nils-herrmann/clean_scirepeval huggingface dataset:
Voluntary Site Accreditation - Improving the Execution of Multicenter Clinical Trials.

n engl j med 377;15 nejm.org October 12, 2017 4. Aysola J, Tahirovic E, Troxel AB, et al. A randomized controlled trial of opt-in versus opt-out enrollment into a diabetes behavioral intervention. . 5. Mehta SJ, Troxel AB, Marcus N, et al. Participation rates with opt-out enrollment in a remote monitoring intervention for patients with myocardial infarction. JAMA Cardiol 2016; 1: 847-8. DOI: 10.1056/NEJMp1707991
Curcumin: An Anti-Inflammatory Molecule from a Curry Spice on the Path to Cancer Treatment

Oxidative damage and inflammation have been pointed out in preclinical studies as the root cause of cancer and other chronic diseases such as diabetes, hypertension, Alzheimer's disease, etc. Epidemiological and clinical studies have suggested that cancer could be prevented or significantly reduced by treatment with anti-oxidant and anti-inflammatory drugs, therefore, curcumin, a principal component of turmeric (a curry spice) showing strong anti-oxidant and anti-inflammatory activities, might be a potential candidate for the prevention and/or treatment of cancer and other chronic diseases. However, curcumin, a highly pleiotropic molecule with an excellent safety profile targeting multiple diseases with strong evidence on the molecular level, could not achieve its optimum therapeutic outcome in past clinical trials, largely due to its low solubility and poor bioavailability. Curcumin can be developed as a therapeutic drug through improvement in formulation properties or delivery systems, enabling its enhanced absorption and cellular uptake. This review mainly focuses on the anti-inflammatory potential of curcumin and recent developments in dosage form and nanoparticulate delivery systems with the possibilities of therapeutic application of curcumin for the prevention and/or treatment of cancer.
Joint-scale LBP: a new feature descriptor for texture classification

This paper presents a simple, efficient, yet robust approach, named joint-scale local binary pattern (JLBP), for texture classification. In the proposed approach, the joint-scale strategy is developed firstly, and the neighborhoods of different scales are fused together by a simple arithmetic operation. And then, the descriptor is extracted from the mutual integration of the local patches based on the conventional local binary pattern (LBP). The proposed scheme can not only describe the micro-textures of a local structure, but also the macro-textures of a larger area because of the joint of multiple scales. Further, motivated by the completed local binary pattern (CLBP) scheme, the completed JLBP (CJLBP) is presented to enhance its power. The proposed descriptor is evaluated in relation to other recent LBP-based patterns and non-LBP methods on popular benchmark texture databases, Outex, CURet and UIUC. Generally, the experimental results show that the new method performs better than the state-of-the-art techniques.
Epithelial MHC Class II Expression and Its Role in Antigen Presentation in the Gastrointestinal and Respiratory Tracts

As the primary barrier between an organism and its environment, epithelial cells are well-positioned to regulate tolerance while preserving immunity against pathogens. Class II major histocompatibility complex molecules (MHC class II) are highly expressed on the surface of epithelial cells (ECs) in both the lung and intestine, although the functional consequences of this expression are not fully understood. Here, we summarize current information regarding the interactions that regulate the expression of EC MHC class II in health and disease. We then evaluate the potential role of EC as non-professional antigen presenting cells. Finally, we explore future areas of study and the potential contribution of epithelial surfaces to gut-lung crosstalk.
Modeling of Step-up Grid-Connected Photovoltaic Systems for Control Purposes

This paper presents modeling approaches for step-up grid-connected photovoltaic systems intended to provide analytical tools for control design. The first approach is based on a voltage source representation of the bulk capacitor interacting with the grid-connected inverter, which is a common model for large DC buses and closed-loop inverters. The second approach considers the inverter of a double-stage PV system as a Norton equivalent, which is widely accepted for open-loop inverters. In addition, the paper considers both ideal and realistic models for the DC/DC converter that interacts with the PV module, providing four mathematical models to cover a wide range of applications. The models are expressed in state space representation to simplify its use in analysis and control design, and also to be easily implemented in simulation software, e.g., Matlab. The PV system was analyzed to demonstrate the non-minimum phase condition for all the models, which is an important aspect to select the control technique. Moreover, the system observability and controllability were studied to define design criteria. Finally, the analytical results are illustrated by means of detailed simulations, and the paper results are validated in an experimental test bench.
CT Saturation Calculations: Are They Applicable in the Modern World?—Part I: The Question

Previously, ANSI/IEEE relay current transformer (CT) sizing criteria were based on traditional symmetrical calculations that are usually discussed by technical articles and manufacturers' guidelines. In 1996, 1996 introduced (1+X/R) offset multiplying, current asymmetry, and current distortion factors, officially changing the CT sizing guideline. A critical concern is the performance of fast protective schemes (instantaneous or differential elements) during severe saturation of low-ratio CTs. Will the instantaneous element operate before the upstream breaker relay trips? Will the differential element misoperate for out-of-zone faults? The use of electromagnetic and analog relay technology does not assure selectivity. Modern microprocessor relays introduce additional uncertainty into the design/verification process with different sampling techniques and proprietary sensing/recognition/trip algorithms. This paper discusses the application of standard CT accuracy classes with modern ANSI/IEEE CT calculation methodology. This paper is the first of a two-part series; Part II provides analytical waveform analysis discussions to illustrate the concepts conveyed in Part I
Modification of the Lund-Kennedy endoscopic scoring system improves its reliability and correlation with patient-reported outcome measures.

To compare three existing endoscopic scoring systems and a newly proposed modified scoring system for the assessment of patients with chronic rhinosinusitis (CRS).



Blinded, prospective cohort study.



CRS patients completed two patient-reported outcome measures (PROMs)-the visual analogue scale (VAS) symptom score and the Sino-Nasal Outcome Test-22 (SNOT-22)-and then underwent a standardized, recorded sinonasal endoscopy. Videos were scored by three blinded rhinologists using three scoring systems: the Lund-Kennedy (LK) endoscopic score; the Discharge, Inflammation, Polyp (DIP) score; and the Perioperative Sinonasal Endoscopic score. The videos were further scored using a modified Lund-Kennedy (MLK) endoscopic scoring system, which retains the LK subscores of polyps, edema, and discharge but eliminates the scoring of scarring and crusting. The systems were compared for test-retest and inter-rater reliability as well as for their correlation with PROMs.



One hundred two CRS patients were enrolled. The MLK system showed the highest inter-rater and test-retest reliability of all scoring systems. All systems except for the DIP correlated with total VAS scores. The MLK was the only system that correlated with the symptom subscore of the SNOT-22 in both unoperated and postoperative patients.



Modification of the LK system by excluding the subscores of scarring and crusting improves its reliability and its correlation with PROMs. In addition, the MLK system retains the familiarity of the widely used LK system and is applicable to any patient irrespective of surgical status. The MLK system may be a more suitable and reliable endoscopic scoring system for clinical practice and outcomes research.
IDCrypt: A Multi-User Searchable Symmetric Encryption Scheme for Cloud Applications

Searchable Encryption (SE) has been extensively examined by both academic and industry researchers. While many academic SE schemes show provable security, they usually expose some query information (e.g., search and access patterns) to achieve high efficiency. However, several inference attacks have exploited such leakage, e.g., a query recovery attack can convert opaque query trapdoors to their corresponding keywords based on some prior knowledge. On the other hand, many proposed SE schemes require significant modification of existing applications, which makes them less practical, weak in usability, and difficult to deploy. In this paper, we introduce a secure and practical searchable symmetric encryption scheme with provable security strength for cloud applications, called IDCrypt, which improves the search efficiency, and enhances the security strength of SE using symmetric cryptography. We further point out the main challenges in securely searching on multiple indexes and sharing encrypted data between multiple users. To address the above issues, we propose a token-adjustment search scheme to preserve the search functionality among multi-indexes, and a key sharing scheme which combines identity-based encryption and public-key encryption. Our experimental results show that the overhead of the key sharing scheme is fairly low.
A robust and imperceptible steganography technique for SD and HD videos

In this era of internet transfer of information is in digital form using multimedia files such as image, video, audio, etc. which relies on secure communication techniques to convey information safely. Due to the frequent transfer of videos over the internet nowadays they have become a good cover media for secure and covert communication in the form of video steganography. For efficient video steganography, it must fulfill its basic requirements such as capacity, imperceptibility, and robustness. In order to make a balance between imperceptibility and robustness, an efficient video steganography scheme is proposed for Standard Definition (SD) and High Definition (HD) videos. This scheme employs DWT (discrete wavelet transforms) for embedding the secret message inside the video frames utilizing only luminance (Y) component, and the security of the proposed scheme is strengthen by pre-processing the secret message with encryption before embedding. The embedding process is done by utilizing the middle-frequency sub-bands after applying second level 2-D DWT to the video frames to decompose it into 16 sub-bands. The performance of the proposed scheme is tested on different videos with quality metrics including peak signal to noise ratio (PSNR), structural similarity (SSIM) index, bit error rate (BER) and also by applying Gaussian and salt & pepper noise attacks. Moreover, the scheme is tested for the different level of compression on stego-video and also compared with U and V components used while embedding. Experimental results show that for both types of videos (HD and SD) the proposed scheme is able to achieve high imperceptibility. Further, it also provides robustness against different types of noise attacks and different compression levels which makes the proposed scheme evident for secure data transmission.
Data science at SoBigData: the European research infrastructure for social mining and big data analytics

Most people have become “big data” producers in their daily life. Our desires, opinions, sentiments, social links as well as our mobile phone calls and GPS track leave traces of our behaviours. To transform these data into knowledge, value is a complex task of data science. This paper shows how the SoBigData Research Infrastructure supports data science towards the new frontiers of big data exploitation. Our research infrastructure serves a large community of social sensing and social mining researchers and it reduces the gap between existing research centres present at European level. SoBigData integrates resources and creates an infrastructure where sharing data and methods among text miners, visual analytics researchers, socio-economic scientists, network scientists, political scientists, humanities researchers can indeed occur. The main concepts related to SoBigData Research Infrastructure are presented. These concepts support virtual and transnational (on-site) access to the resources. Creating and supporting research communities are considered to be of vital importance for the success of our research infrastructure, as well as contributing to train the new generation of data scientists. Furthermore, this paper introduces the concept of exploratory and shows their role in the promotion of the use of our research infrastructure. The exploratories presented in this paper represent also a set of real applications in the context of social mining. Finally, a special attention is given to the legal and ethical aspects. Everything in SoBigData is supervised by an ethical and legal framework.
Identification of novel deletions of 15q11q13 in Angelman syndrome by array-CGH: molecular characterization and genotype–phenotype correlations

Angelman syndrome (AS) is a neurodevelopmental disorder characterized by mental retardation, absent speech, ataxia, and a happy disposition. Deletions of the 15q11q13 region are found in approximately 70% of AS patients. The deletions are sub-classified into class I and class II based on their sizes of ∼6.8 and ∼6.0, respectively, with two different proximal breakpoints and a common distal breakpoint. Utilizing a chromosome 15-specific comparative genomic hybridization genomic microarray (array-CGH), we have identified, determined the deletion sizes, and mapped the breakpoints in a cohort of 44 cases, to relate those breakpoints to the genomic architecture and derive more precise genotype–phenotype correlations. Interestingly four patients of the 44 studied (9.1%) had novel and unusually large deletions, and are reported here. This is the first report of very large deletions of 15q11q13 resulting in AS; the largest deletion being >10.6 Mb. These novel deletions involve three different distal breakpoints, two of which have been earlier shown to be involved in the generation of isodicentric 15q chromosomes (idic15). Additionally, precise determination of the deletion breakpoints reveals the presence of directly oriented low-copy repeats (LCRs) flanking the recurrent and novel breakpoints. The LCRs are adequate in size, orientation, and homology to enable abnormal recombination events leading to deletions and duplications. This genomic organization provides evidence for a common mechanism for the generation of both common and rare deletion types. Larger deletions result in a loss of several genes outside the common Angelman syndrome–Prader–Willi syndrome (AS–PWS) critical interval, and a more severe phenotype.
PAFHWKM : An Enhanced Parallel Approach to Forecast Time Series Data Using Holt-Winters and K-Means Algorithm

Big Data is a recent research style which brings up challenges in decision making process. The size of the dataset turn intotremendously big, the process of extracting valuablefacts by analyzing these data also has become tedious. To solve this problem of information extraction with Big Data, parallel programming models can be used. Parallel Programming model achieves information extraction by partitioning the huge data into smaller chunks. MapReduce is one of the parallel programming models which works well with Hadoop Distributed File System(HDFS) that can be used to partition the data in a more efficient and effective way. In MapReduce, once the data is partitioned based on the <key, value> pair, it is ready for data analytics. Time Series data play an important role in Big Data Analytics where Time Series analysis can be performed with many machine learning algorithms as well as traditional algorithmic concepts such as regression, exponential smoothing, moving average, classification, clustering and model-based recommendation. For Big Data, these algorithms can be used with MapReduce programming model on Hadoop clusters by translating their data analytics logic to the MapReduce job which is to be run over Hadoop clusters. But Time Series data are sequential in nature so that the partitioning of Time Series data must be carefully done to retain its prediction accuracy.In this paper, a novel parallel approach to forecast Time Series data with Holt-Winters model (PAFHW) is proposed and the proposed approach PAFHW is enhanced by combining K-means clusteringfor forecasting the Time Series data in distributed environment.
Toward a Neural Basis of Music Perception – A Review and Updated Model

Music perception involves acoustic analysis, auditory memory, auditory scene analysis, processing of interval relations, of musical syntax and semantics, and activation of (pre)motor representations of actions. Moreover, music perception potentially elicits emotions, thus giving rise to the modulation of emotional effector systems such as the subjective feeling system, the autonomic nervous system, the hormonal, and the immune system. Building on a previous article (Koelsch and Siebel, 2005), this review presents an updated model of music perception and its neural correlates. The article describes processes involved in music perception, and reports EEG and fMRI studies that inform about the time course of these processes, as well as about where in the brain these processes might be located.
Host-directed therapies for bacterial and viral infections

Despite the recent increase in the development of antivirals and antibiotics, antimicrobial resistance and the lack of broad-spectrum virus-targeting drugs are still important issues and additional alternative approaches to treat infectious diseases are urgently needed. Host-directed therapy (HDT) is an emerging approach in the field of anti-infectives. The strategy behind HDT is to interfere with host cell factors that are required by a pathogen for replication or persistence, to enhance protective immune responses against a pathogen, to reduce exacerbated inflammation and to balance immune reactivity at sites of pathology. Although HDTs encompassing interferons are well established for the treatment of chronic viral hepatitis, novel strategies aimed at the functional cure of persistent viral infections and the development of broad-spectrum antivirals against emerging viruses seem to be crucial. In chronic bacterial infections, such as tuberculosis, HDT strategies aim to enhance the antimicrobial activities of phagocytes and to curtail inflammation through interference with soluble factors (such as eicosanoids and cytokines) or cellular factors (such as co-stimulatory molecules). This Review describes current progress in the development of HDTs for viral and bacterial infections, including sepsis, and the challenges in bringing these new approaches to the clinic.
Arduino-based portable system for bioelectrical impedance measurement

Electrochemical Impedance Spectroscopy (EIS) has been recently proposed as a simple non-invasive technique to monitor the amount of fat and liquids contained inside the human body. While the technique capabilities are still questioned, a simple and low cost device capable of performing this kind of measurements would help testing it on many patients with minimal effort. This paper describes an extremely low cost implementation of an EIS system suitable for medical applications that is based on a simple commercial Arduino Board whose cost is below 50$. The circuit takes advantage of the ADC and DAC made available by the microcontroller of the Arduino boards and employs a logarithmic amplifier to extend the impedance measuring range to 6 decades without using complex programmable gain amplifiers. This way the device can use electrodes with sizes in the range of 1 cm2 to 40 cm2. The EIS can be measured in the frequency range of 1 Hz to 100 kHz and in the impedance range of 1 kΩ to 1 GΩ. The instrument automatically compensates the DC voltage due to the skin/electrode contact and runs on batteries. The EIS traces can be stored inside the device and transferred to the PC with a wireless link avoiding safety issues.
An Eigendecomposition Approach to W e ighted Graph Ma tching Problems

Absfruct-This paper discusses an approximate solution to the weighted graph matching prohlem (WGMP) for both undirected and directed graphs. The W G M P is the problem of f inding the opt imum matching between two weighted graphs, which are graphs with weights at each arc. The proposed method employs an analytic, instead of a combinatorial or iterative, approach to the opt imum matching problem of such graphs. By using the eigendecomposit ions of the adjacency matrices (in the case of the undirected graph matching problem) or some Hermitian matrices derived from the adjacency matrices (in the case of the directed graph matching problem), a matching close to the opt imum one can be found efficiently when the graphs are sufficiently close to each other. Simulation experiments are also given to evaluate the performance of the proposed method.
A ring VCO with wide and linear tuning characteristics for a cognitive radio system

This paper presents a novel voltage-controlled ring oscillator fabricated in TSMC 0.18-mum CMOS technology. In order to obtain a linear frequency-voltage characteristic over a wide tuning range while maintaining good phase noise performance, a transmission gate was adopted in a saturated-type ring oscillator. The resistance tuning capability of the transmission gate was then theoretically and experimentally analyzed. The proposed ring oscillator achieved a wide operating frequency range from 20 MHz to 807 MHz covering TV channel bands for the cognitive radio spectrum sensing system. The measured phase noise is -108 dBc/Hz at 1-MHz offset from 630 MHz. The power consumption is 22 mW, and core chip area is 60 mum times 51 mum.
Pattern-based safety development methods: overview and comparison

Design patterns provide good solutions to re-occurring problems and several patterns and methods how to apply them have been documented for safety-critical systems. However, due to the large amount of safety-related patterns and methods, it is difficult to get an overview of their capabilities and shortcomings as there currently is no survey on safety patterns and their application methods available in literature.
 To give an overview of existing pattern-based safety development methods, this paper presents existing methods from literature and discusses and compares several aspects of these methods such as the patterns and tools they use, their integration into a safety development process, or their maturity.
A time improvement technique of lead-acid battery balancing system

In the application of lead-acid series batteries, the voltage imbalance of each battery should be considered. Therefore, additional balancer circuits must be integrated into the battery. An active battery balancing circuit with an auxiliary storage can employ a sequential battery imbalance detection algorithm by comparing the voltage of a battery and auxiliary storage. The system is being in balance if the battery voltage imbalance is less than 10mV/cell. In this paper, a new algorithm is proposed so that the battery voltage balancing time can be improved. The battery balancing system is based on the LTC3305 working principle. The simulation verifies that the proposed algorithm can achieve permitted battery voltage imbalance faster than that of the previous algorithm.