nils-herrmann/clean_scirepeval huggingface dataset:
The hustle and bustle of city life: monitoring the effects of urbanisation in the African lesser bushbaby

Urbanisation has become a severe threat to pristine natural areas, causing habitat loss and affecting indigenous animals. Species occurring within an urban fragmented landscape must cope with changes in vegetation type as well as high degrees of anthropogenic disturbance, both of which are possible key mechanisms contributing to behavioural changes and perceived stressors. We attempted to elucidate the effects of urbanisation on the African lesser bushbaby, Galago moholi, by (1) recording activity budgets and body condition (body mass index, BMI) of individuals of urban and rural populations and (2) further determining adrenocortical activity in both populations as a measure of stress via faecal glucocorticoid metabolite (fGCM) levels, following successful validation of an appropriate enzyme immunoassay test system (adrenocorticotropic hormone (ACTH) challenge test). We found that both sexes of the urban population had significantly higher BMIs than their rural counterparts, while urban females had significantly higher fGCM concentrations than rural females. While individuals in the urban population fed mainly on provisioned anthropogenic food sources and spent comparatively more time resting and engaging in aggressive interactions, rural individuals fed almost exclusively on tree exudates and spent more time moving between food sources. Although interactions with humans are likely to be lower in nocturnal than in diurnal species, our findings show that the impact of urbanisation on nocturnal species is still considerable, affecting a range of ecological and physiological aspects.
Personality traits and concern for privacy: an empirical study in the context of location-based services

March 2008  May 2008 2nd  27 July 2008 Accepted: 11 August 2008  For more than a century, concern for privacy (CFP) has co-evolved with advances in information technology. The CFP refers to the anxious sense of interest that a person has because of various types of threats to the person’s state of being free from intrusion. Research studies have validated this concept and identified its consequences. For example, research has shown that the CFP can have a negative influence on the adoption of information technology; but little is known about factors likely to influence such concern. This paper attempts to fill that gap. Because privacy is said to be a part of a more general ‘right to one’s personality’, we consider the so-called ‘Big Five’ personality traits (agreeableness, extraversion, emotional stability, openness to experience, and conscientiousness) as factors that can influence privacy concerns. Protection motivation theory helps us to explain this influence in the context of an emerging pervasive technology: location-based services. Using a survey-based approach, we find that agreeableness, conscientiousness, and openness to experience each affect the CFP. These results have implications for the adoption, the design, and the marketing of highly personalized new technologies.  (2008) 17, 387–402. doi:10.1057/ejis.2008.29
Dynamic modeling and control design for a self-balancing two-wheel chair

The self-balancing two-wheel chair (SBC) is an unconventional type of personal transportation vehicle. It has unstable dynamics and therefore requires a special control to stabilize and prevent it from falling and to ensure the possibility of speed control and steering by the rider. This paper discusses the dynamic modeling and controller design for the system. The model of SBC is based on analysis of the motions of the inverted pendulum on a mobile base complemented with equations of the wheel motion and motor dynamics. The proposed control design involves a multi-loop PID control. Experimental verification and prototype implementation are discussed.
Two New Low-Power and High-Performance Full Adders

Two new low-power, and high-performance 1bit Full Adder cells are proposed in this paper. These cells are based on low-power XOR/XNOR circuit and Majority-not gate. Majority-not gate, which produces Cout (Output Carry), is implemented with an efficient method, using input capacitors and a static CMOS inverter. This kind of implementation benefits from low power consumption, a high degree of regularity and simplicity. Eight state-of-the-art 1-bit Full Adders and two proposed Full Adders are simulated with HSPICE using 0.18μm CMOS technology at several supply voltages ranging from 2.4v down to 0.8v. Although low power consumption is targeted in implementation of our designs, simulation results demonstrate great improvement in terms of power consumption and also PDP.
Susceptibility tensor imaging (STI) of the brain.

Susceptibility tensor imaging (STI) is a recently developed MRI technique that allows quantitative determination of orientation-independent magnetic susceptibility parameters from the dependence of gradient echo signal phase on the orientation of biological tissues with respect to the main magnetic field. By modeling the magnetic susceptibility of each voxel as a symmetric rank-2 tensor, individual magnetic susceptibility tensor elements as well as the mean magnetic susceptibility and magnetic susceptibility anisotropy can be determined for brain tissues that would still show orientation dependence after conventional scalar-based quantitative susceptibility mapping to remove such dependence. Similar to diffusion tensor imaging, STI allows mapping of brain white matter fiber orientations and reconstruction of 3D white matter pathways using the principal eigenvectors of the susceptibility tensor. In contrast to diffusion anisotropy, the main determinant factor of the susceptibility anisotropy in brain white matter is myelin. Another unique feature of the susceptibility anisotropy of white matter is its sensitivity to gadolinium-based contrast agents. Mechanistically, MRI-observed susceptibility anisotropy is mainly attributed to the highly ordered lipid molecules in the myelin sheath. STI provides a consistent interpretation of the dependence of phase and susceptibility on orientation at multiple scales. This article reviews the key experimental findings and physical theories that led to the development of STI, its practical implementations, and its applications for brain research.
Pelvic tilt. Intratester reliability of measuring the standing position and range of motion.

The purpose of this study was to examine intratester reliability of a test designed to measure the standing pelvic-tilt angle, active posterior and anterior pelvic-tilt angles and ranges of motion, and the total pelvic-tilt range of motion (ROM). After an instruction session, the pelvic-tilt angles of the right side of 20 men were calculated using trigonometric functions. Ranges of motion were determined from the pelvic-tilt angles. Intratester reliability coefficients (Pearson r) for test and retest measurements were .88 for the standing pelvic-tilt angle, .88 for the posterior pelvic-tilt angle, .92 for the anterior pelvic-tilt angle, .62 for the posterior pelvic-tilt ROM, .92 for the anterior pelvic-tilt ROM, and .87 for the total ROM. We discuss the factors that may have influenced the reliability of the measurements and the clinical implications and limitations of the test. We suggest additional research to examine intratester reliability of measuring the posterior pelvic-tilt ROM, intertester reliability of measuring all angles and ROM, and the pelvic tilt of many types of subjects.
The neuromuscular differential diagnosis of joint hypermobility.

Joint hypermobility is the defining feature of various inherited connective tissue disorders such as Marfan syndrome and various types of Ehlers-Danlos syndrome and these will generally be the first conditions to be considered by geneticists and pediatricians in the differential diagnosis of a patient presenting with such findings. However, several congenital and adult-onset inherited myopathies also present with joint hypermobility in the context of often only mild-to-moderate muscle weakness and should, therefore, be included in the differential diagnosis of joint hypermobility. In fact, on the molecular level disorders within both groups represent different ends of the same spectrum of inherited extracellular matrix (ECM) disorders. In this review we will summarize the measures of joint hypermobility, illustrate molecular mechanisms these groups of disorders have in common, and subsequently discuss the clinical features of: 1) the most common connective tissue disorders with myopathic or other neuromuscular features: Ehlers-Danlos syndrome, Marfan syndrome and Loeys-Dietz syndrome; 2) myopathy and connective tissue overlap disorders (muscle extracellular matrix (ECM) disorders), including collagen VI related dystrophies and FKBP14 related kyphoscoliotic type of Ehlers-Danlos syndrome; and 3) various (congenital) myopathies with prominent joint hypermobility including RYR1- and SEPN1-related myopathy. The aim of this review is to assist clinical geneticists and other clinicians with recognition of these disorders.
Investigation of the attitudes of university students to discrimination of the elderly

This study was conducted to determine the attitudes of university students studying in different fields toward discrimination of the elderly.



This descriptive study was conducted with students who were still studying in the 2015-2016 period. A sample size of 416 students was determined by the stratified sampling method, and students were selected by simple random sampling. Data were collected using an identifying information form and an Age Discrimination Attitude Scale (ADAS) by face-to-face interview. Statistical analysis was performed using the program SPSS 20.0.



The mean total ADAS score of students was 67.7±6.0. The total ADAS scores and the scores of male students on limiting the life of the elderly was significantly higher than those of female students (p<0.05).



It was determined that university students studying in different fields have a positive attitude toward the elderly. Action must be taken to remove discrimination of the elderly, and policies must be developed to increase social sensitivity.
Duration modeling of Indian languages Hindi and Telugu

This paper reports a preliminary attempt on data-driven modeling of segmental (phoneme) duration for two Indian languages Hindi and Telugu.  Tree (CART) based data-driven duration modeling for segmental duration prediction is presented. A number of features are proposed and their usefulness and relative contribution in segmental duration prediction is assessed. Objective evaluation of the duration models, by root mean squared prediction error (RMSE) and correlation between actual and predicted durations, is performed. The duration models developed have been implemented in an Indian language Textto-Speech synthesis system  being developed within Festival framework .
A methodology for energy-quality tradeoff using imprecise hardware

Recent studies have demonstrated the potential for reducing energy consumption in integrated circuits by allowing errors during computation. While most proposed techniques for achieving this rely on voltage overscaling (VOS), this paper shows that Imprecise Hardware (IHW) with design-time structural parameters can achieve orthogonal energy-quality tradeoffs. Two IHW adders are improved and two IHW multipliers are introduced in this paper. In addition, a simulation-free error estimation technique is proposed to rapidly and accurately estimate the impact of IHW on output quality. Finally, a quality-aware energy minimization methodology is presented. To validate this methodology, experiments are conducted on two computational kernels: DOT-PRODUCT and L2-NORM -- used in three applications -- Leukocyte Tracker, SVM classification and K-means clustering. Results show that the Hellinger distance between estimated and simulated error distribution is within 0.05 and that the methodology enables designers to explore energy-quality tradeoffs with significant reduction in simulation complexity.
Design of encoder and decoder for Golay code

This paper is based on cyclic redundancy check based encoding scheme. High throughput and high speed hardware for Golay code encoder and decoder could be useful in digital communication system. In this paper, a new algorithm has been proposed for CRC based encoding scheme, which devoid of any linear feedback shift registers (LFSR). In addition, efficient architectures have been proposed for both Golay encoder and decoder, which outperform the existing architectures in terms of speed and throughput. The proposed architecture implemented in virtex-4 Xilinx power estimator. Although the CRC encoder and decoder is intuitive and easy to implement, and to reduce the huge hardware complexity required. The proposed method it improve the transmission system performance level. In this architecture our work is to design a Golay code based on encoder and decoder architecture using CRC generation technique. This technique is used to reduce the circuit complexity for data transmission and reception process.
Characterization of metabolism in the Fe(III)-reducing organism Geobacter sulfurreducens by constraint-based modeling.

Geobacter sulfurreducens is a well-studied representative of the Geobacteraceae, which play a critical role in organic matter oxidation coupled to Fe(III) reduction, bioremediation of groundwater contaminated with organics or metals, and electricity production from waste organic matter. In order to investigate G. sulfurreducens central metabolism and electron transport, a metabolic model which integrated genome-based predictions with available genetic and physiological data was developed via the constraint-based modeling approach. Evaluation of the rates of proton production and consumption in the extracellular and cytoplasmic compartments revealed that energy conservation with extracellular electron acceptors, such as Fe(III), was limited relative to that associated with intracellular acceptors. This limitation was attributed to lack of cytoplasmic proton consumption during reduction of extracellular electron acceptors. Model-based analysis of the metabolic cost of producing an extracellular electron shuttle to promote electron transfer to insoluble Fe(III) oxides demonstrated why Geobacter species, which do not produce shuttles, have an energetic advantage over shuttle-producing Fe(III) reducers in subsurface environments. In silico analysis also revealed that the metabolic network of G. sulfurreducens could synthesize amino acids more efficiently than that of Escherichia coli due to the presence of a pyruvate-ferredoxin oxidoreductase, which catalyzes synthesis of pyruvate from acetate and carbon dioxide in a single step. In silico phenotypic analysis of deletion mutants demonstrated the capability of the model to explore the flexibility of G. sulfurreducens central metabolism and correctly predict mutant phenotypes. These results demonstrate that iterative modeling coupled with experimentation can accelerate the understanding of the physiology of poorly studied but environmentally relevant organisms and may help optimize their practical applications.
Enriching Product Ads with Metadata from HTML Annotations

Product ads are a popular form of search advertizing offered by major search engines, including Yahoo, Google and Bing. Unlike traditional search ads, product ads include structured product specifications, which allow search engine providers to perform better keyword-based ad retrieval. However, the level of completeness of the product specifications varies and strongly influences the performance of ad retrieval. On the other hand, online shops are increasing adopting semantic markup languages such as Microformats, RDFa and Microdata, to annotate their content, making large amounts of product description data publicly available. In this paper, we present an approach for enriching product ads with structured data extracted from thousands of online shops offering Microdata annotations. In our approach we use structured product ads as supervision for training feature extraction models able to extract attribute-value pairs from unstructured product descriptions. We use these features to identify matching products across different online shops and enrich product ads with the extracted data. Our evaluation on three product categories related to electronics show promising results in terms of enriching product ads with useful product data.
Beyond Markov Logic: Efficient Mining of Prediction Rules in Large Graphs

Graph representations of large knowledge bases may comprise billions of edges. Usually built upon human-generated ontologies, several knowledge bases do not feature declared ontological rules and are far from being complete. Current rule mining approaches rely on schemata or store the graph in-memory, which can be unfeasible for large graphs. In this paper, we introduce HornConcerto, an algorithm to discover Horn clauses in large graphs without the need of a schema. Using a standard fact-based condence score, we can mine close Horn rules having an arbitrary body size. We show that our method can outperform existing approaches in terms of runtime and memory consumption and mine high-quality rules for the link prediction task, achieving state-of-the-art results on a widely-used benchmark. Moreover, we nd that rules alone can perform inference signicantly faster than embedding-based methods and achieve accuracies on link prediction comparable to resourcedemanding approaches such as Markov Logic Networks.
A Survey on Mobile Affective Computing

This survey presents recent progress on Affective Computing (AC) using mobile devices. AC has been one of the most active research topics for decades. The primary limitation of traditional AC research refers to as impermeable emotions. This criticism is prominent when emotions are investigated outside social contexts. It is problematic because some emotions are directed at other people and arise from interactions with them. The development of smart mobile wearable devices (e.g., Apple Watch, Google Glass, iPhone, Fitbit) enables the wild and natural study for AC in the aspect of computer science. This survey emphasizes the AC study and system using smart wearable devices. Various models, methodologies and systems are discussed in order to examine the state of the art. Finally, we discuss remaining challenges and future works.
Constraint-based models predict metabolic and associated cellular functions

The prediction of cellular function from a genotype is a fundamental goal in biology. For metabolism, constraint-based modelling methods systematize biochemical, genetic and genomic knowledge into a mathematical framework that enables a mechanistic description of metabolic physiology. The use of constraint-based approaches has evolved over ~30 years, and an increasing number of studies have recently combined models with high-throughput data sets for prospective experimentation. These studies have led to validation of increasingly important and relevant biological predictions. As reviewed here, these recent successes have tangible implications in the fields of microbial evolution, interaction networks, genetic engineering and drug discovery.
Rational Function Fitting of Electromagnetic Transfer Functions from Frequency-Domain and Time-Domain Data

This paper presents a new methodology for synthesis of broadband equivalent circuits for multi-port high speed interconnect systems from numerically obtained and/or measured frequency-domain and time-domain response data. The equivalent circuit synthesis is based on the rational function fitting of admittance matrix, which combines the frequency-domain vector fitting process, VECTFIT with its time-domain analog, TDVF to yield a robust and versatile fitting algorithm. The generated rational fit is directly converted into a SPICE-compatible circuit after passivity enforcement. The accuracy of the resulting algorithm is demonstrated through its application to the fitting of the admittance matrix of a power/ground plane structure
Mobile customer relationship management: an exploratory analysis of Italian applications

The paper’s aims are to estimate the size of the Italian market for mobile customer relationship management (mCRM) services and to try to evaluate some benefits that can be obtained through the use of mCRM applications by companies.  The research involved a census of mCRM applications in order to construct a typology of mCRM applications being used and the analysis of some case studies to assess the impact of such applications on the perspective adopted by the company. This second phase involved interviews with managers of the companies.  In 2005, 1,077 mCRM services were used by 405 companies in Italy. The main benefits found were the improvement of customer satisfaction, an increase in the efficiency of internal processes and an increase in revenue.  The present research considers only Italian services based on data and not on voice. Future research will be required to investigate end-user needs and wants (which are not treated in this paper) and to make a comparison between the Italian market and other markets.  This research is the first step towards the generation of a systematic study of mCRM applications and their future development. The hope is that other companies could benefit from the use of these kinds of technologies.  The present research focuses upon companies that give a strategic role to their relationship with customers. The results provide a systematic typology of current services for those companies that do not know about opportunities offered by the mobile channel.
Modeling MOS snapback for circuit-level ESD simulation using BSIM3 and VBIC models

A novel macro model approach for modeling ESD MOS snapback is introduced. The macro model consists of standard components only. It includes a MOS transistor modeled by BSIM3v3, a bipolar transistor modeled by VBIC, and a resistor for substrate resistance. No external current source, which is essential in most publicly reported macro models, is included since both BSIM3vs and VBIC have formulations built in to model the relevant effects. The simplicity of the presented macro model makes behavior languages, such as Verilog-A, and special ESD equations not necessary in model implementation. This offers advantages of high simulation speed, wider availability, and less convergence issues. Measurement and simulation of the new approach indicates that good silicon correlation can be achieved.
Performance analysis of Ensemble methods on Twitter sentiment analysis using NLP techniques

Mining opinions and analyzing sentiments from social network data help in various fields such as even prediction, analyzing overall mood of public on a particular social issue and so on. This paper involves analyzing the mood of the society on a particular news from Twitter posts. The key idea of the paper is to increase the accuracy of classification by including Natural Language Processing Techniques (NLP) especially semantics and Word Sense Disambiguation. The mined text information is subjected to Ensemble classification to analyze the sentiment. Ensemble classification involves combining the effect of various independent classifiers on a particular classification problem. Experiments conducted demonstrate that ensemble classifier outperforms traditional machine learning classifiers by 3-5%.