Miracle-dz/UniFAR-FTUs huggingface dataset:
Large-scale model quality assessment for improving protein tertiary structure prediction

Motivation: Sampling structural models and ranking them are the two major challenges of protein structure prediction. Traditional protein structure prediction methods generally use one or a few quality assessment (QA) methods to select the best-predicted models, which cannot consistently select relatively better models and rank a large number of models well. Results: Here, we develop a novel large-scale model QA method in conjunction with model clustering to rank and select protein structural models. It unprecedentedly applied 14 model QA methods to generate consensus model rankings, followed by model refinement based on model combination (i.e. averaging). Our experiment demonstrates that the large-scale model QA approach is more consistent and robust in selecting models of better quality than any individual QA method. Our method was blindly tested during the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM group. It was officially ranked third out of all 143 human and server predictors according to the total scores of the first models predicted for 78 CASP11 protein domains and second according to the total scores of the best of the five models predicted for these domains. MULTICOM’s outstanding performance in the extremely competitive 2014 CASP11 experiment proves that our large-scale QA approach together with model clustering is a promising solution to one of the two major problems in protein structure modeling. Availability and implementation: The web server is available at: http://sysbio.rnet. missouri.edu/multicom_cluster/human/. Contact: chengji@missouri.edu
Web service workflow selection using system and network QoS constraints

Web services serve as a leading technology platform for web-based data-centric environments providing flexibility of loose coupling, message-based communication. Interest in more efficient web services selection strategies is rather requisite especially from the business process workflow perspective. We present several strategies to efficiently select a set of web services performing a workflow, fulfilling quality specifications at all workflow steps. The focus is on finding the best performing web service given a history of the execution times and current measured variation in operating system and network resource consumption. To assess their efficiency, we experimentally evaluate them and present comparative results, which strongly indicate that they can effectively reduce the overall workflow execution time in a web service-based workflow with QoS constraints. Approaches are presented for a number of workflows depending on their particular characteristics.
Underwater propulsion using surface tension

While the locomotion of terrestrial snails is relatively well-understood, the locomotion of their marine counterparts is not. Terrestrial snails are able to propel themselves forward on a thin film of secreted fluid – pedal mucus – through foot contractions that propagate along the length of the foot. Pedal waves propagating in the direction of snail motion are called ”direct waves”; ”retrograde waves” travel in the other direction. Because the mucus is a shear-thinning fluid with a finite yield stress, shear waves caused by the foot motion results in flow near the foot, while fluid far from the foot is effectively glued to the solid substrate. Interestingly, marine snails not only able to travel on solid substrates, but also inverted on the underside of water (see Fig. 1). The snails have been observed to employ various modes of locomotion: both retrograde and direct waves (though predominantly retrograde), swimming, and ciliary motion [1]. The kind of motion used appears to be species-dependent. However, the pedal waves of marine snails must generate traction on the underside of water in a manner different to terrestrial locomotion, since the free surface cannot support a shear stress. To date, only one quantitative explanation has been offered for the phenomenon [1]. In the proposed mechanism, pedal waves induce deformations of the free surface, which is coupled to the topography of the snail foot. The resultant free surface is non-periodic, leading to pressure forces on the foot due to the pressure change across the curved surface. Additionally, viscous shear forces
Channel Adaptive Quantization for Limited Feedback MIMO Beamforming Systems

Multiple-input multiple-output (MIMO) wireless systems can achieve significant diversity and array gain by using transmit beamforming and receive combining techniques. In the absence of full channel knowledge at the transmitter, the transmit beamforming vector can be quantized at the receiver and sent to the transmitter using a low-rate feedback channel. In the literature, quantization algorithms for the beamforming vector are designed and optimized for a particular channel distribution, commonly the uncorrelated Rayleigh distribution. When the channel is not uncorrelated Rayleigh, however, these quantization strategies result in a degradation of the receive signal-to-noise ratio (SNR). In this paper, switched codebook quantization is proposed where the codebook is dynamically chosen based on the channel distribution. The codebook adaptation enables the quantization to exploit the spatial and temporal correlation inherent in the channel. The convergence properties of the codebook selection algorithm are studied assuming a block-stationary model for the channel. In the case of a nonstationary channel, it is shown using simulations that the selected codebook tracks the distribution of the channel resulting in improvements in SNR. Simulation results show that in the case of correlated channels, the SNR performance of the link can be significantly improved by adaptation, compared with nonadaptive quantization strategies designed for uncorrelated Rayleigh-fading channels
Enhancing Chlorination Fundamentals for Water Treatment Technology IV course Using on-line multi-media

The current paper demonstrates the use of on-line multi-media, i.e. “chlorination of natural waters” and “dissociation of weak acids” from Merlot database, to enhance teaching and learning for Water Treatment Technology IV course material. This database focuses on fundamental concepts for chlorination as one of the most prominent disinfection treatment technology processes in the world and in South Africa. The course is part of the curriculum for the bachelor of technology degree in civil engineering, water specialisation at the University of South Africa (Unisa). The evaluation of these Merlot learning objects shows that accessibility, interaction usability, learning goal alignment, adaptation and motivation may be achieved during learning.
AN EFFICIENT REPRESENTATION MODEL OF DISTANCE DISTRIBUTION BETWEEN UNCERTAIN OBJECTS

In this paper, we consider the problem of efficient computation of distance between uncertain objects. In many real life applications, data like sensor readings and weather forecasts are usually uncertain when they are collected or produced. An uncertain object has a probability distribution function (PDF) to represent the probability that it is actually located in a particular location. A fast and accurate distance computation between uncertain objects is important to many uncertain query evaluation (e.g., range queries and nearest‐neighbor queries) and uncertain data mining tasks (e.g., classifications, clustering, and outlier detection). However, existing approaches involve distance computations between samples of two objects, which is very computationally intensive. On one hand, it is expensive to calculate and store the actual distribution of the possible distance values between two uncertain objects. On the other hand, the expected distance (the weighted average of the pairwise distances among samples of two uncertain objects) provides very limited information and also restricts the definitions and usefulness of queries and mining tasks. In this paper, we propose several approaches to calculate the mean of the actual distance distribution and approximate its variance. Based on these, we suggest that the actual distance distribution could be approximated using a standard distribution like Gaussian or Gamma distribution. Experiments on real data and synthetic data show that our approach produces an approximation in a very short time with acceptable accuracy (about 90%). We suggest that it is practical for the research communities to define and develop more powerful queries and data mining tasks based on the distance distribution instead of the expected distance.
The Use of Parallelism to Implement a Heuristic Search

The role of parallel processing in heuristic search is examined by means of an example (cryptarithmetic addition). A problem solver is constructed that combines the metaphors of constraint propagation and hypothesize-and-test. The system is capable of working on many incompatible hypotheses at one time. Furthermore, it is capable of allocating different amounts of processing power to running activities and changing these allocations as computation proceeds. It is empirically found that the parallel algorithm is, on the average, more efficient than a corresponding sequential one. Implication* of this for problem solving in general are discussed.
Distributed Knowledge in Crowds: Crowd Performance on Hidden Profile Tasks

Individuals today discuss information and form judgements as crowds in online communities and platforms. "Wisdom of the crowd" arguments suggest that, in theory, crowds have the capacity to bring together diverse expertise, pooling distributed knowledge and thereby solving challenging and complex problems. This paper concerns one way that crowds might fall short of this ideal. A large body of research in the social psychology of small groups concerns the shared information bias, a tendency for group members to focus on common knowledge at the expense of rarer information which only one or a few individuals might possess. We investigated whether this well-known bias for small groups also impacts larger crowds of 30 participants working on Amazon’s Mechanical Turk. We found that crowds failed to adequately pool distributed facts; that they were partially biased in how they shared facts; and that individual perception of group decisions was unstable. Nonetheless, we found that aggregating individual reports from the crowd resulted in moderate performance in solving the assigned task.
A Contemporary Framework for Studying Persons

As the scientific study of the individual person, personality psychology historically has struggled to provide the kind of broad conceptual framework capable of orienting theory and research around human individuality in cultural context. This article presents a new integrative frameworkfor studying persons that brings together recent advances in thefield of personality with the emerging social science emphasis on the narrative study of lives, while situating personality inquiry within the cultural context of contemporary modernity and the unique problems of the modem self The framework builds on a cleardistinction between the "I" and the "Me "features ofpersonality in the modem world and the delineation of three relatively independent levels on which modern persons may be described. In personality, the I may be viewed as the process of "selfing, " of narrating experience to create a modern self, whereas the Me may be viewed as the self that the I constructs. Personality traits, like those included within the Big Five taxonomy, reside at Level I of personality description and provide a general, comparative, and nonconditional dispositional signature for the person. Level II subsumes tasks, goals, projects, tactics, defenses, values, and other developmental, motivational, and/or strategic concerns that contextualize a person's life in time, place, and role. Speaking directly to the modern problem of reflexively creating a unified and purposeful configuration of the Me, life stories reside at the third level ofpersonality, as internalized integrative narrations of the personal past, present, and future. It is mainly through the psychosocial construction of life stories that modern adults create identity in the Me. Life stories may be examined in terms of their structure and content, function, development, individual differences, and relation to mental health and psychosocial adaptation.
Climate control on sulphate and nitrate concentrations in alpine streams of Northern Italy along a nitrogen saturation gradient

The role of meteorology, hydrology and atmo- spheric deposition on the temporal pattern of SO4 and NO3 concentrations was investigated for three streams draining alpine catchments in Northern Italy. The study sites lie on a gradient of atmospheric fluxes of SO4 and NO3 (from about 50 to 80 meq m 2 y 1 , and from 40 to 90 meq m 2 y 1 , respectively). As a consequence of the increasing N input, the three catchments are also repre- sentative of aggrading levels of N saturation. Different meth- ods of statistical analysis were applied to monthly data for the period 1997-2005 to identify which variables (temperature, precipitation, hydrology, SO4 and NO3 deposition) were the main predictors of water chemistry and its change in time. Hydrological changes and snow cover proved to be the main confounding factors in the response to atmospheric deposi- tion in the River Masino catchment. Its particular character- istics (small catchment area, rapid flushing during runoff and thin soil cover) meant that this site responded without a sig- nificant delay to SO 4 deposition decrease. It also showed a clear seasonal pattern of NO3 concentration, in response to hydrology and biological uptake in the growing season. The selected driving variables failed to model the water chemistry at the other study sites. Nevertheless, tempera- ture, especially extreme values, turned out to be important in both SO4 and NO3 export from the catchments. This re- sult might be largely explained by the effect of warm periods on temperature-dependent processes such as mineralization, nitrification and S desorption. Our findings suggest that surface waters in the alpine area will be extremely sensitive to a climate warming scenario: higher temperatures and increasing frequency of drought could exacerbate the effects of high chronic N deposition.
Development of a bedside viable ultrasound protocol to quantify appendicular lean tissue mass

Ultrasound is a non‐invasive and readily available tool that can be prospectively applied at the bedside to assess muscle mass in clinical settings. The four‐site protocol, which images two anatomical sites on each quadriceps, may be a viable bedside method, but its ability to predict musculature has not been compared against whole‐body reference methods. Our primary objectives were to (i) compare the four‐site protocol's ability to predict appendicular lean tissue mass from dual‐energy X‐ray absorptiometry; (ii) optimize the predictability of the four‐site protocol with additional anatomical muscle thicknesses and easily obtained covariates; and (iii) assess the ability of the optimized protocol to identify individuals with low lean tissue mass.
The eugenics movement and its impact on art education in the United States

ABSTRACT This article argues that the eugenics movement has had three major influences on education in the United States, and reveals how these influences have had an impact on visual arts education in particular. The first influence began with a debate between John Dewey and David Snedden that resulted in a two-tiered tracking system that separated college bound and vocational students. The second is the influence of eugenics on the establishment of the hierarchical framework for the public school curriculum. The third influence of eugenics discussed in this article is its impact on standardized testing. These influences have justified American imperialism in schools, and have led to the marginalization of visual arts education in the United States.
Chapter 5 Privacy , Trust and Incentives in Participatory Sensing

In this chapter, we study the socioeconomic issues that can arise in distributed computing environments such as distributed and open, participatory sensing systems. Due to the decentralized nature of such systems, they present many challenges, some of which are equally socioeconomic and technical in essence. Three such major challenges arise in participatory sensing, one economic and two social. The economic problem is centered around the provision of incentives. How can participants be provided with incentives to ensure that they contribute to the system; that they provide sensed data when requested; and take part in various sensing activities? The social problems are related to issues of Trust and Privacy. Trust issues revolve around determining which participants send accurate and truthful data and consequently which participants could be deemed more reliable. Privacy issues revolve around the fact that participants by taking an active part in sensing campaigns, risk exposing private details about themselves, such as their location at particular points in time. In practice all three challenges are interlinked. For example, in order to ensure participants privacy, a system could provide anonymization of the users’ identity. However, given that every node/participant is anonymized, it becomes harder to put in place an effective trust mechanism, which requires the identification of both trustworthy nodes and malicious/unreliable ones. In the same vein, system designers can use incentive schemes to incentivize users to sacrifice their privacy so that an efficient trust mechanism could be put in place.
Some approaches to the issue of subjective aspects of the quality of life

The concept of the measurement of quality of life is used to evaluate the general state of well-being of individual persons and society. The quality of life should not be exchanged with the concept of standard of living, which is primarily based on income. The objective quality of life issues are based on measurements of so called "hard data", i.e. data from institutions and organizations that include financial accounts, civil records, medical statistics, pollution and other information that are routinely collected. Subjective aspect of quality of life is evaluated on the degree of satisfaction with various items and needs. This is a category associated with subjective perceptions of their lives within a system of values and within certain social, economic and political conditions. Subjective indicators (feelings of happiness, satisfaction, etc.) are usually measured and evaluated on the basis of quantitative and qualitative research. Some results of the survey of quality of life are shown in this paper. Several results of a survey conducted point on the subjective perception for example safety and other factors.
When political candidates “go positive”: the effects of flattering the rival in political communication

Abstract In the field of political communication, the effects of negative propaganda strategies have been long studied. In the current work, I investigated the perceived and actual persuasiveness of an unexplored positive propaganda strategy, i.e., addressing a flattery to the rival in a political speech. In a 2 × 2 full-factorial design experiment, a fictitious candidate (a man or a woman) flattered, or did not flatter, an opponent in a political speech. Results showed that when the candidate flattered a rival s/he influenced the likelihood of being voted through source trustworthiness evaluation, irrespective of the candidate’s gender. Theoretical and practical implications are discussed.
Born Weak, Growing Strong: Anti‐Government Protests as a Signal of Rebel Strength in the Context of Civil Wars

All rebel organizations start weak, but how do they grow and achieve favorable conflict outcomes? We present a theoretical model that allows for rebel organizations to gain support beyond their “core” and build their bargaining power during fighting. We highlight that rebel organizations need to win over crucial parts of society to generate the necessary support that allows them to attain favorable civil conflict outcomes. We find empirical support for the argument that lowincome individuals who initially fight the government (rebel organizations) have to convince middle-class individuals to turn out against the government to gain government concessions. Empirically, we demonstrate that government concessions in the form of peace agreements and the onset of negotiations become more likely when protest occurs in the context of civil
Advances in Medical Education and Practice Dovepress Do Medical Students' Scores Using Different Assessment Instruments Predict Their Scores in Clinical Reasoning Using a Computer-based Simulation?

Purpose: The development of clinical problem-solving skills evolves over time and requires structured training and background knowledge. Computer-based case simulations (CCS) have been used for teaching and assessment of clinical reasoning skills. However, previous studies examining the psychometric properties of CCS as an assessment tool have been controversial. Furthermore, studies reporting the integration of CCS into problem-based medical curricula have been limited. Methods: This study examined the psychometric properties of using CCS software (DxR Clinician) for assessment of medical students (n=130) studying in a problem-based, integrated multisystem module (Unit IX) during the academic year 2011–2012. Internal consistency reliability of CCS scores was calculated using Cronbach's alpha statistics. The relationships between students' scores in CCS components (clinical reasoning, diagnostic performance, and patient management) and their scores in other examination tools at the end of the unit including multiple-choice questions, short-answer questions, objective structured clinical examination (OSCE), and real patient encounters were analyzed using stepwise hierarchical linear regression. Results: Internal consistency reliability of CCS scores was high (α=0.862). Inter-item correlations between students' scores in different CCS components and their scores in CCS and other test items were statistically significant. Regression analysis indicated that OSCE scores predicted 32.7% and 35.1% of the variance in clinical reasoning and patient management scores, respectively (P,0.01). Multiple-choice question scores, however, predicted only 15.4% of the variance in diagnostic performance scores (P,0.01), while students' scores in real patient encounters did not predict any of the CCS scores. Conclusion: Students' scores in OSCE are the most important predictors of their scores in clinical reasoning and patient management using CCS. However, real patient encounter assessment does not appear to test a construct similar to what is tested in CCS.
On Enabling Sustainable Edge Computing with Renewable Energy Resources

The emergent paradigm of edge computing advocates that computational and storage resources can be extended to the edge of the network so that the impact of data transmission latency over the Internet can be effectively reduced for time-constrained Internet of Things applications. With the widespread deployment of edge computing devices, the energy demand of these devices has increased and started to become a noticeable issue for the suitable development of urban systems. In this article, we propose a unified energy management framework for enabling a sustainable edge computing paradigm with distributed renewable energy resources. This framework supports cooperation between the energy supply system and the edge computing system so that renewable energy can be fully utilized while offering improved quality of service for time-constrained IoT applications. A prototype system is also implemented by using microgrid (solar-wind hybrid energy system) and edge computing devices together. The experiment results demonstrate that renewable energy is fully capable of supporting the reliable running of edge computing devices in the prototype system during most (94.8 percent) of the experimental period when our proposed framework was employed.