Miracle-dz/UniFAR-FTUs huggingface dataset:
Characterizing OS behavior of Scale-out Data Center Workloads

Data center workloads dominate today’s most popular applications, such as search engine, media streaming, and online big data analysis. Continuing efforts have been take n to characterize the micro-architectural characteristics of scale-out workloads. The most striking conclusion from previous work is that the scale-out workloads suffer from a notable front endstalls when compared with other traditional workloads, which leads to inefficiency of pipeline execution. However, they fail to co nsider the effect of OS execution. As an attempt to shed some lights on the effectiveness of OS kernel on scale-out data center workloads, we quantitati vely break down the OS behavior on scale-out data center workload s characterized by CloudSuite, and take into account the inte rferences between micro-architecture and OS execution. For the first time, we investigate how the pipeline front end is affec ted by OS activities, which are more expensive than application level operations. The insights derived from OS evaluation h elp us identify key limits of current OS paradigms. Our studies on OS behaviors also naturally lead to several OS evolutiona ry recommendations to efficiently manage the diversity of scal e-out data center workloads on future hardware architectures.
A Structural Ranking of Economic Complexity

We propose a structural alternative to the Economic Complexity Index (ECI, Hidalgo and Hausmann 2009; Hausmann et al. 2011) that ranks countries by their complexity. This ranking is tied to comparative advantages. Hence, it reveals information different from GDP per capita on the deep underlying economic capabilities of countries. Our analysis proceeds in three main steps: (i) We first consider a simplified trade model that is centered on the assumption that countries’ global exports are log-supermodular (Costinot, 2009a), and show that a variant of the ECI correctly ranks countries (and products) by their complexity. This model provides a general theoretical framework for ranking nodes of a weighted (bipartite) graph according to some under- lying unobservable characteristic. (ii) We then embed a structure of log-supermodular productivities into a multi-product Eaton and Kortum (2002)-model, and show how our main insights from the simplified trade model apply to this richer set-up. (iii) We finally implement our structural ranking of economic complexity. The derived ranking is robust and remarkably similar to the one based on the original ECI.
Simulating Growth and Development Processes of Quinoa (Chenopodium quinoa Willd.): Adaptation and Evaluation of the CSM-CROPGRO Model

In recent years, the intra-annual yield variability of traditional food crops grown in Europe increased due to extreme weather events driven by climate change. The Andean crop quinoa (Chenopodium quinoa Willd.), being well adapted to drought, salinity, and frost, is considered to be a promising new crop for Europe to cope with unfavorable environmental conditions. However, cultivation guidelines and cropping experiences are missing on a long-term scale. The adaptation of a mechanistic crop growth model will support the long-term evaluation of quinoa if grown under the diverse environmental conditions of Europe. The objective of this study was to adapt the process-based cropping system model (CSM) CROPGRO, which is included in the Decision Support System for Agrotechnology Transfer (DSSAT). Therefore, species and genetic coefficients were calibrated using literature values and growth analysis data, including crop life cycle, leaf area index (LAI), specific leaf area (SLA), dry matter partitioning and nitrogen concentrations in different plant tissues, aboveground biomass, and yield components, of a sowing date experiment (covering two cultivars and four sowing dates) conducted in southwestern Germany in 2016. Model evaluation was performed on the crop life cycle, final aboveground biomass, and final grain yield for different sowing dates using an independent data set collected at the same site in 2017. The resulting base temperatures regarding photosynthetic, vegetative, and reproductive processes ranged between 1 and 10 °C, while the corresponding optimum temperatures were between 15 and 36 °C. On average, the crop life cycle was predicted with a root mean square error (RMSE) of 4.7 and 3.0 days in 2016 and 2017, respectively. In 2016, the mean predicted aboveground biomass during the growth cycle showed a d-index of 0.98 (RMSE = 858 kg ha−1). Furthermore, the LAI, SLA, and leaf nitrogen concentrations were simulated with a high accuracy, showing a mean RMSE of 0.29 (d-index = 0.94), 25 cm2 g−1 (d-index = 0.88), and 0.51% (d-index = 0.95). Evaluations on the grain yield and aboveground biomass across four sowing dates in 2017 suggested a good robustness of the new quinoa model. The mean predicted aboveground biomass and grain yield at harvest maturity were 6479 kg ha−1 (RMSE = 898.9 kg ha−1) and 3843 kg ha−1 (RMSE = 450.3 kg ha−1), respectively. Thus, the CSM-CROPGRO model can be used to evaluate the long-term suitability, as well as different management strategies of quinoa under European conditions. However, further development on the simulation of small seed sizes and under water or nitrogen-limited environments are needed.
A Short Review on Image Caption Generation with Deep Learning

Methodologies that utilize Deep Learning offer great potential for applications that automatically attempt to generate captions or descriptions about images. Image captioning is considered to be one of the intellectually challenging problems in imaging science. The application domains include: automatic caption (or description) generation for images for people who suffer from various degrees of visual impairment; the automatic creation of metadata for images (indexing) for use by search engines; general purpose robot vision systems; and many others. Each of these application domains can positively and significantly impact many other task-specific applications. This paper is not meant to be a comprehensive review of image captioning; rather, it is a concise review of image captioning methodologies based on deep learning, strengths and limitations, the datasets and the evaluation metrics used in automatic image captioning. Finally, a quick discussion about the software and hardware requirements for implementing an image captioning method is presented.
Uptake of Pb(II) Ions from Simulated Aqueous Solution via Nanochitosan

In this work, nanochitosan (NC) was prepared through ionic gelation using low molecular weight chitosan and maleic acid (MA). The synthesized NC was characterized by atomic force microscopy (AFM), Fourier transform infrared spectroscopy (FTIR), and scanning electron microscopy (SEM). During preparation, the particle size of the material depended on parameters such as concentration of chitosan and pH of the aqueous solution. After controlling the mentioned parameters, NC smaller than 100 nm was prepared. The chitosan and prepared NC were employed for the adsorption of Pb(II) from an aqueous solution in the form of a batch system. Among the sorption parameters, pH showed the strongest effect on the sorption process and removal of the maximum number of Pb(II) ions was obtained at pH value of 6. Pseudo-first-order and pseudo-second-order models were used to track the kinetics of the adsorption process. Langmuir and Freundlich’s isotherms were subjected to the absorption data to evaluate absorption capacity. NC proved to be an excellent adsorbent with a remarkable capacity to eliminate Pb(II) ions from aqueous solutions at multiple concentrations. The NC also showed better performance with a comparatively easier preparation process than in other reported work.
A Three-Class Classification of Cognitive Workload Based on EEG Spectral Data

Evaluation of cognitive workload finds its application in many areas, from educational program assessment through professional driver health examination to monitoring the mental state of people carrying out jobs of high responsibility, such as pilots or airline traffic dispatchers. Estimation of multilevel cognitive workload is a task usually realized in a subject-dependent way, while the present research is focused on developing the procedure of subject-independent evaluation of cognitive workload level. The aim of the paper is to estimate cognitive workload level in accordance with subject-independent approach, applying classical machine learning methods combined with feature selection techniques. The procedure of data acquisition was based on registering the EEG signal of the person performing arithmetical tasks divided into six intervals of advancement. The analysis included the stages of preprocessing, feature extraction, and selection, while the final step covered multiclass classification performed with several models. The results discussed show high maximal accuracies achieved: ~91% for both the validation dataset and for the cross-validation approach for kNN model.
The Work-Life Conflict and Well-Being of Turkish Employees

Using data drawn from the 2004 European Social Surv ey, we examine the determinants of the life satisfaction of employees in Turkey. The data reveal that the majority of Turkish wage and salary earner s are either underor overemployed. About half of Turkish workers have to wor k longer than they desire, so, unsurprisingly, the share of workers who say they are pleased with their work schedules is only 22%. Gender turns out t be closely linked with the hours-mismatch status, as the level of over-emp loyment is eight percentage points higher among female workers than male. O rdered probit-model estimates reveal that over-employment (measured as the difference in the actual and preferred weekly number of hours) has a negative impact on wellbeing. We failed to turn up a statistically signifi cant finding for underemployment, which we attribute to the small sample size. We also find no statistically meaningful difference in the impact o n male versus female employees of the work-hours mismatch. This suggests t hat the gender differences that would have been expected in this context are a lready incorporated into the respondents' subjectively determined desired ho urs f work. In addition, we find that family-to-work conflict is less common , but has a larger impact on well-being than work-to-family conflict. JEL codes: C25, I31, J21, J22
Testing the Conditional CAPM using GARCH-type Models without any other Restrictions

We develop a new approach to testing conditional asset pricing models that avoids placing restrictions on the price of risk. The only assumption made in the model is on the form of the dynamics of the conditional covariance matrix of asset returns. Existing GARCHbased models require an assumption on the price of risk, which we avoid in our approach. We illustrate the methodology by testing a conditional version of the simple single-factor CAPM using monthly returns and show that accounting for time varying betas using our preferred model, which uses daily returns and accounts for the autocovariance in daily returns to model conditional monthly volatilities, reduces average absolute alphas by 32% compared with an unconditional model. Ultimately, we are unable to reject the null hypothesis that the conditional CAPM prices the size and industry sorted portfolios but reject the model for the Fama-French 25 portfolios.
Simplified Fractional Order Controller Design Algorithm

Classical fractional order controller tuning techniques usually establish the parameters of the controller by solving a system of nonlinear equations resulted from the frequency domain specifications like phase margin, gain crossover frequency, iso-damping property, robustness to uncertainty, etc. In the present paper a novel fractional order generalized optimum method for controller design using frequency domain is presented. The tuning rules are inspired from the symmetrical optimum principles of Kessler. In the first part of the paper are presented the generalized tuning rules of this method. Introducing the fractional order, one more degree of freedom is obtained in design, offering solution for practically any desired closed-loop performance measures. The proposed method has the advantage that takes into account both robustness aspects and desired closed-loop characteristics, using simple tuning-friendly equations. It can be applied to a wide range of process models, from integer order models to fractional order models. Simulation results are given to highlight these advantages.
Local Pixel Manipulation Detection with Deep Neural Networks

In times of digital images and easy to achieve manipulations, tampered photos are ubiquitous. Well carried out manipulations are almost impossible to identify, even for humans. To earn back trust it is necessary to develop techniques that can detect such manipulations. Two of the most commonly used manipulations are splicing and copy-move, e.g., copy a part from one image and paste in into another or the same image. In this thesis, we present an approach based on deep learning that significantly improves the possibilities to detect such manipulations. The approach uses a combination of a VGG-Net for feature extraction and Global Average Pooling for classification as its architecture. Our approach not only classifies the images, for being manipulated or not, but also localizes where the manipulations occur. To achieve this localization, it uses patches combined with image classification. We evaluate our approach and conduct several experiments, in which we compare the rate of classification against other well-known techniques, such as SIFT (copy-move), Expectation Maximization with segmentation (splicing) and a retrained Faster-RCNN (both). Our approach achieves the highest F1 score across all evaluated techniques, reaching about 77% macro average for our generated COCO segmentation data set for splicing and 79% for the Columbia data set, respectively.
Investigation of the Rheological Properties of Rotomolding Resins

There are many influential factors and processing variables that can impact the mechanical and aesthetic properties of a rotomolded part. One of the main variables is the resin being processed and its associated rheological properties. The manner by which the polymer powder sinters and fuses together needs to be understood to ensure the correct processing cycle is used to obtain an optimum cured part. The influence of bubbles that form during the sintering phase and the melt index of the material, contribute to the quality of the part being produced.
Organizational Culture and Quality of Work Life Among Nurses in Tertiary Hospitals, Yunnan Province, The People’s Republic of China

Quality of work life (QWL) of health professionals is an important component in the healthcare system to achieve positive organizational outcomes. Studies have indicated a relationship between organizational culture and nurses’ quality of work life. The purpose of this descriptive correlational study were to describe the characteristics of organizational culture, to identify the level of quality of work life, and to explore the relationship between each dimension of organizational culture and quality of work life among nurses in tertiary hospitals in Yunnan Province, the People’s Republic of China. The subjects were 416 nurses from six tertiary hospitals in Yunnan Province. Research instruments were the Organizational Culture Profile (OCP) and the Quality of Work Life Scale (QWLS). The reliability of the OCP and the QWLS were . 93, and . 91, respectively. Data were analyzed using descriptive statistics and Spearman’s Rank-Order Correlation. The results of this study are as follows: 1. Four dimensions of organizational culture including competitiveness, performance orientation, stability, and social responsibility were prominent. The other 3 dimensions, namely supportiveness, innovation, and emphasis on rewards were perceived as less prominent. 2. The overall mean score of quality of work life was at a moderate level. 3. Two dimensions of organizational culture, including supportiveness and emphasis on rewards, had strong positive relationships with quality of work life. Two dimensions, innovation and stability, had moderate positive relationships with quality of work life. Three dimensions, competitiveness, performance orientation and social responsibility, had weak positive relationships with quality of work life. The results of this study provide basic information for nurse administrators and hospital administrators to develop hospital policies and strategies to improve organizational culture in order to enhance quality of work life among nurses.
Transitional Flow on Model Propellers and Their Influence on Relative Rotative Efficiency

Unexpected low value of the relative rotative efficiency ηR is sometimes noted when scaling the towing tank model-test result with the ITTC-78 method to obtain the propulsive efficiency factors of propellers. The paper explains the causes of this phenomenon. The boundary layer state of three propellers was studied by a paint test and a RANS method. The paint tests showed that the propellers in behind conditions at low Reynolds number (Rn) are covered mainly with laminar flow, which is different from open water tests conducted at a high Rn. Apart from that a moderate difference in Rn between the open water and the self-propulsion test may lead to a low ηR value, the paper points out that flow separation in behind conditions could be another significant reason for the drop of ηR for some propellers. Therefore, two factors will lead to an unexpected decrease of ηR: (1) A slightly lower open water torque interpolated from an open water test carried out at a high Rn and (2) a slightly higher torque in a self-propulsion test due to laminar flow separation near the trailing edge. The phenomenon is caused by the Rn scaled effect and closely associated with design philosophy like the blade section profile, the chord length, and chordwise load distribution.
Cultural Heterogeneity towards Standardization and Adaptation of Marketing Mix: A study on Multinational Companies in Ghana

This paper examines the strategic application of standardisation and adaptation of Multinational companies' (MNCs) marketing mix (4P's) on a diverse cultural environment. Business Strategy Approach was employed as a theoretical foundation for the study . Eighty two managers of the multinational companies operating in Accra and Kumasi, Ghana were conveniently and purposively sampled for the study. Cochran Q Test statistic was used to analyse the data on a linear continuum across a three time point.The study identified that, multinational manufacturing companies employ a combination of both adaptation and standardisation strategies on their marketing mixes. Price was observed to be the most adapted element of the marketing mix. The study recommended for managers of multinational companies to utilize more of adaptation strategies rather than standardisation due to changes in cultural dynamics, consumer characteristics, market economy as well as government’s business laws and regulations which are different within the African continent.
PRODUCTION of AMYLASE by A NOVEL Bacillus sp. ZBP10 in SUBMERGED FERMENTATION

Bacillus sp. ZBP10 is an amylase producing strain isolated from a soil sample collected from a potato cultivation field in Sakarya. In this study, culture conditions were optimized for Bacillus sp. ZBP10 in order to increase amylase production using submerged fermentation. The effects of temperature (30-40°C), fermentation time (24-72 h), initial medium pH (6.0-9.0), carbon sources (soluble, wheat, rice and corn starches) and substrate concentration (5-30 g/L) on the production of amylase were determined. According to the results, the bacterium produced maximum amount of amylase, when the initial pH of the medium was 7.0, at 33°C, and within 48 h. Soluble starch was the best substrate among the starches tested. Optimum substrate concentration was 20 g/L for enzyme production with which 3.57±0.19 U/mL enzymatic activity was obtained.
Do Investor-State Disputes Harm FDI ?

What are the consequences of being sued for violating bilateral investment treaties (BITs)? The conventional wisdom is that investor-state disputes (ISDS) extend beyond the case at hand, tarnishing countries' compliance record, and depressing FDI inflows. We re-examine this belief in light of recent trends in ISDS. We expect that the rapid increase in the volume of cases, their declining rate of success, and a shift towards claims alleging "indirect expropriation" have combined to decrease the informational value of the average claim, minimizing any reputational cost. The signal sent by the average ISDS claim should be a reflection of the selection of cases. We find support for this expectation by analyzing the effects of all 812 investor-state disputes from 1987 to present day. Financial consequences are limited to cases alleging “direct expropriation," and are smaller today than they were 15 years ago. ISDS just isn't what it used to be. 10,791 words, including footnotes and references.
Fractions and Pythagorean Tuning—An Interdisciplinary Study in Secondary Education

Formal education is experiencing a series of reforms that favor the integration of the contents of different areas in the teaching and learning of the different educational stages. The present study examined the use of an interdisciplinary music and mathematics experience in Secondary Education in Galicia (Spain) in the 2016/17 academic year. A descriptive–exploratory design was used, through a Likert questionnaire applied to 197 students with a diagnostic test and a reference test, and a study of multiple cases was carried out in which information was collected through classroom observations. The results show improvements in the understanding of mathematical and musical concepts, and attitudes and procedures so we can argue that the use of interdisciplinary activities have favored the development of teaching–learning opportunities in mathematical and musical training.
IMPACT OF INTERNAL GOVERNANCE MECHANISMS ON CORPORATE PERFORMANCE IN DEPOSIT MONEY BANKS IN NIGERIA

The importance of internal mechanism in corporate organisations is vital for deliberate effort to be placed in this area of financial institutions. Sequel to this, this study examines the relationship between the internal corporate governance mechanisms related to the board of directors, the audit committee characteristics and the performance of listed Deposit Money Banks (DMBs) in Nigeria. The study covers the period of seven years (2005-2011), with the population of seventeen (17), a sample of fourteen (14) DMBs. Multiple regression is employed as a tool of analysis on the data which are extracted from the annual reports of the sampled DMBs. The results indicate that board characteristics and audit committee characteristics are essential factors of internal control mechanism sequel to the fact that both board and audit committee characteristics have significantly influenced DMBs performance during the period of the study (Board composition (BC), Audit committee activities/meetings (ACA)and Audit committee independence (ACI) have a significant and positive impact on performance while Board size (BZ) has a negative but significant impact on performance of DMBs. Consequently, we recommend, among others, that management/shareholders in the Nigerian DMBs to consider these board and audit committee characteristics (using these variables of the study) as benchmark of embarking on enhancing performance. As a matter of policy input, regulatory authorities such as CBN, NDIC, SEC, NSE and other stake holders of concern should strengthen and ensure compliance with best internal governance practices. Ensuring adequate compliance will boost the level of firms’ performance and thereby improving the overall trust and confidence of stakeholders in the financial sector