nils-herrmann/clean_scirepeval huggingface dataset:
Evaluation of Morinda citrifolia as an endodontic irrigant.

The purpose of this study was to compare the in vitro effectiveness of Morinda citrifolia juice (MCJ) with sodium hypochlorite (NaOCl) and chlorhexidine gluconate (CHX) to remove the smear layer from the canal walls of endodontically instrumented teeth. Sixty extracted, single-rooted, mature, permanent, human premolar teeth with a single canal were inoculated with Enterococcus faecalis at 37 degrees C in a CO2 atmosphere for 30 days. The teeth were randomly allocated to 6 treatment groups; the pulp chamber was accessed, cleaned, and shaped by using ProTaper and ProFile rotary instrumentation to a size 35. During instrumentation the irrigation was provided by MCJ, NaOCl, CHX, MCJ/CHX, followed by a final flush of 17% ethylenediaminetetraacetic acid (EDTA). MCJ irrigation was also followed by a final flush of saline, and saline irrigation was also used as a negative control. The teeth were then processed for scanning electron microscopy, and the removal of smear layer was examined. Data were analyzed by chi2 statistical tests (P values) at a significance of 95%. The most effective removal of smear layer occurred with MCJ and NaOCl, both with a rinse of 17% EDTA. Both MCJ and NaOCl treatments were similarly effective with a rinse of 17% EDTA (P < .2471) to completely remove up to 80% of the smear layer from some aspects of the root canal. MCJ was more effective than CHX for removing smear layer (P < .0085) and saline as the negative control (P < .0001). The efficacy of MJC was similar to NaOCl in conjunction with EDTA as an intracanal irrigant. MJC appears to be the first fruit juice to be identified as a possible alternative to the use of NaOCl as an intracanal irrigant.
Literature Review and General Consideration of Energy Efficient Routing Protocols in MANETs

A mobile wireless infrastructure-less network is a collection of wireless mobile nodes dynamically forming a temporary network without the use of any preexisting network infrastructure or centralized administration. However, the battery life of these nodes is very limited, if their battery power is depleted fully, then this result in network partition, so these nodes becomes a critical spot in the network. These critical nodes can deplete their battery power earlier because of excessive load and processing for data forwarding. These unbalanced loads turn to increase the chances of nodes failure, network partition and reduce the route lifetime and route reliability of the MANETs. Due to this, energy consumption issue becomes a vital research topic in wireless infrastructure -less networks. The energy efficient routing is a most important design criterion for MANETs. This paper focuses of the routing approaches are based on the minimization of energy consum ption of individual nodes and many other ways. This paper surveys and classifies numerous energy-efficient routing mechanisms proposed for wireless infrastructure-less networks. Also presents detailed comparative study of lager number of energy efficient/power aware routing protocol in MANETs. Aim of this paper to helps the new researchers and application developers to explore an innovative idea for designing more efficient routing protocols.  Ad hoc Network Routing, Load Distribution, Energy Eff icient, Power Aware,
A Wearable Nutrition Monitoring System

Maintaining appropriate levels of food intake anddeveloping regularity in eating habits is crucial to weight lossand the preservation of a healthy lifestyle. Moreover, maintainingawareness of one's own eating habits is an important steptowards portion control and ultimately, weight loss. Though manysolutions have been proposed in the area of physical activitymonitoring, few works attempt to monitor an individual's foodintake by means of a noninvasive, wearable platform. In thispaper, we introduce a novel nutrition-intake monitoring systembased around a wearable, mobile, wireless-enabled necklacefeaturing an embedded piezoelectric sensor. We also propose aframework capable of estimating volume of meals, identifyinglong-term trends in eating habits, and providing classificationbetween solid foods and liquids with an F-Measure of 85% and86% respectively. The data is presented to the user in the formof a mobile application.
CitNetExplorer: A new software tool for analyzing and visualizing citation networks

We present CitNetExplorer, a new software tool for analyzing and visualizing citation networks of scientific publications. CitNetExplorer can for instance be used to study the development of a research field, to delineate the literature on a research topic, and to support literature reviewing. We first introduce the main concepts that need to be understood when working with CitNetExplorer. We then demonstrate CitNetExplorer by using the tool to analyze the scientometric literature and the literature on community detection in networks. Finally, we discuss some technical details on the construction, visualization, and analysis of citation networks in CitNetExplorer.
Comparative study of xylanase kinetics using dinitrosalicylic, arsenomolybdate, and ion chromatographic assays.

Xylanases are commonly assayed by the dinitrosalicylic acid (DNS) or the arsenomolybdate (ARS) method. However, specific activities are many times higher with DNS than with ARS. This is because the DNS assay is more reactive and the ARS assay is less reactive with xylooligosaccharides than with xylose. Xylose is often used as a standard, even though oligosaccharides are prevalent, so the DNS method overestimates and the ARS method underestimates specific activity. Ion chromatography, with pulsed amperometric detection, separates and measures all products and intermediates, but quantitation on a molar basis is difficult, because few xylooligosaccharide response factors are known. This report directly compares these three assay methods for the assay of xylanase activities.
New antenna design for GNSS application

A new radiating element design of the slot stripline leaky-wave antennas with right-hand circular polarization is proposed for high-accuracy positioning using Global satellite navigation signals (GNSS) GPS (L1/L2) and GLONASS (L1/L2/L3). Technical characteristics of the antenna with the new radiator have been studied. It is shown that the application of the new radiator decreases the axial ratio and improves the crosspolarization suppression and stability of the phase center, allowing one to increase the accuracy of GLONASS/GPS positioning.
Inter- and intraobserver reliability of the vertebral, local and segmental kyphosis in 120 traumatic lumbar and thoracic burst fractures: evaluation in lateral X-rays and sagittal computed tomographies

Evaluation of the kyphosis angle in thoracic and lumbar burst fractures is often used to indicate surgical procedures. The kyphosis angle could be measured as vertebral, segmental and local kyphosis according to the method of Cobb. The vertebral, segmental and local kyphosis according to the method of Cobb were measured at 120 lateral X-rays and sagittal computed tomographies of 60 thoracic and 60 lumbar burst fractures by 3 independent observers on 2 separate occasions. Osteoporotic fractures were excluded. The intra- and interobserver reliability of these angles in X-ray and computed tomogram, using the intra class correlation coefficient (ICC) were evaluated. Highest reproducibility showed the segmental kyphosis followed by the vertebral kyphosis. For thoracic fractures segmental kyphosis shows in X-ray “excellent” inter- and intraobserver reliabilities (ICC 0.826, 0.802) and for lumbar fractures “good” to “excellent” inter- and intraobserver reliabilities (ICC = 0.790, 0.803). In computed tomography, the segmental kyphosis showed “excellent” inter- and intraobserver reliabilities (ICC = 0.824, 0.801) for thoracic and “excellent” inter- and intraobserver reliabilities (ICC = 0.874, 0.835) for the lumbar fractures. Regarding both diagnostic work ups (X-ray and computed tomography), significant differences were evaluated in interobserver reliabilities for vertebral kyphosis measured in lumbar fracture X-rays (p = 0.035) and interobserver reliabilities for local kyphosis, measured in thoracic fracture X-rays (p = 0.010). Regarding both fracture localizations (thoracic and lumbar fractures), significant differences could only be evaluated in interobserver reliabilities for the local kyphosis measured in computed tomographies (p = 0.045) and in intraobserver reliabilities for the vertebral kyphosis measured in X-rays (p = 0.024). “Good” to “excellent” inter- and intraobserver reliabilities for vertebral, segmental and local kyphosis in X-ray make these angles to a helpful tool, indicating surgical procedures. For the practical use in lateral X-ray, we emphasize the determination of the segmental kyphosis, because of the highest reproducibility of this angle. “Good” to “excellent” inter- and intraobserver reliabilities for these three angles could also be evaluated in computed tomographies. Therefore, also in computed tomography, the use of these three angles seems to be generally possible. For a direct correlation of the results in lateral X-ray and in computed tomography, further studies should be needed.
Reinventing the Wheel: Transforming Steering Wheel Systems for Autonomous Vehicles

In this paper, we introduce two different transforming steering wheel systems that can be utilized to augment user experience for future partially autonomous and fully autonomous vehicles. The first one is a robotic steering wheel that can mechanically transform by using its actuators to move the various components into different positions. The second system is a LED steering wheel that can visually transform by using LEDs embedded along the rim of wheel to change colors. Both steering wheel systems contain onboard microcontrollers developed to interface with our driving simulator. The main function of these two systems is to provide emergency warnings to drivers in a variety of safety critical scenarios, although the design space that we propose for these steering wheel systems also includes the use as interactive user interfaces. To evaluate the effectiveness of the emergency alerts, we conducted a driving simulator study examining the performance of participants (N=56) after an abrupt loss of autonomous vehicle control. Drivers who experienced the robotic steering wheel performed significantly better than those who experienced the LED steering wheel. The results of this study suggest that alerts utilizing mechanical movement are more effective than purely visual warnings.
Using LIP to Gloss Over Faces in Single-Stage Face Detection Networks

This work shows that it is possible to fool/attack recent state-of-the-art face detectors which are based on the single-stage networks. Successfully attacking face detectors could be a serious malware vulnerability when deploying a smart surveillance system utilizing face detectors. In addition, for the privacy concern, it helps prevent faces being harvested and stored in the server. We show that existing adversarial perturbation methods are not effective to perform such an attack, especially when there are multiple faces in the input image. This is because the adversarial perturbation specifically generated for one face may disrupt the adversarial perturbation for another face. In this paper, we call this problem the Instance Perturbation Interference (IPI) problem. This IPI problem is addressed by studying the relationship between the deep neural network receptive field and the adversarial perturbation. As such, we propose the Localized Instance Perturbation (LIP) that confines the adversarial perturbation inside the Effective Receptive Field (ERF) of a target to perform the attack. Experimental results show the LIP method massively outperforms existing adversarial perturbation generation methods – often by a factor of 2 to 10.
Consumers' perceived attitudes to wearable devices in health monitoring in China: A survey study

Capital market and consumer market interest in wearable devices has surged in recent years, however, their actual acceptance in the field of health monitoring is somewhat not as expected. This study aims to understand the perceptions of wearable devices of general consumers, analyze the review of the devices by users, and find existing problems associated with current wearable devices.



Sojump.com, an on-line questionnaire tool, was used to generate the questionnaire, which focused on four aspects. The snowball sampling method was employed to collect questionnaires by making use of the author's social network.



(1) A total of 2058 valid questionnaires were received from the respondents from every province in China; of the respondents, 52.4% have used a wearable device. (2) The respondents had a low level of knowledge about wearable devices (2.79/5) but were optimistic with regard to the devices' future (3.86/5), and 84% recognized an acceptable price of less than 2000 RMB. Nearly half of the respondents were unwilling to continuously wear the device (47.1%) and share their health data (44.7%). (3) The functions of wearable devices that the respondents expected were mainly health management (63.5%), mobile phone accessories (61.9%), and location tracking (61.2%), and the promising hot future functions were mainly data analysis (74.2%), exercise coaching (60.5%), and child tracking (58.8%). Regarding the health monitoring functions, the respondents were most interested in heart health monitoring. (4) The respondents had different levels of emphasis regarding the existing problems of wearable devices at different use stages. Being easily damaged or lost (49.7%), being incapable of providing health recommendations based on data analysis (46.7%), and being uncomfortable to wear (45.8%) likely lead consumers to abandon the use of wearable devices.



Consumers are optimistic about the prospects of wearable devices; however, there is a large gap between the reliability of the measurement data, the ease of use, and the interpretation of measurement data of current wearable products and consumer expectations. Consumer demand for health management functions is higher than that for daily auxiliary-type functions, which is an issue that should be properly addressed and resolved by manufacturers.
How bacteria talk to each other: regulation of gene expression by quorum sensing.

Quorum sensing, or the control of gene expression in response to cell density, is used by both gram-negative and gram-positive bacteria to regulate a variety of physiological functions. In all cases, quorum sensing involves the production and detection of extracellular signalling molecules called autoinducers. While universal signalling themes exist, variations in the design of the extracellular signals, the signal detection apparatuses, and the biochemical mechanisms of signal relay have allowed quorum sensing systems to be exquisitely adapted for their varied uses. Recent studies show that quorum sensing modulates both intra- and inter-species cell-cell communication, and it plays a major role in enabling bacteria to architect complex community structures.
A model predictive approach for cyber-attack detection and mitigation in control systems

The paper presents a new approach for control security. Specifically, cyber-attacks on the controller are investigated by means of optimization techniques in order to determine the worst-case scenario. Then, a novel attack detector based on limit checking is introduced. The particularity of this detector is that no specific controller knowledge is necessary. Hence, the vulnerability of the detector can be reduced since no reconfiguration is required (limited accessibility). Finally, the paper shows that the effect of the attacks on the system can be significantly mitigated by applying proper optimal control laws.
Multipart Vehicle Detection Using Symmetry-Derived Analysis and Active Learning

On-road vehicle detection is a critical operation in automotive active safety systems such as collision avoidance, merge assist, lane change assistance, etc. In this paper, we present VeDAS-Vehicle Detection using Active learning and Symmetry. VeDAS is a multipart-based vehicle detection algorithm that employs Haar-like features and Adaboost classifiers for the detection of fully and partially visible rear views of vehicles. In order to train the classifiers, a modified active learning framework is proposed that selects positive and negative samples of multiple parts in an automated manner. Furthermore, the detected parts from the classifiers are associated by using a novel iterative window search algorithm and a symmetry-based regression model to extract fully visible vehicles. The proposed method is evaluated on seven different datasets that capture varying road, traffic, and weather conditions. Detailed evaluations show that the proposed method gives high true positive rates of over 95% and performs better than existing state-of-the-art rear-view-based vehicle detection methods. Additionally, VeDAS also detects partially visible rear views of vehicles using the residues left behind after detecting the fully visible vehicles. VeDAS is able to detect partial rear views with a detection rate of 87% on a new partially visible rear-view vehicle dataset that we release as part of this paper.
Breast Cancer: Insights into Risk Factors, Pathogenesis, Diagnosis and Management

Breast cancer is the most common invasive cancer in females worldwide. It usually presents with a lump in the breast with or without other manifestations. Diagnosis of breast cancer depends on physical examination, mammographic findings and biopsy results. Treatment of breast cancer depends on the stage of the disease. Lines of treatment include mainly surgical removal of the tumor followed by radiotherapy or chemotherapy. Other lines including immunotherapy, thermochemotherapy and alternative medicine may represent a hope for breast cancer
Four minutes of in-class high-intensity interval activity improves selective attention in 9- to 11-year olds.

The amount of time allocated to physical activity in schools is declining. Time-efficient physical activity solutions that demonstrate their impact on academic achievement-related outcomes are needed to prioritize physical activity within the school curricula. "FUNtervals" are 4-min, high-intensity interval activities that use whole-body actions to complement a storyline. The purpose of this study was to (i) explore whether FUNtervals can improve selective attention, an executive function posited to be essential for learning and academic success; and (ii) examine whether this relationship is predicted by students' classroom off-task behaviour. Seven grade 3-5 classes (n = 88) were exposed to a single-group, repeated cross-over design where each student's selective attention was compared between no-activity and FUNtervals days. In week 1, students were familiarized with the d2 test of attention and FUNterval activities, and baseline off-task behaviour was observed. In both weeks 2 and 3 students completed the d2 test of attention following either a FUNterval break or a no-activity break. The order of these breaks was randomized and counterbalanced between weeks. Neither motor nor passive off-task behaviour predicted changes in selective attention following FUNtervals; however, a weak relationship was observed for verbal off-task behaviour and improvements in d2 test performance. More importantly, students made fewer errors during the d2 test following FUNtervals. In supporting the priority of physical activity inclusion within schools, FUNtervals, a time efficient and easily implemented physical activity break, can improve selective attention in 9- to 11-year olds.
Double image compression and encryption scheme using logistic mapped convolution and cellular automata

Due to the availability and increased usage of multimedia applications, features such as compression and security has gained more importance. Here, we propose a key generation algorithm and a double image encryption scheme with combined compression and encryption. The keys for encryption are generated using a novel modified convolution and chaotic mapping technique. First, the four least significant bits of the two images were truncated and then combined after permutation using the proposed logistic mapping. Also, cellular automata based diffusion is performed on the resultant image to strengthen the security further. Here, both confusion and diffusion seem to be integrated thus improvising the encryption scheme. The performance results and the test of randomness of the key and the algorithm were found to be successful. Since two images are compressed and encrypted simultaneously, it is useful in real - time scenarios.
Coffee: biochemistry and potential impact on health.

This review provides details on the phytochemicals in green coffee beans and the changes that occur during roasting. Key compounds in the coffee beverage, produced from the ground, roasted beans, are volatile constituents responsible for the unique aroma, the alkaloids caffeine and trigonelline, chlorogenic acids, the diterpenes cafestol and kahweol, and melanoidins, which are Maillard reaction products. The fate of these compounds in the body following consumption of coffee is discussed along with evidence of the mechanisms by which they may impact on health. Finally, epidemiological findings linking coffee consumption to potential health benefits including prevention of several chronic and degenerative diseases, such as cancer, cardiovascular disorders, diabetes, and Parkinson's disease, are evaluated.
e-Services: Problems, Opportunities, and Digital Platforms

Services that are delivered over the Internet—e-services— pose unique problems yet offer unprecedented opportunities. In this paper, we classify e-services along the dimensions of their level of digitization and the nature of their target markets (business-to-business, business-toconsumer, consumer-to-consumer). Using the case of application services, we analyze how they differ from traditional software procurement and development. Next, we extend the concept of modular platforms to this domain and identify how knowledge management can be used to assemble rapidly new application services. We also discuss how such traceabilty-based knowledge management can facilitate e-service evolution and version-based market segmentation.
Comparative Analysis of Various Multiuser Detection Techniques in SDMA-OFDM System Over the Correlated MIMO Channel Model for IEEE 802 . 16 n

SDMA (Space-Division Multiple Access) is a MIMO (Multiple-Input and Multiple-Output) based wireless communication network architecture which has the potential to significantly increase the spectral efficiency and the system performance. The maximum likelihood (ML) detection provides the optimal performance, but its complexity increases exponentially with the constellation size of modulation and number of users. The QR decomposition (QRD) MUD can be a substitute to ML detection due its low complexity and near optimal performance. The minimum mean-squared-error (MMSE) multiuser detection (MUD) minimises the mean square error (MSE), which may not give guarantee that the BER of the system is also minimum. But the minimum bit error rate (MBER) MUD performs better than the classic MMSE MUD in term of minimum probability of error by directly minimising the BER cost function. Also the MBER MUD is able to support more users than the number of receiving antennas, whereas the rest of MUDs fail in this scenario. In this paper the performance of various MUD techniques is verified for the correlated MIMO channel models based on IEEE 802.16n standard.  Multiple input multiple output, multiuser detection, orthogonal frequency division multiplexing, space division multiple access, Bit error rate