nils-herrmann/clean_scirepeval huggingface dataset:
Robust Bayesian Inference for Gas Identification in Electronic Nose Applications by Using Random Matrix Theory
Venue: IEEE Sensors Journal

Finding a rapid gas identification algorithm with high accuracy and a closed form solution that does not require any manual tuning of parameters is the major challenge to overcome in adopting electronic nose technology in daily life applications. Recently, bio inspired rank order based classifiers have been proposed to meet this challenge by transforming multidimensional sensitivity vectors into temporally ordered spike sequences for target gases. The performance of these classifiers, however, is limited when the spike sequences corresponding to all the target gases do not contain sufficient discriminatory information to identify them. Moreover, their identification decision is delayed up to the computation of the sensitivity vectors at steady state, which incurs a long waiting time. In this paper, we adopt a Bayesian parametric method with a normal distribution model as an alternative approach that provides a closed form solution with only second order statistics, i.e. mean and covariance. However, for electronic nose applications, a reliable estimation of the covariance matrix is a major challenge with the commonly used maximum likelihood estimate in Bayesian inference because of the limited number of available measurements for each target gas. We exploit random matrix theory principles to reduce randomness in the sample covariance matrix for its reliable estimation. Moreover, transient features are used to accelerate the gas identification. In order to validate the effectiveness of this approach, data of eight gases, namely, C3H8, C6H6, CH2O, CL2, CO, CO2, NO2, and SO2, are acquired in the laboratory. We achieve a 7.73% performance improvement as compared with Bayesian inference using the maximum likelihood estimate, and an overall accuracy rate of 99.40% on the experimental data set.
Group work activities for improving speaking skills

This study was conducted at SMAN 2 Sigli to improve speaking skills in English through group work activities with the third year students of XII IPA1 through a Classroom Action Research project. Before this study was conducted, only 25% of the students met the speaking target test or Minimal Grade Criteria Kriteria Ketuntasan Minimal or KKM) which was 75. The researcher and the collaborator worked together in designing a new lesson plan, implementing the actions and making conclusions and reflections. The study was done in three cycles by following action research procedures: planning an action, implementing the plan, observing the action, and reflecting. To collect the data, observation sheets, tests and a questionnaire were used as instruments. The findings showed that group work activities were effective for improving the students' ability in speaking and the teacher's performance in teaching speaking as well. From the pre test the highest score was 80 and the lowest 60 while from the post test after the third cycle the highest score was 95 and the lowest was 70. This means that most of the students improved a lot in speaking. Also the results from the observations of the teacher, started from 58% and increased to 75% and 86% and for the students from 56% increased to 68% and 84% from the first cycle to the second and then the third cycle. The result of this research also indicates that the students responded very well towards the implementation of the group work activities. Based on these findings, it is suggested that other English teachers should use group work activities for the teaching of speaking English at schools. since they are get better results
3D Reconstruction Survey of Complex Informal Settlements Towards an understanding of the genesis of form

The Brazilian favelas are a kind of informal settlements characterized by steep topography and a maze like structure. Like many other settlements of its kind that are prevalent in developing countries today, they are often considered a problem rather than a solution. This paper is part of a larger research that taking a realistic stand aims to understand the formal structure of this city shaping force and capture it into a rule based, computational model. The goal is to develop appropriate requalifying procedures to intervene in informal settlements and guidelines for designing formal settlements in similar sites. The paper is focused on the use of digital technologies to reconstruct in 3D a favela used as a case study, a preliminary step to understand its formal structure and create a computational model.
Video based 3D reconstruction, laparoscope localization and deformation recovery for abdominal minimally invasive surgery: a survey
Venue: The international journal of medical robotics computer assisted surgery MRCAS

The intra operative three dimensional (3D) structure of tissue organs and laparoscope motion are the basis for many tasks in computer assisted surgery (CAS) such as safe surgical navigation and registration of pre operative and intra operative data for soft tissues.
Taxonomy of 3D Sensors A Survey of State of the Art Consumer 3D Reconstruction Sensors and their Field of Applications
Venue: VISIGRAPP

Sensors used for 3D reconstruction determine both the quality of the results and the nature of reconstruction algorithms. The spectrum of such sensors ranges from expensive to low cost, from highly specialized to out of the shelf, and from stereo to mono sensors. The list of available sensors has been growing steadily and is becoming difficult to manage, even in the consumer sector. We provide a survey of existing consumer 3D sensors and a taxonomy for their assessment. This taxonomy provides information about recent developments, application domains and functional criteria. The focus of this survey is on low cost 3D sensors at an accessible price. Prototypes developed in academia are also very interesting, but the price of such sensors can not easily be estimated. We try to provide an unbiased basis for decision making for specific 3D sensors. In addition to the assessment of existing technologies, we provide a list of preferable features for 3D recon struction sensors. We close with a discussion of common problems in available sensor systems and discuss common fields of application, as well as areas which could benefit from the application of such sensors.
Efficiency of the machine grading of chestnut structural timber: prediction of strength classes by dry and wet measurements

Sweet chestnut is a timber species used for construction since many centuries thanks to its good mechanical performances and its natural durability. The use as solid timber is historical in many Mediterranean countries, but today it needs to be strength graded if applied as structural product. Visual grading have been recently developed, but machine grading could allow a more efficient use of the material and could be a first step also for the implementation of structural engineered products. Therefore, this paper analyse the machine grading of chestnut timber, deriving the machine settings according the European regulations, highlighting weaknesses and strengths, and verifying the feasibility of the strength grading on wet timber. Both the dynamic modulus of elasticity and the merely frequency of vibration were compared as different machine indicating properties. There were 781 timber pieces collected and tested, with different cross sections and these were divided into four sub samples originating from the southern, central and northern regions of Italy. Both D and C strength classes (EN 338, Structural timber strength classes, 2009) were included in the calculations and the causes of wrong upgrading were analysed. Machine grading performed satisfactory, several class combinations were possible and higher strength classes were attainable when compared with the visual grading process, which allows sorting of only one strength grade. The assignment to C classes allowed for higher yields in upper classes, while the D upper classes were unpredictable by the only frequency measurement. Machine grading performed directly on wet timber achieved comparable yields to dry grading, but practically could be carried out only by means of dynamic modulus measurement.
Sex Differences in Physician Salary in US Public Medical Schools.
Venue: JAMA internal medicine

Limited evidence exists on salary differences between male and female academic physicians, largely owing to difficulty obtaining data on salary and factors influencing salary. Existing studies have been limited by reliance on survey based approaches to measuring sex differences in earnings, lack of contemporary data, small sample sizes, or limited geographic representation.  To analyze sex differences in earnings among US academic physicians.  Freedom of Information laws mandate release of salary information of public university employees in several states. In 12 states with salary information published online, salary data were extracted on 10 241 academic physicians at 24 public medical schools. These data were linked to a unique physician database with detailed information on sex, age, years of experience, faculty rank, specialty, scientific authorship, National Institutes of Health funding, clinical trial participation, and Medicare reimbursements (proxy for clinical revenue) Sex differences in salary were estimated after adjusting for these factors.  Physician sex.  Annual salary.  Among 10 241 physicians, female physicians (n 3549) had lower mean (SD) unadjusted salaries than male physicians $206 641 $88 238] vs $257 957 $137 202] absolute difference, $51 315 [95% CI, $46 330 $56 301] Sex differences persisted after multivariable adjustment $227 783 [95% CI, $224 117 $231 448] vs $247 661 [95% CI, $245 065 $250 258] with an absolute difference of $19 878 [95% CI, $15 261 $24 495] Sex differences in salary varied across specialties, institutions, and faculty ranks. For example, adjusted salaries of female full professors $250 971 [95% CI, $242 307 $259 635] were comparable to those of male associate professors $247 212 [95% CI, $241 850 $252 575] Among specialties, adjusted salaries were highest in orthopedic surgery $358 093 [95% CI, $344 354 $371 831] surgical subspecialties $318 760 [95% CI, $311 030 $326 491] and general surgery $302 666 [95% CI, $294 060 $311 272] and lowest in infectious disease, family medicine, and neurology (mean income, $200 000) Years of experience, total publications, clinical trial participation, and Medicare payments were positively associated with salary.  Among physicians with faculty appointments at 24 US public medical schools, significant sex differences in salary exist even after accounting for age, experience, specialty, faculty rank, and measures of research productivity and clinical revenue.
Education Job Match, Salary, and Job Satisfaction Across the Public, Non Profit, and For Profit Sectors: Survey of recent college graduates

Using data from the 2006 Survey of Recent College Graduates, this study examines how education job match and salary may explain recent college graduates' job satisfaction in the public, non profit, and for profit sectors. The results imply that while education job match increases job satisfaction in all three sectors, for profit workers may compensate the loss in job satisfaction due to poor match with increased satisfaction from higher salary. The findings suggest that, in the public and non profit sectors, increased salary cannot make up the loss in job satisfaction from poor education job match as much as it does in the for profit sector.
Salary, Performance, and Superintendent Turnover

Superintendent retention is an important goal for many school districts, yet the factors contributing to superintendent turnover are poorly understood. Most prior quantitative studies of superintendent turnover have relied on small, cross sectional samples, limiting the evidence base. Utilizing longitudinal administrative records from Missouri, we employ panel methods to investigate factors that predict turnover, including superintendent salary and district performance.  We model turnover probability as a function of superintendent and district characteristics. Further investigation differentiates types of turnover, including movement to other superintendent positions and exits from the system. A series of binary and multinomial regression models with district, labor market, and/or superintendent fixed effects are estimated.  Like prior cross sectional work, we find that district characteristics such as size and student race/ethnicity predict superintendent turnover, but only before district fixed effects are included. Districts with lower test scores also have higher rates of turnover, though we also find surprising evidence of nonlinearities, with lower turnover in the lowest performing districts. Superintendent salary is an especially strong turnover predictor; even with district and superintendent fixed effects, higher paid superintendents are substantially more likely to stay, an association that is even stronger in high performing districts. Moreover, moves to new superintendent positions are associated with substantial salary gains and systematic changes in district characteristics, such as increases in district size and achievement level, with rural districts losing superintendents to urban and suburban districts.  Increasing superintendent salary may be a worthwhile strategy for retaining superintendents, and may be especially important in smaller and rural districts and districts with lower student achievement whose superintendents are more likely to move to higher paying positions in larger, higher performing districts in more urban areas.
Bioremediation at a global scale: from the test tube to planet Earth
Venue: Microbial biotechnology

Planet Earth's biosphere has evolved over billions of years as a balanced bio geological system ultimately sustained by sunpower and the large scale cycling of elements largely run by the global environmental microbiome. Humans have been part of this picture for much of their existence. But the industrial revolution started in the XIX century and the subsequent advances in medicine, chemistry, agriculture and communications have impacted such balances to an unprecedented degree and the problem has nothing but exacerbated in the last 20 years. Human overpopulation, industrial growth along with unsustainable use of natural resources have driven many sites and perhaps the planetary ecosystem as a whole, beyond recovery by spontaneous natural means, even if the immediate causes could be stopped. The most conspicuous indications of such a state of affairs include the massive change in land use, the accelerated increase in the levels of greenhouse gases, the frequent natural disasters associated to climate change and the growing non recyclable waste (e.g. plastics and recalcitrant chemicals) that we release to the Environment. While the whole planet is afflicted at a global scale by chemical pollution and anthropogenic emissions, the ongoing development of systems and synthetic biology, metagenomics, modern chemistry and some key concepts from ecological theory allow us to tackle this phenomenal challenge and propose large scale interventions aimed at reversing and even improving the situation. This involves (i) identification of key reactions or processes that need to be re established (or altogether created) for ecosystem reinstallation, (ii) implementation of such reactions in natural or designer hosts able to self replicate and deliver the corresponding activities when/where needed in a fashion guided by sound ecological modelling, (iii) dispersal of niche creating agents at a global scale and (iv) containment, monitoring and risk assessment of the whole process.
Diffusion NMR studies of macromolecular complex formation, crowding and confinement in soft materials.
Venue: Progress in nuclear magnetic resonance spectroscopy

Label free methods to obtain hydrodynamic size from diffusion measurements are desirable in environments that contain multiple macromolecular species at a high total concentration: one example is the crowded cellular environment. In complex, multi species macromolecular environments in this article, we feature aqueous systems involving polymers, surfactants and proteins the link between dynamics and size is harder to unpack due to macromolecular crowding and confinement. In this review, we demonstrate that the pulsed field gradient NMR technique, with its spectral separation of different chemical components, is ideal for studying the dynamics of the entire system simultaneously and without labelling, in a wide range of systems. The simultaneous measurement of the dynamics of multiple components allows for internal consistency checks and enables quantitative statements about the link between macromolecular dynamics, size, complex formation and crowding in soft materials.
STRATEGI BELAJAR YANG TERCERMIN DALAM KESALAHAN INTERLANGUAGE SISWA MAN I SURAKARTA

The current study concerns learning strategy and its relation to interlanguage errors as Selinker believes that interlanguage errors are the result of cognitive mechanism or learning strategy used by second language learner. This specifically tries to describe the learning strategy used by the learners which result in interlanguage errors. The data are in the form of sentences containing errors taken from students' compositions. The technique used to collect the data is elicitation and documentation. The data were analyzed qualitatively. The result of the research indicates that there are three major types of learning strategy used by the learners, namely: overgeneralization, first language transfer, and simplification and the dominant learning strategy is overgeneralization. This implies that the students have relied more on their linguistic knowledge on the target language (English) rather than on that of their first language. The pedagogical implication is that English teachers should have positive attitude on interlanguage errors since errors are inevitable process in foreign language learning. They must also provide appropriate training so that students are aware the differences between English and Indonesian. Such an understanding may help them eliminate the interlanguage errors and develop their interlanguage system.
Presence of thallium in the environment: sources of contaminations, distribution and monitoring methods
Venue: Environmental Monitoring and Assessment

Thallium is released into the biosphere from both natural and anthropogenic sources. It is generally present in the environment at low levels; however, human activity has greatly increased its content. Atmospheric emission and deposition from industrial sources have resulted in increased concentrations of thallium in the vicinity of mineral smelters and coal burning facilities. Increased levels of thallium are found in vegetables, fruit and farm animals. Thallium is toxic even at very low concentrations and tends to accumulate in the environment once it enters the food chain. Thallium and thallium based compounds exhibit higher water solubility compared to other heavy metals. They are therefore also more mobile (e.g. in soil) generally more bioavailable and tend to bioaccumulate in living organisms. The main aim of this review was to summarize the recent data regarding the actual level of thallium content in environmental niches and to elucidate the most significant sources of thallium in the environment. The review also includes an overview of analytical methods, which are commonly applied for determination of thallium in fly ash originating from industrial combustion of coal, in surface and underground waters, in soils and sediments (including soil derived from different parent materials) in plant and animal tissues as well as in human organisms.
Personalized Adaptive Learning using Neural Networks
Venue: L@S

Adaptive learning is the core technology behind intelligent tutoring systems, which are responsible for estimating student knowledge and providing personalized instruction to students based on their skill level. In this paper, we present a new adaptive learning system architecture, which uses Artificial Neural Network to construct the Learner Model, which automatically models relationship between different concepts in the curriculum and beats Knowledge Tracing in predicting student performance. We also propose a novel method for selecting items of optimal difficulty, personalized to student's skill level and learning rate, which decreases their learning time by 26.5% as compared to standard pre defined curriculum sequence item selection policy.
Destructive and Transformational Leadership in Africa

The continent of Africa presents a unique context of study for leadership scholars. A vast expanse of land encompassing over 50 countries, territories, and states with over 1.1 billion people, Africa's diversity of ethnicities, cultures, and languages are both sources of richness and potential conflict. In this article, we explore examples of two leadership extremes within the context of Africa: transformational and destructive leadership. Through foundational work on transformational leadership, as well as relatively newer work on destructive leadership, we explore some of the psychological, situational, and institutional forces that account for the contrasting natures of exemplary transformational and notorious despotic African leaders. Following this contrast, we present countermeasures that can be taken to survive and thrive despite narcissistic leaders, and even the possibility of transforming them before they become truly destructive.
Creating a Stakeholder Democracy under Existing Corporate Law

Much of the current debate in corporate governance is framed in terms of stakeholder versus shareholder forms of corporate governance. While one would find little debate that stakeholders' interests are important to any business, there is substantial debate regarding whether any stakeholder besides shareholders should have a formal role in corporate governance. What has been largely ignored in this debate is the issue of private ordering: since corporate law is largely enabling rather than mandatory, can stakeholder governance structures be voluntarily created within the current shareholder centric default corporate law structure? This article argues that this is clearly the case, sets forth specific methods for how this can be accomplished, and discusses the implications this has for stakeholder democracy and other stakeholder centric corporate law reforms which have been put forth.
Robot Motion Planning on a Chip
Venue: Robotics: Science and Systems

We describe a process that constructs robot specific circuitry for motion planning, capable of generating motion plans approximately three orders of magnitude faster than existing methods. Our method is based on building collision detection circuits for a probabilistic roadmap. Collision detection for the roadmap edges is completely parallelized, so that the time to determine which edges are in collision is independent of the number of edges. We demonstrate planning using a 6 degreeof freedom robot arm in less than 1 millisecond.