empathy emphasizes the importance of the observer's compassion on judgments regarding the actors. The influence of empathy is tested in the legal context through an experiment using undergraduate respondents' reactions as mock jurors to statements attributed to criminals and victims. Included in each statement are nonverbal cues of either a sad or relaxed emotion display. Path models show the significant relationships among emotion displays, empathy, and identity. The importance of empathy to affect control theory is discussed, in addition to the importance of empathy in understanding legal decision making.
Model-Driven Generation: From Models to MVC2 Web Applications

Transformation is one of the prominent features and the rising research area of MDA (Model Driven Architecture) since last few years. MDA is a new paradigm of software engineering that considers models as first-class entities. Indeed, techniques of model transformations may be implemented to automatically generate elements of the system from models. In this paper, we have conducted a new technique of model transformation to generate the code of web application. This technique is based on the combination of diagrams. In this latter, we focus on the combination of the UML class diagram and the UML sequence diagram. This technique of transformation is defined by an algorithm. In this algorithm, we consider only the operations belonging to the two diagrams already combined. Practically, we transform only the operations that have a sequence diagram and belong to the class diagram. This algorithm is appeared in transformation rules. These rules are written in ATL transformation language. The objective of these rules is to generate an MVC2 web model. The generated model is used as an input file of JET template in order to generate anapplication web code. Also; it presents a case study to illustrate this proposal.
SEASONAL ZOOPLANKTON COMMUNITY VARIATION IN KARATAS LAKE, TURKEY

This study was carried out to determine seasonal variation and zooplankton community structure in Karatas Lake, Southern Turkey. Zooplankton samples were collected seasonally between 2002 and 2003 in two stations using a zooplankton net of 55-μm mesh size. A total of 42 taxa were identified, including 19 taxa (45.2 %) Rotifera, 16 taxa (38.1 %) Cladocera, and 7 taxa (16.7 %). Copepoda. Among them, Keratella quadrata, Asplanchna priodonta from Rotifera, Daphnia longispina, Ceriodaphnia quadrangula, Chydorus sphaericus, Coranatella rectangula from Cladocera, and Eudiaptomus drieschi, Eucyclops speratus from Copepoda were dominant species. Spring and autumn seasons were found to be the most similar by using Sorenson index value.
Using oceanic‐atmospheric oscillations for long lead time streamflow forecasting

We present a data‐driven model, Support Vector Machine (SVM), for long lead time streamflow forecasting using oceanic‐atmospheric oscillations. The SVM is based on statistical learning theory that uses a hypothesis space of linear functions based on Kernel approach and has been used to predict a quantity forward in time on the basis of training from past data. The strength of SVM lies in minimizing the empirical classification error and maximizing the geometric margin by solving inverse problem. The SVM model is applied to three gages, i.e., Cisco, Green River, and Lees Ferry in the Upper Colorado River Basin in the western United States. Annual oceanic‐atmospheric indices, comprising Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO), and El Nino–Southern Oscillations (ENSO) for a period of 1906–2001 are used to generate annual streamflow volumes with 3 years lead time. The SVM model is trained with 86 years of data (1906–1991) and tested with 10 years of data (1992–2001). On the basis of correlation coefficient, root means square error, and Nash Sutcliffe Efficiency Coefficient the model shows satisfactory results, and the predictions are in good agreement with measured streamflow volumes. Sensitivity analysis, performed to evaluate the effect of individual and coupled oscillations, reveals a strong signal for ENSO and NAO indices as compared to PDO and AMO indices for the long lead time streamflow forecast. Streamflow predictions from the SVM model are found to be better when compared with the predictions obtained from feedforward back propagation artificial neural network model and linear regression.
The Aftermath of Civil War

Using an event-study methodology, the article analyzes the aftermath of civil war in a cross-section of countries. It focuses on cases where the end of conflict marks the beginning of relatively lasting peace. The analysis considers 41 countries involved in internal wars over the period 1960-2003. To provide a comprehensive evaluation of the aftermath of war, a range of social areas is considered: basic indicators of economic performance, health and education, political development, demographic trends, and conflict and security issues. For each indicator the post and prewar situations are compared and their dynamic trends during the post conflict period are examined. The analysis is conducted in both absolute terms and relative to control groups of countries that are similar except for conflict. The findings indicate that even though war has devastating effects and its aftermath can be immensely difficult, when the end of war marks the beginning of lasting peace, recovery and improvement are achieved.