nils-herrmann/clean_scirepeval huggingface dataset:
When fast is better: protein folding fundamentals and mechanisms from ultrafast approaches
Venue: The Biochemical journal

Protein folding research stalled for decades because conventional experiments indicated that proteins fold slowly and in single strokes, whereas theory predicted a complex interplay between dynamics and energetics resulting in myriad microscopic pathways. Ultrafast kinetic methods turned the field upside down by providing the means to probe fundamental aspects of folding, test theoretical predictions and benchmark simulations. Accordingly, experimentalists could measure the timescales for all relevant folding motions, determine the folding speed limit and confirm that folding barriers are entropic bottlenecks. Moreover, a catalogue of proteins that fold extremely fast (microseconds) could be identified. Such fast folding proteins cross shallow free energy barriers or fold downhill, and thus unfold with minimal co operativity (gradually) A new generation of thermodynamic methods has exploited this property to map folding landscapes, interaction networks and mechanisms at nearly atomic resolution. In parallel, modern molecular dynamics simulations have finally reached the timescales required to watch fast folding proteins fold and unfold in silico. All of these findings have buttressed the fundamentals of protein folding predicted by theory, and are now offering the first glimpses at the underlying mechanisms. Fast folding appears to also have functional implications as recent results connect downhill folding with intrinsically disordered proteins, their complex binding modes and ability to moonlight. These connections suggest that the coupling between downhill (un)folding and binding enables such protein domains to operate analogically as conformational rheostats.
Childhood obesity: prevention is better than cure
Venue: Diabetes, metabolic syndrome and obesity targets and therapy

Obesity and its associated comorbidities have emerged as a major health problem garnering interests from both public health agencies and mainstream media consumers. With increasing awareness on its impact on health, finances, and community at large, it has come to the forefront for scientific research and development of health plans. The need for better strategies and novel interventions to manage obesity is now being recognized by the entire health care system. Obesity and overweight is now the fifth leading global risk factor for mortality. Strategic investment is thus urgently needed to implement population based childhood obesity prevention programmes which are effective and also culturally appropriate. Population based prevention is crucial to stem this rising tide of childhood obesity which is fast reaching epidemic proportions. Obesity has its onset very early in life; therefore, children constitute a major group of this disease. It is thus imperative to lay utmost importance on prevention of obesity in children and herald its progress, if present already. Furthermore, treatment is still in preliminary stage, so early prevention holds better than treatment at later stages. This article is an attempt to lay emphasis on childhood obesity as a problem that needs to be recognized early and measures for its prevention.
Associations of teacher rated social, emotional, and cognitive development in kindergarten to self reported wellbeing, peer relations, and academic test scores in middle childhood

In two longitudinal studies, we examined to what extent teacher rated social competence, emotional maturity, and language and cognitive development in kindergarten (measured with the Early Development Instrument, EDI; Janus Offord, 2007) are associated with children's self reported social relations with peers, emotional well being (measured with the Middle Years Development Instrument, MDI; Schonert Reichl et al. 2013) and numeracy and literacy (assessed with standardized achievement tests) in middle childhood. The studies were conducted using population based data linkages (N 7000) from Western Canada. Using multilevel regression analyses, we found that teacher rated social competence in kindergarten most strongly predicted 4th graders' self report of their connectedness to peers, and emotional maturity most strongly predicted emotional well being. Teacher rated cognitive and language development in kindergarten most strongly predicted 4th graders' standardized numeracy and literacy test results. We discuss our results with regard to previous findings in the literature, and address methodological and conceptual challenges in regard to examining children's early development across interdependent domains.
Hearing Loss and Cognitive Communication Test Performance of Long Term Care Residents With Dementia: Effects of Amplification.
Venue: Journal of speech, language, and hearing research JSLHR

The study aims were (a) to explore the relationship between hearing loss and cognitive communication performance of individuals with dementia, and (b) to determine if hearing loss is accurately identified by long term care (LTC) staff. The research questions were (a) What is the effect of amplification on cognitive communication test performance of LTC residents with early to middle stage dementia and mild to moderate hearing loss? and (b) What is the relationship between measured hearing ability and hearing ability recorded by staff using the Resident Assessment Instrument Minimum Data Set 2.0 (RAI MDS; Hirdes et al. 1999)  Thirty one residents from 5 long term care facilities participated in this quasiexperimental crossover study. Residents participated in cognitive communication testing with and without amplification. RAI MDS ratings of participants' hearing were compared to audiological assessment results.  Participants' speech intelligibility index scores significantly improved with amplification; however, participants did not demonstrate significant improvement in cognitive communication test scores with amplification. A significant correlation was found between participants' average pure tone thresholds and RAI MDS ratings of hearing, yet misclassification of hearing loss occurred for 44% of participants.  Measuring short term improvement of performance based cognitive communication may not be the most effective means of assessing amplification for individuals with dementia. Hearing screenings and staff education remain necessary to promote hearing health for LTC residents.
TRADITIONAL RURAL CHICKEN PRODUCTION IN NORTHERN ODISHA: GENDER ROLE AND DECISION MAKING

The present study aimed at assessment of gender role and decision making pattern in traditional rural chicken production in northern Odisha. A total of 120 rural household keeping chickens were interviewed and informations were collected using a structured interview schedule. The study revealed higher ownership of women (71.7% compared to men (28.3% in rural chicken production. Women participation in housing management such as let out and shut down of chicken, cleaning, disposal of waste, egg collection, nest preparation and tying or casing chicken were dominated over male (45 100% vs. 2.5 26.7% Women involved more (62.3 100% in preparation of finely ground rice, caring of broody and laying hen, caring of young chicks, health management (treatment, isolation and care of sick birds) and marketing of chicken. However, men played major role (70 100% in shelter construction, caring of fighting cock, medicine purchase, dead bird disposal and dealer contact. Feeding and watering of chicken, predator chasing, protecting crops and thatched roof from chickens are mostly taken care together by women, men and children (92.5 100% Women dominated on decision making in all aspects of rural chicken production (63 100% Results of the present study indicated major participation of women in traditional rural chicken production for uplifting their livelihood.
Multi Objective Optimization of Squeeze Casting Process using Evolutionary Algorithms
Venue: Int. J. Swarm Intell. Res.

The present work focuses on determining optimum squeeze casting process parameters using evolutionary algorithms. Evolutionary algorithms, such as genetic algorithm, particle swarm optimization, and multi objective particle swarm optimization based on crowing distance mechanism, have been used to determine the process variable combinations for the multiple objective functions. In multi objective optimization, there are no single optimal process variable combination due to conflicting nature of objective functions. Four cases have been considered after assigning different combination of weights to the individual objective function based on the user importance. Confirmation tests have been conducted for the recommended process variable combinations obtained by genetic algorithm GA, particle swarm optimization PSO, and multiple objective particle swarm optimization based on crowing distance MOPSO CD. The performance of PSO is found to be comparable with that of GA for identifying optimal process variable combinations. However, PSO outperformed GA with regard to computation time.
Assessment of ductile iron casting process with the use of the DRSA method

The paper introduces a concept of assessment of a ductile iron casting process with use of the rule based approach, known as DRSA (dominance based rough set approach) The research was conducted in a large Polish foundry. The collected data concern the chemical composition and mechanical properties of the used ductile cast iron. In the paper, a methodology of creating a rule based moulding model for the tensile strength was proposed. The quality, sensitivity and accuracy of the model extracted from the data were examined. The studies proved its usefulness in the industrial practice and for aiding of the decision making process.
Quality improvement of a casting process using design of experiments Mejoramiento de la calidad de un proceso de fundicion utilizando diseno de experimentos

In order to minimize the castings which do not meet the customer acceptance specifications, it is not only necessary to identify the process parameters related to the specific defects, but also it is necessary to identify the levels of these parameters to produce acceptable castings. This research study, was aimed to optimize the production of grey cast pump impellent castings using Response Surface Methodology (RSM) approach in a foundry producing grey cast iron components. Process factors like clay percentage, moisture percentage and mold hardness were found to be dominant factors for production process control. Three different levels of each factor were considered for experimentation.  Statistical Software was used to analyze and optimize process parameters for further confirmatory experiments. Significant parameters were identified by means of an Analysis of Variance (ANOVA) test. Parameter optimal settings obtained, and validated from confirmatory experiments, produced a high per cent of defect free pump impeller castings. The research concluded that careful adjustment of process dominance parameters is necessary, since they have significant effects on quality improvement of castings produced.
An improved epsilon constraint handling method embedded in MOEA/D for constrained multi objective optimization problems
Venue: 2016 IEEE Symposium Series on Computational Intelligence (SSCI)

This paper proposes an improved epsilon constraint handling method embedded in the multi objective evolutionary algorithm based on decomposition (MOEA/D) to solve constrained multi objective optimization problems (CMOPs) More specifically, it dynamically adjusts the epsilon level, which is a critical parameter in the epsilon constraint method, according to the feasible ratio of solutions in the current population. In order to verify the effect of the improved epsilon constraint handling method, three algorithms MOEA/D CDP, MOEA/D Epsilon, and MOEA/D IEpsilon (MOEA/D with the improved epsilon constraint handling mechanism) are tested on nine CMOPs (CMOP1 CMOP9) The comprehensive experimental results indicate that the proposed epsilon constraint handling method is very effective on the performance of both convergence and diversity.
Self Concealment Scale: Validation of two Portuguese versions
Venue: European Psychiatry

Self Concealment Scale (SCS) is composed of ten items to measure self concealment, defined as a tendency to conceal from others personal information that one perceives as distressing or negative (Larson and Chastain, 1990)  To investigate the psychometric properties of the SCS 10 Portuguese version and of an adapted version containing two additional items specifically focused on self concealment related do health problems (physical and psychological) SCS 12.  The Portuguese version of the SCS 12 and other validated questionnaires designed to evaluate self reported health, perfectionism and optimism pessimism were administered to a convenience sample of 555 adults from the community (60.5% females; mean age 43.49 10.565) Results The SCS 10 and SCS 12 Cronbach's alphas were a 0.80. In both versions, all the items contribute to the internal consistency. The factor analysis, following the Kaiser and the Cattel's Scree Plot criteria, revealed that SCS 10 is unidimensional and that SCS 12 reliably and validly evaluates two dimensions: F1 Keeping secrets (Explained variance 48.60% a 0.816) F2 Personal concealment including health problems (9.65% a 0.797) The pattern of correlations of the SCS dimensional and total scores was as follow: negative low correlations with physical health 0.20) negative moderate correlations with psychological health .30) moderate correlations with self oriented perfectionism, social prescribed perfectionism, pessimism @0.25) and optimism 0.20) Conclusions The Portuguese versions of SCS have good reliability and validity (construct and convergent divergent) The factorial structure partially overlaps with the original. SCS could be useful for research proposes, namely in an ongoing project on the role of the mentioned personality traits on illness and health behavior. Disclosure of interest The authors have not supplied their declaration of competing interest.
Particle swarm optimization of the fuzzy logic controller for a hybrid energy storage system in an electric car
Venue: 2016 18th European Conference on Power Electronics and Applications (EPE'16 ECCE Europe)

This paper describes the particle swarm optimization of the fuzzy logic controller for a hybrid energy storage system in an electric vehicle. The Sugeno type fuzzy inference system has been applied to divide power between the battery and ultracapacitor energy storage systems, as well as to manage the amount of energy stored in ultracapacitors. The two output signals of the described fuzzy logic controller represent power for each energy storage system, and are the weighted sums of all inference rule outputs. The particle swarm optimization has been proposed to determine the weights of rules. A simulation and experimental validation of the power management algorithm is also introduced in this paper.
Water Distribution Network Design for SRM University using EPANET

The main objective was to study and design the water distribution system requirements using EPANET, so that water is supplied equitably to the consumers with sufficient pressure head at the desired locations in SRM University. The materials used for this study include SRM campus plan, water distribution parameters such as block wise population, and water demand, distribution network parameters such as elevations, pipe length and EPANET software. The water demand was obtained after considering the population of each block. The nodal elevations were measured using Height and Instrument method of levelling. Digitization of streets and buildings in SRM campus was done in Google Earth and it was further used as backdrop in EPANET to carry out the hydraulic simulation. The water distribution network of SRM campus consists of 29 pipes of uniform material, 32 junctions, 5 pumps and a source reservoir from which water is pumped and later distributed to the entire network. The pipes used in the network system are of uniform diameter of 250 mm. The cast iron pipes having roughness coefficient of 85 are used throughout the network system. The total length of the pipes in the network is 2422 m. The water demand during the peak hour is around 310 m 3 /hr, while the demand during the non peak hour is around 83 m 3 /hr. Thus the overall water demand for a day is about 3354 m 3 although the supplied quantity of water is about 4950 m 3 Hence there is no overall shortage of water throughout the day. Moreover the excess water generated during the non peak hours can be stored in the sump and later used during peak hours. The demand during the peak hours is 3.75 times the demand during the non peak hours. There is also a decrease in pressure head occurring at the peak hour as compared to the non peak hours with an overall reduction of 26% throughout the nodes. The main problem encountered in this water distribution network is the presence of dead ends which in turn leads to stagnation of water in pipes and thereby reducing the pressure and velocity at these ends. Although this constraint can be removed by looping the pipes in the network, the site conditions are not conducive for looping, as the area near the dead ends when looped goes out of the campus limits.
Reduced sediment transport in the Yellow River due to anthropogenic changes

The erosion, transport and redeposition of sediments shape the Earth's surface, and affect the structure and function of ecosystems and society(1,2) The Yellow River was once the world's largest carrier of fluvial sediment, but its sediment load has decreased by approximately 90% over the past 60 years(3) The decline in sediment load is due to changes in water discharge and sediment concentration, which are both influenced by regional climate change and human activities. Here we use an attribution approach to analyse 60 years of runoff and sediment load observations from the traverse of the Yellow River over China's Loess Plateau the source of nearly 90% of its sediment load. We find that landscape engineering, terracing and the construction of check dams and reservoirs were the primary factors driving reduction in sediment load from the 1970s to 1990s, but large scale vegetation restoration projects have also reduced soil erosion from the 1990s onwards. We suggest that, as the ability of existing dams and reservoirs to trap sediments declines in the future, erosion rates on the Loess Plateau will increasingly control the Yellow River's sediment load.
Mechanics of Sediment Transport

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SediFoam: A general purpose, open source CFD DEM solver for particle laden flow with emphasis on sediment transport
Venue: Comput. Geosci.

With the growth of available computational resource, CFD DEM (computational fluid dynamics discrete element method) becomes an increasingly promising and feasible approach for the study of sediment transport. Several existing CFD DEM solvers are applied in chemical engineering and mining industry. However, a robust CFD DEM solver for the simulation of sediment transport is still desirable. In this work, the development of a three dimensional, massively parallel, and open source CFD DEM solver SediFoam is detailed. This solver is built based on open source solvers OpenFOAM and LAMMPS. OpenFOAM is a CFD toolbox that can perform three dimensional fluid flow simulations on unstructured meshes; LAMMPS is a massively parallel DEM solver for molecular dynamics. Several validation tests of SediFoam are performed using cases of a wide range of complexities. The results obtained in the present simulations are consistent with those in the literature, which demonstrates the capability of SediFoam for sediment transport applications. In addition to the validation test, the parallel efficiency of SediFoam is studied to test the performance of the code for large scale and complex simulations. The parallel efficiency tests show that the scalability of SediFoam is satisfactory in the simulations using up to O 10 7 particles.
Automatic Segmentation of Hippocampus for Longitudinal Infant Brain MR Image Sequence by Spatial Temporal Hypergraph Learning
Venue: Patch MI@MICCAI

Accurate segmentation of infant hippocampus from Magnetic Resonance (MR) images is one of the key steps for the investigation of early brain development and neurological disorders. Since the manual delineation of anatomical structures is time consuming and irreproducible, a number of automatic segmentation methods have been proposed, such as multi atlas patch based label fusion methods. However, the hippocampus during the first year of life undergoes dynamic appearance, tissue contrast and structural changes, which pose substantial challenges to the existing label fusion methods. In addition, most of the existing label fusion methods generally segment target images at each time point independently, which is likely to result in inconsistent hippocampus segmentation results along different time points. In this paper, we treat a longitudinal image sequence as a whole, and propose a spatial temporal hypergraph based model to jointly segment infant hippocampi from all time points. Specifically, in building the spatial temporal hypergraph, (1) the atlas to target relationship and (2) the spatial/temporal neighborhood information within the target image sequence are encoded as two categories of hyperedges. Then, the infant hippocampus segmentation from the whole image sequence is formulated as a semi supervised label propagation model using the proposed hypergraph. We evaluate our method in segmenting infant hippocampi from T1 weighted brain MR images acquired at the age of 2 weeks, 3 months, 6 months, 9 months, and 12 months. Experimental results demonstrate that, by leveraging spatial temporal information, our method achieves better performance in both segmentation accuracy and consistency over the state of the art multi atlas label fusion methods.