nils-herrmann/clean_scirepeval huggingface dataset:
Acyclovir prophylaxis of herpes-simplex-virus infections.

We conducted a double-blind, placebo-controlled study of acyclovir prophylaxis against infection with herpes simplex virus (HSV) in 20 seropositive recipients of bone-marrow transplants. Acyclovir or placebo was administered for 18 days, starting three days before transplantation. Culture-positive HSV lesions developed during the study in seven of the 10 patients who received placebo. In contrast, no such lesions appeared in the 10 patients who received acyclovir (P congruent to 0.003). None of the patients had evidence of drug toxicity. Five of the patients treated with acyclovir had mild culture-positive HSV infections after cessation of the drug, and two additional patients shed virus without having lesions. Acyclovir appears to be a potent inhibitor of HSV replication. Although acyclovir does no appear to eradicate latent infection, it can provide effective prophylaxis against reactivated infections.
Developing content-based recommender system using Hadoop Map Reduce

Proliferation of information is a major confront faced by e-commerce industry. To ease the customers from this information proliferation, Recommender Systems (RS) were introduced. To improve the computational time of a RS for large scale data, the process of recommendation can be implemented on a scalable, fault tolerant and a distributed processing framework. This paper proposes a Content-Based RS implemented on scalable, fault tolerant and distributed framework of Hadoop Map Reduce. To generate recommendations with improved computational time, the proposed technique of Map Reduce Content-Based Recommendation (MRCBR) is implemented using Hadoop Map Reduce which follows the traditional process of content-based recommendation. MRCBR technique comprises of user profiling and document feature extraction which uses the vector space model followed by computing similarity to generate recommendation for the target user. Recommendations generated for the target user is a set of Top N documents. The proposed technique of recommendation is executed on a cluster of Hadoop and is tested for News dataset. News items are collected using RSS feeds and are stored in MongoDB. Computational time of MRCBR is evaluated with a Speedup factor and performance is evaluated with the standard evaluation metric of Precision, Recall and F-Measure.
On and Off-Blockchain Enforcement of Smart Contracts

In this paper we discuss how conventional business contracts can be converted into smart contracts—their electronic equivalents that can be used to systematically monitor and enforce contractual rights, obligations and prohibitions at run time. We explain that emerging blockchain technology is certainly a promising platform for implementing smart contracts but argue that there is a large class of applications, where blockchain is inadequate due to performance, scalability, and consistency requirements, and also due to language expressiveness and cost issues that are hard to solve. We explain that in some situations a centralised approach that does not rely on blockchain is a better alternative due to its simplicity, scalability, and performance. We suggest that in applications where decentralisation and transparency are essential, developers can advantageously combine the two approaches into hybrid solutions where some operations are enforced by enforcers deployed on–blockchains and the rest by enforcers deployed on trusted third parties.
Classification of Large DNA Methylation Datasets for Identifying Cancer Drivers

DNA methylation is a well-studied genetic modification crucial to regulate the functioning of the genome. Its alterations play an important role in tumorigenesis and tumor-suppression. Thus, studying DNA methylation data may help biomarker discovery in cancer. Since public data on DNA methylation become abundant – and considering the high number of methylated sites (features) present in the genome – it is important to have a method for efficiently processing such large datasets. Relying on big data technologies, we propose BIGBIOCL an algorithm that can apply supervised classification methods to datasets with hundreds of thousands of features. It is designed for the extraction of alternative and equivalent classification models through iterative deletion of selected features. We run experiments on DNA methylation datasets extracted from The Cancer Genome Atlas, focusing on three tumor types: breast, kidney, and thyroid carcinomas. We perform classifications extracting several methylated sites and their associated genes with accurate performance (accuracy>97%). Results suggest that BIGBIOCL can perform hundreds of classification iterations on hundreds of thousands of features in few hours. Moreover, we compare the performance of our method with other state-of-the-art classifiers and with a wide-spread DNA methylation analysis method based on network analysis. Finally, we are able to efficiently compute multiple alternative classification models and extract from DNA-methylation large datasets a set of candidate genes to be further investigated to determine their active role in cancer. BIGBIOCL, results of experiments, and a guide to carry on new experiments are freely available on GitHub at https://github.com/fcproj/BIGBIOCL.
The effect of different corrective feedback methods on the outcome and self confidence of young athletes.

This experiment investigated the effects of three corrective feedback methods, using different combinations of correction, or error cues and positive feedback for learning two badminton skills with different difficulty (forehand clear - low difficulty, backhand clear - high difficulty). Outcome and self-confidence scores were used as dependent variables. The 48 participants were randomly assigned into four groups. Group A received correction cues and positive feedback. Group B received cues on errors of execution. Group C received positive feedback, correction cues and error cues. Group D was the control group. A pre, post and a retention test was conducted. A three way analysis of variance ANOVA (4 groups X 2 task difficulty X 3 measures) with repeated measures on the last factor revealed significant interactions for each depended variable. All the corrective feedback methods groups, increased their outcome scores over time for the easy skill, but only groups A and C for the difficult skill. Groups A and B had significantly better outcome scores than group C and the control group for the easy skill on the retention test. However, for the difficult skill, group C was better than groups A, B and D. The self confidence scores of groups A and C improved over time for the easy skill but not for group B and D. Again, for the difficult skill, only group C improved over time. Finally a regression analysis depicted that the improvement in performance predicted a proportion of the improvement in self confidence for both the easy and the difficult skill. It was concluded that when young athletes are taught skills of different difficulty, different type of instruction, might be more appropriate in order to improve outcome and self confidence. A more integrated approach on teaching will assist coaches or physical education teachers to be more efficient and effective.  pointsThe type of the skill is a critical factor in determining the effectiveness of the feedback types.Different instructional methods of corrective feedback could have beneficial effects in the outcome and self-confidence of young athletesInstructions focusing on the correct cues or errors increase performance of easy skills.Positive feedback or correction cues increase self-confidence of easy skills but only the combination of error and correction cues increase self confidence and outcome scores of difficult skills.
Efficient Continuous-Time SLAM for 3D Lidar-Based Online Mapping

Modern 3D laser-range scanners have a high data rate, making online simultaneous localization and mapping (SLAM) computationally challenging. Recursive state estimation techniques are efficient but commit to a state estimate immediately after a new scan is made, which may lead to misalignments of measurements. We present a 3D SLAM approach that allows for refining alignments during online mapping. Our method is based on efficient local mapping and a hierarchical optimization back-end. Measurements of a 3D laser scanner are aggregated in local multiresolution maps by means of surfel-based registration. The local maps are used in a multi-level graph for allocentric mapping and localization. In order to incorporate corrections when refining the alignment, the individual 3D scans in the local map are modeled as a sub-graph and graph optimization is performed to account for drift and misalignments in the local maps. Furthermore, in each sub-graph, a continuous-time representation of the sensor trajectory allows to correct measurements between scan poses. We evaluate our approach in multiple experiments by showing qualitative results. Furthermore, we quantify the map quality by an entropy-based measure.
Supporting Data-Intensive Workflows in Software-Defined Federated Multi-Clouds

Cloud computing is emerging as a viable platform for scientific exploration. Elastic and on-demand access to resources (and other services), the abstraction of “unlimited” resources, and attractive pricing models provide incentives for scientists to move their workflows into clouds. Generalizing these concepts beyond a single virtualized datacenter, it is possible to create federated marketplaces where different types of resources (e.g., clouds, HPC grids, supercomputers) that may be geographically distributed, are collectively exposed as a single elastic infrastructure. This presents opportunities for optimizing the execution of application workflows with heterogeneous and dynamic requirements, and tackling larger scale problems. In this paper, we introduce a framework to manage the end-to-end execution of data-intensive application workflows in dynamic software-defined resource federation. This framework enables the autonomic execution of workflows by elastically provisioning an appropriate set of resources that meet application requirements, and by adapting this set of resources at runtime as the requirements change. It also allows users to customize scheduling policies that drive the way resources federated and used. To demonstrate the benefits of our approach, we study the execution of two different data-intensive scientific workflows in a multi-cloud federation using different policies and objective functions.
Sentence Ranking with the Semantic Link Network in Scientific Paper

Sentence ranking is one of the most important research issues in text analysis. It can be used in text summarization and information retrieval. Graph-based methods are a common way of ranking and extracting sentences. In graph based methods, sentences are nodes of graph and edges are built based on the sentence similarities or on sentence co-occurrence relationship. PageRank style algorithms can be applied to get sentence ranks. In this paper, we focus on how to rank sentences in a single scientific paper. A scientific literature has more structural information than general texts and this structural information has not been fully explored yet in graph based ranking models. We investigated several different methods that used the is-part-of link on paragraph and section and similar link and co-occurrence link to construct a heterogeneous graph for ranking sentences. We conducted experiments on these methods to compare the results on sentence ranking. It shows that structural information can help identify more representative sentences.
Symmetry axis computation for almost-symmetrical and asymmetrical objects: Application to pigmented skin lesions

The detection of symmetry axes through the optimization of a given symmetry measure, computed as a function of the mean-square error between the original and reflected images, is investigated in this paper. A genetic algorithm and an optimization scheme derived from the self-organizing maps theory are presented. The notion of symmetry map is then introduced. This transform allows us to map an object into a symmetry space where its symmetry properties can be analyzed. The locations of the different axes that globally and locally maximize the symmetry value can be obtained. The input data are assumed to be vector-valued, which allow to focus on either shape. color or texture information. Finally, the application to skin cancer diagnosis is illustrated and discussed.
VLSI design of sequential minimal optimization algorithm for SVM learning

The sequential minimal optimization (SMO) algorithm has been widely used for training the support vector machine (SVM). In this paper, we present the first chip design for sequential minimal optimization. This chip is implemented as an intellectual property (IP) core, suitable to be utilized in an SVM-based recognition system on a chip. The proposed SMO chip has been tested to be fully functional, using a prototype system based on the Altera DE2 board with Cyclone II 2C70 FPGA (field-programmable gate array).
MC1R gene mutation and its association with oculocutaneous albinism type (OCA) phenotype in a consanguineous Pakistani family.

Brown SJ, McLean WH. One remarkable molecule: filaggrin.   Sandilands A, Terron-Kwiatkowski A, Hull PR, O’Regan GM, Clayton TH, Watson RM, et al. Comprehensive analysis of the gene encoding filaggrin uncovers prevalent and rare mutations in ichthyosis vulgaris and atopic eczema.  2007;39:650–4.  Margolis DJ, Apter AJ, Gupta J, Hoffstad O, Papadopoulos M, Campbell LE, et al. The persistence of atopic dermatitis and Filaggrin mutations in a US longitudinal cohort.  Smith FJ, Irvine AD, Terron-Kwiatkowski A, Sandilands A, Campbell LE, Zhao Y, et al. Loss-of-function mutations in the gene encoding filaggrin cause ichthyosis vulgaris.   Paternoster L, Standl M, Chen CM, Ramasamy A, Bonnelykke K, Duijts L, et al. Meta-analysis of genome-wide association studies identifies three new risk Table 1 Reliability and validity comparisons for FLG null mutations as assayed by TaqMan and beadchip methods.
Improved Bat Algorithm for Reliability-Redundancy Allocation Problems

The bat algorithm is a recently proposed meta-heuristic algorithm. Usually in solving the problem of optimization, the position of virtual bats is updated by flying speed, which decreases efficiency of the algorithm and accuracy of the solution. This paper has improved the location update strategy and individual selection strategy of bat algorithm, then puts forward an improved bat algorithm. The algorithm is used to solve three typical reliability-redundancy allocation problems, and the simulation experiment results show that the presented algorithm greatly enhances the computation efficiency, convergence speed and precision of the optimal solution in addressing the problem of reliability redundancy optimization. When compared with the best results reported in the previous literatures, the algorithm achieves a better or equally good optimal solution. It is demonstrated that the proposed algorithm is effective in solving reliability-redundancy allocation problems.
Vulvar cancer: epidemiology, clinical presentation, and management options

EPIDEMIOLOGY
Vulvar cancer can be classified into two groups according to predisposing factors: the first type correlates with a HPV infection and occurs mostly in younger patients. The second group is not HPV associated and occurs often in elderly women without neoplastic epithelial disorders.



Squamous cell carcinoma (SCC) is the most common malignant tumor of the vulva (95%).



Pruritus is the most common and long-lasting reported symptom of vulvar cancer, followed by vulvar bleeding, discharge, dysuria, and pain.



The gold standard for even a small invasive carcinoma of the vulva was historically radical vulvectomy with removal of the tumor with a wide margin followed by an en bloc resection of the inguinal and often the pelvic lymph nodes. Currently, a more individualized and less radical treatment is suggested: a radical wide local excision is possible in the case of localized lesions (T1). A sentinel lymph node (SLN) biopsy may be performed to reduce wound complications and lymphedema.


PROGNOSIS
The survival of patients with vulvar cancer is good when convenient therapy is arranged quickly after initial diagnosis. Inguinal and/or femoral node involvement is the most significant prognostic factor for survival.
The effects of a player's network centrality on resource accessibility, game enjoyment, and continuance intention: A study on online gaming communities

1567-4223/$ see front matter 2011  ⇑ Corresponding author. Tel.: +886 2 2939 3091x85 E-mail addresses: jerrycchsiao@gmail.com (C.-C. (J.-S. Chiou). This study applies social capital theory to investigate how a player’s network centrality in an online gaming community (i.e., a guild) affects his/her attitude and continuance intention toward a Massive Multiplayer Online Game (MMOG). Analysis of 347 usable responses shows that players’ network centrality has a negative impact on their ties to players who belong to other guilds (i.e., non-guild interaction), but a positive effect on players’ access to resources. However, players’ network centrality fails to increase their perceived game enjoyment directly. Players’ resource accessibility and perceived game enjoyment play mediating roles in the relationship between network centrality and attitude toward playing an MMOG, which in turn influences game continuance intention. The results also show that although players’ non-guild interaction is negatively related to their resource accessibility from the networks, it is positively associated with perceived game enjoyment. The article concludes with implications and limitations of the study.
A Low Loss High Isolation DC-60 GHz SPDT Traveling-Wave Switch With a Body Bias Technique in 90 nm CMOS Process

In this letter, a low loss high isolation broadband single-port double-throw (SPDT) traveling-wave switch using 90 nm CMOS technology is presented. A body bias technique is utilized to enhance the circuit performance of the switch, especially for the operation frequency above 30 GHz. The parasitic capacitance between the drain and source of the NMOS transistor can be further reduced using the negative body bias technique. Moreover, the insertion loss, the input 1 dB compression point (P1 dB)> and the third-order intermodulation (IMD3) of the switch are all improved. With the technique, the switch demonstrates an insertion loss of 3 dB and an isolation of better than 48 dB from dc to 60 GHz. The chip size of the proposed switch is 0.68 × 0.87 mm2 with a core area of only 0.32 × 0.21 mm2.
Spontaneous Lens Absorption Initially Misdiagnosed as Crystalline Lens Luxation

Spontaneous lens absorption (SLA) is a rare complication of hypermature cataract. However, this condition has been reported in several cases of hypermature cataracts that were caused by trauma, senility, uveitic disorders such as Fuchs’ uveitis syndrome (FUS), and infectious disorders including leptospirosis and rubella. We report a case of spontaneous absorption of a hypermature cataract secondary to FUS. To our knowledge, this is the first report of SLA that was followed by dislocation of the capsular remnants into the vitreous and resulted in a misdiagnosis as crystalline lens luxation.
Whatever it takes to win : Rivalry increases unethical behaviour

Rivalry is a competitive relationship that is built up over repeated and evenly-matched competition. There are many famous examples of rivalries gone awry. Many people still vividly remember the brutal sabotage attempt launched by Tonya Harding’s ex-husband against her rival Nancy Kerrigan in the 1994 Winter Olympics. Fewer may know that Thomas Edison and his right-hand man Harold Brown staged savage public electrocutions of animals in an attempt to spread fear over alternating current (AC), the form of electricity being promoted by Edison’s rival, Nikola Tesla. Examples of rivalry turned ugly are also prevalent in business, such as the ‘Dirty Tricks’ campaign launched by British Airways against Virgin Atlantic, which included stealing Virgin’s customer data and then lying to Virgin customers about their flights being canceled.
Innovative scheme for smart grid distribution SCADA system

In deployment of smart grid it is imperative to adopt advanced and smart technologies in SCADA of distribution system for smart monitoring, automation and control of a power system. The present paper focuses the status of present SCADA of small distribution systems and proposes the use of smart meter for variety of tasks to be performed in smart distribution systems. Sample smart operations for monitoring and control task using latest communication technologies are demonstrated with simulation and hardware results. The proposed scheme can be extended and implemented effectively to gratify variety of errands as mandatory in smart grid.
Verbal Redundancy in Multimedia Learning Environments : A Meta-Analysis

Verbal redundancy arises from the concurrent presentation of text and verbatim speech. To inform theories of multimedia learning that guide the design of educational materials, a meta-analysis was conducted to investigate the effects of spoken-only, written-only, and spoken–written presentations on learning retention and transfer. After an extensive search for experimental studies meeting specified inclusion criteria, data from 57 independent studies were extracted. Most of the research participants were postsecondary students. Overall, this meta-analysis revealed that outcomes comparing spoken–written and written-only presentations did not differ, but students who learned from spoken–written presentations outperformed those who learned from spoken-only presentations. This effect was dependent on learners’ prior knowledge, pacing of presentation, and inclusion of animation or diagrams. Specifically, the advantages of spoken–written presentations over spoken-only presentations were found for low prior knowledge learners, system-paced learning materials, and picture-free materials. In comparison with verbatim, spoken–written presentations, presentations displaying key terms extracted from spoken narrations were associated with better learning outcomes and accounted for much of the advantage of spoken–written over spoken-only presentations. These findings have significant implications for the design of multimedia materials.