nils-herrmann/clean_scirepeval huggingface dataset:
Measuring quality of life in Macedonia using human development indicators
Year: 2006

By the end of the 1980s, the central issue of development was focused on the growth of income and not on the growth of quality of life. Therefore, the development strategies were oriented towards production and left no significant space for improving the welfare of individuals. In the beginning of the 1990s, the human development concept emerged, stressing that economic development ultimately should result in growth of quality of life of individuals, while the goal of the development process was to expand the capabilities of individuals by placing them in the focus of the efforts for development. This paper if focused on the quality of life of the individuals. Moreover, in addition to the previous practice in Macedonia of calculating the human development index (HDI) as a measure of quality of life, an attempt will be made to calculate the human poverty index (HPI 2) as a measure of non income poverty, gender development index (GDI) as a measure of inequality between men and women, as well as the human development index at the level of aggregated urban and rural municipalities. We hope that it will contribute to the improvement of the quality of decisions made by the state and local authorities in Macedonia when it comes to issues concerning the human development.
The importance of delineating networks by activity type in bottlenose dolphins (Tursiops truncatus) in Cedar Key, Florida
Venue: Royal Society Open Science
Year: 2015

Network analysis has proved to be a valuable tool for studying the behavioural patterns of complex social animals. Often such studies either do not distinguish between different behavioural states of the organisms or simply focus attention on a single behavioural state to the exclusion of all others. In either of these approaches it is impossible to ascertain how the behavioural patterns of individuals depend on the type of activity they are engaged in. Here we report on a network based analysis of the behavioural associations in a population of bottlenose dolphins (Tursiops truncatus) in Cedar Key, Florida. We consider three distinct behavioural states socializing, travelling and foraging and analyse the association networks corresponding to each activity. Moreover, in constructing the different activity networks we do not simply record a spatial association between two individuals as being either present or absent, but rather quantify the degree of any association, thus allowing us to construct weighted networks describing each activity. The results of these weighted activity networks indicate that networks can reveal detailed patterns of bottlenose dolphins at the population level; dolphins socialize in large groups with preferential associations; travel in small groups with preferential associates; and spread out to forage in very small, weakly connected groups. There is some overlap in the socialize and travel networks but little overlap between the forage and other networks. This indicates that the social bonds maintained in other activities are less important as they forage on dispersed, solitary prey. The overall network, not sorted by activity, does not accurately represent any of these patterns.
Logistics and supply chain management
Year: 2013

In this paper an introduction to the principles and methods used in logistics and supply chain management is presented. It begins by a discussion on fundamentals and explains the relevant terms. Next policy and practice associated with logistics and freight services are regarded with a focus on the EU policy for the sector which greatly influences the development of logistics chains and services. Mathematical formulation of typical transport and logistics related problems is also presented followed by a discussion on the concept of sustainability.
Out of sample prediction of the oil futures market volatility: A comparison of new and traditional combination approaches
Venue: Energy Economics
Year: 2019

This paper aims to use both the standard and iterated combination approaches to accurately predict the oil futures market volatility. We further make a comprehensive comparison of the out of sample forecasting performance between the two paired combination approaches. According to both the Diebold Mariano test and model confidence set test, the iterated combination approach generates significantly more accurate volatility forecasts than the standard counterpart. The Direction of Change test suggests that the iterated combination approach also has substantially higher directional accuracy. We document that these results are robust to various settings. Furthermore, a mean variance investor can obtain sizeable economic gains when she uses the iterated combination forecasts instead of the standard ones to allocate her portfolio.
Effects of Peanut Shell Biochar on Soil Nutrients, Soil Enzyme Activity, and Rice Yield in Heavily Saline Sodic Paddy Field
Year: 2021

This study evaluated the effect of biochar on the soil nutrients, soil enzyme activity, and rice yield in a heavily saline sodic paddy soil using a 2 year field experiment conducted in Jilin province in the northeastern part of China. The soil was amended with biochar at 0 biochar (B0) 33.75 t ha 1 (B1) 67.5 t ha 1 (B2) and 101.25 t ha 1 (B3) The field experiment was arranged in a randomized complete block design. Each treatment was replicated three times. The results show that the addition of biochar significantly increased the availability of soil total N, available P, and available K, while it remarkably reduced the content of the soil's alkali hydrolysable nitrogen, among which NH 4 N and NO 3 N were reduced significantly in 2 years. Biochar applications significantly increased the soil organic matter and soil C/N ratio. The soil Na /K ratio was significantly reduced after biochar application in both 2 years. All of the biochar amendment applications improved the soil catalase activity, soil alkaline phosphatase activity, soil urease activity, and soil sucrose activity. The rice biomass, grain yield, and harvest index were significantly increased. Biochar applications can improve the soil nutrient status, decrease Na /K concentration in soil, promote rice growth, and increase the rice yield in heavily saline sodic paddy soils. It is anticipated that the study results will be useful for formulating novel management ways for improving crop production on saline sodic soil.
A Framework for Checking Regression Test Selection Tools
Venue: 2019 IEEE/ACM 41st International Conference on Software Engineering (ICSE)
Year: 2019

Regression test selection (RTS) reduces regression testing costs by re running only tests that can change behavior due to code changes. Researchers and large software organizations recently developed and adopted several RTS tools to deal with the rapidly growing costs of regression testing. As RTS tools gain adoption, it becomes critical to check that they are correct and efficient. Unfortunately, checking RTS tools currently relies solely on limited tests that RTS tool developers manually write. We present RTSCheck, the first framework for checking RTS tools. RTSCheck feeds evolving programs (i.e. sequences of program revisions) to an RTS tool and checks the output against rules inspired by existing RTS test suites. Violations of these rules are likely due to deviations from expected RTS tool behavior, and indicative of bugs in the tool. RTSCheck uses three components to obtain evolving programs: (1) AutoEP automatically generates evolving programs and corresponding tests, (2) DefectsEP uses buggy and fixed program revisions from bug databases, and (3) EvoEP uses sequences of program revisions from actual open source projects' histories. We used RTSCheck to check three recently developed RTS tools for Java: Clover, Ekstazi, and STARTS. RTSCheck discovered 27 bugs in these three tools.
Faktor faktor yang mempengaruhi kompetensi petani dalam melakukan usahatani ikan air tawar di kecamatan Polanharjo kabupaten Klaten
Year: 2020

Ability is an individual capacity to do various tasks in a profession or activity. This study aimed at scrutinizing the internal factors (age, education level, farming experience, and cosmopolitan level) and external factors (the roles of agricultural extension officers, the roles of the heads of farmer groups, local government support, and access to mass media) of the farmers in practicing freshwater fish farming in Polanharjo Sub district, Klaten Regency, and the correlation between both the internal and external factors and farmers' ability in practicing freshwater fish farming in Polanharjo Sub district, Klaten Regency. This research applied a qualitative method with a survey technique. The research location was determined by considering that Polanharjo Sub district in Klaten Regency Further, Nganjat Village, and Janti. Samples were taken using proportional random sampling, involving 60 respondents. Data were analyzed using Spearman's rank correlation test with IBM SPSS 20.0. The results of this study include three major points. The farmers' age and education levels were considered high, while their farming practice experience and cosmopolitan levels were low. The role of agricultural extension officers and the support of the local government was low, while the role of heads of farmer groups and access to mass media was very low. The roles of agricultural extension officers and the heads of farmer groups had a highly significant relationship with the farmers' ability to practice freshwater fish farming. Nevertheless, Farmers' age, education level, farming experience, and cosmopolitan level, local government support, and access to mass media did not show any noteworthy relationship with farmers' ability to practice freshwater fish farming.
The Salary Taboo: Privacy Norms and the Diffusion of Information
Year: 2018

The limited diffusion of salary information has implications for labor markets, such as wage discrimination policies and collective bargaining. Access to salary information is believed to be limited and unequal, but there is little direct evidence on the sources of these information frictions. Social scientists have long conjectured that privacy norms around salary (i.e. the "salary taboo" play an important role. We provide unique evidence of this phenomenon based on a field experiment with 755 employees at a multibillion dollar corporation. We provide revealed preference evidence that many employees are unwilling to reveal their salaries to coworkers and reluctant to ask coworkers about their salaries. These frictions are still present, but smaller in magnitude, when sharing information that is less sensitive (seniority information) We discuss implications for pay transparency policies and the gender wage gap.
Blockchain and Economic Development Hype vs Reality
Year: 2017

Increasing attention is being paid to the potential of blockchain technology to address long standing challenges related to economic development. Blockchain proponents argue that it will expand opportunities for exchange and collaboration by reducing reliance on intermediaries and the frictions associated with them. The purpose of this paper is to provide a clear eyed view of the technology's potential in the context of development. In it, we focus on identifying the questions that development practitioners should be asking technologists, and challenges that innovators must address for the technology to meet its potential.
Hybrid optimization scheme for intrusion detection using considerable feature selection
Venue: Neural Computing and Applications
Year: 2019

The intrusion detection is an essential section in network security because of its immense volume of threats which bothers the computing systems. The real time intrusion detection dataset comprises redundant or irrelevant features. The duplicate features make it quite challenging to locate the patterns for intrusion detection. Hybrid optimization scheme (HOS) is designed for combining adaptive artificial bee colony (AABC) with adaptive particle swarm optimization (APSO) for detecting intrusive activities. The schemes are aggregated for locating improved optimization based outcomes, and the precision during categorization is acquired using tenfold cross validation scheme. The main objective of the proposed method is to improve the rate of precision in intrusion activities in internetwork by choosing the relevant features. Effectiveness of the hybrid categorization scheme is accessed using an NSL KDD dataset. Single feature selection method and random feature selection method are used to assess the proposed HOS intrusion detection approaches. The effectiveness of the designed scheme is evaluated with existing machine learning schemes such as Naive Bayes, AABC, APSO, and support vector machine, which outperform the HOS.
Managing Talents for Global Leadership Positions in Multinational Corporations
Year: 2011

The identification and development of internal high potential employees is referred to as ,talent management" within the human resources function. Previous research argues that national culture influences organizational culture and leadership, and that human resource management practices should be adapted to local needs. There is little prior research in regards to how Western multinational corporations address this issue within their global approach to talent management, especially in China, where there is an acknowledged shortage of Chinese nationals that operate effectively within higher leadership levels of Western multinational corporations. This study shows how those multinational corporations identify and develop local leadership talents for global leadership positions, globally compared to in China. The research is based on more than 20 qualitative interviews with 14 large multinational corporations across different industries. The main finding is that in most corporations, adaptations of talent management processes in China are limited, but do exist. However, at the higher leadership levels, there are virtually no adaptations of global leadership standards as of today, and most multinational corporations are striving to continuously improve and implement a global talent management approach.
Tensor train decompositions on recurrent networks
Venue: ArXiv
Year: 2020

Recurrent neural networks (RNN) such as long short term memory (LSTM) networks are essential in a multitude of daily live tasks such as speech, language, video, and multimodal learning. The shift from cloud to edge computation intensifies the need to contain the growth of RNN parameters. Current research on RNN shows that despite the performance obtained on convolutional neural networks (CNN) keeping a good performance in compressed RNNs is still a challenge. Most of the literature on compression focuses on CNNs using matrix product (MPO) operator tensor trains. However, matrix product state (MPS) tensor trains have more attractive features than MPOs, in terms of storage reduction and computing time at inference. We show that MPS tensor trains should be at the forefront of LSTM network compression through a theoretical analysis and practical experiments on NLP task.
Audio Visual Emotion Recognition Using a Hybrid Deep Convolutional Neural Network based on Census Transform
Venue: 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)
Year: 2019

Over the last years, recognition of emotions based on multimodal channels has received increasing attention from the scientific community. Many application fields can benefit from multimodal emotion recognition, such as human computer interactions, educational software, behavior prediction, interpersonal relations. Speech and facial expressions are two natural and effective ways to express emotions in human human interaction. In this work, we introduce a hybrid deep convolutional neural network to extract audio and visual features from videos. Initially, for extracting audio data, we transform the audio signal into an image representation as input to a 2D Convolutional Neural Network (CNN) For extracting visual data, we introduce a Census Transform (CT) based on CNN. Then, we fuse both audio and visual features, reducing them through Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) Finally, K Nearest Neighbor (K NN) Support Vector Machine (SVM) Logistic Regression (LR) and Gaussian Naive Bayes (GNB) classifiers are employed for emotion recognition. Experimental results on RML, eNTERFACE05 and BAUM 1s datasets demonstrated that our model reached competitive recognition rates compared to other state of the art approaches.
Theory of Atomic and Molecular Clusters: With a Glimpse at Experiments
Year: 2012

Phases and Phase Changes of Small Systems Physics of Clusters and Cluster Assemblies Structures, Vibrational Frequency Shifts and Photodissociation of ArnHF van der Waals Clusters Rearrangements of Water Dimer and Hexamer Fullerene Collisions Predicting the Properties of Semiconductor Clusters Structure, Reactivity and Dynamics of Atomic and Molecular Clusters Ultrafast Structural Response and Nonlinear Fragmentation Dynamics Electron Dynamics in Metal Clusters Accurate Phase Spase Theory and Molecular Dynamics Calculations of Aluminum Cluster Dissociation Electronic Structure of Bimetallic Clusters Based on Alkali Elements Alloy Clusters Quantum Mechanics of Hydrogen on Nickel and Palladium Clusters Metal Cluster Surface Interactions Experimental Studies of the Structures and Isomerization of Atomic Clusters Silver Clusters and Silver Cluster Ammonia Complexes Laser Femtochemistry of Small Clusters.
China's new lost generation: the casualty of China's economic transformation
Year: 2016

China's surge into global middle income status over the space of three decades has been spectacular. However, a potentially large and burdensome cost has been imposed on a generation of adolescents and young adults who abandoned the countryside, and with it access to basic education, in order to seek the anticipated advantages of jobs in the country's burgeoning urban industrial sector. This large swath of off farm migrants transformed China. It propelled China to the status of the 'world's factory' and created the scale and accumulated learning by doing enabling China's transition to a 'knowledge economy' that no longer depends on the labor of China's new 'Lost Generation. As the Lost Generation and its left behind children, who suffer from a chronic lack of schooling, thicken the lower tail of China's income distribution, it may be the rising, prosperous urban middle class that ultimately incurs the social, economic, and political challenges associated with China's generation of off farm migrant households once essential for launching China's economic ascent.
An improved representation of geographically isolated wetlands in a watershed scale hydrologic model
Year: 2016

Geographically isolated wetlands (GIWs) defined as wetlands surrounded by uplands, provide an array of ecosystem goods and services. Within the United States, federal regulatory protections for GIWs are contingent, in part, on the quantification of their singular or aggregate effects on the hydrological, biological, or chemical integrity of waterways regulated by the Clean Water Act (CWA) However, limited tools are available to assess the downgradient effects of GIWs. We constructed a Soil and Water Assessment Tool (SWAT) model with improved representations of GIW hydrologic processes for the approximately 1700 km2 Pipestem Creek watershed in the Prairie Pothole Region of North Dakota, USA. We then executed a series of novel modifications on the Pipestem Creek SWAT model. We (1) redefined the model's hydrologic response unit spatial boundaries to conform to mapped GIWs and associated watershed boundaries, (2) constructed a series of new model input files to direct the simulation of GIW fill spill hydrology and upland flows to GIWs, and (3) modified the model source code to facilitate use of the new SWAT input files and improve GIW water balance simulations. We then calibrated and verified our modified SWAT model at a daily time step from 2009 through 2013. Simulation results indicated good predictive power (the maximum Nash Sutcliffe Efficiency statistic was 0.86) and an acceptable range of uncertainty (measured using the Sequential Uncertainty Fitting v.2 uncertainty statistics) Simulation results additionally indicated good model performance with respect to GIW water balance simulations based on literature based descriptions of regional GIW hydrologic behaviour. Our modified SWAT model represents a critical step in advancing scientific understandings of the watershed scale hydrologic effects of GIWs and provides a novel method for future assessments in different watersheds and physiographic regions.
The Syntax of Multiple que Sentences in Spanish: Along the left periphery
Year: 2015

1. Preface 2. List of abbreviations 3. Chapter 1.  Chapter 2. Toward a syntactic analysis of Spanish recomplementation 5. Chapter 3. Two distinct complementizers in disguise: Implications for the syntax of preverbal subjects 6. Chapter 4. On the impossibility of movement across non primary complementizers in Spanish 7. Chapter 5. Analyzing the locality effect with non primary que complementizers in Spanish 8.
Effects of different modalities of inspiratory muscle training as an add on to conventional treatment of patients with chronic obstructive pulmonary disease (COPD) study protocol for a randomized controlled trial
Venue: Trials
Year: 2019

BackgroundChronic obstructive pulmonary disease (COPD) leads to peripheral and respiratory muscle dysfunctions. Nowadays, inspiratory muscle training can be geared toward strength or endurance gains. This study aims to investigate the effects of an inspiratory muscle training (IMT) protocol using different therapeutic modalities to be implemented in pulmonary rehabilitation programs. The effects of IMT on exercise capacity were considered as the primary endpoint, and the effects of IMT on inspiratory muscle function, health related quality of life, and daily physical activity level were considered as the secondary outcomes.MethodsThis study is a blinded investigator randomized controlled clinical trial. Sixty subjects will be randomly allocated into three groups: (1) pulmonary rehabilitation (PR) associated with inspiratory muscle training without any load (PRWIMT) (2) PR associated with inspiratory muscle training with a linear load (PRIMTLL) and (3) PR associated with inspiratory muscle training with isocapnic voluntary hyperpnea (PRIMTIVH) The protocol will be performed 5 days a week (3 days with supervision) for 10 weeks. The study will assess anthropometric data, lung function, respiratory muscle strength, and functional capacity by the Incremental Shuttle Walking Test and the Six Minute Walk Test, lung volumes during the submaximal endurance test, peripheral muscle strength of the upper and lower limbs, dyspnea, and quality of life related to health, before and after the training protocol. Normality will be tested using the Kolmogorov Smirnov test, and variables will be compared by two way analysis of variance. The significance level was set at p 0.05. Ethics approval was obtained from the Institutional Ethics Committee in Research (1.663.411) The study results will be disseminated through presentation at specific scientific conferences and publication in peer reviewed journals.DiscussionThe different IMT protocols used in our study will be able to guide respiratory therapists to understand and to include in conventional PR programs the most effective respiratory muscle training type in subjects with COPD.Trial registrationBrazilian Clinical Trials Registry, RBR 94v6kd. Registered on 11 March 2017.