nils-herrmann/clean_scirepeval huggingface dataset:
Chemical origins of life: Prebiotic RNA unstuck.

The ‘RNA world’ hypothesis describes an early stage of life on Earth, prior to the evolution of coded protein synthesis, in which RNA served as both information carrier and functional catalyst1,2. Not only is there a significant body of evidence to support this hypothesis3, but the ‘ribo-organisms’ from this RNA world are likely to have achieved a significant degree of metabolic sophistication4. From the perspective of the origins of life, the path from pre-life chemistry to the RNA world probably included cycles of template-directed RNA replication, with the RNA templates assembled from prebiotically generated ribonucleotides  RNA seems well suited for the task of replication because its components pair in a complementary fashion. One strand of nucleic acid could thereby serve as a template to direct the polymerization of its complementary strand. Nevertheless, even given abundant ribonucleotides and prebiotically generated RNA templates, significant problems are believed to stand in the way of an experimental demonstration of multiple cycles of RNA replication. For example, non-enzymatic RNA template-copying reactions generate complementary strands that contain 2ʹ,5ʹ-phosphodiester linkages randomly distributed amongst the 3ʹ,5ʹ-linkages  This heterogeneity has been generally presumed to preclude the evolution of heritable RNA with functional properties. A second problem with the RNA replication cycle concerns the high ‘melting temperatures’ required to separate the strands of the RNA duplexes formed by template copying7. For example, 14mer RNA duplexes with a high proportion of guanine–cytosine pairs can have melting temperatures well above 90 °C. Such stability would prohibit strand separation and thereby halt progression to the next generation of replication. Yet another difficulty results from the hydrolysis and cyclization reactions of chemically activated mononucleotide and oligonucleotide substrates7, which would deactivate them for template copying. Together, these and other issues have precluded the demonstration of chemically driven RNA replication in the laboratory. Now, two new studies reported in Nature Chemistry — one from the Szostak laboratory and the other from the Sutherland group — offer potential solutions to these problems8,9. Szostak and co-workers have challenged the assumption that backbone homogeneity was a requirement for the primordial RNA replication process, and considered whether RNAs that contain significant levels of 2ʹ,5ʹ-linkages can be tolerated within known ribozymes and aptamers8. They synthesized two well-known functional RNAs — the flavin mononucleotide (FMN) aptamer and hammerhead ribozyme — containing varying amounts (10–50%) of randomly distributed 2ʹ,5ʹ-linkages. Overall, FMN aptamers and hammerhead ribozymes possessing high levels of CHEMICAL ORIGINS OF LIFE
Adopt: asynchronous distributed constraint optimization with quality guarantees

The Distributed Constraint Optimization Problem (DCOP) is able to model a wide variety of distributed reasoning tasks that arise in multiagent systems. Unfortunately, existing methods for DCOP are not able to provide theoretical guarantees on global solution quality while allowing agents to operate asynchronously. We show how this failure can be remedied by allowing agents to make local decisions based on conservative cost estimates rather than relying on global certainty as previous approaches have done. This novel approach results in a polynomial-space algorithm for DCOP named Adopt that is guaranteed to find the globally optimal solution while allowing agents to execute asynchronously and in parallel. Detailed experimental results show that on benchmark problems Adopt obtains speedups of several orders of magnitude over other approaches. Adopt can also perform bounded-error approximation – it has the ability to quickly find approximate solutions and, unlike heuristic search methods, still maintain a theoretical guarantee on solution quality.
Duloxetine: mechanism of action at the lower urinary tract and Onuf’s nucleus

Urinary incontinence is the inability to willingly control bladder voiding. Stress urinary incontinence (SUI) is the most frequently occurring type of incontinence in women. No widely accepted or approved drug therapy is yet available for the treatment of stress urinary incontinence. Numerous studies have implicated the neurotransmitters, serotonin and norepinephrine in the central neural control of the lower urinary tract function. The pudendal somatic motor nucleus of the spinal cord is densely innervated by 5HT and NE terminals. Pharmacological studies confirm central modulation of the lower urinary tract activity by 5HT and NE receptor agonists and antagonists. Duloxetine is a combined serotonin/norepinephrine reuptake inhibitor currently under clinical investigation for the treatment of women with stress urinary incontinence. Duloxetine exerts balanced in vivo reuptake inhibition of 5HT and NE and exhibits no appreciable binding affinity for receptors of neurotransmitters. The action of duloxetine in the treatment of stress urinary incontinence is associated with reuptake inhibition of serotonin and norepinephrine at the presynaptic neuron in Onuf’s nucleus of the sacral spinal cord. In cats, whose bladder had initially been irritated with acetic acid, a dose–dependent improvement of the bladder capacity (5–fold) and periurethral EMG activity (8–fold) of the striated sphincter muscles was found. In a double blind, randomized, placebocontrolled, clinical trial in women with stress urinary incontinence, there was a significant reduction in urinary incontinence episodes under duloxetine treatment. In summary, the pharmacological effect of duloxetine to increase the activity of the striated urethral sphincter together with clinical results indicate that duloxetine has an interesting therapeutic potential in patients with stress urinary incontinence.
Detection of glaucoma using retinal fundus images

This paper proposes an image processing technique for the detection of glaucoma which mainly affects the optic disc by increasing the cup size. During early stages it was difficult to detect Glaucoma, which is in fact second leading cause of blindness. In this paper glaucoma is categorized through extraction of features from retinal fundus images. The features include (i) Cup to Disc Ratio (CDR), which is one of the primary physiological parameter for the diagnosis of glaucoma and (ii) Ratio of Neuroretinal Rim in inferior, superior, temporal and nasal quadrants i.e. (ISNT quadrants) for verification of the ISNT rule. The novel technique is implemented on 80 retinal images and an accuracy of 97.5% is achieved taking an average computational time of 0.8141 seconds.
Phosphate solubilizing bacteria and their role in plant growth promotion.

The use of phosphate solubilizing bacteria as inoculants simultaneously increases P uptake by the plant and crop yield. Strains from the genera Pseudomonas, Bacillus and Rhizobium are among the most powerful phosphate solubilizers. The principal mechanism for mineral phosphate solubilization is the production of organic acids, and acid phosphatases play a major role in the mineralization of organic phosphorous in soil. Several phosphatase-encoding genes have been cloned and characterized and a few genes involved in mineral phosphate solubilization have been isolated. Therefore, genetic manipulation of phosphate-solubilizing bacteria to improve their ability to improve plant growth may include cloning genes involved in both mineral and organic phosphate solubilization, followed by their expression in selected rhizobacterial strains. Chromosomal insertion of these genes under appropriate promoters is an interesting approach.
Secure communication for underwater acoustic sensor networks

UASNs are widely used in many applications, and many studies have been conducted. However, most current research projects have not taken network security into consideration, despite the fact that a UASN is typically vulnerable to malicious attacks due to the unique characteristics of an underwater acoustic communication channel (e.g., low communication bandwidth, long propagation delays, and high bit error rates). In addition, the significant differences between UASNs and terrestrial wireless sensor networks entail the urgent and rapid development of secure communication mechanisms for underwater sensor nodes. For the above mentioned reasons, this article aims to present a somewhat comprehensive survey of the emerging topics arising from secure communications in UASNs, which naturally lead to a great number of open research issues outlined afterward.
Unsupervised adversarial domain adaptation for acoustic scene classification

A general problem in acoustic scene classification task is the mismatched conditions between training and testing data, which significantly reduces the performance of the developed methods on classification accuracy. As a countermeasure, we present the first method of unsupervised adversarial domain adaptation for acoustic scene classification. We employ a model pre-trained on data from one set of conditions and by using data from other set of conditions, we adapt the model in order that its output cannot be used for classifying the set of conditions that input data belong to. We use a freely available dataset from the DCASE 2018 challenge Task 1, subtask B, that contains data from mismatched recording devices. We consider the scenario where the annotations are available for the data recorded from one device, but not for the rest. Our results show that with our model agnostic method we can achieve ∼ 10% increase at the accuracy on an unseen and unlabeled dataset, while keeping almost the same performance on the labeled dataset.
PARP inhibitors: Synthetic lethality in the clinic

PARP inhibitors (PARPi), a cancer therapy targeting poly(ADP-ribose) polymerase, are the first clinically approved drugs designed to exploit synthetic lethality, a genetic concept proposed nearly a century ago. Tumors arising in patients who carry germline mutations in either BRCA1 or BRCA2 are sensitive to PARPi because they have a specific type of DNA repair defect. PARPi also show promising activity in more common cancers that share this repair defect. However, as with other targeted therapies, resistance to PARPi arises in advanced disease. In addition, determining the optimal use of PARPi within drug combination approaches has been challenging. Nevertheless, the preclinical discovery of PARPi synthetic lethality and the route to clinical approval provide interesting lessons for the development of other therapies. Here, we discuss current knowledge of PARP inhibitors and potential ways to maximize their clinical effectiveness.
What make long term contributors: Willingness and opportunity in OSS community

To survive and succeed, software projects need to attract and retain contributors. We model the individual's chances to become a valuable contributor through their capacity, willingness, and the opportunity to contribute at the time of joining. Using issue tracking data of Mozilla and Gnome, we find that the probability for a new joiner to become a Long Term Contributor (LTC) is associated with her willingness and environment. Specifically, during their first month, future LTCs tend to be more active and show more community-oriented attitude than other joiners. Joiners who start by commenting on instead of reporting an issue or ones who succeed to get at least one reported issue to be fixed, more than double their odds of becoming an LTC. The macro-climate with high project relative sociality and the micro-climate with a large, productive, and clustered peer group increase the odds. On the contrary, the macro-climate with high project popularity and the micro-climate with low attention from peers reduce the odds. This implies that the interaction between individual's attitude and project's climate are associated with the odds that an individual would become a valuable contributor or disengage from the project. Our findings may provide a basis for empirical approaches to design a better community architecture and to improve the experience of contributors.
The effect of programming language on error rates of novice programmers

This paper describes the design and testing of a new introductory programming language, GRAIL1. GRAIL was designed to minimise student syntax errors, and hence allow the study of the impact of syntax errors on learning to program. An experiment was conducted using students learning programming for the first time. The students were split into two groups, one group learning LOGO and the other GRAIL. The resulting code was then analysed for syntax and logic errors. The groups using LOGO made more errors than the groups using GRAIL, which shows that choice of programming language can have a substantial impact on error rates of novice programmers.
Analysis of a mathematical model for treatment of cancer with oncolytic virotherapy

In this paper, we will present a model of cancer tumor growth that describes the interaction between an oncolytic virus and tumor cells. This is a tree-population model that includes uninfected cells, tumor cells, and the oncolytic virus. We give the basic reproduction number R0 and we show that there exists a disease free equilibrium points (DFE) and an endemic equilibrium point (DEE). Using a Lyapunov function, we prove that the DFE is globally asymptotically stable if R0 < 1 and unstable otherwise. We also prove that under an additional condition, the DEE is stable when R0 > 1. To illustrate our results numerical simulations are also presented.
Author Name Disambiguation for Citations Using Topic and Web Correlation

Today, bibliographic digital libraries play an important role in helping members of academic community search for novel research. In particular, author disambiguation for citations is a major problem during the data integration and cleaning process, since author names are usually very ambiguous. For solving this problem, we proposed two kinds of correlations between citations, namely, Topic Correlation and Web Correlation, to exploit relationships between citations, in order to identify whether two citations with the same author name refer to the same individual. The topic correlation measures the similarity between research topics of two citations; while the Web correlation measures the number of co-occurrence in web pages. We employ a pair-wise grouping algorithm to group citations into clusters. The results of experiments show that the disambiguation accuracy has great improvement when using topic correlation and Web correlation, and Web correlation provides stronger evidences about the authors of citations.
Purposive Behavior Acquisition for a Real Robot by Vision-Based Reinforcement Learning

This paper presents a method of vision-based reinforcement learning by which a robot learns to shoot a ball into a goal. We discuss several issues in applying the reinforcement learning method to a real robot with vision sensor by which the robot can obtain information about the changes in an environment. First, we construct a state space in terms of size, position, and orientation of a ball and a goal in an image, and an action space is designed in terms of the action commands to be sent to the left and right motors of a mobile robot. This causes a state-action deviation problem in constructing the state and action spaces that reflect the outputs from physical sensors and actuators, respectively. To deal with this issue, an action set is constructed in a way that one action consists of a series of the same action primitive which is successively executed until the current state changes. Next, to speed up the learning time, a mechanism of Learning from Easy Missions (or LEM) is implemented. LEM reduces the learning time from exponential to almost linear order in the size of the state space. The results of computer simulations and real robot experiments are given.
Smart card technology integration in a higher education institution

The application of smart card technology in many industries locally and abroad is common nowadays. The technology is used in ensuring security and attaining functional capabilities. Based on an Internet search, there appears to be several reported cases of successful smart card technology implementation projects. However, there may not be as many challenged projects reported. In this paper, we report a challenged implementation of smart card technology in a higher education institution using the Project Management Body of Knowledge (PMBoK) as the framework.
DHA status of vegetarians.

Docosahexaenoic acid (22:6n-3; DHA) is absent from vegan diets and present in limited amounts in vegetarian diets.



To review DHA status in vegetarians and vegans.



To identify published studies and review their findings.



Dietary analyses show that vegan diets are devoid of DHA and vegetarian diets that included dairy food and eggs only provide about 0.02 g DHA/d. Vegetarian and especially vegan diets supply more linoleic acid (18:2n-6) than omnivore diets. The intake of alpha-linolenic acid (18:3n-3) also tends to be similar or greater but depends on culinary oils used. The proportions of DHA in plasma, blood cells, breast milk, and tissues are substantially lower in vegans and vegetarians compared with omnivores. The lower proportions of DHA are accompanied by correspondingly higher proportions of the long-chain derivatives of linoleic acid, indicating that the capacity to synthesize long-chain polyunsaturated fatty acids is not limited. Short-term dietary supplementation with alpha-linolenic acid increases the proportion of eicosapentaenoic acid (20:5n-3) but does not increase the proportion of DHA in blood lipids. Small amounts of preformed DHA (as low as 200mg) result in a large increase in the proportion of DHA in blood lipids in vegetarians and vegans. There is no evidence of adverse effects on health or cognitive function with lower DHA intake in vegetarians.



Preformed DHA in the diet of omnivores explains the relatively higher proportion of this fatty acid in blood and tissue lipids compared with vegetarians. The pathophysiological significance of this difference remains to be determined.
SYNTHESES Running to stand still: adaptation and the response of plants to rapid climate change

Alistair S. Jump* and Josep Peñuelas Unitat d’Ecofisiologia CSICCEAB-CREAF, Centre de Recerca Ecològica i Aplicacions Forestals, Universitat Autònoma de Barcelona, E-08193, Bellaterra, Barcelona, Spain *Correspondence: E-mail: a.s.jump@creaf.uab.es  Climate is a potent selective force in natural populations, yet the importance of adaptation in the response of plant species to past climate change has been questioned. As many species are unlikely to migrate fast enough to track the rapidly changing climate of the future, adaptation must play an increasingly important role in their response. In this paper we review recent work that has documented climate-related genetic diversity within populations or on the microgeographical scale. We then describe studies that have looked at the potential evolutionary responses of plant populations to future climate change. We argue that in fragmented landscapes, rapid climate change has the potential to overwhelm the capacity for adaptation in many plant populations and dramatically alter their genetic composition. The consequences are likely to include unpredictable changes in the presence and abundance of species within communities and a reduction in their ability to resist and recover from further environmental perturbations, such as pest and disease outbreaks and extreme climatic events. Overall, a range-wide increase in extinction risk is likely to result. We call for further research into understanding the causes and consequences of the maintenance and loss of climate-related genetic diversity within populations.
Race and racism in Internet Studies: A review and critique

Race and racism persist online in ways that are both new and unique to the Internet, alongside vestiges of centuries-old forms that reverberate significantly both offline and on. As we mark 15 years into the field of Internet studies, it becomes necessary to assess what the extant research tells us about race and racism. This paper provides an analysis of the literature on race and racism in Internet studies in the broad areas of (1) race and the structure of the Internet, (2) race and racism matters in what we do online, and (3) race, social control and Internet law. Then, drawing on a range of theoretical perspectives, including Hall’s spectacle of the Other and DuBois’s view of white culture, the paper offers an analysis and critique of the field, in particular the use of racial formation theory. Finally, the paper points to the need for a critical understanding of whiteness in Internet studies.
Contextual Weisfeiler-Lehman graph kernel for malware detection

In this paper, we propose a novel graph kernel specifically to address a challenging problem in the field of cyber-security, namely, malware detection. Previous research has revealed the following: (1) Graph representations of programs are ideally suited for malware detection as they are robust against several attacks, (2) Besides capturing topological neighbourhoods (i.e., structural information) from these graphs it is important to capture the context under which the neighbourhoods are reachable to accurately detect malicious neighbourhoods. We observe that state-of-the-art graph kernels, such as Weisfeiler-Lehman kernel (WLK) capture the structural information well but fail to capture contextual information. To address this, we develop the Contextual Weisfeiler-Lehman kernel (CWLK) which is capable of capturing both these types of information. We show that for the malware detection problem, CWLK is more expressive and hence more accurate than WLK while maintaining comparable efficiency. Through our largescale experiments with more than 50,000 real-world Android apps, we demonstrate that CWLK outperforms two state-of-the-art graph kernels (including WLK) and three malware detection techniques by more than 5.27% and 4.87% F-measure, respectively, while maintaining high efficiency. This high accuracy and efficiency make CWLK suitable for large-scale real-world malware detection.
LIBXSMM: Accelerating Small Matrix Multiplications by Runtime Code Generation

Many modern highly scalable scientific simulations packages rely on small matrix multiplications as their main computational engine. Math libraries or compilers are unlikely to provide the best possible kernel performance. To address this issue, we present a library which provides high performance small matrix multiplications targeting all recent x86 vector instruction set extensions up to Intel AVX-512. Our evaluation proves that speed-ups of more than 10× are possible depending on the CPU and application. These speed-ups are achieved by a combination of several novel technologies. We use a code generator which has a built-in architectural model to create code which runs well without requiring an auto-tuning phase. Since such code is very specialized we leverage just-in-time compilation to only build the required kernel variant at runtime. To keep ease-of-use, overhead, and kernel management under control we accompany our library with a BLAS-compliant frontend which features a multi-level code-cache hierarchy.