nils-herrmann/clean_scirepeval huggingface dataset:
A Method of Coastline Extraction from Synthetic Aperture Radar Raw-Data

As a kind of imaging radars, synthetic aperture radar (SAR) improves its resolution by means of moving and emitting pulse repetitiously. The issues about target detection of SAR are often a ‘post-process’ of the SAR imaging. A method for coastline extraction in the state of non-imaging based on analyzing the typical algorithms of SAR imaging and target detection is presented in this paper. Experimental results indicate the validity of the algorithm for coastline extraction. The algorithms are simple, able to recurrent, and easy for real-time processing and hardware implementation.
Model Predictive Control of a Nonlinear Large-Scale Process Network Used in the Production of Vinyl Acetate

In this work, we focus on the development and application of two Lyapunov-based model predictive control (LMPC) schemes to a large-scale nonlinear chemical process network used in the production of vinyl acetate. The nonlinear dynamic model of the process consists of 179 state variables and 13 control (manipulated) inputs and features a cooled plug-flow reactor, an eight-stage gas−liquid absorber, and both gas and liquid recycle streams. The two control schemes considered are an LMPC scheme which is formulated with a convectional quadratic cost function and a Lyapunov-based economic model predictive control (LEMPC) scheme which is formulated with an economic (nonquadratic) cost measure. The economic cost measure for the entire process network accounts for the reaction selectivity and the product separation quality. In the LMPC and LEMPC control schemes, five inputs, directly affecting the economic cost, are regulated with LMPC/LEMPC and the remaining eight inputs are computed by proportional−integral controllers. Simulations are carried out to study the economic performance of the closed-loop system under LMPC and under LEMPC formulated with the proposed economic measure. A thorough comparison of the two control schemes is provided.  Vinyl acetate is mostly used in manufacturing polyvinyl acetate and other vinyl acetate copolymers. Polyvinyl acetate is the fundamental ingredient for polyvinyl alcohol and polyvinyl acetate resins. Three raw materials, ethylene (C2H4), oxygen (O2), acetic acid (HAc), react to form the desired product vinyl acetate (VAc) as well as two byproducts: carbon dioxide (CO2) and water (H2O). An inert component, ethane (C2H6), enters the process with the ethylene feed stream. The exothermic and irreversible gas phase chemical reactions are
Dark Clouds, Io&#!+, and [Crystal Ball Emoji]: Projecting Network Anxieties with Alternative Design Metaphors

This design inquiry engages concerns set within the frame of network anxieties. Our work projects and engages negative affective dimensions of digital networks including anxiety, exhaustion, overstimulation, overload, paranoia, unease, distrust, fear, and creepiness. We do this by designing alternative Internet metaphors and then applying these metaphors to the design of IoT (Internet of Things) technologies to generate speculative design proposals.
Through the HoloLens™ looking glass: augmented reality for extremity reconstruction surgery using 3D vascular models with perforating vessels

Precision and planning are key to reconstructive surgery. Augmented reality (AR) can bring the information within preoperative computed tomography angiography (CTA) imaging to life, allowing the surgeon to 'see through' the patient's skin and appreciate the underlying anatomy without making a single incision. This work has demonstrated that AR can assist the accurate identification, dissection and execution of vascular pedunculated flaps during reconstructive surgery. Separate volumes of osseous, vascular, skin, soft tissue structures and relevant vascular perforators were delineated from preoperative CTA scans to generate three-dimensional images using two complementary segmentation software packages. These were converted to polygonal models and rendered by means of a custom application within the HoloLens™ stereo head-mounted display. Intraoperatively, the models were registered manually to their respective subjects by the operating surgeon using a combination of tracked hand gestures and voice commands; AR was used to aid navigation and accurate dissection. Identification of the subsurface location of vascular perforators through AR overlay was compared to the positions obtained by audible Doppler ultrasound. Through a preliminary HoloLens-assisted case series, the operating surgeon was able to demonstrate precise and efficient localisation of perforating vessels.
High-Voltage Spark Gap in a Regime of Subnanosecond Switching

This paper describes an investigation of a high-voltage spark gap in the conditions of subnanosecond switching. The high-voltage pulsed generator “Sinus” is used to charge a coaxial line loaded to a high-pressure spark gap. Typical charging time for the coaxial line is in a range from 1 to 2 ns, maximum charging voltage is up to 250 kV, and a range of pressures for the gap is from 2 to 9 MPa. The theoretical models of the switching process on subnanosecond time scale are examined. A general equation for temporal behavior of the gap voltage, which is applicable for the avalanche model and the Rompe-Weitzel model has been obtained. It is revealed that the approach based on the avalanche model offers a possibility to describe the switching process only at extremely high overvoltages. The Rompe-Weitzel model demonstrates a good agreement with the experimental data both for the conditions of static breakdown and for the regime of a high overvolted gap. Comparison of experimental and calculated voltage waveforms has made it possible to estimate an empirical constant in the Rompe-Weitzel model (the price of ionization). This constant is varied from 420 to 920 eV, depending on the initial electric field in the gap.
State Space Model based Trust Evaluation over Wireless Sensor Networks: An Iterative Particle Filter Approach

In this paper we propose a state space modeling approach for trust evaluation in wireless sensor networks. In our state space trust model (SSTM), each sensor node is associated with a trust metric, which measures to what extent the data transmitted from this node would better be trusted by the server node. Given the SSTM, we translate the trust evaluation problem to be a nonlinear state filtering problem. To estimate the state based on the SSTM, a component-wise iterative state inference procedure is proposed to work in tandem with the particle filter, and thus the resulting algorithm is termed as iterative particle filter (IPF). The computational complexity of the IPF algorithm is theoretically linearly related with the dimension of the state. This property is desirable especially for high dimensional trust evaluation and state filtering problems. The performance of the proposed algorithm is evaluated by both simulations and real data analysis. Index Terms state space trust model, wireless sensor network, trust evaluation, particle filter, high dimensional. ✦
2 State Transition Graph ( STG )

SIS is an interactive tool for synthesis and optimization of sequential circuits. Given a state transition table, a signal transition graph, or a logic-level description of a sequential circuit, it produces an optimized net-list in the target technology while preserving the sequential input-output behavior. Many different programs and algorithms have been integrated into SIS, allowing the user to choose among a variety of techniques at each stage of the process. It is built on top of MISII  and includes all (combinational) optimization techniques therein as well as many enhancements. SIS serves as both a framework within which various algorithms can be tested and compared, and as a tool for automatic synthesis and optimization of sequential circuits. This paper provides an overview of SIS. The first part contains descriptions of the input specification, STG (state transition graph) manipulation, new logic optimization and verification algorithms, ASTG (asynchronous signal transition graph) manipulation, and synthesis for PGA’s (programmable gate arrays). The second part contains a tutorial example illustrating the design process using SIS.
Chapter 2 GIS and Remote Sensing-Based Forest Resource Assessment , Quanti fi cation , and Mapping in Amhara Region , Ethiopia

World forest resources are continually depleting. Assessing and quantifying the current forest resources status is a prerequisite for forest resources improvement planning and implementation. The objectives of this study are to assess, quantify, and map forest resources in the Amhara National Regional State, Ethiopia. GIS, GPS, and Remote Sensing technologies were applied for the study. As a result, forest distribution map is prepared. Most of the forest covers were found along the lowland belt of Mirab Gojam, Awi, and Semen Gonder zones bordering the neighboring country, Sudan and the Tigray and Benishangul-Gumz regions. The total forest cover of the region is 12,884 km, that is, about 8.2 % of the total land area. Including bushlands, it is about 21,783 km, which is about 13.85 %. Woodlands, natural dense forest, riverine forest, bushlands, and plantations are 740,808, 463,950, 20,653, 889,912, and 62,973 ha in area with percentage coverage of 4.71, 2.95, 0.13, 5.66, and 0.40 respectively. GIS, GPS, and Remote Sensing were found to be important tools for forest resource assessment and mapping. M. Mekonnen (&) M. Gebeyehu B. Azene Amhara National Regional State, Bureau of Agriculture, Natural Resource Conservation and Management Department, PO Box 1188, Bahir Dar, Ethiopia e-mail: mulatiemekonneng@gmail.com; mulatie.mekonnen@yahoo.com M. Gebeyehu e-mail: mulu_gebeyehu@yahoo.com B. Azene e-mail: aze_bayleyegn@yahoo.com T. Sewunet Amhara National Regional State, Bureau of Finance and Economic Development, Bahir Dar, Ethiopia e-mail: tsegayesewinet@gmail.com A.M. Melesse Department of Earth & Environment, Florida International University, 11200 SW 8th Street, Miami, USA e-mail: melessea@fiu.edu  Soils and Hydrological Processes in Varied Climates, Springer Geography, DOI 10.1007/978-3-319-18787-7_2 9
How do we know the minds of others? Domain-specificity, simulation, and enactive social cognition

In what ways, and to what extent, is social cognition distinguished from cognition in general? And how do data from cognitive neuroscience speak to this question? I review recent findings that argue social cognition may indeed be specialized, and at multiple levels. One particularly interesting respect in which social cognition differs from the rest of cognition is in its close interaction with the social environment. We actively probe other people in order to make inferences about what is going on in their minds (e.g., by asking them questions, and directing our gaze onto them), and we use the minds of other people as a collective resource. Experiments from our own laboratory point to the amygdala as one structure that is critically involved in such processes.
Towards the Temporally Perfect Virtual Button: Touch-Feedback Simultaneity and Perceived Quality in Mobile Touchscreen Press Interactions

Pressing a virtual button is still the major interaction method in touchscreen mobile phones. Although phones are becoming more and more powerful, operating system software is getting more and more complex, causing latency in interaction. We were interested in gaining insight into touch-feedback simultaneity and the effects of latency on the perceived quality of touchscreen buttons. In an experiment, we varied the latency between touch and feedback between 0 and 300 ms for tactile, audio, and visual feedback modalities. We modelled the proportion of simultaneity perception as a function of latency for each modality condition. We used a Gaussian model fitted with the maximum likelihood estimation method to the observations. These models showed that the point of subjective simultaneity (PSS) was 5ms for tactile, 19ms for audio, and 32ms for visual feedback. Our study included the scoring of perceived quality for all of the different latency conditions. The perceived quality dropped significantly between latency conditions 70 and 100 ms when the feedback modality was tactile or audio, and between 100 and 150 ms when the feedback modality was visual. When the latency was 300ms for all feedback modalities, the quality of the buttons was rated significantly lower than in all of the other latency conditions, suggesting that a long latency between a touch on the screen and feedback is problematic for users. Together with PSS and these quality ratings, a 75% threshold was established to define a guideline for the recommended latency range between touch and feedback. Our guideline suggests that tactile feedback latency should be between 5 and 50 ms, audio feedback latency between 20 and 70 ms, and visual feedback latency between 30 and 85 ms. Using these values will ensure that users will perceive the feedback as simultaneous with the finger's touch. These values also ensure that the users do not perceive reduced quality. These results will guide engineers and designers of touchscreen interactions by showing the trade-offs between latency and user preference and the effects that their choices might have on the quality of the interactions and feedback they design.
Staff-student relationships and their impact on nursing students' belongingness and learning.

This paper is a report of selected findings from a study exploring the relationship between belongingness and placement experiences of preregistration nursing students.



Staff-student relationships are an important influence on students' experiences of belongingness and their clinical learning. The need to belong is universal and pervasive, exerting a powerful influence on thought processes, emotions, behaviour, health and happiness. People deprived of belongingness are more likely to experience diminished self-esteem, increased stress and anxiety, depression and a decrease in general well-being. Nursing students' motivation and capacity to learn, self-concept, confidence, the extent to which they are willing to question or conform to poor practice and their future career decisions are influenced by the extent to which they experience belongingness.



During 2006, 18 third year students from two Australian universities and one United Kingdom university participated in in-depth semi-structured interviews. Data were analysed thematically.



Participants described placement experiences spanning a continuum from those promoting a high degree of belongingness to those provoking intense feelings of alienation. Staff-student relationships (including receptiveness, inclusion/exclusion, legitimization of the student role, recognition and appreciation, challenge and support) were the most important influence on students' sense of belonging and learning. Similarities between sites were remarkable, despite the differences in healthcare and higher education systems.



Staff-student relationships are key to students' experience of belongingness. Understanding the types of interactions and behaviours that facilitate or impede students' belongingness and learning are essential to the creation of positive clinical experiences.
Isolation of amniotic stem cell lines with potential for therapy

Stem cells capable of differentiating to multiple lineages may be valuable for therapy. We report the isolation of human and rodent amniotic fluid–derived stem (AFS) cells that express embryonic and adult stem cell markers. Undifferentiated AFS cells expand extensively without feeders, double in 36 h and are not tumorigenic. Lines maintained for over 250 population doublings retained long telomeres and a normal karyotype. AFS cells are broadly multipotent. Clonal human lines verified by retroviral marking were induced to differentiate into cell types representing each embryonic germ layer, including cells of adipogenic, osteogenic, myogenic, endothelial, neuronal and hepatic lineages. Examples of differentiated cells derived from human AFS cells and displaying specialized functions include neuronal lineage cells secreting the neurotransmitter L-glutamate or expressing G-protein-gated inwardly rectifying potassium channels, hepatic lineage cells producing urea, and osteogenic lineage cells forming tissue-engineered bone.
Authorship attribution for textual data on online social networks

Authorship Attribution, (AA) is a process of determining a particular document is written by which author among a list of suspected authors. Authorship attribution has been the problem from last six decades; when there were handwritten documents needed to be identified for the genuine author. Due to the technology advancement and increase in cybercrime and unlawful activities, this problem of AA becomes forth most important to trace out the author behind online messages. Over the past, many years research has been conducted to attribute the authorship of an author on the basis of their writing style as all authors possess different distinctiveness while writing a piece of document. This paper presents a comparative study of various machine learning approaches on different feature sets for authorship attribution on short text. The Twitter dataset has been used for comparison with varying sample size of a dataset of 10 prolific authors with various combinations of feature sets. The significance and impact of combinations of features while inferring different stylometric features has been reflected. The results of different approaches are compared based on their accuracy and precision values.
The streamlined cognitive walkthrough method, working around social constraints encountered in a software development company

The cognitive walkthrough method described by Wharton et al. may be difficult to apply in a large software development company because of social constraints that exist in such companies. Managers, developers, and other team members are pressured for time, tend to lapse into lengthy design discussions, and are sometimes defensive about their user-interface designs. By enforcing four ground rules, explicitly defusing defensiveness, and streamlining the cognitive walkthrough method and data collection procedures, these social constraints can be overcome, and useful, valid data can be obtained. This paper describes a modified cognitive walkthrough process that accomplishes these goals, and has been applied in a large software development company.
Characterization of semilumped CPW elements for Millimeter-wave filter design

In this paper, two accurate models for interdigital capacitors and shunt inductive stubs in coplanar-waveguide structures are presented and validated over the entire W-band frequency range. Using these models, a novel bandpass filter (BPF) and a miniaturized high-pass filter are designed and fabricated. By inserting interdigital capacitors in BPF resonators, an out-of-band transmission null is introduced, which improves rejection level up to 17 dB over standard designs of similar filters. A high-pass filter is also designed, using semilumped-element models in order to miniaturize the filter structure. It is shown that a fifth-order high-pass filter can be built with a maximum dimension of less than /spl lambda//sub g//3. Great agreement between simulated and measured responses of these filters is demonstrated.
Microwave Impedance Measurement for Nanoelectronics

The rapid progress in nanoelectronics showed an urgent need for microwave measurement of impedances extremely different from the 50Ω reference impedance of measurement instruments. In commonly used methods input impedance or admittance of a device under test (DUT) is derived from measured value of its reflection coefficient causing serious accuracy problems for very high and very low impedances due to insufficient sensitivity of the reflection coefficient to impedance of the DUT. This paper brings theoretical description and experimental verification of a method developed especially for measurement of extreme impedances. The method can significantly improve measurement sensitivity and reduce errors caused by the VNA. It is based on subtraction (or addition) of a reference reflection coefficient and the reflection coefficient of the DUT by a passive network, amplifying the resulting signal by an amplifier and measuring the amplified signal as a transmission coefficient by a common vector network analyzer (VNA). A suitable calibration technique is also presented.
An online blog reading system by topic clustering and personalized ranking

There is an increasing number of people reading, writing, and commenting on blogs. According to a recent survey made by Technorati, there are about 75,000 new blogs and 1.2 million new posts everyday. However, it is difficult and time consuming for a blog reader to find the most interesting posts in the huge and dynamic blog world. In this article, an online Personalized Blog Reader (PBR) system is proposed, which facilitates blog readers in browsing the coolest and newest blog posts of their interests by automatically clustering the most relevant stories. PBR aims to make a user's potential favorite topics always ranked higher than those nonfavorite ones. This is accomplished in the following steps. First, the system collects and provides a unified incremental index of posts coming from different blogs. Then, an incremental clustering algorithm with a flexible half-bounded window of observation is proposed to satisfy the requirements of online processing. It learns people's personalized reading preferences to present a user with a final reading list. The experimental results show that the proposed incremental clustering algorithm is effective and efficient, and the personalization of the PBR performs well.
An introduction to neural networks

Exercise 1 Regression and Widrow-Hoff learning Make a function: rline[slope_,intercept_] to generate pairs of random numbers {x,y} where x ranges between 0 and 10, and whose y coordinate is a straight line with slope, slope_ and intercept, intercept_ but perturbed by additive uniform random noise over the range -2 to 2. Generate a data set from rline with 200 samples with slope 11 and intercept 0. Use the function Fit[] to find the slope and intercept of this data set. Here is an example of how it works:
Industrial Clusters , Focal Firms , and Economic Dynamism : A Perspective from Italy

This paper discusses the role of clusters and focal firms in the economic performance of small firms in Italy. Using the example of the packaging industry of northern Italy, it shows how clusters of small firms have emerged around a few focal or leading companies. These companies have helped the clusters grow and diversify through technological and managerial spillover effects, through the provision of purchase orders, and sometimes through financial links. The role of common local training institutes, whose graduates often start up small firms within the local cluster, is also discussed.
Probable Bioweapon : Influenza Type A Virus – A Short Case Report .

Influenza type A virus (Influenza virus A), an old foe of mankind, is presently the most significant pathogen causing both pandemics and epizootics, worldwide. The proliferative husbandry of poultry and pigs, primarily, constitutes a key factor in ongoing generation of pandemic and pre-pandemic strains, which is fueled by remarkable wild aquatic bird permissiveness of the virus. Those attributes are here thoroughly inquired into, so as to profile and rate threat and usability. Also, various human interventions and misuses, including human experimental infections, undesirable vaccinations, as well as unauthorized and unskillful operations, led to bad corollaries and may rather be reassessed and modified or disallowed. Diversified interfaces between influenza and human manners are thereby brought out and elucidated, along with their lessons.