nils-herrmann/clean_scirepeval huggingface dataset:
Accurate and interpretable nanoSAR models from genetic programming based decision tree construction approaches
Venue: Nanotoxicology

The number of engineered nanomaterials (ENMs) being exploited commercially is growing rapidly, due to the novel properties they exhibit. Clearly, it is important to understand and minimize any risks to health or the environment posed by the presence of ENMs. Data driven models that decode the relationships between the biological activities of ENMs and their physicochemical characteristics provide an attractive means of maximizing the value of scarce and expensive experimental data. Although such structure activity relationship (SAR) methods have become very useful tools for modelling nanotoxicity endpoints (nanoSAR) they have limited robustness and predictivity and, most importantly, interpretation of the models they generate is often very difficult. New computational modelling tools or new ways of using existing tools are required to model the relatively sparse and sometimes lower quality data on the biological effects of ENMs. The most commonly used SAR modelling methods work best with large datasets, are not particularly good at feature selection, can be relatively opaque to interpretation, and may not account for nonlinearity in the structure property relationships. To overcome these limitations, we describe the application of a novel algorithm, a genetic programming based decision tree construction tool (GPTree) to nanoSAR modelling. We demonstrate the use of GPTree in the construction of accurate and interpretable nanoSAR models by applying it to four diverse literature datasets. We describe the algorithm and compare model results across the four studies. We show that GPTree generates models with accuracies equivalent to or superior to those of prior modelling studies on the same datasets. GPTree is a robust, automatic method for generation of accurate nanoSAR models with important advantages that it works with small datasets, automatically selects descriptors, and provides significantly improved interpretability of models.
The Counseling, Self Care, Adherence Approach to Person Centered Care and Shared Decision Making: Moral Psychology, Executive Autonomy, and Ethics in Multi Dimensional Care Decisions
Venue: Health communication

This article argues that standard models of person centred care (PCC) and shared decision making (SDM) rely on simplistic, often unrealistic assumptions of patient capacities that entail that PCC/SDM might have detrimental effects in many applications. We suggest a complementary PCC/SDM approach to ensure that patients are able to execute rational decisions taken jointly with care professionals when performing self care. Illustrated by concrete examples from a study of adolescent diabetes care, we suggest a combination of moral and psychological considerations to support the claim that standard PCC/SDM threatens to systematically undermine its own goals. This threat is due to a tension between the ethical requirements of SDM in ideal circumstances and more long term needs actualized by the context of self care handled by patients with limited capacities for taking responsibility and adhere to their own rational decisions. To improve this situation, we suggest a counseling, self care, adherence approach to PCC/SDM, where more attention is given to how treatment goals are internalized by patients, how patients perceive choice situations, and what emotional feedback patients are given. This focus may involve less of a concentration on autonomous and rational clinical decision making otherwise stressed in standard PCC/SDM advocacy.
Improving Construction Labor Productivity Using Automatic Rebar Tying Gun

Rebar tying is labor intensive and expensive, with a high learning curve that restricts proficiency at the craft to a great deal of construction field experience. Obtaining this experience requires tasks that are taxing on the human body, often resulting in muscular and skeletal injuries. Previously, research and engineering controls for rebar tying/rod busting have been reasonably limited. The main contribution of this study is investigating the use of a new advanced technology to reduce the time, cost, and hazard associated with rebar tying. Hence, several experiments were conducted on the effectiveness of an automatic rebar tying gun by comparing the speed and cost effectiveness of this tool with the common industry practice of manually tying rebar with a spool of wire and pliers. The study results show that the automatic rebar tying gun could lower the learning curve, thereby reducing training times and minimizing redundant routines. By minimizing the amount of time invested in training employees, the possibility of saving time and money is apparent. However, risk reduction is also implied by the lessening of time invested in training employees. This is because resignations frequently happen before a return on the investment of training is produced, resulting in sunk costs. Various repetitive, often manual, movements required of workers have been observed to be reduced from the use of the rebar tying gun. The results of this study also shows that the automatic rebar tying gun has a potential to save time, money, and ergonomic liabilities without risking productivity.
Supervizyon Iliskisi: Psikolojik Danisma Supervizyonunda Kritik Bir Oge

Bu calismanin amaci, (a) supervizyon iliskisine dair alanyazinda bulunan kavramsal ve ampirik arastirma bulgularinin bir derlemesini sunmak, (b) supervizyon iliskisine katki saglayan ve bu iliskiyi engelleyen degiskenleri incelemek ve (c) alanyazindaki supervizyon arastirmalarinin bulgulari isiginda nitelikli supervizyon iliskisinin supervizyon surecindeki rolunu tartismaktir. Supervizyon iliskisini ilk ele alan calisma 1980'li yillarin basinda Edward S. Bordin tarafindan yapilmistir. Bordin'e gore supervizyon calisma uyumunun uc bileseni vardir. Bu bilesenler ortak anlayis gorevler ve duygusal bag 'dir. Alanyazin incelendiginde, yurtdisinda supervizyon iliskisinin niteligini ve bu iliskiyi etkileyen degiskenleri belirlemeye yonelik pek cok arastirma yapildigi gorulmektedir. Bu arastirmalarin sonuclari supervizor ile supervizyon alan kisi arasindaki supervizyon iliskisinin supervizyon alan kisinin profesyonel gelisiminde en kritik ogelerden biri oldugunu gostermistir. Ancak Turkiye'de psikolojik danisman egitiminde supervizyon iliskisi konusundaki arastirmalarin sinirli sayida oldugu gorulmektedir. Bu dogrultuda, Turkiye'de supervizyon iliskisi konusunun kesfedilmeyi bekleyen bir arastirma alani oldugu soylenebilir. Bu baglamda, bu calismanin Turkiye'de supervizyon iliskisi konusunda supervizorlere isik tutmasi ve yapilacak arastirmalara ilham vermesi beklenmektedir.
Multi Image Encryption Technique Based on Permutation of Chaotic System

Noora Shihab Ahmed Collage of Science, Department of Computer Science, Halabja University Halabja, Kurdistan, Iraq noora.ahmed1982@gmail.com Abstract The key stream generator is the key design issue of an encryption system. In this work presents an n array three key stream generators (KSI, KSII and KSIII) Based on permutation of three chaotic maps (Logistic map, Kent map and tent map) This work reviews of some image encryption algorithm and finally investigate three methods for image encryption. First algorithm is encryption of original image by using KSI system. Second algorithm relies on KSII system to randomly generate two sequences of numbers by means of selecting proper factors along with seed value. Afterwards, the randomly produced numbers are employed to permute the image by means of shuffling its rows, columns and pixels sequentially in a manner by which first sequence is utilized to shuffle rows while second sequence is utilized to shuffle columns. Afterwards masking process is achieved by means of basic XOR processes between neighboring rows and columns. This technique employs the values of the two sequences together to shuffle the pixels. Third algorithm relies on KSIII system when the same procedures returned on image encryption. The results shows that the proposed algorithm has a high security, speed and gives perfect reconstruction of the decrypted image
Multi image encryption using genetic computation
Venue: CSI Transactions on ICT

The menaces of viruses, hackers and eavesdroppers have made security to be of paramount importance. With paradigm shift of data from being textual to images, there is need for reliable, efficient and practical encryption techniques. In this paper, we propose one such novel algorithm which has its basis in genetic computation. The algorithm selects two images from the data set, applies two point crossover and mutation on the images for encryption. A secret key is generated for two point crossover and mutation independently. The proposed algorithm is elegant, fast and scalable. The biggest advantage is that of lossless decryption with multiple images encrypted simultaneously.
Real Time Benefit Analysis and Industrial Implementation for Distribution System Automation and Control
Venue: IEEE Transactions on Industry Applications

Smart grid technologies are expected to increase system efficiency and reliability using advancement in automation, communication, computation, and optimization. Several control algorithms have been developed or enhanced for operation and control of smart distribution grid. In recent years, volt/var control (VVC) algorithms have been proposed for energy saving in distribution systems due to advancement provided by smart grid automation and control. VVC helps to lower distribution feeder voltage to decrease energy consumption. However, quantification of this impact is hard due to several external factors such as weather and end users' behavior. On the other hand, existing evaluation methods of VVC algorithms are either not suitable for long term study or intrusive. This paper addresses these issues by proposing a new technique to estimate "distribution system demand without smart grid implementation" utilizing "data measured from system with smart grid implementation." Interdependence of voltage and load is considered based on estimated load characteristic. Our key contribution is developing a method for quantifying the real time energy saving of smart grid automation and control focused on VVC and implementing in an electric utility in eastern Washington, USA. The algorithm is developed using both commercial and open source software.
Functional data analysis for density functions by transformation to a Hilbert space

Functional data that are nonnegative and have a constrained integral can be considered as samples of one dimensional density functions. Such data are ubiquitous. Due to the inherent constraints, densities do not live in a vector space and, therefore, commonly used Hilbert space based methods of functional data analysis are not applicable. To address this problem, we introduce a transformation approach, mapping probability densities to a Hilbert space of functions through a continuous and invertible map. Basic methods of functional data analysis, such as the construction of functional modes of variation, functional regression or classification, are then implemented by using representations of the densities in this linear space. Representations of the densities themselves are obtained by applying the inverse map from the linear functional space to the density space. Transformations of interest include log quantile density and log hazard transformations, among others. Rates of convergence are derived for the representations that are obtained for a general class of transformations under certain structural properties. If the subject specific densities need to be estimated from data, these rates correspond to the optimal rates of convergence for density estimation. The proposed methods are illustrated through simulations and applications in brain imaging.
Characterization of Biosynthetic Pathways for the Production of the Volatile Homoterpenes DMNT and TMTT in Zea mays[OPEN]
Venue: Plant Cell

Biosynthetic pathways for the terpenes DMNT and TMTT in maize (Zea mays) and their corresponding enzymes were identified by nested association mapping of herbivore induced volatile terpenes. Plant volatiles not only have multiple defense functions against herbivores, fungi, and bacteria, but also have been implicated in signaling within the plant and toward other organisms. Elucidating the function of individual plant volatiles will require more knowledge of their biosynthesis and regulation in response to external stimuli. By exploiting the variation of herbivore induced volatiles among 26 maize (Zea mays) inbred lines, we conducted a nested association mapping and genome wide association study (GWAS) to identify a set of quantitative trait loci (QTLs) for investigating the pathways of volatile terpene production. The most significant identified QTL affects the emission of (E) nerolidol, linalool, and the two homoterpenes (E) 3,8 dimethyl 1,4,7 nonatriene (DMNT) and (E,E) 4,8,12 trimethyltrideca 1,3,7,11 tetraene (TMTT) GWAS associated a single nucleotide polymorphism in the promoter of the gene encoding the terpene synthase TPS2 with this QTL. Biochemical characterization of TPS2 verified that this plastid localized enzyme forms linalool, (E) nerolidol, and (E,E) geranyllinalool. The subsequent conversion of (E) nerolidol into DMNT maps to a P450 monooxygenase, CYP92C5, which is capable of converting nerolidol into DMNT by oxidative degradation. A QTL influencing TMTT accumulation corresponds to a similar monooxygenase, CYP92C6, which is specific for the conversion of (E,E) geranyllinalool to TMTT. The DMNT biosynthetic pathway and both monooxygenases are distinct from those previously characterized for DMNT and TMTT synthesis in Arabidopsis thaliana, suggesting independent evolution of these enzymatic activities.
AN ODORANT BINDING PROTEIN INVOLVED IN PERCEPTION OF HOST PLANT ODORANTS IN LOCUST Locusta migratoria.
Venue: Archives of insect biochemistry and physiology

Locusts, Locusta migratoria (Orthoptera: Acrididae) are extremely destructive agricultural pests, but very little is known of their molecular aspects of perception to host plant odorants including related odorant binding proteins (OBPs) though several OBPs have been identified in locust. To elucidate the function of LmigOBP1, the first OBP identified from locust, RNA interference was employed in this study to silence LmigOBP1, which was achieved by injection of dsRNA targeting LmigOBP1 into the hemolymph of male nymphs. Compared with LmigOBP1 normal nymphs, LmigOBP1 knockdown nymphs significantly decreased food (maize leaf, Zea mays) consumption and electro antennography responses to five maize leaf volatiles, (Z) 3 hexenol, linalool, nonanal, decanal, and (Z) 3 hexenyl acetate) These suggest that LmigOBP1 is involved in perception of host plant odorants.
Online Tracking: A 1 million site Measurement and Analysis
Venue: CCS

We present the largest and most detailed measurement of online tracking conducted to date, based on a crawl of the top 1 million websites. We make 15 types of measurements on each site, including stateful (cookie based) and stateless (fingerprinting based) tracking, the effect of browser privacy tools, and the exchange of tracking data between different sites "cookie syncing" Our findings include multiple sophisticated fingerprinting techniques never before measured in the wild. This measurement is made possible by our open source web privacy measurement tool, OpenWPM, which uses an automated version of a full fledged consumer browser. It supports parallelism for speed and scale, automatic recovery from failures of the underlying browser, and comprehensive browser instrumentation. We demonstrate our platform's strength in enabling researchers to rapidly detect, quantify, and characterize emerging online tracking behaviors.
Online monitoring of a pipe conveyor. Part I: Measurement and analysis of selected operational parameters

The need to maximize the performance and operational reliability of ecological continuous conveyor systems is increasing nowadays and their requirements are difficult to fulfil. One of the main reasons to this is the complexity of ecological continuous conveyor systems. Regular tracking and monitoring of systems selected parameters and indicators support their proper functioning and operational reliability. However, the process becomes useless if the parameters are not tracked and evaluated. The paper shall present the results of research aimed at determination of evaluation criteria for selected parameters. The research was carried out by a method of experimental measurement on an experimental rig the construction of which is similar to the construction of real pipe conveyors used in practice. Some of the convenient parameters to be tracked on a tube conveyor are a tension force and contact forces on hexagonal idler housing. The paper aims to track the course of contact forces and their mutual relations with intensity of tension forces. In order to create a comprehensive evaluation and analysis of the research, the experimental measurements were carried out for two cases, with and without material. The experimental tests are evaluated with the use of basic mathematical and statistics methods.
Rotating blade vibration analysis using photogrammetry and tracking laser Doppler vibrometry

Online structural dynamic analysis of turbomachinery blades is conventionally done using contact techniques such as strain gauges for the collection of data. To transfer the captured data from the sensor to the data logging system, installation of telemetry systems is required. This is usually complicated, time consuming and may introduce electrical noise into the data. In addition, contact techniques are intrusive by definition and can introduce significant local mass loading. This affects the integrity of the captured measurements. Advances in technology now allow for the use of optical non contact methods to analyse the dynamics of rotating structures. These include photogrammetry and tracking laser Doppler vibrometry (TLDV) Various investigations to establish the integrity of photogrammetry measurements for rotating structures involved a comparison to data captured using accelerometers. Discrepancies that were noticed were attributed to the intrusive nature of the contact measurement technique. As an extended investigation, the presented work focuses on the validation of photogrammetry applied to online turbomachinery blade measurements, using TLDV measurements. Through a frequency based characterisation approach of the dynamics of the two scanning mirrors inside the scanning head of a scanning laser Doppler vibrometer (SLDV) TLDV is employed in developing a system that can be used to achieve a perfect circular scan with a Polytec SLDV, (PSV 300) Photogrammetry out of plane displacements of a laser dot focused on a specific point on a rotating blade are compared to displacements captured by the laser scanning system. It is shown that there is good correlation between the two measurement techniques when applied to rotating structures, both in the time and frequency domains. The presence of slight discrepancies between the two techniques after elimination of accelerometer based errors illustrated that the optical system noise floor of photogrammetry does contribute to inconsistencies between photogrammetry and other measurement techniques.
Identification of asymmetric conditional heteroscedasticity in the presence of outliers

The identification of asymmetric conditional heteroscedasticity is often based on sample cross correlations between past and squared observations. In this paper we analyse the effects of outliers on these cross correlations and, consequently, on the identification of asymmetric volatilities. We show that, as expected, one isolated big outlier biases the sample cross correlations towards zero and hence could hide true leverage effect. Unlike, the presence of two or more big consecutive outliers could lead to detecting spurious asymmetries or asymmetries of the wrong sign. We also address the problem of robust estimation of the cross correlations by extending some popular robust estimators of pairwise correlations and autocorrelations. Their finite sample resistance against outliers is compared through Monte Carlo experiments. Situations with isolated and patchy outliers of different sizes are examined. It is shown that a modified Ramsay weighted estimator of the cross correlations outperforms other estimators in identifying asymmetric conditionally heteroscedastic models. Finally, the results are illustrated with an empirical application.
Risk Factors for Childhood Obesity in the First 1,000 Days: A Systematic Review.
Venue: American journal of preventive medicine

Mounting evidence suggests that the origins of childhood obesity and related disparities can be found as early as the "first 1,000 days" the period from conception to age 2 years. The main goal of this study is to systematically review existing evidence for modifiable childhood obesity risk factors present from conception to age 2 years.  PubMed, Embase, and Web of Science were searched for studies published between January 1, 1980, and December 12, 2014, of childhood obesity risk factors present during the first 1,000 days. Prospective, original human subject, English language research with exposure occurrence during the first 1,000 days and with the outcome of childhood overweight or obesity (BMI =85th percentile for age and sex) collected between age 6 months and 18 years were analyzed between December 13, 2014, and March 15, 2015. EVIDENCE SYNTHESIS Of 5,952 identified citations, 282 studies met inclusion criteria. Several risk factors during the first 1,000 days were consistently associated with later childhood obesity. These included higher maternal pre pregnancy BMI, prenatal tobacco exposure, maternal excess gestational weight gain, high infant birth weight, and accelerated infant weight gain. Fewer studies also supported gestational diabetes, child care attendance, low strength of maternal infant relationship, low SES, curtailed infant sleep, inappropriate bottle use, introduction of solid food intake before age 4 months, and infant antibiotic exposure as risk factors for childhood obesity.  Modifiable risk factors in the first 1,000 days can inform future research and policy priorities and intervention efforts to prevent childhood obesity.
Mutual Assistance System for Automobile Safety

Advanced driver assistance systems (ADAS) are effective measures for reducing the risk of traffic accidents. This paper provides evaluation results for ADAS using the mutual assistance paradigm, in which drivers mutually assist each other for automobile safety. The goal of the mutual assistance system is not only to reduce the risk of traffic accidents but also to improve the driver's attitude. In this research, evaluation of an assistance system was performed with a driving simulator. The experimental results revealed that the automation level of the mutual assistance system heavily changed the driver's attitude. The semi automatic system was more effective than the fully automatic system for making positive attitude changes. In addition, the semi automatic system was the most effective for decreasing the driver collision rate. Therefore, the semi automatic system with some voluntary actions was most suitable for the mutual assistance system and can possibly restrain risk compensation behavior.